Operational context and policy relevance

This analysis demonstrates how Spire’s Soil Moisture Insights can complement government programs designed to reduce illicit coca cultivation and strengthen terrain-based enforcement planning. In Colombia, this intelligence can support agencies working to prevent coca expansion by revealing which areas are most accessible for suppression or alternative development efforts.

Insights for enforcement & policy

Spire’s soil-moisture intelligence provides more than environmental awareness – it delivers predictive mobility intelligence. By measuring how quickly specific terrain in certain regions transitions from saturated to stable conditions, soil moisture data accessed via Spire’s DeepInsights Cirrus platform identifies when and where movement across remote regions becomes possible. These insights allow enforcement, logistics, and policy teams to anticipate accessibility, rather than react to it.

For operations in frontier terrain, soil moisture is a far stronger indicator of mobility than rainfall. Rainfall data shows when storms occur; soil moisture data reveals how long their effects last. This distinction transforms climate information into actionable intelligence, supporting everything from patrol scheduling to aerial ISR timing and eradication or enforcement campaigns that depend on soil stability. In civilian applications, the same insight can guide infrastructure maintenance, humanitarian access, or post-flood recovery logistics.

This same methodology can be replicated across other frontier environments, from West Africa’s Sahel corridors to Southeast Asia’s borderlands, wherever mobility depends on terrain state.

Limitations & safeguards

Soil data quantify environmental feasibility, not human intent. While soil-moisture anomalies reveal when terrain can or cannot support movement, they should always be combined with complementary intelligence streams (such as HUMINT, SIGINT, or geospatial observation) to interpret behavior.

To prevent misuse or adversary adaptation, high-resolution soil moisture outputs should remain restricted to vetted users and used only within secure operational frameworks. These safeguards ensure environmental intelligence enhances decision-making without overextending inference.

Environmental & geographic drivers of coca expansion

Colombia’s surge in coca cultivation has deep roots in geography and land-use dynamics, as well as in enforcement and policy cycles. According to the 2023 UNODC Coca Survey, the national coca area reached 230,000 hectares by 2024, the highest figure since monitoring began.

The most significant increases occurred in Putumayo, Nariño, and Cauca, where mountainous terrain and tropical rainfall provide both fertile growing conditions and logistical cover for processing and transport. Complementary analyses by the IUCN and the Global Initiative Against Transnational Organized Crime link this expansion to broader patterns of deforestation and informal road development in the Amazon fringe – physical transformations that reshape access routes and settlement patterns across southern Colombia.

Deforestation plays a direct enabling role in coca expansion. The clearing of forests opens remote terrain to roads and human movement, allowing farmers and traffickers to reach areas that were previously inaccessible. Newly exposed soils also create short-term agricultural openings (fertile ground for short-cycle crops like coca) before nutrients are depleted. These same clearings fragment the forest canopy, making cultivation easier to conceal across dispersed patches while leaving lasting environmental signatures visible in soil-moisture data.

While policy attention often centers on the social and economic drivers of coca cultivation, environmental accessibility remains a determining factor that is rarely quantified.

Seasonal cycles dictate the rhythm of both production and enforcement. During the rainy months, saturated soils can isolate remote areas, forcing traffickers to rely on rivers and small airstrips. During dry periods, unpaved tracks reopen, facilitating the transport of precursors and products across the forest frontier. Traditional rainfall datasets capture when storms occur, but not how long soils remain saturated after they pass. Soil moisture, rather than rainfall, determines when eradication teams can access target areas and when illicit networks can move resources through them.

This difference between rainfall and soil response underscores the need for a new kind of monitoring: one that tracks the persistence of saturation and drying cycles over time.

2023 – 2024 precursors: Environmental cycles shaping accessibility

Open-source reporting and field studies from 2023 to 2024 reveal a clear sequence of environmental and logistical changes across Colombia’s southern coca frontier. Together, they reveal how fluctuations in land accessibility and seasonal moisture shaped both coca cultivation and the movement of goods across the Putumayo–Nariño corridor.

June – September 2023 – expansion during extended dry conditions

In mid-2023, an unusually long dry window altered movement across Colombia’s Andean-Amazon frontier. Roads that had been impassable for months hardened under weeks of low rainfall. Regional journalists described the renewed presence of truck and motorcycle traffic near Puerto Asís, Mocoa, and Orito, where compacted soils reopened interior routes used for transportation and supply.

According to Colombia’s meteorological institute IDEAM, rainfall totals in Putumayo and Nariño fell 25-40 percent below seasonal norms. These conditions allowed eradication patrols to reach farther upriver but also enabled farmers to move fertilizer and fuel into newly accessible clearings.

Environmental organizations monitoring deforestation detected corresponding spikes in forest clearing and road cutlines during July and August. The IUCN’s 2023 report described this as a “seasonal pulse” of land conversion: once soils dried, machinery entered to fell timber and plant short-cycle crops, particularly coca, before the rains returned.

Satellite alerts from Global Forest Watch also indicated ongoing tree-cover loss in Putumayo, including in areas of intact forest, corroborating physical clearing activity in regions under pressure from frontier expansion.

Key implication:

The extended dryness of mid-2023 coincided with a surge in frontier accessibility, which hardened unpaved roads and facilitated the transport of inputs to newly accessible terrain, triggering a short-term wave of deforestation and coca cultivation.

March – April 2024 – Saturation and disrupted access

By early 2024, the return of Colombia’s rainy season dramatically shifted mobility across the southern frontier. Continuous downpours triggered flooding and landslides, ultimately leading to weeks of isolation in Putumayo, Cauca, and Nariño, disrupting both licit and illicit movement across the region.

The national meteorological agency IDEAM reported above-average rainfall totals across the southwestern Amazon piedmont from February through April, noting that monthly precipitation exceeded climatological norms by 30–50 percent in parts of Putumayo. Roads connecting Mocoa, Villagarzón, and Puerto Guzmán were repeatedly closed due to landslides, according to dispatches from El Espectador and local civil-defense bulletins.

Independent coverage from InfoAmazonia mapped flooding along the Putumayo River basin, where satellite imagery showed overbank inundation of low-lying forest and agricultural plots. Journalists with Vorágine documented how traffickers and residents adapted to the changing conditions, shifting to river transport for supply shipments while relying on small airstrips on higher ground for essential goods.

Officials interviewed by El Tiempo described a temporary stand-down of land-based eradication efforts as vehicles became bogged down or stranded in saturated terrain. Field accounts from humanitarian workers further noted that isolated communities turned to river commerce to offset supply shortages, creating temporary micro-economies along navigable stretches of the Putumayo and Caquetá rivers.

Key implication:

The early-2024 rains underscored the region’s environmental sensitivity – how short bursts of extreme precipitation can immobilize land routes, redirect trafficking toward river corridors, and reshape local economies until terrain conditions stabilize.

May – July 2024 – Dry-down and frontier road expansion

As the rains subsided in mid-2024, dry conditions once again reshaped movement and land use across Colombia’s southern frontier. Soil surfaces hardened after months of saturation, reopening overland routes that had been closed since the start of the year.

According to the Associated Press (AP), deforestation and informal road construction accelerated in the Amazon fringe of southern Colombia during this period, particularly around Mocoa, Puerto Guzmán, and northern Caquetá. Field organizations cited by AP reported the return of heavy machinery and logging trucks to areas that had been inaccessible during the rains.

Local coverage from La Silla Vacía described how the “verano” (the brief mid-year dry season) enables a surge in transport activity as rural roads dry out. In interviews with community leaders, the outlet noted that large vehicles carrying timber, fuel, and agricultural inputs used the short dry window to move goods deeper into the forest frontier, where new road cutlines often precede coca planting and settlement expansion. Environmental alerts from Global Forest Watch also recorded localized spikes in tree-cover loss during June and July, corresponding to these newly reopened corridors in Putumayo and Caquetá.

Key implication:

The mid-2024 dry-down reopened overland corridors, enabling the construction of access routes that underpin both coca cultivation and associated illicit economies.

August – October 2024 – Variable terrain and adaptive mobility

By late 2024, conditions across Colombia’s southern frontier had become increasingly erratic. Alternating weeks of drought and heavy rainfall created unstable terrain, upending predictable transport patterns along the Putumayo–Ecuador border.

InSight Crime reported that trafficking networks operating in the region began alternating between land and river routes as weather swings disrupted ground access. Interviews with local officials revealed that these shifts were often unplanned, responding to sudden road washouts or rapid dry-downs that reopened dirt tracks within days.

The International Crisis Group noted similar volatility in its late-2024 regional brief, warning that environmental instability compounded security and logistical challenges for both state and non-state actors. Municipal authorities in Puerto Leguízamo and La Hormiga reported repeated infrastructure damage from back-to-back storms, followed by intense drying that left unpaved roads cracked and impassable.

Local coverage from El Espectador described how rural residents adjusted by relying on motorcycles, mule convoys, and riverboats within the same month, illustrating how rapidly mobility decisions in the coca frontier now hinge on terrain conditions rather than fixed routes.

Key implication:

Late-2024 volatility underscored the frontier’s growing environmental unpredictability. As alternating extremes of saturation and drought reshaped ground conditions in a matter of days, both enforcement and trafficking operations became increasingly reactive, dependent on real-time awareness of terrain state rather than established seasonal patterns.

2025: Recent environmental and trafficking dynamics (April–October)

April – May 2025 – Flooding, saturation, and isolation in the Putumayo Basin

In early to mid-April 2025, heavy rainfall and river overflow once again brought localized flooding to the lower Putumayo corridor, particularly around Puerto Leguízamo and neighboring river settlements near the Ecuador border. The surge in water levels constrained access along both river and overland channels. According to a UN OCHA Regional Situational Update, flooding in Bajo Putumayo displaced or otherwise affected roughly 3,300 people as water levels rose in the Putumayo and Caquetá Rivers.

At the same time, Mongabay reported that between October 2024 and March 2025, over 11,000 hectares of forest in the Putumayo department were cleared, and approximately 80 kilometers of irregular (mostly dirt) roads were carved through forest margins, particularly in Puerto Guzmán and eastern Putumayo districts. These road cutlines were often flanked by newly deforested patches, suggesting that the forest edges were actively being penetrated.

The combination of rising river levels and fresh road incursions suggests a dual pressure on frontier mobility:

• The flooding would have limited overland transport, particularly via small secondary tracks and forest roads.
• The new road cuts, however, suggest that once soils began to dry, traffickers and land-clearing actors expected or anticipated windows of accessibility.

Operationally, this pattern shows how traffickers and land-clearing actors plan ahead of environmental shifts: they build during isolation, anticipating terrain recovery.

AOI (Area of Interest) 1 (Putumayo River Basin) will test this behavior using Spire’s soil-moisture anomaly data to measure how quickly soils transitioned from saturation back toward dryness between April and June 2025.

July – August 2025 – Mid-year dry-down, road reopening & deforestation pressure

By mid-2025, a clear dry-down across southern Colombia reopened access routes that had been saturated earlier in the year. Reports from Puerto Asís, Mocoa, and the northern edge of Caquetá described renewed vehicle and machinery traffic along secondary forest roads as soils hardened and transport resumed.

In its article “Deforestation & Illegal Roads Advancing Fast in Colombia’s Largest Natural Area“, Mongabay documented that during early 2025, roughly 22 kilometers of illegal roads were cut and 856 hectares of forest cleared in the Llanos del Yarí–Yaguará reserve, underscoring that road-building remains a key tactic for penetrating remote regions.

At the national scale, Colombia’s Environment Ministry reported a 33 percent decline in deforestation during the first quarter of 2025 compared with 2024, dropping from about 40,000 to 27,000 hectares, but noted that this reduction was concentrated in protected Amazon parks. Pressure along frontier departments such as Putumayo persisted, particularly where dry conditions allowed access for clearing and construction.

By late July, that temporary reprieve had reversed. Reuters reported a 43 percent year-on-year surge in Amazon deforestation, driven by fires, land grabbing, and unregulated road expansion, including in areas tied to illicit cultivation.

Together, these signals point to a consistent environmental rhythm: once the rains recede, soil drying rapidly restores mobility, enabling both legitimate and illicit actors to move equipment deeper into the forest frontier. In Putumayo and adjacent Caquetá, this mid-year hardening of terrain likely reopened unpaved roads and set the stage for the next cultivation cycle – conditions that Spire’s Soil Moisture Insights can quantify through declining soil-moisture anomalies during July–August.

AOI 2 (Puerto Asís–Mocoa Corridor) focuses on this overland axis where soil drying and re-hardened tracks correspond to the July–August expansion window. Soil moisture anomaly data for this region will be used to quantify the transition from wet to dry conditions that reopened these transport routes.

September – October 2025 – Volatility, route switching, and frontier adaptation

From September 5 through mid-October 2025, terrain and access across southern Caquetá and western Putumayo, especially near La Hormiga and Solano, became increasingly volatile – forcing dynamic adaptation by traffickers and farmers. A Reuters article highlighted that many frontier zones remain cut off from basic infrastructure; roads are unpaved, utilities are absent, and seasonal access is uncertain.

This kind of reporting underscores that even small shifts in soil saturation or ground hardness can open or close access routes entirely. In such conditions, traffickers and transporters adapt continuously, shifting from river to motorcycle or mule routes during saturation, then back to small airstrips or forest tracks once the ground hardens. These short-lived mobility windows depend directly on soil stability rather than rainfall timing, a dynamic measurable through daily soil moisture anomaly data.

In practice, these tactical shifts mean mobility decisions become reactive to terrain conditions on weekly or even daily scales – a regime that soil-moisture anomaly data is especially well positioned to detect and corroborate.

AOI 3 (Upland Caquetá Transition) captures this pattern of rapid alternation, allowing Spire’s soil moisture time-series data to quantify the volatility that Reuters described qualitatively.

Integrated interpretation: What these trends suggest

1. Recurrence of the seasonal cycle
   The April flooding, mid-year dry pulse, and late-year volatility map closely onto the patterns documented in 2023–2024. These are not one-off events but a repeating environmental rhythm shaping frontier access.
2. Pre-positioning strategy
   The road cuts and deforestation activity reported even during wet months suggest that actors anticipate favorable terrain windows. They position infrastructure just behind canopy lines so that, as soon as the soil dries, they can expand rapidly.
3. Frontier as a pulse system
   The frontier doesn’t expand monotonically – it pulses. Some months it contracts under saturation, other months it surges under dryness, and then adapts under volatility. This calls for intelligence systems that detect when and where mobility becomes feasible.
4. Sensitivity to thresholds
   Terrain conditions likely cross critical thresholds: small shifts in soil moisture might flip a route from impassable to passable. Open-source reporting hints at these edges (road washouts, closures, transport mode shifts) but cannot quantify exactly where or when those thresholds occur.
5. Role of disparate pressures
   The mixed deforestation data (declines in some quarters, surges in others) suggest that enforcement, governance, and local resistance can modulate frontier expansion. Soil-moisture data helps disaggregate environmental constraints from policy constraints.

Spire Soil Moisture analysis: Terrain accessibility and anomalies

Spire’s Cirrus platform provides near–real-time and historic satellite-derived soil-moisture intelligence that captures terrain conditions invisible to conventional rainfall data. Across Colombia’s southern frontier, Spire’s Soil Moisture Insights validate how saturation and drying cycles shaped movement, cultivation, and enforcement activity from 2023 through 2024.

Three areas of interest (AOIs) were analyzed for 2025 to illustrate how soil-moisture anomalies influence ground accessibility and transport feasibility along the coca frontier:

1. AOI 1 – Putumayo River Basin: Riverine corridor from Puerto Leguízamo to the Ecuador border.
2. AOI 2 – Frontier Road Network (Puerto Asís–Mocoa Axis): Unpaved routes and secondary roads linking interior coca regions.
3. AOI 3 – Upland Agricultural Zone (Northern Caquetá): Transition belt between cleared forest and high-elevation cultivation zones.

AOI 1: Putumayo River Basin (April – June 2025)

Flood persistence and recovery across the lower Putumayo.

Spire’s Soil Moisture Insights for the lower Putumayo River Basin confirm a short but intense flooding phase followed by a rapid drying period.

Between April 5 and April 29, 2025, anomalies averaged +0.08 to +0.18 m³/m³, indicating sustained saturation along the river corridor near Puerto Leguízamo and neighboring lowlands. These conditions align with UN OCHA’s late-April 2025 situational update and InfoAmazonia’s reporting of river overflow and community displacement in Bajo Putumayo.

Figure 1a. Soil moisture anomaly map – April 12, 2025 (high saturation)

Beginning April 30, anomalies reversed sharply negative (–0.03 to –0.08 m³/m³) through May 12, showing that surface soils dried faster than climatological norms.

Figure 1b. Soil moisture anomaly map – May 5, 2025 (rapid dry-down)

This 7–10-day transition marks a critical shift from isolation to renewed accessibility, quantifying the short recovery window described in field reporting and supporting evidence of early logistical repositioning along river and forest tracks.

AOI 2: Puerto Asís–Mocoa Corridor (June – August 2025)

Dry-down and renewed overland accessibility across the interior frontier.

Spire’s soil-moisture anomaly data, as analyzed in the DeepInsights Cirrus platform, show a sustained drying trend across the Puerto Asís–Mocoa transport corridor during July 2025, confirming the terrain recovery described in field reports. Between June 20 and July 25, 2025, anomalies declined from near-neutral (+0.01 to +0.03 m³/m³) to markedly negative (–0.08 to –0.14 m³/m³), indicating rapid hardening of surface soils along secondary forest roads.

In late June, near-neutral anomalies (+0.01 to +0.03 m³/m³) reflected residual moisture from preceding rainfall. Terrain remained partially saturated, limiting vehicular access.

Figure 2a. Soil moisture anomaly map – June 20, 2025 (pre-dry-down)

By mid-July, negative anomalies (–0.08 to –0.14 m³/m³) extended across the Puerto Asís–Mocoa corridor, marking widespread surface hardening. This period corresponds to the reactivation of overland transport described in multiple field and media reports.

Figure 2b. Soil moisture anomaly map – July 17, 2025 (peak dryness)

By early August, partial moisture recovery (–0.02 to 0.05 m³/m³) signaled the end of the dry window, reducing road accessibility once again.

Figure 2c. Soil moisture anomaly map – August 11, 2025 (end of dry-down period)

In practical terms, this sequence marks the transition from water-logged to compacted soils – conditions that allow heavy vehicles and machinery to traverse previously inaccessible terrain.

By late July, these drier anomalies formed a continuous belt along the Puerto Asís–Villagarzón–Mocoa axis, suggesting a corridor-wide reopening of ground mobility. The spatial extent mirrors patterns visible in Sentinel-derived deforestation alerts and supports open-source accounts of intensified land clearing and road extension.

This one-month transition quantifies the environmental recovery window that reopened ground mobility and enabled road expansion across southern Colombia’s forest frontier.

AOI 3: Upland Caquetá Transition (September – October 2025)

Volatile terrain conditions and adaptive mobility at the frontier edge

Spire soil-moisture anomaly data for the upland Caquetá transition zone confirm the environmental volatility reported in open-source coverage from September to October 2025. This region, spanning the foothills around La Hormiga, Solano, and the upper Caquetá River basin, experienced rapid oscillations between saturation and dryness, creating unpredictable ground conditions that directly affected transport and enforcement access.

Between September 5 and September 20, 2025, anomaly values shifted from strongly negative (–0.10 to –0.15 m³/m³) to near-neutral (–0.01 to +0.02 m³/m³) within roughly two weeks, indicating abrupt re-wetting of previously hardened soils after heavy rainfall events.

Figure 3a. Soil moisture anomaly map – September 10, 2025 (dry-phase terrain)

By late September, renewed saturation (+0.06 to +0.12 m³/m³) spread across interior valleys and road corridors, followed by another reversal toward dryness in early October. These swings compressed normal seasonal patterns into short, irregular pulses.

Figure 3b. Soil moisture anomaly map – September 26, 2025 (re-saturation period)

In operational terms, these alternating phases reflect the “stop-start” mobility dynamics described in local reports: motorbike and mule routes reopening for days before becoming impassable again, and enforcement teams facing abrupt changes in ground trafficability.

This anomaly sequence quantifies that volatility, illustrating how soil conditions, rather than rainfall totals alone, govern real-world accessibility in Colombia’s southern uplands. Rapid shifts of 0.10 to 0.15 m³/m³ within two-week windows represent threshold crossings that can flip a route from passable to impassable.

The AOI 3 pattern reinforces the broader finding: Colombia’s coca frontier now operates as a pulse system, where environmental thresholds, not calendars, dictate movement. For intelligence and enforcement planning, daily soil-moisture monitoring provides the situational awareness needed to anticipate when those pulses will open or close.

Conclusion

Across Colombia’s coca frontier, Soil Moisture Insights validated how rapid environmental change governs accessibility, from flooded isolation to reopened corridors and volatile uplands, reinforcing the operational insights outlined above. These terrain-driven cycles define when operations, cultivation, and enforcement can move and when they cannot.

Spire’s DeepInsights™ Cirrus platform and soil-moisture visualizations capture these shifts with daily, global coverage and long-term baselines drawn from over 40 years of historical data, converting climate variability into operational foresight. Soil Moisture Insights are also accessible via APIs at 6 km, 500 m, and 100 m (custom) resolutions, allowing clients to integrate terrain intelligence directly into their existing operational workflows or decision-support systems.

Whether for defense, law enforcement, or environmental management, Soil Moisture Insights delivers a clear strategic advantage: the ability to see when terrain itself becomes the variable that determines success.

Extreme rainfall & flood report timeline

July 25, 2025 (Baoding, China)

On July 25th, 2025, northern China was hit by torrential storms, with Baoding (Hebei province) receiving nearly a year’s worth of precipitation in just a single day. In the Yi district of northwest Baoding, more than 448 mm fell within 24 hours, flooding streets, cutting power in villages, and damaging bridges and roads. The surge forced the evacuation of more than 19,000 residents across six townships.

In Zhuozhou, just east of Baoding, precipitation surpassed 190 mm by Friday morning, disrupting access to bridges and highways in a city that had already suffered severe flooding in 2023. Authorities in Baoding issued a “red alert” for heavy rain, while Hebei province elevated its emergency response posture in preparation for the storms.

Further north in Beijing, roughly 160 kilometers from Baoding, flash flood alerts were issued for four of its districts after forecasts projected more than 50 mm of rain between the afternoon of July 25th and the morning of July 26th. Officials warned of rising stormwater and landslide risk in the capital’s mountainous northern and western districts.

The storms also affected transport infrastructure beyond Hebei and Beijing, including Inner Mongolia, where rail services were suspended along numerous high-risk routes from July 25th to July 29th.

July 26, 2025 (Fuping, China)

On July 26, 2025, Beijing issued geological disaster warnings for ten of its sixteen districts, citing heightened risks of landslides and mudslides following consecutive days of torrential downpours. The alerts came as storms again swept through Hebei province, where Fuping County in Baoding recorded some of the most intense rainfall of the event.

At the Xizhuang weather station, precipitation peaked at 145 mm in a single hour, while totals reached 540 mm in just eight hours – surpassing Baoding’s average annual of around 500 mm.

The rainfall affected more than 46,000 residents in Fuping, with at least 4,655 people forced to evacuate. Flash floods and saturated slopes cut access across mountainous terrain, while state media highlighted the destructive force of the water that, in just two days, had matched or exceeded annual averages across different districts of Baoding.

National authorities extended flood warnings to eleven provinces, including Beijing and Hebei, warning of surging torrents in small and medium rivers and the need to ensure the safety of reservoirs and silt dams. Across northern China, cumulative precipitation pushed thirteen rivers in seven provinces beyond flood warning levels by as much as 1.4 meters.

In Inner Mongolia and Shaanxi, tributaries of the Dahei and Yanhe rivers registered their largest floods on record, while in northeastern Jilin province, two small reservoirs were operating above capacity, and five larger dams were activated to discharge water.

The storms reinforced a broader monsoon-driven pattern of extreme weather that has repeatedly tested China’s ageing flood defenses and threatened widespread disruption to infrastructure and local communities.

July 27, 2025 (Regional-Northern China)

On July 27, 2025, the flooding turned deadly as authorities confirmed the first fatalities of the event. State broadcaster CCTV reported that two people were killed and two others were missing in Hebei province, while thousands more residents were forced to relocate.

In Beijing’s Miyun district, floods and landslides struck rural towns, including Fengjiayu, where electricity and communications were cut and more than 3,000 residents were evacuated. The Miyun Reservoir reached record inflows of 6,550 cubic meters per second – pushing the capital’s main water supply system to its limits.

Forecasts warned that rainfall across Beijing’s northern districts could exceed 100 mm in six hours, raising the risk of additional slope failures and flash flooding in low-lying areas.

At the national level, the Water Resources Ministry expanded flood warnings across 11 provinces and regions, including Beijing, Hebei, Inner Mongolia, and Shaanxi. Officials highlighted the dangers of torrents in smaller rivers and stressed the need for close monitoring of dams and reservoirs.

Thirteen rivers across seven provinces were already reported above their flood thresholds, underscoring the systemic pressure the monsoon-driven storms were placing on China’s flood defenses and infrastructure.

July 28, 2025 (Miyun, China)

On July 28, 2025, the disaster deepened as heavy rain triggered a landslide in northern Hebei province, killing four people and leaving eight others missing. Authorities relocated more than 4,400 residents in Beijing’s Miyun district as flash floods and slope failures inundated rural villages. Images circulated on Chinese social media showed cars floating on submerged roads and floodwaters reaching the lower levels of residential buildings.

Electricity outages affected more than 10,000 people across the district, while officials confirmed that Xiwanzi Village in Shicheng Town had been severely hit, forcing an additional 100 villagers into emergency shelters.

The crisis placed renewed stress on the capital’s water infrastructure. After already reaching record inflows the previous day, the Miyun Reservoir continued to operate at peak levels of 6,550 cubic meters per second, straining dam capacity and prompting Beijing to issue its highest-level flood alert.

In Pinggu District, two high-risk road sections were closed due to slope instability, and across Shanxi and Shaanxi provinces, flash flood warnings were raised as rivers burst their banks and roads were swept by torrents.

National authorities expanded disaster relief measures. The National Development and Reform Commission allocated 50 million yuan (US$6.98 million) for recovery efforts in Hebei, targeting the repair of damaged roads, bridges, embankments, schools, and hospitals. Search and rescue operations were underway across multiple provinces, including Datong, where a driver went missing during the floods.

August 1, 2025 (Northern China, Regional)

By August 1, the cumulative toll of the flooding across Beijing and Hebei had risen sharply, with authorities confirming more than 70 deaths nationwide and dozens still missing.

In Beijing, the toll reached 44 fatalities, including 31 elderly residents who drowned after floodwaters from the Qingshui River engulfed a care facility in Taishitun, Miyun district. Nearly 80 people were trapped inside; while 48 were rescued, officials later acknowledged serious lapses in preparedness and evacuation planning for vulnerable populations.

Relief and recovery operations scaled up across the region. In Beijing, more than 104,000 residents were evacuated, over 300,000 people were affected citywide, and 24,000 homes sustained damage. The hardest-hit districts included Miyun, Yanqing, Huairou, and Pinggu. A joint civil-military command mobilized 6,000 soldiers and firefighters, backed by heavy machinery, to clear debris, reinforce embankments, and reopen blocked transport routes. By August 1, 364 of 424 rural roads were restored, and all cut-off villages had access to emergency water supplies.

At a press briefing, Beijing’s Executive Vice Mayor Xia Linmao described the floods as “one of the most severe natural disasters in decades.” Officials observed a moment of silence for the victims, while pledging stronger protections for the elderly, children, and other vulnerable groups, and committing to improving forecasting, early warning systems, and disaster planning for future events.

Spire soil moisture validation

July 25, 2025 (Baoding, Yi District, China)

Spire’s near-real-time soil moisture data captured the rapid transition from normal conditions to full saturation during the extreme rainfall in Baoding. The sequence below (July 23–25) illustrates how soils in Yi District shifted from baseline levels to extreme wetness in under 48 hours, following the reported 448 mm of rainfall by local Chinese outlets.

Soil Moisture Insights (6 km) in Baoding/Yi District, China for July 23, 2025 through July 26, 2025

Prior to the heavy rainfall, soil moisture levels across Baoding and the Yi District remained relatively stable, according to Spire’s daily updates on July 23 through July 25, with values hovering around 0.20 m³/m³ in most areas. Fields and river basins appeared within the normal seasonal range for late July, indicating that the ground was not unusually saturated in the days leading up to the storm. In other words, the soil still had plenty of capacity to absorb water.

By July 26, following reports of 448 mm of rainfall in under 24 hours, Spire’s near-real-time soil moisture data captured a dramatic shift. Values surged across Yi District, with localized cells showing >0.40 m³/m³, nearly double the levels from just two days earlier. This anomaly corresponds directly to the reported rainfall intensity and helps showcase how quickly the land transitioned from normal to flood-prone saturation.

In short, Spire’s soil moisture record not only validates the extreme rainfall totals reported in Baoding but also reveals the hydrological tipping point that turned heavy rain into a cascading flood hazard. The near-real-time spike made it clear that soils had lost their buffering capacity, ultimately amplifying runoff and increasing infrastructure risk.

This perspective goes beyond open-source rainfall reports, demonstrating how Spire’s data captures the land-surface response that ultimately drives disaster impacts.

July 26, 2025 (Fuping, China)

Spire’s anomaly data highlights just how exceptional the Fuping rainfall event was compared to the region’s long-term climatology.

Spire’s Soil Moisture Insights Anomaly maps (6 km) from July 24, 2025 to July 28, 2025 show soils transforming from neutral to drier than average to saturated as the flooding rainfall event unfolded.

On July 24, soil moisture anomalies across Fuping were primarily neutral to slightly negative, reflecting drier-than-average conditions leading up to the storm. Fields and slopes still had significant absorption capacity, a typical baseline for late July in central Hebei.

By July 25 into July 26, as storms intensified, localized anomalies began shifting positive, though much of the county remained within historical variability. This transitional state is consistent with reports of heavy overnight rainfall, but it shows that the soils had not yet reached total saturation across the basin.

After intense precipitation on July 26, the soil moisture anomalies showed a dramatic swing by July 27. Soil moisture values surged well above the 30-year baseline, with anomalies exceeding +0.18 m³/m³ in multiple cells around Fuping. This confirms that the county not only absorbed extraordinary rainfall but also quickly crossed into unprecedented saturation territory.

Spire’s validation demonstrates that the July 26 floods were not simply a function of short-term downpours but a departure from decades of climatological norms. The near-real-time anomaly signal highlights how soils transitioned from dry-to-average moisture into record wetness in less than 48 hours, amplifying slope instability and flash flood potential across mountainous terrain.

July 27, 2025 (Miyun District / Miyun Reservoir, China)

Spire’s near-real-time soil moisture data captured the rapid escalation of saturation across the Miyun basin as inflows surged into Beijing’s primary reservoir. The sequence below (July 25–27) illustrates how soils in the upstream catchment transitioned from moderately wet to fully saturated in under 48 hours, aligning with official reports of inflows peaking at 6,550 m³/s.

July 25, 2025: Historical context for soil moisture anomalies in Miyun District, China

Soil Moisture Insights (6 km) in Miyun District, China for July 26, 2025 through July 29, 2025

On July 25, soil moisture anomalies around Miyun and its northern catchments remained near seasonal norms, ranging from 0–0.12 m³/m³. Despite several days of rainfall, the watershed still held limited buffering capacity, indicating that the basin had not yet tipped into full saturation.

By July 26, soil moisture levels had risen sharply across northern Miyun and its adjacent mountain districts. Large areas exceeded 0.36 m³/m³, mirroring the surge in reported inflows at Miyun Reservoir. Localized anomalies highlight how soils were nearing full saturation, amplifying flood and landslide potential.

On July 27 into July 28, soils across the basin reached widespread saturation, with pockets registering above 0.48 m³/m³. At this stage, rainfall could no longer infiltrate the soil, converting directly into runoff and reservoir inflows.

This transition corresponds directly with eyewitness accounts of landslides, flash flooding, and record stress on the dam system.

Spire’s data validates the reported extremes while providing a crucial insight: the disaster was not only about rainfall intensity but also about soils losing their buffering capacity in real-time. This hydrological tipping point explains why Miyun’s inflows became unmanageable and why downstream flooding escalated so quickly.

July 28 – August 1, 2025 (Regional impacts across Northern China)

By July 28, the disaster had moved beyond isolated rainfall spikes to systemic impacts across Beijing and Hebei. Landslides in Miyun killed at least four people, flash floods displaced thousands, and images of submerged cars underscored the scale of the crisis. Electricity and communications were cut in multiple towns, while emergency shelters were filled with evacuees.

Spire’s soil moisture anomalies during this period remained at or above peak saturation, confirming that the land surface had lost virtually all buffering capacity. This prolonged waterlogging amplified slope

instability and sustained high inflows into Miyun Reservoir, which continued operating at record discharge levels.

By August 1, the official toll exceeded 70 deaths nationwide, including 31 elderly residents who drowned in a flooded care facility near the Qingshui River in Miyun. More than 300,000 people were affected across Beijing, with over 100,000 displaced and thousands of homes damaged. National authorities mobilized military and emergency forces for debris clearance, embankment reinforcement, and road restoration.

Final insights from Spire

Together, the open-source reports and Spire’s soil moisture record illustrate how an initial storm evolved into cascading hazards: floods, landslides, infrastructure failures, and tragic human loss. Spire’s validation highlights not only the rainfall intensity but also the sustained soil saturation that prolonged disaster conditions through the first week of August.

By pairing precipitation reports with near-real-time soil moisture validation, Spire shows not only how much rain fell but also how the land surface responded, providing deep insight that traditional rainfall data alone cannot offer.

Beyond this single event, near-real-time soil moisture data also reveal the hidden thresholds that drive disaster impacts worldwide. By tracking anomalies against decades of climatology, it becomes possible to identify when a basin transitions from stable to flood-prone, or when drought stress begins to erode resilience long before crops fail or infrastructure is compromised.

Delivered globally, with daily updates and field-scale detail, this intelligence is designed to scale across various missions, including agricultural yield forecasting, commodity trading, infrastructure risk management, humanitarian planning, and defense logistics. Combined with soil moisture forecasts, the ability to anticipate these tipping points enhances situational awareness by adding a predictive layer.

Background of seasonal conditions affecting soil moisture

From the start of Russia’s invasion of Ukraine in February 2022, weather and terrain have shaped battlefield realities, with very few factors proving more decisive than soil moisture. When Ukraine’s rich soils become saturated, they turn into deep mud that can immobilize tanks, stall convoys, and confine heavy artillery to hardened roads.

This seasonal phenomenon, known in Russia as “rasputitsa” and in Ukraine as “bezdorizhzhya”, has disrupted operations in Eastern Europe for centuries.

In both spring and autumn thaws, fields and backroads become sloppy pits of mud and water, forcing troops and equipment into narrow and often predictable corridors. For today’s mechanized military forces, these conditions translate into increased fuel consumption, higher breakdown rates, and most importantly, heightened vulnerability when mobility is constrained.

Soil moisture is not just a seasonal complication, either. It’s more accurately described as a tactical determinant. Days or weeks of heavy rainfall can quickly put the brakes on offensives, while a stretch of dry weather can unlock footpaths and accelerate advances. Both Russian and Ukrainian forces have been forced to adapt to these seasonal changes, shaping their operations as much around mud and rainfall as around enemy fire.

A string of soil moisture reporting (2022 – current)

Spring 2022: The Rasputitsa returns

One of the best examples of how rain and mud affect wartime operations came during the first months of Russia’s full-scale invasion of Ukraine. The Guardian and other outlets published images of Russian armored equipment stuck in the mud and vehicles abandoned or towed away by Ukrainian farmers.

With dirt roads and forest paths becoming impassable, convoys became easy prey for ambushes and artillery offensives, leaving paved roads as the only way forward. What was meant to be a fast-moving advance ended motionless in the mud, forcing Russian commanders to rethink their offensive strategy and pivot based on uncontrollable and hard-to-predict weather conditions.

The following year, the same seasonal cycle returned, once again bogging down both armies.

Late 2023: Mud slows operations down

In 2023, the same seasonal challenges returned. By November, both armies were once again slogging in Ukraine’s autumn mud. The War Zone, a news reporting outlet consistently covering the conflict, described how supply convoys stalled and the frontlines shifted into defensive holding patterns.

Reports from the Institute for the Study of War backed their reporting, noting that reduced maneuverability had occurred across eastern Ukraine as wetter-than-normal conditions left troops in fortified, defensive positions. For months, the battlefield was shaped less by offensive maneuver than by the environment itself.

As 2024 approached, commanders became familiar with the seasonal shifts and sought to anticipate the coming rains – launching offensives before the mud could close maneuver corridors again.

Autumn 2024: Rushed offensives before the mud strikes

Heading into fall 2024, forces looked to move before conditions deteriorated again. By early October, Russian commanders ramped up mechanized assaults in eastern Ukraine, especially across the Donetsk and Luhansk axes.

Analysts at the Institute for the Study of War noted intensified pushes toward Pokrovsk and Kurakhove, while Ukrainian spokespeople reported increased deployment of armored support to break through before seasonal rains turned the terrain into mud.

Fighting also escalated further north along the Kupiansk-Svatove-Kreminna line, a corridor already notorious for poor ground conditions that worsen sharply with autumn rainfall.

As the month wore on, these offensives collided with the realities of rasputitsa. Some battlefield descriptions conveyed that localized muddy zones in western Zaporizhzhia caused vehicles to become immobilized, with some reporting vehicles stuck so deep in the mud that they couldn’t see most of the wheels.

By winter 2025, however, the rhythm shifted once more, as frozen soils and bare landscapes reshaped the pace of operations.

Spring 2025: From slowdown to escalation

In early 2025, Russia’s offensive momentum had slowed dramatically. A Wall Street Journal analysis noted that in January, it took nearly six days to seize an area the size of Manhattan, roughly twice the pace as late 2024. Gains in February were even smaller, despite Russia sending tens of thousands of troops into areas near Pokrovsk and across Donetsk.

Several factors came together. Frozen, unstable ground limited mechanized maneuver, while leafless landscapes left Russian infantry exposed to Ukrainian drones. By late 2024, Russia had suffered hundreds of thousands of casualties, with many replacements poorly trained for the task at hand. Even mass assaults were blunted by Ukraine’s mix of artillery and drones.

The results were anything but significant. Russia captured only small towns, such as Kurakhove and Selydove, at a high cost, while the key logistics hub of Pokrovsk remained beyond reach. Analysts warned that Moscow’s armored reserves were running thin, forcing reliance on unprotected infantry and improvised vehicles.

By April, the environment began to change. Warmer weather and weeks of intermittent rainfall gave way to a steady drying of Ukraine’s topsoils. Donetsk’s fields, which were impassable in March, gradually hardened. At the same time, the first foliage returned, offering cover from overhead drones.

A snapshot of Spire Soil Moisture Insights time series near Kyiv, Ukraine. Soil moisture data at a 500 m resolution shows a notable drying trend throughout April 2025, punctuated by occasional upticks associated with rainfall events.

Together, these shifts altered both maneuverability and visibility.

On April 9th, Ukraine’s commander, General Oleksandr Syrskiy, warned that Russian assault operations had doubled in just a week. By mid-April, video footage captured Russian units advancing again with vehicles and infantry moving across newly hardened ground near Pokrovsk. The Wall Street Journal reported that Ukraine’s 14th Brigade stopped one such assault on April 17th, destroying dozens of vehicles.

Still, the significance of the moment was clear: after months of being slowed by mud and exposure, Russian forces were attempting to reintroduce mechanized movements into their offensives.

Ukrainian officers described the shift in stark terms.

The “liquid ground” described in March was giving way to firmer soil, opening pathways for armored vehicles that had been impassable for weeks. At the same time, the budding leaves along tree lines began to reduce the effectiveness of Ukrainian drones, making it harder to spot Russian positions and movements.

Analysts warned that these environmental shifts would gradually tilt the operational balance – not enough to guarantee breakthroughs, but enough to enable higher-tempo Russian assaults.

Spire’s data turns mud into measurable intelligence

While Ukraine’s war provides vivid examples of mud affecting regional military operations, the larger lesson is universal – the environment can dictate outcomes. The challenge is that most of these shifts have only been recognized after the fact, through on-the-ground reporting and field observation.

From March 2025 onward, Spire’s climate-anomaly data began capturing these dynamics in real time.

In Donetsk and surrounding regions, soil moisture levels rose above baseline during the March rains, aligning with reports of immobilized Russian vehicles. By mid-April, anomalies dropped back toward seasonal averages, signaling a reopening of maneuver corridors – the very window Russian forces exploited with renewed assaults near Pokrovsk.

How does Spire deliver unparalleled climate insights?

At Spire, we take a different approach to soil monitoring by listening, not just looking. Our satellites use a technique called GNSS reflectometry, which measures how GPS and other navigation signals bounce off the Earth’s surface. Because this method relies on radio waves rather than optical imagery, it works to collect data through clouds, smoke, and darkness – all of which are conditions that are nearly always present in conflict zones.

Once collected, this data is enhanced with AI and machine learning and fused with public datasets, resulting in our Soil Moisture Insights product. This dataset is updated daily with a 24-hour latency, allowing commanders to gain deeper insights into local and regional conditions.

Just as important, our data isn’t limited to simple snapshots. Instead, it’s built on a decades-long archive, which makes it possible to detect anomalies. In other words, users are able to see when the soil is much wetter or drier than the historical norm, delivering actionable intelligence at both tactical and strategic scales. Those anomalies serve as early warning signals for when routes will collapse into mud or when they will reopen and become accessible to heavy vehicles.

Accessing and applying Spire’s soil moisture insights

For analysts in the field, access comes in two ways.

1. Cirrus Data Visualizer: Spire’s browser-based interface allows users to draw an area of interest, visualize time series through meteograms, and export daily maps directly into reports.
2. Spire’s Weather API: The same data can be pulled programmatically, feeding straight into GIS platforms or route-risk scoring tools without human intervention.

Coverage is global, even in remote or traditionally under-covered regions, and does not require tasking. That means the same constellation tracking mud in Donetsk is also collecting over other global areas of interest at the same time. Behind it all is a scientific lineage rooted in GNSS-R and validated against ground-level truth, with performance comparable to NASA-aligned missions.

For defense planners, these insights are not theoretical. They provide an early-warning system to predict when terrain will open or close, a decisive factor in any modern conflict.

The need for more accurate weather forecasting

As climate change accelerates and weather patterns become more volatile, the need for more accurate weather forecasting is clear.

In fact, most of the world’s leading organizations have made this a priority. From NASA to the NOAA, from EUMETSAT to the Met Office, organizations around the world have made statements outlining the severity of the issue, the need for better climate and environmental data, and, ultimately, more accurate weather forecasting.

“As we confront the growing challenges of climate change, it’s crucial that we have robust and consistent methods for managing and sharing data in emerging fields like marine carbon dioxide removal.”
NOAA on the Importance of Environmental Data in Combating Climate Change

“NASA’s Earth-observing satellites provide societally important data and demonstrate transformative applications. The need for more data and better scientific information on Earth’s interacting systems has only increased in urgency in recent years, making investment in the work of NASA’s Earth Science Division (ESD) all the more vital.”
NASA on How Scientific Data Provides Crucial Evidence for the Impacts of Climate Change

“As Europe’s operational satellite agency, EUMETSAT is committed to taking the necessary steps to address climate change and its consequences through cooperative action. The climate data EUMETSAT collects and processes enable experts to better understand climate change and policymakers to mitigate further damage to the planet.”
EUMETSAT on its Commitment to Data-Driven Climate Action

The implications of climate change on weather forecasting

It is no longer deniable: climate change is transforming global weather systems and creating a new, more volatile reality, in which extreme weather events are becoming more frequent, more intense, and more complex to predict. While it’s not the case in every geographic location, average global temperatures are rising, leading to stronger storms, altered rainfall patterns, and shifting seasonal cycles.

Simply put, weather forecasting has become more complex and crucial than ever before.

How climate change affects weather events and seasonal climate

• Rapid Storm Intensification: Hurricanes and tropical cyclones are strengthening at unprecedented rates, leading to heightened states of risk for people, communities, and the natural world. Hurricane Milton, which made landfall in Florida in October 2024, is a prime example of how storms now intensify at record speeds. In just 49 hours, it developed into a Category 5 hurricane, with wind speeds increasing from 35 mph to 160 mph during that time. This kind of rapid intensification challenges traditional forecasting methods, especially those trained on historical patterns that no longer reflect the extreme storm behavior we’re seeing today.

• Unpredictable Rainfall Patterns: Areas that were once unaffected by heavy rainfall and drought are now seeing unexpected shifts year-by-year and, sometimes, season-by-season. Some regions, like certain areas across the Midwest that historically had mild spring and summer weather, are now experiencing floods and season-long droughts. These changes have led to unpredictable and fluctuating agricultural production, hard-to-manage water resources, and infrastructure issues that were not as common just a decade or two ago.

• Shifting Seasonal Patterns: Seasonal patterns are shifting, leading to some areas of the world enduring long periods of extreme heat while others experience record snowfall and ice accumulation. Since the shift in seasonal patterns is global in nature, managing global supply chains, infrastructure development, and disaster response is harder than ever.

How climate change complicates weather forecasting

While weather forecasting technologies have certainly improved over the years, this does not mean that the complexity of weather forecasting has become any simpler.

As discussed above, weather and climate trends are no longer following their traditional patterns, creating the need for complex technologies that can predict changes based on real-time insights rather than historical data and seasonal assumptions.

California is an example of a state that is notorious for experiencing droughts and wildfires most years. Still, the number of wildfires and water shortages we’ve seen in recent years is unprecedented, and these events are showing no sign of slowing down anytime soon. What’s worse is that these changes are skewing historical data so much that it’s becoming harder and harder to use it as a benchmark for forecasting.

In states like South Carolina and Georgia, tropical storms and hurricanes are now occurring more frequently than in previous decades due to rising sea surface temperatures. A 2022 study published in Nature Communications found that over the last four decades, climate change-induced increases in sea surface temperatures doubled the probability of “extremely active tropical cyclone seasons.”

Since ocean surface temperatures can change quickly and are affected by everything from currents to solar radiation (all of which are impacted individually by climate change), it’s become a much greater challenge to predict storms and extreme weather events as a result.

A real-world example: The El Niño Southern Oscillation

While climate change is certainly impacting specific geographic locations, it is taking a toll on things that arguably have greater implications.

The El Niño Southern Oscillation (ENSO) is a climate pattern that drives yearly variations in global weather phenomena, from simple rainfall patterns to complex hurricane systems and heat waves.

In the past, ENSO, which involves periods of warming (El Niño) and cooling (La Niña) in the tropical Pacific Ocean, has been a key factor in how weather patterns fluctuate globally. In the last couple of years, however, ENSO observations have behaved much differently than expected, complicating weather forecasting and creating new challenges in global climate predictions.

What has changed?

• Unusual Ocean Surface Temperatures: Although climate models have projected more frequent El Niño-like warming, observational data tell a more nuanced story. A recent study attributes this cooling in parts of the eastern tropical Pacific to enhanced upwelling, and even a La Niña-like sea surface temperature (SST) trend pattern, even as the western Pacific warms. This phenomenon arises from strengthened trade winds driven by human activity, which intensify upwelling of cooler, subsurface waters, offsetting the warming trend locally while increasing the zonal SST gradient.

• Increased La Niña Conditions: From 2020 to early 2023, the Pacific experienced an unusually long-lived La Niña event, one of the longest on record. While ENSO conditions are currently neutral, this prolonged cooling phase disrupted typical weather patterns across the Looking ahead, El Niño events are still expected to recur, but they may do so within an ocean landscape increasingly characterized by baseline warming. This matters because La Niña conditions can amplify hurricane activity in the Atlantic, increase drought risk in the southern US, and intensify typhoon development in Southeast Asia.

What is the impact?

• Harder to Predict ENSO Conditions: The discrepancy between observed and predicted sea surface temperatures is making weather forecasting much more difficult than it once was. Traditional climate technologies have failed to predict environmental factors like ocean upwelling and atmospheric flows over the Pacific successfully, creating significant variations in different climate models and weather As you might expect, this makes preparing and responding to significant weather events much harder and increases the risk for those in affected regions.

• Global Weather Changes: Prolonged periods of La Niña conditions will almost certainly create challenges in various parts of the world. For example, La Niña conditions are known to increase the risk of drought in the Horn of Africa, a region notorious for water scarcity and food security issues. With increased drought in the region, agricultural production becomes more challenging, ultimately exacerbating existing issues that already threaten local communities.

• Complicated Climate Projections: Long-term climate models play an important role in global economies, business operations, and With harder-to-predict ENSO conditions, long-term climate models become unreliable and worrisome, leaving everyone from individual farmers to national governments more vulnerable than ever to the changing global climate.

The economic impacts of inaccurate weather forecasts

It’s interesting to consider the dynamic between weather forecasting and global economics. While some might not have considered the correlation, others are fully aware of just how much the global climate can dictate trade and operations.

According to research from Deloitte, unchecked climate change could cost the global economy up to $178 trillion over the next half-century.

A large portion of those losses would stem from inaccurate or delayed weather forecasts and would almost certainly lead to a loss of human life. In fact, research from the Center for Economic Studies estimates that if weather forecasts were 50% more accurate than they are currently, it would save approximately 2,200 US lives per year.

While inaccurate weather forecasting poses at least some level of risk in most markets, some industries are more threatened than others.

Transportation

The transportation sector is highly vulnerable to the effects of climate change and inaccurate weather forecasting, which impact things like global supply chains, trade logistics, and public safety.

In aviation, for example, weather data and forecasting are crucial to operations and safety. Poor or delayed weather forecasts can result in flight scheduling issues, routing mismanagement, in-flight turbulence, prolonged flight times, cancellations, and accidents. According to the FAA, nearly 70% of all flight delays globally are weather-related, which collectively cost passengers and airlines upwards of $30 billion a year.

While most of the impacts on the aviation industry are economic, the impacts of poor weather forecasting on road transportation hold a different value. According to the US Department of Transportation, more than 5,000 people are killed in weather-related crashes every year, and more than 400,000 are injured. Of course, this also holds a pretty high economic loss, but the loss of life is and will remain the primary concern. With more accurate weather forecasting, it is undeniable that we could prevent such severe injury and loss of life at home and abroad.

And what about the maritime industry?

In the maritime industry, specifically maritime shipping, operations are highly reliant on weather forecasting and sea conditions. Shipping routes are managed based on wind patterns, ocean currents, swell fluctuations, and the shifting cycles of marine environments. When delayed or inaccurate weather forecasts impact operations, it has a similar effect to that of dominoes. Everything from supply chains to port operations is affected, which can cost the global economy billions. In fact, storm-related port disruptions cost the US economy around $7.5 billion every year, which is just a drop in the bucket on a global scale.

Energy

In the energy sector, unexpected weather events, like a heat wave or cold spell, can create miscalculations that severely impact the production and consumption of energy. Grid operators, for example, rely on temperature forecasts for managing heating and cooling demands. If conditions don’t unfold as expected, the miscalculations can result in significant financial loss.

When it comes to renewables, the impacts are relatively straightforward.

Solar farms rely on solar energy for production, and if a solar operator expects to produce a certain amount of energy over a particular period but fails to do so, it spells trouble for the energy market. If less power is generated than what was calculated from bad forecasting, a solar operator might not be able to satisfy the trade demand.

Wind farms are another clear example. When wind conditions don’t align with weather forecasts, less wind energy might be generated, which, again, impacts trade and wind energy value.

Storms and severe weather can also damage wind turbines and solar arrays, which might lead to repair and maintenance costs or even complete system overhauls.

These types of unforeseen events nearly always lead to energy trading inefficiencies and supply chain disruptions, resulting in substantial financial losses that impact governments and economies. While common, these instances could be prevented with better climate data and a more curated approach to how it’s applied.

Insurance

The insurance industry is facing new challenges due to the rapidly changing climate. Extreme weather events are developing faster than ever before and becoming more frequent and severe than in years past. When weather models fail to accurately predict the development or severity of incoming weather events, insurers are left scrambling to manage the resulting fallout.

Think about it. Every insurer, from agricultural insurers to automotive insurers to property insurers, is directly impacted by these types of weather events. When inadequate weather data leads to inaccurate or delayed forecasting, insured assets and commodities are impacted, leading to raised premiums for customers, higher insurance payouts, brand reputation damages, and more.

In a 2024 report, Swiss Re, one of the world’s biggest reinsurers, said that the insurance industry grossly underestimates the fallout from natural disasters and extreme weather events, creating some areas, at least across Europe, that the company considers “uninsurable.” The report stated that in recent years, weather models have been off by factors, estimating that global insured losses from natural disasters exceeded $100 billion for more than four years running.

Agriculture

The agricultural industry, which is inherently entangled with local and regional weather patterns, is becoming increasingly volatile when it comes to crop yields and harvest cycles.

Why? Well, crop yields are a direct result of how a farmer can manage their crop from seed to harvest. If extreme weather events, like droughts, floods, heat waves, strong winds, or other similar instances occur, crops can become stressed, limiting the full potential and output of the crop.

When seasonal shifts occur, it could also lead to crop and input mismanagement by the farmer. If a certain amount of fertilizer is required under specific rainfall conditions, for example, inaccurate forecasting could result in the incorrect amount of fertilizer being distributed across a field. This would undoubtedly result in less output at harvest, and could cost both the farmer and the local economy as a result.

While it’s hard to put an exact number on the economic benefit of accurate weather data in agriculture, some studies suggest that crop yields can be increased by 30-40% with more accurate weather forecasts.

Weather can also impact and disrupt supply chains. When perishable goods like agricultural harvests are delayed due to bad weather and inaccurate weather forecasting, trade loss is likely to occur, be it on a small scale for short disruptions or a much grander scale for longer delays.

Lastly, a bad year of weather can significantly impact the cost of commodity prices. When a year of bad weather results in less yield regionally or locally, supply-demand dynamics can drive up prices and create overwhelming pressure on vendors and food suppliers.

With more accurate weather forecasting and climate data, economic losses in the agricultural sector can be significantly mitigated.

A call for innovation: how Spire Global is revolutionizing weather forecasting

The biggest issue we currently face is that traditional weather forecasting methods are falling short. Weather forecasting has traditionally relied on terrestrial weather stations and dated satellite systems – neither of which can keep pace with today’s increasingly unpredictable weather patterns and need for near-real time decision making.

The solution? Better weather data, faster updates, and enhanced accuracy.

At Spire Global, we are pioneering new and innovative ways to improve global weather forecasting for the sake of people and the planet. Rather than continuing to settle for traditional weather forecasting tools, we have developed a new remote sensing payload that can fit aboard nanosatellites and operate easily in LEO.

These are called Hyperspectral Microwave Sounding (HyMS) sensors, next-generation instruments designed to overcome coverage gaps and data limitations in today’s weather forecasting systems.

Microwave sounders are widely recognized as one of the most impactful sources of weather data for improving forecast accuracy. However, despite the impact of these sensors, they have been limited by their sheer size and the limited number of sensing channels. Spire’s Hyperspectral Microwave Sounder (HyMS) is the next frontier for this powerful data source. By capturing hundreds of frequency channels, Spire’s HyMS sensors deliver deeper, all-weather atmospheric profiles from compact satellites in Low Earth Orbit (LEO), unlocking critical data even through clouds, storms, and severe conditions.

What advantages will Spire’s HyMS sensors offer compared to traditional sensing tools for forecasting?

• Near real-time atmospheric monitoring
• Improved vertical resolution throughout the atmosphere
• High spatial and temporal precision
• More accurate storm development predictions
• Better data integration
• Continuous, global coverage

The agricultural industry’s vulnerabilities in a changing climate

While many industries face threats from the rapidly changing global climate, agriculture is among the most severely affected.

The impact of rapidly shifting weather patterns

Those who work in agriculture know that changing weather patterns, season by season and year by year, are causing severe disruptions in food production. Weather and storm cycles are now so variable that farmers have trouble preparing for the following season. One of the only ways to build resilience is to become more diversified ahead of a “worst-case” scenario.

While diversification in farming can be beneficial, it can also mean lower profit margins, as different resources and strategies drive up operational costs.

The problem is that changes aren’t consistent. In fact, they are far from consistent. Rainfall patterns shift so much that a single location can see floods one year and droughts the following. When drought and flood events occur during planting or harvest, they can completely dismantle a growing season, leaving farmers to “pick up the pieces” and wait for their next opportunity.

The economic toll of extreme weather events

Extreme weather events do more than just hurt crops. They lead to sometimes irreversible financial losses that impact everything from global supply chains all the way down to individual households. When there are not enough products available to meet demand, you can expect everyone to feel the impact, from the grower to the consumer.

To make matters worse, some agricultural insurance companies are rolling back coverage and raising premiums, showing just how much financial loss can come from unpredictable weather patterns. In fact, crop insurance costs reached record highs in 2022, with crop insurance indemnities paying out over $19 billion to farmers that year.

The challenges of adapting to shifting weather patterns

While farmers have always needed to adapt to changing weather patterns and environmental conditions, the new level of unpredictability makes once-appropriate adaptation strategies ineffective at best.

But what can farmers do to build resilience to these often unusual swings in weather patterns?

• Diversify crops
• Improve irrigation methods
• Focus on soil management
• Plant climate-resilient crops

The examples above illustrate how farmers can prepare for unpredictability. However, each strategy requires significant effort, some of which drives down income due to higher operational costs or smaller harvests.

Without accurate, real-time weather forecasting data that can better predict temperature fluctuations, storms, and other stressful weather events, farmers are left scrambling for solutions.

The economic impact of inaccurate weather forecasting on agricultural supply chains

Having explored how climate change and sporadic weather patterns can affect agricultural production and global economies, let’s look at how inaccurate or delayed weather forecasting can impact food supply chains and end markets.

Disruptions to supply chains from poor weather predictions

Inaccurate or delayed weather forecasting can severely impact agricultural supply chains. Poor predictions can result in challenges with harvests, transportation, and trade, all of which disrupt the flow of goods and pressure regional and global food security.

How does this happen?

It’s just a bit of economics: supply and demand. When extreme weather events wipe out crop cycles, there is less supply, creating kinks in the global food supply chain. The only way to satisfy demand is to find new ways to fill the pipeline, which not only compounds the greenhouse gas emissions from supply chains (which are responsible for more than half of global emissions) but also drives up food costs for the consumer.

Economic losses from weather-related delays

Supply chains have many moving variables, and when weather-related delays occur, they can lead to significant economic losses, particularly when perishable goods like fruits and vegetables are involved. Often, food is shipped globally, not only regionally, so a delay of just a couple of days can lead to food becoming contaminated, growing mold, or rotting.

According to a study by the FAO, around 30% of food produced for human consumption globally is lost annually along the supply chain, a staggering amount of food and money, all things considered.

Price volatility due to uncertainty in weather patterns

Volatility is another concern in agricultural markets, often fueled by supply chain challenges stemming from poor weather predictions and changing environmental conditions.

If yields and harvests are less than expected in a given season due to challenges related to a changing climate, the commodity’s price can increase drastically in a short period. According to the World Economic Forum, climate change is the most significant factor contributing to rising food costs.

This inherently affects global food markets, creating volatility that can lead to economic instability, food insecurity, and famine, especially in countries or communities that rely heavily on imports (i.e., islands, remote locations, etc.).

HyMS sensor technology: enhancing weather forecasting for agriculture

Now that we know how climate change and inaccurate weather forecasting can affect everything from individual farmers to global food markets, let’s get into how companies like Spire Global are building resilience to the changes happening on our planet.

What is HyMS sensor technology?

Hyperspectral Microwave Sounding (HyMS) sensor technology is set to revolutionize the weather forecasting landscape. The sensors, which fit on a satellite the size of your standard carry-on luggage, provide more accurate atmospheric measurements than traditional microwave sensors used in the industry.

Compared to traditional weather data sensors, the fine-tuned atmospheric measurements from HyMS sensors can be used to predict weather events with far greater precision. How? Gathering data for temperature, moisture, and precipitation throughout the entire column (fine vertical level) of the atmosphere using the unique high spectral resolution of the sensor.

How does HyMS sensor technology work?

HyMS sensors passively measure faint microwave signals from the Earth’s atmosphere to the satellite in LEO, at a range of frequencies. Once received, they are used to understand current weather patterns and atmospheric conditions.

This method, which produces highly accurate and high-resolution insights, greatly benefits the agriculture industry. Understanding the conditions within the atmospheric environment and providing insights into hydrometeors, such as precipitation, has proven critical to better forecasting (and nowcasting) and should continue to drive innovation and improvements.

Timely atmospheric monitoring and vertical resolution

While HyMS sensors offer numerous benefits that position them as the future of data collection for weather forecasting, two key advantages stand out: their ability to provide timely observations from a planned constellation to assess and monitor atmospheric conditions and collect data across finer levels of the atmosphere and provide timely precipitation information, critical for agriculture.

Since accurate weather forecasting can make or break a growing season, farmers must be able to utilize timely weather data to avoid potentially catastrophic losses. The good news is that satellites equipped with HyMS sensors can collect this data without gaps, as they can receive data through all sorts of weather conditions and at night, enabling agricultural producers to react to changing weather and climate conditions before an event occurs.

When you combine the above with the ability to collect data on precipitation, storm formation, cloud movement, and pressure with greater accuracy and finer vertical resolution of the atmosphere, you have a revolutionary technology that drives change throughout the agricultural sector and beyond.

Global coverage and high precision insights

No state-of-the-art sensor can provide much insight or value without being able to monitor the area needed to make a real difference. While HyMS sensors can provide atmospheric data under nearly any weather condition and at all times of day, they won’t deliver the insights needed for enhanced global weather forecasting applications unless they are positioned in orbit at the right time and with the right trajectory.

Space-as-a-service companies like Spire Global operate expansive constellations of small satellites in LEO, enabling organizations to deploy HyMS sensors into space and ensure their coverage needs are met. Since Spire’s satellites can be developed and operated for mission-specific needs, it helps customers eliminate the costs of creating their own satellite fleets, collecting data only when and where needed.

Leveraging HyMS data to improve crop yield and mitigate risk

One of the most significant ways in which HyMS sensors provide value to farmers is by improving crop yields and mitigating risks associated with inaccurate weather forecasting.

Optimizing crop management with accurate forecasts

Accurate and timely weather forecasting empowers food producers to make better decisions about managing their crops and mending their fields for the coming years. With HyMS, farmers have a clear outlook on weather conditions, allowing them to plant, apply pesticides and fertilizers, and harvest at optimal times. Making more informed decisions about these matters is known as precision farming, which has been proven to improve crop yields significantly.

According to two 2021 studies, precision farming can increase yields by an average of 6%. That could mean hundreds of millions of dollars or more of economic inputs on a national and global scale.

Preventing crop damage from extreme weather events

It’s becoming more and more common in the United States and abroad. Extreme weather events like droughts, floods, heat waves, and storms are developing at a record pace, leaving little to no warning for those unequipped with the right weather insights. By utilizing weather forecasts developed with HyMS sensor technology, farmers can better prepare for extreme weather events.

How do they prepare? With advanced notice, farmers can take preventive measures, such as protecting their most valuable crops with covers, preparing additional drainage systems, and avoiding fertilizer applications before heavy rain. All of the above can save food producers a significant amount of money while increasing their resilience to future challenges.

Maximizing resource efficiency and reducing waste

Precision weather forecasting with HyMS can lead to far more effective research management than traditional predictions. With more insight into future weather conditions, farmers can reduce watering or pesticide applications before heavy rainfall, limit soil tillage ahead of heavy windstorms, or minimize soil disturbance ahead of heat waves – all of which can significantly improve resource use.

Building resilience with HyMS data from Spire Global

With the agricultural sector facing very real challenges due to unpredictable weather patterns and climate change, Spire recognizes the need for significant improvements in weather forecasting.

Spire’s HyMS-enabled constellations provide weather forecasters and climate scientists with highly accurate, timely weather data that can not only improve the state of agricultural operations but also limit risk and build resilience to the rapidly changing global environment.

Hyperspectral Microwave Sounding for weather forecasting

Before we jump in, let’s answer an important question. What is Hyperspectral Microwave Sounding?

Microwave sounders are crucial for weather forecasting models due to their unique capability to measure within and through the cloud layer. Out of all weather data, they consistently rank the highest impact observations in terms of weather forecast accuracy. Despite their significance, they have been limited in the number of sensing channels they observe. Hyperspectral Microwave Sounding (HyMS) significantly advances this critical remote sensing technique by collecting data across numerous frequency bands in the microwave spectrum. In other words, HyMS technology collects detailed information from the different ‘colors’ of microwave signals, even though these colors can’t be seen with the naked eye.

How is Hyperspectral Microwave Sounding used for weather forecasting?

HyMS sensors capture detailed profiles of the Earth’s atmosphere, measuring important atmospheric variables including temperature, humidity and precipitation. Since the sensors leverage fine spectral resolution across various microwave bands, they can collect data efficiently in all sorts of conditions, including dense cloud cover or heavy rainfall.

The data collected with HyMS enhances the vertical resolution of atmospheric soundings, enables greater accuracy of temperature and water vapour, and provides greater information content on hydrometeors (e.g., rain, snow, ice cloud). A major motive is also to ensure the resilience of this critical observation against the growing threat of radio frequency interference from sources such as 5G and future 6G. Overall, this next-generation hyperspectral approach will substantially improve weather forecasting capabilities.

What’s more is that since the HyMS was developed in a compact form, it can fit neatly on a 16U Nanosatellite platform, showcasing the abilities and advantages of miniaturized space technology for enhanced atmospheric profiling and weather forecasting. Allowing for a miniaturized satellite form factor that can operate in constellation scale in Low Earth Orbit, therefore bringing more reliable and constantly refreshed data from this LEO proximity of collection.

What makes HyMS a step change over traditional microwave sounder technologies?

HyMS technology has been shown through various studies to provide substantial advantages for weather forecasting, including but not limited to the following:

1. As with other microwave sensing technologies, environmental conditions like dense cloud cover or heavy rainfall will not stop data collection efforts from LEO. While visible and infrared sensors are severely limited in their ability to collect data under such conditions, microwave sensors can seamlessly collect data.
2. Spire’s hyperspectral sensor samples at fine (narrow) resolution across a broad continuous bandwidth (>16 GHz instantaneously) versus traditional microwave sensors, which sample only select parts of the atmospheric spectrum. Since each frequency interacts differently with varying levels of the atmosphere, it ultimately allows for more precise measurements of atmospheric parameters at different altitudes (higher vertical resolution). Sampling across the atmospheric spectrum for temperature and water vapour also improves the accuracy of these atmospheric variables.
3. HyMS sensors offer the ability to detect Radio Frequency Interference (RFI) sources from the emerging threat of 5G, future 6G, and telecom service satellites that are moving to higher microwave frequencies adjacent to critical bands. It can do this through its high-resolution sampling and signal processing methods that enable the detection and filtering out of unwanted signals from outside sources.
4. Spire’s progress towards a small satellite constellation of HyMS will improve our ability to observe the same spot on Earth at faster revisit rates, supporting the growing need for real-time weather monitoring and forecasting (Nowcasting).

Spire’s approach to commercializing HyMS-enabled technology

Here at Spire, we’ve developed a unique approach to atmospheric data collection and weather forecasting, pioneered with innovative technologies that bridge the gap between atmospheric observations and weather predictions.

There are three key stages of reaching the commercialization of HyMS-enabled satellites for weather forecasting.

1. Hyperspectral Microwave Sounding (HyMS)

In-Orbit Demonstration of Technology: Stage one involves the development and demonstration of Spire’s proprietary HyMS technology. RAL Space developed this novel sensor, and Spire won the NOAA contract to provide high-resolution atmospheric data by capturing fine measurements across different frequency bands of the microwave spectrum. Spire will undertake building the space mission, manufacturing the satellite for the sensor, devising the launch plan, as well as operations of the satellites once in orbit for the next 4+ years.

2. Operational Hyperspectral Microwave Sounder-Satellite (OHMS-Sat)

Stage two is the integration of Spire’s HyMS technology aboard a commercialized satellite platform. OHMS-Sat represents the transition from our ‘proof-of-concept’ to a practical and scalable solution for real-world weather forecasting applications.

3. AI-driven high-resolution forecasts

Spire will adapt its high-resolution AI weather forecasting models and assimilate the novel hyperspectral microwave data set to deliver advanced forecasting for downstream businesses critically dependent on accurate real-time weather forecasting, such as the renewable energy sector. The weather AI models are driven by the quality of the data they ingest. When combined with its established Radio Occultation data, Spire’s Hyperspectral Microwave Sounder (HyMS) will set new benchmarks for weather forecasting accuracy. These scalable sensors deliver an unprecedented update rate for monitoring rapidly evolving weather events. Paired with advanced AI forecasting algorithms, they not only improve forecast precision but also extend predictive capabilities further into the future.

Each of the above initiatives helps address the traditional limitations of weather forecasting by delivering high-resolution data, enhanced global coverage, and real-time atmospheric insights from satellites in Low Earth Orbit (LEO). Together, they compose a sequence of interconnected weather forecasting solutions, enabling us here at Spire to reinvent how the world approaches forecasting.

Spire’s innovative weather forecasting technologies in action

Spire x NOAA – HyMS-enabled on-orbit demonstration

Spire’s proprietary Hyperspectral Microwave Sounding (HyMS) sensor technology is gaining attention after being awarded a two-year, $4 million NOAA contract to enhance the value and accuracy of NOAA’s Numerical Weather Predictions (NWP). The contract will fund Spire’s in-orbit demonstration of its HyMS-enabled 16U nanosatellites, which will showcase the extent to which HyMS technology can improve nowcasting and forecasting capabilities.

This partnership builds on Spire’s history of successful collaborations with various government agencies, including NOAA’s prior contract with Spire for Radio Occultation (RO) data, and further demonstrates NOAA’s confidence in Spire to deliver actionable, scalable, and real-time insights into the world of weather forecasting.

How will HyMS support NOAA’s primary mission?

Spire’s HyMS-enabled nanosatellites will support NOAA’s mission by filling some of the most critical gaps in atmospheric data.

Traditional weather forecast systems utilize large-scale satellites (carrying multiple sensors and weighing ~ 4 Tonnes), this limits the number of satellites that can be launched and the technology update rate due to the costs and timescales involved with such large missions. Spire’s approach is to use an advanced digital backend enabled microwave sensor and miniaturisation approach. This will provide NOAA, and other NWP centres, complimentary observations to the larger weather satellites (that offer additional essential utility) by ultimately increasing the number of microwave sounders in orbit to improve global coverage. Spire’s unique hyperspectral digital back end approach will introduce new capabilities for enhancing Numerical Weather Prediction models including”.

• Improved vertical resolution of atmospheric temperature and water vapour
• Improvement in the accuracy of atmospheric profiles
• All-Weather Data Collection at High Spectral Resolution
• Radio Frequency interference detection and mitigation

HyMS innovations

This era of HyMS-enabled nanosatellites for weather forecasting is revolutionary for two primary reasons: high performance and miniaturization.

Historically, microwave sounders have been deployed on large multi-sensor platforms (e.g., JPSS or MetOP). Spire has now made significant progress by fitting the advanced capabilities into a small-form satellite bus. The compact design of Spire’s HyMS sensors can fit on a small satellite platform, reaffirming how weight, size, and cost reductions can be applied to atmospheric sensing technology in low-Earth orbit.

Miniaturization unlocks a constellation-ready system that will drive substantially improved life on Earth through better forecasting capabilities. This will be a future-proof observation system that is resilient to emerging radio frequency interference threats and highly complements existing and future government observation infrastructure.

Competitive landscape for HyMS technology

While weather forecasting technologies have been developed and improved decade after decade, Spire’s HyMS technology is making a unique mark on the history of meteorology.

Spire will be the first company to provide hyperspectral microwave weather data across critical temperature and water vapor bands in a satellite. Spire’s ability to combine its HyMS sensor payloads with miniaturized satellite platforms will position it as the frontrunner in cost-effective, scalable, and high-performance solutions moving forward. Beyond those basics, Spire is a global leader in space-based data services, allowing it to provide unmatched expertise to the weather industry and those operating within it.

Spire x STAR-Dundee/Met Office/STFC RAL Space – Operational Hyperspectral Microwave Sounder-Satellite (OHMS-Sat)

Building on the successes of the Hyperspectral Microwave Sounding (HyMS) in-orbit demonstration with NOAA, Spire’s OHMS-Sat project will be a pivotal milestone in the journey toward HyMS-enabled weather forecasting missions.

The ambitious OHMS-Sat initiative is a UK Space Agency-supported program spearheaded by Spire Global in partnership with STAR-Dundee, the UK Met Office, and STF RAL Space. The project will build on HyMS’s prior developments and accelerate its progress towards an operational mission that supplies weather forecasting data to global Numerical Weather Prediction (NWP) centers and creates new and unique weather products.

Collaborations & vision

Led by Spire Global and supported by the UK Space Agency (UKSA), the £4.9 million OHMS-Sat program includes a £3.5 million contribution from UKSA. The contribution comes through the UK’s National Space Innovation Program, which is making a £33 million investment to unlock growth and drive innovation in UK space technologies.

The OHMS-Sat program will asses HyMS in orbit data with the UK Met Office and build and launch the next iteration of HyMS, the Operational Hyperspectral Microwave Sounder – Satellite (OHMS-Sat), in collaboration with;

• STAR-Dundee Ltd, which will develop a state-of-the-art digital back-end ultra-wideband spectrometer, a critical component of the hyperspectral capability.
• The Met Office will carry out a study with the HyMS observations to demonstrate the impact of assimilation in a global NWP system and support airborne demonstrations of hyperspectral microwave sounding to further assess the potential impact of the data.
• STFC RAL Space will provide critical space-qualified mm-wave receiver components and calibration targets for space flight and on-ground testing before launch.

OHMS-Sat next steps

OHMS-Sat is the second stage of bringing Spire’s HyMS technology to its widespread adoption. The coming steps in this transition involve the distribution of funding for key developments, including:

• Testing and validation: STFC RAL Space will develop millimetre wave technology for the HyMS sensor payloads and ensure reliability throughout their operational lifespans in LEO.
• Data assimilation: The Met Office will evaluate the impact of hyperspectral data in existing global weather models to demonstrate the practical application of high-resolution data in an applied context.
• Commercialization: This will support the development of full-scale, commercialized satellite constellations that support Spire’s innovative HyMS payloads, which are designed to enhance global weather forecasting.

Spire x NASA/NOAA – Sounder for Microwave-based Applications (SMBA)

The team was awarded a $4.6 million, 12-month Phase A contract for NOAA’s Near-Earth Orbit Network (NEON) program and participated alongside Ball Aerospace, Northrop Grumman, and Orbital Micro Systems. Each contractor has been awarded a specific amount of money to develop and refine their microwave-sounding designs for LEO. Spire supported this Phase A study on the basis of its unique hyperspectral architecture and microwave expertise.

Building the backbone: Jon Beezley on Spire’s APIs and data infrastructure

Jon Beezley didn’t take a conventional path into weather tech, but his journey through applied mathematics and data assimilation and wildfire modeling research has uniquely equipped him to architect Spire’s robust API infrastructure.

With a Ph.D. in applied mathematics from the University of Colorado Denver campus, postdoc research at Meteo France in Toulouse, and a background in data assimilation and wildfire modeling, Beezley brings deep technical knowledge to Spire’s engineering team.

“I’m not a meteorologist, but I worked with WRF and statistical modeling, so I understand the data and how users expect to interact with it,” Beezley explained. “That familiarity with geospatial and weather data, in addition to my familiarity with backend architecture like APIs gave me the foundation I needed when I moved into backend engineering from academia.”

Today, as Principal Engineer, Beezely leads the design and reliability of Spire’s weather data APIs, which serve clients across sectors like maritime shipping, energy trading, logistics, and insurance.

“We support several data access patterns,” he explained. “There’s the file API, which subsets massive global forecast datasets. Then there’s the point API, which returns forecast data for a specific location. For maritime customers, we offer route-based APIs—forecasts along a moving track. And then there’s our Cirrus data viewer, which requires fast, responsive, visual access to all of this.”

Each of these requires careful architectural planning.

“With Cirrus especially, the data has to load instantly and visually. You can’t make a user download a massive grid file. So, we build access patterns that feel instantaneous while handling massive amounts of data.”

Spire processes tens of terabytes of weather data every day. But often, customers only need a single point forecast or a specific regional file.

“You can’t just load 10 terabytes into memory to return a few numbers,” Beezley, who has been at Spire for about four years, said. “So, a huge part of the job is designing efficient data delivery systems that are fast, scalable, and cost-effective.”

An image of a Spire Optimized Point Forecast for the Boulder Municipal Airport from May 15, 2025

Behind every decision is a delicate balancing act: minimizing latency and infrastructure cost while preserving accuracy and speed for customers who depend on real-time insights to manage risk and operations.

Learn more about our weather APIs & data solutions

Designing clarity from complexity: Jason Kent on the Cirrus user experience

While Jon handles the data plumbing, Jason Kent brings Spire’s forecasts to life, designing and developing the Cirrus data visualization platform to make powerful weather intelligence accessible and intuitive as a Senior Frontend Developer.

Like Beezely, Kent’s career journey to a frontend development at Spire wasn’t linear. He studied IT and computer science at the University of West Florida. His career began focused with web architect roles, before he pivoted toward a more programmatic and logic-based focus when he accepted a role in the Washington, DC, area as a JavaScript developer.

“My background is in web development and data visualization,” Kent explains. “Prior to coming to Spire, I worked on a tool called Worldview at NASA’s Goddard Space Flight Center, which let users browse hundreds of satellite datasets. When I found the job posting for Cirrus, it felt like the perfect match.”

Since joining Spire a couple of years ago, Kent has led the frontend development of Cirrus, focusing on efficiency, user experience, and visual clarity. Recent updates include:

• Last 10 Site Recall – Cirrus now remembers the last ten locations a user clicked, so frequent checks don’t require retyping or map searching.
• Layer State Restoration – The platform now picks up where users left off, restoring layer settings, filters, and views automatically.
• Layer Collections – Users can save and reload sets of layers and visual configurations tailored to specific workflows or weather phenomena.
• Threshold Filtering – Advanced controls allow users to highlight values within custom thresholds, improving data visibility and decision-making.
• GeoJSON Reference Layers – Users are able to overlay custom boundaries, such as service areas or points of interest, for richer context.

“Many of these changes seem small, but they save users significant time and mental load,” Kent said. “These updates make Cirrus more efficient. It’s all about letting users get what they need quickly—without reconfiguring the application.”

The most recent update with GeoJSON reference layers adds greater customizations for clients, with the ability to load in key supply chain routes, asset locations, etc.

Kent also works closely with early adopters like Dominion Energy to troubleshoot and refine features in real time.

“Jason Kent has been incredibly responsive and collaborative as we’ve worked with Spire’s Cirrus data viewer. His willingness to listen to feedback and quickly implement meaningful improvements has helped us get even more value from the platform in a short amount of time,” Jeff Mock, Lead Meteorologist at Dominion Energy, said.

What’s next for Cirrus? More dynamic data interaction. “We’re working on ways to animate and compare forecast issuances across time,” Kent explained. “The challenge is to make it intuitive, so users understand exactly what they’re seeing without needing a manual.”

A snapshot of the Spire High-Resolution Forecast on April 29, 2025, shows relative humidity values filtered to display values below 30%, sustained wind barbs filtered to show values over 15 mph, and wind gusts (color fill and values) above 15 mph, indicating areas of high fire threat.

Although they work on different ends of the stack, Beezely and Kent collaborate closely to ensure Cirrus and API systems connect cleanly.

Together, they support massive volumes of data, serve multiple industries, and create a seamless experience for users who need answers in seconds.

Coming soon: AI-driven ensemble forecasts and advanced visual interactions

One of the most anticipated updates—both from Beezley’s and Kent’s perspectives—is the integration of AI-powered probabilistic forecasts (AI-WX and AI-S2S) into Spire’s API and Cirrus suite.

“We’ve been adding the finishing touches to our AI ensemble forecast model output in our APIs,” Beezley said. “They’re going to unlock new probabilistic insights for decision-makers.”

On the frontend, Kent is preparing for what that means visually. “It’ll be just another product from a technical standpoint, but it’s an opportunity with huge potential to show uncertainty and variability in meaningful ways.”

Future enhancements in Cirrus will also include the ability to compare forecast model runs over time, animate changes, and deliver deeper insights through visual storytelling.

These updates aim to give Spire users the edge—whether they’re managing grid volatility, trading renewable energy assets, navigating ports, or optimizing assets across supply chains.

A snapshot of the Spire High-Resolution Forecast shows simulated radar, convective available potential energy (CAPE) values above 1,000 Joules/kg, and wind barbs indicating 0-6 km wind shear values above 30 m/s on April 17, 2025, amid an enhanced severe weather risk.

A shared passion for problem-solving

While they work in different layers of the stack, Beezley and Kent share a love of solving large, technical problems that have tangible real-world impacts.

“I enjoy staying current with new tech and building creative solutions on large-scale systems that solve hard problems,” Beezley said. “And I get to do that every day.”

For Kent, the motivation is personal, too. “I live in Colorado and love hiking, climbing, and backpacking. Cirrus helps me plan. When I’m heading into the mountains, I want hyperlocal detail. So, building a tool that does that—for me and for thousands of others—is really rewarding.”

And behind every click, load, or forecast update, they’re quietly orchestrating a system that brings satellite-derived and model data, and user context together, seamlessly.

“Jon and Jason are essential to shaping our customers’ experience. When it comes to weather and climate data, it’s not just about delivering raw information—it’s about providing the tools that help customers make sense of it,” said Chris Manzeck, Director of Product. “Through our APIs and the Cirrus interface, we enable users to contextualize and act on the data they receive from Spire, offering far more than just repackaged datasets.”

Their work is a testament to what’s possible when deep technical expertise and user-centric design come together—and it’s helping businesses turn weather data into a strategic asset.

Why validation matters

Satellite-based soil moisture products only deliver value when they reliably capture the key spatial and temporal variability that drives operational decision-making. To ensure our data meets the demands of decision-makers in the field, we’ve conducted a validation campaign using in-situ soil moisture measurements from a wide range of monitoring networks.

These ground-based measurements serve as a critical benchmark, allowing us to assess the performance of our retrieval algorithms across different soil types, vegetation covers, and weather conditions.

Our validation approach

We compared our satellite-derived soil moisture data against in-situ data from several well-established monitoring networks, including:

• COSMOS-UK
• TERENO in Germany
• USCRN in North America

The validation campaign covered a variety of geographic regions and climate zones, providing a robust assessment of the product performance under different environmental conditions.

Key results

In this section, we present two sets of results: (1) spatial maps of Spire’s 500-meter soil moisture product (D-ESSM) over the United Kingdom for January, April, July, and October 2020, alongside the locations of in-situ measurement sites from the COSMOS-UK network; and (2) six time series plots comparing Spire’s D-ESSM data with in-situ soil moisture observations from multiple stations.

D-ESSM

500-meter soil moisture over the United Kingdom

Figure 1. Spire D-ESSM over the UK for four dates in 2020, with placement of COSMOS-UK measurement network (black dots). Fincham and Heytesbury stations are highlighted (purple dots) as the locations of the validations below.

The following plots display daily soil moisture values, where Spire’s D-ESSM data (red circles, solid line) is compared against in-situ observations at 5 cm depth (grey x-marks, dashed line). This period spans over two full seasonal cycles, capturing the natural variability in soil moisture. The inset box reports key validation metrics, including bias, correlation coefficient (Corr), root mean square error (RMSE), and mean absolute error (MAE), which quantify the agreement between the datasets.

COSMOS-UK STATIONS

ESA CCI Landcover: Cropland, rainfed
Climate: Temperate Without Dry Season, Warm Summer
In-situ Instrument: TDT, Depth from 0.05 to 0.05 [m]

Figure 2. Comparison of Spire’s 500-meter soil moisture product (D-ESSM) with in-situ measurements at Fincham (UK station), from January 2020 to June 2022.

ESA CCI Landcover: Grassland
Climate: Temperate Without Dry Season, Warm Summer
In-situ Instrument: TDT, Depth from 0.05 to 0.05 [m]

Figure 3. Comparison of Spire’s 500-meter soil moisture product (D-ESSM) with in-situ measurements at Heytesbury (UK station), from January 2020 to June 2022.

TERENO STATIONS

ESA CCI Landcover: Cropland, rainfed
Climate: Temperate Without Dry Season, Warm Summer
In-situ Instrument: Hydraprobe-II-Sdi-12, Depth from 0.05 to 0.05 [m]

Figure 4. Comparison of Spire’s 500-meter soil moisture product (D-ESSM) with in-situ measurements at Merzenhausen (station in Germany), from January 2020 to June 2022.

ESA CCI Landcover: Tree cover, needleleaved, evergreen, closed to open (>15%)
Climate: Temperate Without Dry Season, Warm Summer
In-situ Instrument: Hydraprobe-II-Sdi-12, Depth from 0.05 to 0.05 [m]

Figure 5. Comparison of Spire’s 500-meter soil moisture product (D-ESSM) with in-situ measurements at Wildenrath (station in Germany), from January 2020 to June 2022. The in-situ measurements have a gap of more than 8 consecutive months starting from August 2020.

USCRN STATIONS

ESA CCI Landcover: Tree cover, broadleaved, deciduous, Closed (>40%)
Climate: Temperate Without Dry Season, Hot Summer
In-situ Instrument: Stevens-Hydraprobe-lII-Sdi-12, Depth from 0.05 to 0.05 [m]

Figure 6. Comparison of Spire’s 500-meter soil moisture product (D-ESSM) with in-situ measurements at Bowling-Green-21-NNE (station in US), from January 2020 to June 2022. The in-situ measurements have a gap of 12 consecutive months from January 2020.

ESA CCI Landcover: Mosaic herbaceous cover (>50%) / tree and shrub (<50%)
Climate: Temperate Without Dry Season, Hot Summer
In-situ Instrument: Stevens-Hydraprobe-lII-Sdi-12, Depth from 0.05 to 0.05 [m]

Figure 7. Comparison of Spire’s 500-meter soil moisture product (D-ESSM) with in-situ measurements at Durham-11-W (station in US), from January 2020 to June 2022.

Summary of results:

Our results show the accuracy and reliability of our soil moisture estimates. Here are a few highlights:

• High correlation with in-situ data: Across all validation sites, we observe correlation coefficients ranging from 0.7 to 0.94, depending on soil depth and site characteristics.
• Low bias and error: Root Mean Square Error (RMSE) values were consistently within 10% of the mean observed soil moisture, with minimal bias across seasons.
• Continuous, gap-filled coverage and consistent data: Unlike in-situ networks, which often suffer from data gaps and outages, our satellite-derived product delivers continuous, spatially and temporally complete soil moisture data, ensuring reliable insights even in regions with limited ground instrumentation.

What’s next?

Our upcoming whitepaper will dive deeper into:

• Validation methodologies (including temporal and spatial matching techniques)
• Breakdown of performance by biome, season, and land use
• Comparison with other existing soil moisture products
• Case studies showcasing real-world applications

Final thoughts

By combining data from L-band radiometers, GNSS-R, and SAR sensors, we deliver a soil moisture product that is both scientifically robust and enables critical, timely decision making for our customers. These sensors differ significantly in terms of revisit frequency, spatial resolution, and sensitivity to soil moisture which our proprietary AI-based algorithms take advantage of to produce high-resolution soil moisture data with daily updates.

Stay tuned for the full whitepaper later this year.

It’s important to note that we do not expect a perfect match between satellite-derived soil moisture and in-situ measurements. In-situ sensors measure soil moisture at a single point, typically at a fixed depth and location, and are often influenced by highly localized factors such as soil heterogeneity, vegetation cover, microtopography, and even sensor installation or maintenance issues.

In contrast, satellite-based products represent an area-average over a broader footprint (in our case, 500 meters), and integrate signals from the surface layer across that area. As a result, some level of discrepancy is natural and expected. Rather than seeking exact one-to-one correspondence, validation efforts focus on statistical agreement and overall consistency across time and space, which provide more meaningful indicators of product quality and utility. Comparisons with traditional sources give equivalency in customer workflows and demonstrate utility for application.

Hurricane preparedness isn’t just about evacuation plans

Hurricane preparation is often focused on coastal evacuations and sandbagging, which are vital for safeguarding communities and mitigating flooding risks. However, for businesses, the checklist goes much deeper:

• Grid operators must assess grid hardening strategies and identify which assets are most vulnerable to outages and damage from hurricane-force winds or flooding.
• Traders need to align positions with real-time weather insights to minimize exposure to price volatility driven by refinery shutdowns, fuel demand shifts, or power generation losses.
• Agricultural firms should revisit planting schedules, harvest timelines, and storage logistics.
• Logistics and freight operators should pre-plan alternate transport routes, reposition assets, and coordinate with clients in vulnerable supply chains.

“Storms like Hurricane Helene and Hurricane Harvey show how impacts can extend far beyond the point of landfall, especially when it comes to flooding and extreme rainfall,” Spire Meteorologist and Expert Risk Communicator Rhiannon McDermid said. “As hurricanes grow stronger and bring larger-scale impacts, with some indications that greater rainfall amounts are linked to climate change, businesses well inland may face risks they’ve never encountered before. It’s critical to expand preparedness beyond the coast.”

Having timely, high-resolution, and accurate forecasts well in advance of disruption can be a significant differentiator.

Forecasting with precision: Why lead time matters

Longer lead times translate directly to better decisions—from adjusting vessel routes to hedging risk. Today, satellite-derived weather data, AI-enhanced forecasts, and probabilistic models allow businesses to gain earlier insights into potential disruptions.

Spire Weather & Climate’s space-powered forecasts deliver:

• High-resolution hourly forecasts that track storms and impacts up to six days in advance
• AI ensemble weather and sub-seasonal models (AI-WX, 20 days out, and AI-S2S, up to 45 days out) that reduce uncertainty and improve medium-range and long-range probabilistic risk assessment
• Decision support from an around-the-clock team of meteorologists, with expertise in risk communication, and our DeepVision™ risk management solution
• Global marine weather forecasts delivered through our Deep Navigation Analytics™ solution help to safeguard shipping and offshore operations
• Sector-specific forecasts and solutions for utilities, energy, agriculture, and logistics

Businesses leveraging these capabilities are able to act faster and with more confidence—whether it means scaling back offshore activity or optimizing energy portfolios.

The hidden risks of hurricane season

Wind speeds and rainfall often dominate attention, and for good reason as exhibited by the impactful 2024 hurricane season that dealt major blows from Hurricanes Beryl, Helene, and Milton. But the broader impacts of hurricanes can be financially detrimental in less visible ways, including:

• Supply chain disruptions: Temporary port closures, damaged rail lines, or washed-out roads can cause cascading logistics delays in affected regions.
• Data center vulnerabilities: Storm surge or flash flooding in unexpected regions can threaten backup systems and business continuity.
• Volatility in commodity and energy markets: Even distant hurricanes can rattle commodity prices or disrupt demand forecasts across regions not directly impacted.
• Worker safety and insurance risk: Displaced workforces and increased liability risks can delay projects and raise operational costs.

Understanding these ripple effects helps businesses prepare more comprehensively.

10 smart steps for business hurricane resilience

From supply chain disruptions to operational downtime, hurricanes pose multi-faceted risks to businesses. With storms growing more intense and erratic, resilience demands more than a weather eye. Here are ten proactive steps to help safeguard your operations before, during, and after landfall:

1. Audit critical operations: Identify facilities, infrastructure, supply chains, and personnel most vulnerable to storm impacts.
2. Leverage probabilistic forecasts: Use ensemble and risk-based outlooks and meteorologist support to drive scenario planning. Relying solely on deterministic track forecasts can leave your business at risk from far-reaching hurricane impacts.
3. Establish and communicate emergency action plans: Develop site-specific hurricane protocols, evacuation routes, and safety procedures, and ensure all employees are trained and clear on their roles.
4. Review and strengthen insurance coverage: Reassess policies annually to confirm adequate protection against flood, wind, and business interruption.
5. Streamline internal and external communications: Empower employees with clear emergency procedures, communication plans, and tools to remain safe and informed in a storm event. Ensure customers and stakeholders receive clear, consistent, and timely updates.
6. Evaluate and secure infrastructure: Reinforce physical structures, invest in flood barriers, and manage tree canopies or nearby hazards that could damage property.
7. Plan for secondary disruptions: Anticipate cascading effects like fuel shortages, transportation delays, and limited contractor availability.
8. Develop flexible continuity plans: Establish work-from-home capabilities, backup data centers, and alternate locations for time-critical operations.
9. Run hurricane-specific simulations: Conduct tabletop exercises tailored to your sector to uncover gaps in crisis response and recovery procedures.
10. Assess vendor and partner readiness: Confirm business partners and key suppliers have continuity plans aligned with your resilience standards.

As hurricane risks evolve, so must the way businesses interpret forecasts and build resilience. The best time to prepare is long before the next storm develops, and ideally, well ahead of hurricane season.

Weather intelligence as a strategic advantage

Too many companies treat weather as non-essential, until it’s too late. Leading organizations are integrating weather intelligence into their day-ahead, week-ahead, and seasonal planning processes, translating forecasts into ROI-driven decisions.

Spire’s solutions are built with B2B use in mind, combining proprietary satellite data with advanced modeling to deliver tailored insights for:

• Utilities and energy operators managing outage risk and generation variability
• Traders optimizing portfolios around supply shocks and market swings
• Insurance and finance evaluating risk exposure for underwriting and claims
• Logistics and transportation planning asset movements ahead of storms

The bottom line to protecting your bottom line: Prepare and act earlier to stay resilient

Hurricane season doesn’t just test the strength of your infrastructure—it tests the strength of your foresight. With intelligent weather insights and sector-specific planning, businesses can turn potential disruption into an opportunity to lead with resilience.

The 2025 season will bring uncertainty. But with the right tools, you don’t have to face it unprepared.

Weather data in advertising—a proven tool, now smarter than ever

Traditional weather forecasts paint broad strokes—regional outlooks, generalized conditions. But Spire’s weather data is anything but traditional. It’s hyper-local, real-time, and powered by one of the world’s largest satellite constellations, capturing granular atmospheric insights via Radio Occultation and other cutting-edge technologies.

For advertisers, this is a game-changer. It means moving beyond the vague “chance of rain” to pinpointing exactly when and where that rain will fall—and acting on it with precision. Think personalized, timely campaigns that automatically trigger when environmental conditions align with consumer needs.

Because let’s be honest: weather drives behavior. Whether it’s craving sunscreen or reaching for allergy relief, context is everything—and context is exactly what Spire delivers.

From the sky to the screen: Seamless integration with DSPs

Spire’s data feeds directly into programmatic platforms through streamlined APIs, empowering Demand-Side Platforms (DSPs) to trigger ads the moment they’ll matter most. Picture this: a sudden drop in temperature in Chicago, London, Paris, Stockholm, Taipei, Beijing, or Tokyo? Winter apparel ads fire. A rise in humidity in Houston, Cape Town, Dubai, Mumbai, or Singapore? Deodorant promotions go live.

This isn’t theoretical. It’s automated, real-world execution that is seamless, smart, and scalable.

Industries already winning with weather-triggered campaigns

Industries where weather and consumer behavior are closely linked—retail, QSR, travel—are already reaping the rewards.

Take a major sports apparel brand: by aligning ad placements with sunny, mild days perfect for outdoor workouts, they saw a measurable spike in engagement and sales. Or a QSR like McDonald’s, which dynamically shifts its messaging based on current conditions—think cold drink promos on scorching days, hot coffee when it cools off.

Weather-based advertising works because it taps into real-time need and immediate intent.

Beyond rain or shine: Unlocking niche conditions for nuanced targeting

What sets Spire apart is the depth of insight. We’re not just talking temperature—our data allows for nuanced targeting based on humidity, UV index, and more. That means advertisers can trigger campaigns for skincare when the UV is high, or frizz-fighting hair products on humid days.

This is hyper-personalization without invading privacy.

In essence, our data empowers brands to create more dynamic and effective campaigns, responding to a wide range of real-time weather conditions that directly impact consumer behavior.

Cookieless and compliant: A privacy-first approach to targeting

As privacy regulations tighten and the world moves towards a cookieless future, weather data offers a privacy-compliant solution for audience targeting without relying on personal identifiers. Since weather data is anonymized and based on environmental conditions, it doesn’t involve tracking individual users, making it an ethical alternative to traditional targeting methods that rely on cookies and personal data.

Spire helps brands reach consumers based on shared environmental experiences rather than personal data. It’s compliant, future-proof, and remarkably effective.

AI-driven weather insights: Predict, don’t just react

Spire is a leading weather data provider and an early adopter in the AI weather space. With our global data assimilation and weather prediction team, we’re building cutting-edge AI-driven weather models to deliver medium and long-range forecasts. In partnership with NVIDIA, Spire is consistently innovating at scale, making us well-positioned in this rapidly evolving field.

AI plays a crucial role in enhancing Spire’s weather data offerings by enabling predictive analytics that help advertisers anticipate and respond to shifts in consumer behavior. By leveraging AI, advertisers can analyze vast amounts of weather data to spot patterns and trends that influence purchasing behavior.

For advertisers, this means more accurate forecasting and real-time, data-driven decision-making. AI optimizes campaign timing, ensuring ads are triggered precisely when weather conditions align with consumer intent.

This sophisticated approach enables brands to stay ahead of the curve in the programmatic space, ensuring their campaigns remain relevant and highly responsive to immediate, weather-driven consumer needs. It’s proactive, not reactive—and that’s a huge edge in today’s fast-paced digital landscape.

Cut wasted impressions. Optimize spend. Drive results.

Every wasted impression is a missed opportunity—and wasted budget. With Spire’s real-time weather insights, advertisers can minimize ad spend on irrelevant audiences and maximize ROI by targeting when conditions are optimal for conversion.

It’s not only about more impressions. It’s about smarter impressions.

Fueling DCO with real-time relevance

Dynamic Creative Optimization (DCO) thrives on timely, tailored messaging—and weather data supercharges that. Swap a raincoat for sunglasses depending on the forecast? Done. Adjust imagery, copy, even call-to-action in real time? Absolutely.

This level of contextual relevance boosts engagement, improves click-through rates, and enhances the consumer experience.

Overcoming adoption hurdles with trusted support

Coming from a media background, I’ve seen the challenges advertisers face when adopting weather-based targeting. One of the main hurdles is data integration – ensuring that weather data seamlessly fits into existing ad tech stacks and workflows. Another challenge is ensuring data accuracy and reliability, especially when making real-time decisions in executing media campaigns.

Integrating weather data doesn’t have to be daunting. Spire’s team offers robust API solutions, hands-on support, and the reliability of satellite-driven accuracy. We partner with agencies and brands to ensure smooth implementation and real-time execution, helping them navigate the shift with confidence.

The forecast for advertising

Looking through the remainder of 2025 and beyond, weather data will play an even more central role in the evolution of programmatic advertising. As advertisers seek to enhance relevance and precision at scale, hyperlocal weather insights will become more deeply integrated with other data sources, such as consumer behavior and location data. This convergence will enable real-time, dynamic targeting that is highly contextual, and more personalized than ever before.

Expect predictive models and deeper integration across digital ecosystems. Weather will become a foundational layer in how brands connect with audiences in a way that is relevant, responsive, and remarkably resonant.

Programmatic advertising is evolving. Spire’s precision weather data ensures you’re not just keeping up—you’re staying ahead.

Why weather drives electricity price volatility

Traditionally, power generation relied on dispatchable sources—coal, natural gas, nuclear—where utilities adjusted output based on demand forecasts. Weather mattered, but primarily for predicting consumption. Now it dictates production, too.

As renewable energy production climbs past 20% and approaches the 30% threshold of total electricity production, price volatility spikes. Why? Because solar and wind can’t be switched on at will. Batteries can’t yet scale fast enough to store surplus energy. Electricity supply is now at the mercy of the weather. Also, when demand and supply don’t align, prices swing—sometimes dramatically.

For today’s energy market, weather now influences all three variables:

• Demand (heat waves or cold snaps drive consumption)
• Supply from solar (dependent on sun exposure)
• Supply from wind (dependent on wind patterns)

This makes weather one of the most potent market drivers—and one of the most lucrative, if you know how to predict it. The result is an energy economy where anyone with flexible electricity usage can think like an electricity trader.

Leveraging weather-driven energy volatility as a strategic business advantage

Consider Bitcoin miners: their operations devour electricity. But in some markets, electricity prices go negative when there’s too much renewable supply. Miners who can forecast those periods profit by consuming energy when it’s cheapest or even when they’re being paid to take it off the grid.

Tech giants like Google are leading the way in weather-driven energy management. Google leverages energy trading to optimize its data centers, shifting operations to low-cost or negative-price periods, capitalizing on renewable energy volatility. Besides optimizing the processing of data that isn’t time-sensitive, Google also dynamically changes its source of electricity. This strategy not only reduces costs but also aligns with Google’s net-zero goals by 2030, showcasing how businesses profit from energy volatility.

Manufacturers are catching on. If a factory can shift its operations to run during off-peak, low-cost hours, it can slash expenses.

These companies aren’t just reducing costs—they’re strategically responding to market signals like a commodity trader would.

This is especially crucial in regions like Europe and Texas, where renewable penetration is significant and price volatility is frequent. The ability to forecast price movements and respond in real time is emerging as a competitive differentiator.

According to the IEA, renewable energy market volatility strategies are critical as wind and solar surpass coal.

This graphic shows Spire’s AI-powered Power Generation Forecasts for Germany with wind power generation (top) versus solar power generation (bottom).

The power of AI-driven weather forecasts for renewable energy trading

This new paradigm demands more than a five-day forecast. Traditional physics-based weather models were built for deterministic forecasts. But in energy markets, the profit often lies in the tails—those rare, high-impact events. That’s where AI comes in.

AI-powered weather forecasts for renewable energy production enable traders and companies to predict wind and solar output more accurately. Modern AI-driven weather models, like Spire’s ensemble sub-seasonal and weather forecasts (AI-S2S and AI-WX), generate 200 and 30 forecast simulations, respectively, mapping probability distributions rather than single outcomes. Instead of a simplistic “it will be windy,” traders see the likelihood of a range of wind speeds—and the price implications that follow.

For example, a utility forecasting a sudden drop in wind generation can activate reserve power sources in advance, avoiding costly penalties for under-delivery. Commodity traders can hedge against low solar output days or seize short-term buying opportunities during windy periods.

Direct-to-asset forecasting: The next frontier in energy trading for industry

Looking ahead, AI won’t just forecast the weather—it will forecast power.

Instead of a two-step process (weather forecast → generation estimate), AI will be trained to predict energy output at the asset level. A turbine in Oklahoma or a solar farm in California could have a bespoke model trained on hyperlocal data and historical performance.

This direct-to-asset AI modeling improves accuracy, optimizes bidding strategies, and helps energy providers and consumers align production and use more effectively.

Risk, reward, and reframing volatility

Volatility is often framed as a risk. But businesses that can anticipate it and adapt are better positioned to turn it into profit.

A Boston Consulting Group report put it simply: every company needs to think like an energy trader now. Electricity isn’t just a cost—it’s a controllable input.

With AI forecasts and access to probabilistic weather insights, energy-intensive industries can optimize when they operate, where they source power, and how they hedge risk.

And it’s not just tech or manufacturing that stand to reap the rewards. Any organization with significant electricity demand—from retail distribution hubs and water treatment plants to cold storage facilities—can participate. Those who don’t manage this risk are being left behind.

Space-powered weather intelligence for managing energy price volatility

As climate change accelerates, the baselines are shifting. A windier-than-normal season may now be the new normal. Companies focused on compliance; like those disclosing under new SEC climate risk rules; need intelligent, evolving forecasts that reflect changing climatology.

Spire’s satellite-driven weather intelligence helps businesses do just that—from AI-driven 45-day sub-seasonal forecasts and solar and wind power generation forecasts to high-resolution weather forecasts.

Electricity is no longer just a utility, it’s a tradable asset. And in a future defined by volatility, climate change, and competition, the smartest companies will be those that treat weather as a strategic input—and forecasting as a financial edge.

Why does near real-time soil moisture data matter?

Reducing data latency has been one of the most common requests from our clients. By delivering near-real-time soil moisture data, Spire is unlocking a broad range of time-sensitive, high-impact applications, including:

• Early warning systems for drought, flood and wildfire risks

• Soil moisture forecasting for agriculture and hydrology
• Risk assessment for insurance and financial sectors

With this latency cut—from 96 hours to under 24 hours—Spire makes satellite-based soil moisture data significantly more valuable for real-time decision-making and operational use cases.

Temporal comparison of Spire’s 500 m soil moisture product over South Texas. Previously, a March 30 request would return data from March 26 (left). With the new sub-24-hour latency data stream, users access more recent observations (right), revealing higher soil moisture levels that contrast with the drier conditions shown in the four-day latency product.

How did Spire achieve sub-24-hour soil moisture data delivery?

Achieving sub-24-hour global soil moisture delivery required a significant engineering effort, driven by two key innovations:

• Expanded access to low-latency satellite data. We broadened our data ingestion pipeline to incorporate additional low-latency observations from Spire’s GNSS-R LEMUR satellite constellation—including the recent launch of two new GNSS-R satellites—as well as external datasets such as NASA’s soil moisture measurements.
• Optimized processing infrastructure. We enhanced our cloud-based processing system to efficiently manage large volumes of satellite data, enabling faster computation and seamless delivery at scale.

These combined improvements allow Spire to deliver high-resolution, gap-filled soil moisture data with global coverage in near real-time—empowering users with faster, more useful insights.

What makes Spire’s near real-time soil moisture intelligence unique?

Spire’s soil moisture product stands out thanks to a combination of technical precision, consistency, reliability, and usability. The key differentiators include:

• High spatial resolution, available down to 100 meters
• Daily global observations, delivered at 12:00 pm local time
• Low latency, with data available in less than 24 hours
• Spatio-temporal gap-filled coverage, ensuring consistency
• Global scale, with seamless integration

The gap-filling capability is particularly valuable for Earth observation and AI applications. By providing harmonized, ready-to-use datasets, Spire eliminates the need for extensive calibration and validation steps. This allows users to integrate soil moisture data directly into models and decision-making workflows, without dealing with missing values or preprocessing challenges.

Direct comparison of Spire’s 500 m soil moisture product over southern Italy: four-day latency (left) vs. new one-day latency (middle). Both reflect the same date, with minor differences (right) due to variations in sensor data inputs—demonstrating the high quality of Spire’s new near-real-time product.

What’s next for Spire’s Soil Moisture Insights?

2025 is shaping up to be a transformative year for Spire’s Soil Moisture Insights products. Our development roadmap is focused on delivering even more value to both existing and future clients.

As our satellite constellation grows, the system is designed to scale naturally, further reducing latency and improving data resolution. We’re also continuing to refine our processing pipeline to boost accuracy, speed, and geographic coverage.

Most importantly, we’re committed to listening to client feedback—integrating new features and enhancements based on user needs. Whether you’re building AI models, managing agricultural risk, or monitoring climate conditions, Spire’s soil moisture data will keep evolving to power your most critical decisions.

Harnessing AI for medium-range weather forecasting

Spire’s AI-WX leverages deep learning techniques to perform global weather forecasting with exceptional speed and scalability. Rather than relying solely on traditional numerical weather prediction (NWP) models, which are expensive and time-consuming to run, AI-WX uses one of the world’s top-performing open-source AI models adapted with Spire’s proprietary data to generate forecasts far more efficiently.

“Training an AI model can be resource-intensive, but once it’s trained, running a forecast—or inference—is dramatically cheaper,” said Dr. Luis Vela, Spire’s Senior AI Weather Scientist. “In some cases, inference is up to 1,000 times more efficient than traditional NWP. That cost savings opens the door to running more ensemble members, which means better forecasts.”

Where traditional NWP systems often rely on CPUs and are limited by hardware constraints, AI-WX is optimized for NVIDIA GPU-based acceleration. This not only improves computational efficiency but also enables frequent model updates—AI-WX runs four times a day, delivering fresh forecasts for every six hours out to 20 days.

AI-WX operates at 0.25° resolution (~25 km grid), capturing localized conditions with global scale—ideal for both regional and international operations.

Spire’s AI-WX forecast initialized on March 27, 2025, at 12z shows 12 ensemble forecasts for 100-m wind speed and mean sea level pressure predictions on April 3, 2025 (168 hours in advance). AI-WX has 30 ensemble members operationally.

The power of 30 ensemble members for probabilistic risk analysis

At the heart of AI-WX is its ensemble-based design. With 30 members per forecast run, the model provides a probabilistic view of the future atmosphere, rather than a single deterministic scenario. This probabilistic approach enables businesses to quantify uncertainty, assess risk, and make more informed decisions.

“You’re not just getting one outcome—you’re getting 30 possible futures,” said Dr. Vela. “If they cluster tightly, confidence is high. If they spread out, there’s more uncertainty. This is especially valuable in industries where wrong decisions have real costs.”

Unlike many AI models that assume a simple Gaussian distribution (bell curve), AI-WX can capture more complex patterns, including bimodal outcomes. This added insight helps users interpret extreme or less likely scenarios that could otherwise be missed.

“Instead of saying ‘this will happen,’ we say: ‘here are 30 ways it could play out, and here’s how likely each scenario is.’ That’s the future of forecasting,” Vela added.

Spire’s proprietary data advantage with AI-driven medium-range weather forecasting

What makes AI-WX stand out among emerging AI models is the quality of its input data. Spire operates one of the only commercial global data assimilation (DA) systems and feeds the AI-WX model with exclusive GNSS radio occultation (RO) data collected from its proprietary satellite constellation.

“AI forecasting is only as good as the data that feeds it. That’s why we’ve built our model on a top-tier open-source AI framework—but powered it with Spire’s own satellite data,” said Dr. Tom Gowan, Spire’s Director of Weather Prediction and AI. “Our data assimilation system integrates this high-resolution observational data, improving the accuracy of the forecasts.”

Spire’s DA system is a key differentiator in an industry where high-quality initial conditions often make the difference between a good forecast and a great one.

AI-WX is built for real-world impact and industry applications

While most AI-based models offer forecasts out to 10 or 15 days, AI-WX extends the horizon to 20 days. This longer lead time is particularly important for sectors requiring medium-range planning, such as agriculture, energy, and supply chain logistics.

Additionally, AI-WX was developed not as a research tool, but as an operational forecasting product, designed to solve real-world business challenges. Its probabilistic approach and rapid update cycle are already showing strong value across several sectors:

• Energy and commodity trading: Probabilistic forecasts help traders hedge risk more effectively by providing confidence ranges around temperature, wind, and demand-driven variables
• Agriculture: Farmers gain better insight into frost risk, rainfall variability, and planting conditions well ahead of time
• Supply chain and logistics: Companies can optimize routes and operations by quantifying uncertainty in wind, precipitation, or extreme events
• Utilities and infrastructure: Operators benefit from longer-range planning tools for maintenance scheduling and load forecasting

“Forecasting is just the start. The real value is in translating weather data into business decisions—like hedging strategies or power grid adjustments,” Dr. Vela explained, adding that the Spire DeepVision™ Weather Support Team is talented and skilled at providing weather risk assessments and tailored forecasting services.

With hurricane season approaching, Spire’s clients are also turning to AI-WX for extreme weather risk management. Ensemble models are especially valuable in tracking potential hurricane paths and understanding where uncertainty is highest.

Spire’s AI-WX forecast initialized on March 10, 2025, at 12z shows 15 ensemble forecasts for 500-1000 hPa thickness and mean sea level pressure predictions on March 15, 2025 (108 hours in advance). AI-WX has 30 ensemble members operationally.

Effortless integration into business workflows and stunning visualization

AI-WX will be accessible via API and Spire’s Cirrus visualization platform, making it easy to incorporate into existing workflows or explore forecasts visually. Users can access raw ensemble data or post-processed summaries, including ensemble means, percentiles, and full distributions.

Spire is also building out features such as anomaly detection, MJO forecasts, and backcasts—tools that will provide even deeper insights into atmospheric patterns and trends.

Spire’s AI model roadmap for the future

AI-WX is just the beginning. Spire’s long-term vision includes building entirely new AI models from the ground up, much like Spire’s AI-S2S model, and training directly on raw satellite measurements. By bypassing traditional data assimilation workflows, this approach could unlock even faster, more scalable forecasting, with even more frequent forecast updates.

With its foundation of proprietary data, efficient architecture, and ensemble intelligence, AI-WX represents a significant advancement in AI-driven weather prediction. Moreover, it’s designed not just to forecast weather in the medium range, but to help businesses better plan for it.

“We own the satellites. We produce the data. And we have the infrastructure to do something no one else in the market can,” said Dr. Vela. “This is our opportunity to redefine how weather forecasting is done.”

Bridging the ‘valley of unpredictability’ with AI innovation in long-range weather forecasting

Sub-seasonal forecasting has traditionally been a formidable challenge, often referred to as the “valley of unpredictability” in meteorology. Forecast accuracy significantly declines beyond the 10-15-day range, leaving industries vulnerable to weather disruptions. Spire’s AI-S2S model disrupts this paradigm by leveraging deep learning techniques, probabilistic forecasting, and Spire’s exclusive satellite data to push the boundaries of predictability up to 45 days in advance.

“Our model is uniquely designed to capture long-range weather dependencies, integrating slow-evolving variables like sea surface temperature (SST) and soil moisture to enhance forecast reliability,” said Dr. Nachiketa Acharya, Senior AI Weather and Climate Scientist at Spire Global. “This level of accuracy and foresight has been largely unattainable — until now.”

A snapshot of 240-hour, 2-meter temperature forecasts is shown for 12 ensemble members generated by Spire Global’s AI-S2S model, which has 200 ensemble members operationally.

Dr. Oyebade Oyedotun, a Senior Machine Learning Scientist at Spire, holds a PhD in computer science from the University of Luxembourg, where he specialized in machine learning and computer vision. “Traditional numerical models rely on solving complex equations with many assumptions,” Dr. Oyedotun said. “AI, on the other hand, learns patterns directly from data, making it more flexible and adaptive for long-range forecasting.”

Why AI-S2S is revolutionary in long-range weather forecasting

Most existing AI weather models operate on deterministic frameworks, providing a single, best-guess forecast. Spire’s AI-S2S model, however, takes a fundamentally different approach by offering a probabilistic forecast with 200 ensemble members. This means businesses don’t just get one potential outcome — they receive a distribution of possibilities, allowing for better risk assessment and strategic planning, leading to better preparation for extreme weather events.

Dr. Oyedotun explains: “Weather is inherently chaotic, and small differences in initial conditions can lead to vastly different outcomes. By running 200 ensemble members, our model quantifies uncertainty with exceptional granularity, providing industries with a much clearer picture of potential scenarios.”

Powered by Nvidia GPUs, Spire’s AI models run 1,000 times faster than traditional physics-based models, enabling large ensemble forecasts that capture the full range of possible weather outcomes.

Dr. Acharya, who earned a PhD in statistics from Utkal University, India, has spent more than 15 years of his career refining sub-seasonal and seasonal forecasting methods, focused on real-world applications. “By embedding probabilistic approaches directly into our AI model instead of just running deterministic models with different initial conditions, we can quantify uncertainty in ways never before possible,” Acharya said.

Satellite data assimilation: Spire’s unique strength for enhancing forecast accuracy

A major differentiator of the AI-S2S model is its integration of Spire’s proprietary satellite data. Unlike conventional AI models that rely on publicly available reanalysis datasets, Spire’s satellite constellation provides real-time, high-resolution data on critical atmospheric and environmental variables.

“By training our AI model with exclusive satellite data — such as Radio Occultation (RO) measurements and GNSS-R derived soil moisture and ocean surface winds — we ensure that our forecasts are rooted in the most up-to-date and accurate information available,” said Dr. Luis Vela, Senior AI Weather Scientist at Spire. With a PhD spanning research across Germany, Australia, the United States, and Spain, Vela’s background in computational physics and numerical simulations helps optimize the infrastructure that powers Spire’s AI-S2S model. “This allows us to significantly improve forecast reliability beyond what traditional models can achieve.”

Daily mean inputs are also used instead of instantaneous values, enhancing forecast accuracy for long-range predictions.

“In sub-seasonal forecasting, we’re more interested in large-scale weather patterns over time rather than fine details. Using daily mean values rather than instantaneous six-hour intervals helps smooth out short-term fluctuations that aren’t relevant to long-term trends. By using daily means, we filter out short-term noise and focus on persistent weather patterns, improving long-range forecast stability,” Oyedotun said.

Accurate initial conditions are critical for high-quality forecasts, but for sub-seasonal predictions, they aren’t enough.

“You also need a strong modeling system that can accurately capture how these conditions evolve over time,” Dr. Oyedotun explained.

“For example, if you want to predict weather 20 days from now, your system needs to process the initial conditions and project them forward in a way that accurately reflects real-world atmospheric evolution,” he added. “That’s where AI comes in. We’re leveraging state-of-the-art AI techniques to train models that not only start with good initial conditions but also provide high-quality long-range forecasts.”

A snapshot of 240-hour, 100-meter wind speed forecasts is shown for 12 ensemble members generated by Spire Global’s AI-S2S model, which has 200 ensemble members operationally.

Key industry applications: Enabling better decisions for energy, agriculture, and finance

“The scale of this model’s impact is immense,” said Mike Eilts, General Manager of Spire Weather & Climate. “From predicting energy demand fluctuations to helping farmers anticipate drought risks, AI-S2S provides insights that drive smarter decision-making across industries that have long sought out actionable sub-seasonal forecasts. With Spire’s AI-S2S model, we’ve turned that vision into reality.”

Spire’s AI-S2S model is poised to revolutionize multiple industries by delivering useful, long-range weather forecasting insights:

• Energy trading and commodities — Traders can anticipate temperature-driven energy demand shifts, market fluctuations, and optimize pricing strategies based on probabilistic weather outcomes
• Agriculture and food security — Farmers can better plan for drought risks, precipitation trends, and temperature variations to inform planting, irrigation, pest and disease management, and harvesting decisions
• Financial markets and risk management — Investors and insurers can hedge financial risk tied to extreme weather, allowing for refined pricing of policies by assessing long-term risk
• Supply chain and logistics — Companies can proactively adjust logistics and inventory planning in response to predicted weather disruptions such as adjusting shipping routes when severe weather is forecast

“Beyond energy and agriculture, S2S forecasting has critical applications in disaster preparedness,” Dr. Vela added. “Predicting droughts, floods, and wildfires weeks in advance can help governments and businesses mitigate risks. Climate change is making extreme weather more frequent, so having a reliable long-range forecast can be a game changer for resilience planning.”

Spire’s commitment to AI leadership in weather forecasting

Spire is setting a new benchmark in AI-driven weather intelligence. Unlike competitors that blend AI models with traditional numerical weather prediction (NWP), Spire has developed the AI-S2S model entirely in-house, optimizing every component for operational forecasting at scale.

“Spire’s AI-S2S model isn’t just a technological breakthrough — it’s the culmination of world-class AI, meteorology, and computational physics team expertise. With Dr. Acharya leading AI-driven weather and S2S modeling, Dr. Oyedotun advancing machine learning techniques, and Dr. Vela optimizing the computational infrastructure, and help from a diverse team of experts, Spire is setting a new standard for AI-based sub-seasonal forecasting,” said Dr. Tom Gowan, Spire Director of Weather Prediction and AI.

As industries face growing climate uncertainties, Spire’s AI-S2S model empowers businesses with the confidence to navigate the future.

“This is not just an experimental model — it’s an operational product designed to deliver real-world value to industries that rely on accurate long-range forecasts,” said Dr. Acharya. “By seamlessly integrating AI, ensemble forecasting, and satellite data assimilation, Spire is redefining what’s possible in sub-seasonal forecasting.”

Why inter-satellite links matter for weather forecasting

Inter-satellite links allow satellites to communicate directly with each other, bypassing the need to wait for a ground station pass to relay data. The result? Faster data transmission, reduced latency, and more timely weather insights.

“Our Radio Occultation (RO) profiles, along with other observational data sources, are used to produce an accurate estimate of the initial atmospheric state for weather forecasting,” said Dr. Vu Nguyen, GNSS Radio Occultation Technical Director at Spire Global. “Observations that are ingested into the model with reduced latency will help produce better initial conditions, which are critical for forecast accuracy.”

The value of low-latency data is even greater for ionospheric forecasting, where conditions evolve more rapidly than in the lower atmosphere.

The ionosphere (the charged portion of our upper atmosphere) changes rapidly, impacting GPS, communications, and radar. To be useful, measurements must arrive within 15 minutes. Inter-satellite links ensure this data is available in time, enhancing space weather monitoring.

“OISLs are necessary to ensure RO-derived ionospheric variables are assimilated into ionospheric forecasting models with maximum impact,” Dr. Nguyen added.

A High-Resolution Forecast snapshot shows predicted composite radar reflectivity and relative humidity, indicating severe weather potential in the Southern US.

Optimizing efficiency of satellite data transmission

One of the biggest challenges in ensuring RO data reaches forecasting models in time is the dependency on ground stations. Satellites must fly over a ground station to downlink data, which means data delivery times can vary. Spire has built a dense global network of ground stations to minimize this delay, but optical inter-satellite links (OISLs) have the potential to provide an even more effective solution. OISLs allow satellites to communicate directly, transmitting data in orbit and reducing the reliance on ground passes. This means weather-critical data could reach models faster, leading to more precise forecasts.

Expanding capabilities with Polarimetric Radio Occultation

One of the satellites launching in March includes Polarimetric Radio Occultation (PRO) capability, which enhances traditional RO measurements by detecting precipitation and cloud properties. Unlike standard RO, which primarily measures atmospheric temperature, pressure, and humidity, PRO can also analyze hydrometeors—such as precipitation rate and type and clouds—by leveraging polarization differences in GNSS signals.

“PRO can be thought of as ‘augmented’ RO,” explained Dr. Nguyen. “These measurements are still sensitive to temperature and water vapor but also provide valuable insights into hydrometeors, offering potential improvements for numerical weather models.”

PRO enhances Spire’s ability to accurately represent cloud microphysics, including moisture distribution, cloud cover, and precipitation intensity. By improving cloud analysis and ingestion during data assimilation, PRO strengthens the accuracy of the Spire High-Resolution Forecast. More precise cloud simulations lead to better forecasts for precipitation, energy balance, surface conditions, and soil moisture.

A satellite image shows Tropical Cyclone Pam churning over the South Pacific Ocean.

How OISLs enhance tropical storm forecasting

Spire’s polar, sun-synchronous orbits ensure global coverage, including key tropical regions where tropical cyclones form. Since these storms develop rapidly, reducing data latency through OISLs could help forecasters detect and predict their evolution with greater precision.

“Sun-synchronous orbits provide global coverage and observations at the same local time. For tropical cyclones, this means being able to observe the formation of a tropical cyclone even in remote areas like the South Indian Ocean or South Pacific Ocean,” Spire Data Assimilation Expert Dr. Sanita Vetra-Carvalho explained. “OISL will allow us to downlink this data faster, especially from locations that are quite remote with fewer ground stations.”

Learn more about our Optical Inter-Satellite Link (OISL) payloads

Spire’s March launch: Expanding capabilities and building our constellation

The March launch will introduce seven LEMUR satellites, each playing a key role in enhancing Spire’s data capabilities. Among them:

• Four Radio Occultation (RO)-capable satellites – These satellites will strengthen Spire’s ability to collect atmospheric temperature, pressure, and humidity data. One of these satellites is also PRO capable, meaning it can measure precipitation and cloud properties.
• Two Optical Inter-Satellite Link (OISL) test satellites – These satellites will test Spire’s ability to transmit data between satellites using optical laser links. By securely transmitting data almost instantaneously across distances up to 5,000 kilometers, OISLs hold the promise of reducing data latency and improving overall data flow within Spire’s constellation.
• One customer payload satellite – Expanding Spire’s Space Services offerings by integrating partner missions into the launch.

Advancing weather and climate intelligence

Spire is scaling up its constellation to meet growing demand for high-quality, low-latency Earth observation data. This includes expanding RO and PRO measurements and integrating Hyperspectral Microwave Sounding (HyMS), which will provide even more detailed atmospheric insights.

PRO utilizes a passive grazing path geometry to detect cloud hydrometeors at various vertical levels, while HyMS provides a more direct active nadir-view perspective beneath the satellite with high vertical resolution. By combining PRO with HyMS, along with geostationary infrared (IR) and visible satellite data, Spire will improve the horizontal and vertical localization of precipitation—leading to more precise, high-resolution weather forecasts.

“Spire will continue to build out its constellation of Earth-observing satellites focused on data quantity, quality, and spatial-temporal coverage,” Dr. Nguyen said.

“Spire’s future deployment of optical inter-satellite links will ensure these data arrive at end users and are ingested into weather forecast models in a timely manner to maximize impact,” he added.

As the need for real-time weather intelligence grows, Spire’s continued innovations will enhance forecast precision and help businesses and governments make better decisions in an increasingly volatile climate.

EarthDaily’s mission: Making geospatial data actionable

EarthDaily specializes in leveraging satellite constellations and geospatial analytics to deliver industry-specific solutions. The company operates across agriculture, mining, energy, and insurance, simplifying complex geospatial data for practical applications. With the acquisitions of Descartes Labs and Geosite, EarthDaily expanded its modeling and insurance capabilities, enhancing its ability to provide industry-leading insights.

EarthDaily’s insurance solutions focus on making geospatial data accessible to underwriters, claims teams, and risk managers. Its flagship platform, Ascend, integrates weather data and property analytics, enabling insurers to understand and act on climate-related risks with unprecedented precision.

“The core of our vision is to make geospatial data easier to use by tailoring it to specific industries. Geospatial data is inherently complex, and unless tools are designed to speak the language of their users, they’re too difficult to implement effectively,” Rachel Olney, EarthDaily  Vice President of Insurance, said. “This is where Spire’s data plays a crucial role. In the insurance industry, we focus on interpreting slices of this data into actionable insights that insurance companies can use without being overwhelmed by the volume of information.”

Spire’s data was used in Ascend to assess the total impact of a severe weather incident on carriers’ portfolios. Space-powered weather insights, portfolio data, and post-event imagery were combined to streamline the process from reserving to claims.

Shifting from reactive to proactive risk management

Traditional insurance models rely on post-disaster assessments, but Spire Weather & Climate and EarthDaily are changing this paradigm.

“The partnership is transformative. Insurance is a unique product because it’s based on theoretical risk analysis,” Olney explained. “By incorporating Spire’s granular weather data, we can provide insurers with a clearer understanding of risks, allowing them to create better products and respond proactively to events.”

“For example, weather events like hailstorms or high winds can be monitored in real-time. Insurers can then notify policyholders and arrange inspections or repairs before further damage occurs,” she added.

By incorporating Spire’s high-resolution weather data into EarthDaily’s Ascend platform, insurers can:

• Predict and mitigate risks before they escalate, such as issuing early warnings for hail, heavy rain, or high winds
• Alert policyholders to take protective measures, such as securing loose shingles before a storm intensifies
• Deploy adjusters preemptively to assess potential damage and expedite claims processing

“This proactive approach reduces claims costs and improves customer satisfaction. For instance, during a major storm in southern Australia, insurers used our platform to identify flooded properties and provide emergency funds to displaced residents before they even returned home. This level of responsiveness builds trust and mitigates losses,” Olney said.

Seamless integration of space-powered weather and geospatial data

EarthDaily’s integration of Spire Weather & Climate’s insights streamlines insurance workflows, eliminating the need for multiple platforms. By cross-referencing policy locations with real-time weather data, insurers can:

• Identify affected properties immediately after extreme weather events
• Estimate damages using wind speed, hail size, and flood depth data
• Prioritize claims adjustments for the most impacted areas

“Geospatial data plays a critical role throughout the insurance lifecycle. Initially, insurers use historical data to price risk and develop new products,” Olney said. “For example, they analyze past weather events to predict future risks and create climate-adjusted models. Once a product is launched, geospatial data helps insurers manage risk by tracking policy locations and monitoring weather events in real-time.”

Users can filter their portfolios to identify policies affected by specific weather events, such as high winds or heavy rainfall. This allows insurers to prioritize claims adjustments and estimate potential losses more accurately.

Moreover, APIs bring EarthDaily’s geospatial data and Spire’s weather data directly into insurers’ existing systems, ensuring seamless, real-time access to crucial information. Claims teams no longer need to toggle between platforms; instead, they receive automated alerts and detailed reports directly within business process management systems (BPMS) or policy admin systems.

Climate change and the future of insurance

The increasing frequency and severity of extreme weather events—wildfires, droughts, floods, and hurricanes—has rendered traditional insurance models unsustainable. Spire and EarthDaily  are at the forefront of change, providing insurers with climate-adjusted risk models to:

• Improve underwriting precision by incorporating real-time climate-adjusted forward-looking models in addition to historical weather insights
• Enhance resilience by allowing insurers to anticipate and respond to evolving climate threats through more precise risk selection and management
• Reduce losses by leveraging proactive risk mitigation strategies

EarthDaily and Spire envision a future where insurers are not just reactive responders but proactive risk managers. Imagine an insurance company automatically dispatching a contractor to reinforce a home’s roof before a storm arrives, preventing costly damage and policyholder distress.

A smarter, more resilient insurance industry

As the insurance sector grapples with increasing climate-driven risks, partnerships like that of Spire and EarthDaily offer a glimpse into a more resilient future. By merging geospatial intelligence with hyper-accurate, space-powered weather data, they empower insurers to navigate uncertainty, minimize losses, and build stronger relationships with policyholders.

“Our ultimate goal is to make geospatial data so intuitive and accessible that users don’t even realize they’re interacting with it,” Olney said. “This vision of proactive risk management benefits everyone involved by reducing losses and improving resilience. By embedding geospatial insights into everyday operations, we can help industries adapt to the challenges of climate change and build a more resilient future.”

This collaboration showcases the transformative power of technology, paving the way for smarter insurance solutions. The dream of seamless, proactive risk management is no longer a distant possibility—it is becoming a reality.

AI-driven Power Generation Forecasts for wind and solar: Spire’s approach

Spire’s Power Generation Forecast integrates advanced high-resolution forecasting, state-of-the-art deep learning methodologies, and satellite-driven insights to refine power production estimates:

• Satellite-enhanced meteorology – Spire’s proprietary satellite data ensures more accurate forecasts by incorporating real-time observations of atmospheric conditions, including wind speeds at hub heights and solar radiation at the surface, critical for wind and solar power forecasting
• High-granularity inputs – Driven by Spire’s High-Resolution Forecast model, which captures fine-scale atmospheric dynamics other models miss
• Machine learning optimization – AI models continuously refine predictions using historical weather and power generation data, improving accuracy over time
• Hourly power output predictions – The model delivers MW-level power production estimates at a national or regional scale, helping traders anticipate fluctuations in renewable energy supply

The Netherlands wind power forecast

Forecast issuance: Mon 24 Feb 2025 – 12 GMT

A Power Generation Forecast chart from the Spire DeepInsights™ Cirrus data viewer is shown for wind energy in the Netherlands.

Who benefits from Spire’s renewable energy forecasts with high-granularity data inputs?

Spire’s Power Generation Forecast is designed for:

• Energy traders – Provides high-precision forecasts to enhance trading strategies, optimize hedging decisions, and anticipate fluctuations in renewable energy supply
• Utilities and grid operators – Supports grid balancing and operational planning by offering accurate forecasts of renewable generation potential
• Renewable energy investors – Delivers insights that help assess long-term investment viability and market trends

Regional availability and expansion

Spire currently provides Power Generation Forecasts for France, the Netherlands, Germany, Austria, Hungary, and the United Kingdom.

Spire is also in the process of expanding coverage to ERCOT (Texas) and additional North American energy markets.

As Spire Senior Machine Learning Engineer Elliott Wobler explains: “For any new region, we need access to historical, hourly power generation data to train and validate the model. We already have initial results for ERCOT and are working on optimization strategies now.”

How energy traders and grid operators access the data

The Power Generation Forecast is available through:

• API integration – Simple, structured data feeds allow traders to integrate forecasts directly into their analytical platforms and algorithms
• Spire’s Cirrus data viewer platform – Users can visualize power generation forecasts, explore meteograms, and quickly assess trends in renewable energy output

Market validation and early adoption

Early adopters, energy trading firms, have already started integrating Spire’s forecasts into their trading workflows, providing valuable feedback that continues to refine the model’s accuracy. With frequent iteration and real-world testing, Spire is ensuring that its forecasts meet the rigorous demands of energy market professionals.

“Our clients use multiple forecasting providers, so we’ve received valuable anonymized comparisons. By leveraging Spire’s High-Resolution Forecast model, we’ve seen strong early results, especially in solar power forecasting in Europe,” Wobler explained.

Hungary solar power forecast

Forecast issuance: Mon 24 Feb 2025 – 12 GMT

A Power Generation Forecast chart from the Spire DeepInsights™ Cirrus data viewer is shown for solar energy in Hungary.

Solar’s soaring growth in Europe and Texas signals a renewable shift

The European energy landscape experienced a major shift in 2024 as solar power became the fastest-growing electricity source, surpassing coal for the first time. According to Ember’s “European Electricity Review 2025,” solar generation in the EU increased by 22% year-over-year, reaching 304 TWh—enough to edge out coal, which declined to 269 TWh. This marks a significant milestone, as coal, which was the EU’s third-largest power source in 2019, has now dropped to sixth place. Solar’s expansion is widespread across Europe, with more than half of EU nations either phasing out coal entirely or reducing its share to less than 5% of their power mix, Ember reported.

During peak production hours, solar energy is approaching a new threshold in several EU countries, covering a substantial portion of electricity demand. The Netherlands and Hungary saw particularly notable growth, with over 70 days where solar generation exceeded 80% of total demand during peak hours — a significant jump from Hungary’s 10 days in 2023, according to Ember.

In the United States, Texas is experiencing a similar surge in renewable energy capacity, with solar and battery storage leading grid expansion. According to Federal Reserve Bank of Dallas research published in 2024, solar additions nearly doubled from 4,570 MW in 2023 to 9,700 MW in 2024, while battery storage capacity tripled, underscoring the rapid shift toward clean energy solutions.

This rapid acceleration of solar shines a light on the increasing need for precise, AI-driven forecasts that help energy traders, utilities, and grid operators optimize renewable energy use. Spire’s Power Generation Forecast delivers this critical insight, equipping market participants with high-resolution, satellite-powered data to anticipate fluctuations in solar output and maximize efficiency in an evolving energy landscape.

Future enhancements and expansion into key energy markets

Spire is continuously evolving its forecasting capabilities, with several enhancements to the Power Generation Forecast in the pipeline:

• Expanding coverage to key US energy markets such as ERCOT, MISO, and other key US energy markets
• Continuously improving forecast accuracy through AI model refinements and additional satellite data assimilation
• In the future, Spire aims to provide AI-driven probabilistic power generation forecasts, helping traders quantify uncertainty and refine risk management
• With customer-provided data, Spire’s system can scale to granular, site-specific forecasts, producing turbine-level or solar farm-specific forecasts
• Exploring adjacent solutions, such as outage prediction models, to further support energy market participants

By partnering with industry users, Spire aims to refine and expand this innovative solution, providing the most accurate and actionable renewable energy forecasts on the market.

Leverage Spire’s AI-driven Power Generation Forecasts for precise trading strategies

Spire’s Power Generation Forecast is available now, with API access and free trials for energy traders and professionals looking for an edge.

When milliseconds and margins matter, Spire delivers timely, accurate, and exclusive weather intelligence—so you can optimize, hedge, and win the market

Get a free trial of Spire’s Power Generation Forecast

What sets SMI Anomalies apart?

Building on Spire’s Soil Moisture Insights, which already delivers accurate, high-resolution soil moisture data, the new SMI Anomalies product introduces historical context and advanced analytics. Soil moisture data is derived from Spire’s proprietary GNSS-R collections, leveraging Spire’s satellite constellation. Additionally, Spire’s soil moisture climatic archive extends back to 1978 using the ESA Climate Change Initiative (CCI) data. This dataset is used to cross-calibrate Spire’s historical soil moisture records, creating a seamless, statistically consistent climate dataset from 1978 to the present.

By combining next-generation satellite technology with AI and machine learning, Spire delivers unmatched accuracy and consistency, enabling users to analyze trends with confidence and precision.

Maps illustrate SMI Anomalies in southern and eastern Spain before, during, and after severe flooding in late October to early November 2024. The 6 km resolution anomalies are based on a seven-day rolling window compared to a 10-year climatological median. The left map shows conditions five days before the event, the center map captures the event, and the right map highlights persistent wet soil moisture five days afterward.

Key features of SMI Anomalies

SMI Anomalies provides unparalleled context with three essential metrics:

• Delta from the median – quantifies how current soil moisture differs from historical medians, revealing significant deviations
• Percentile rank – ranks current conditions within long-term records, pinpointing extremes from the climatic record
• Agricultural Drought Index – tracks the consecutive days of soil moisture deficit, indicating the severity and duration of drought conditions and offering a powerful tool for drought analysis

These features deliver actionable insights to industries reliant on soil moisture data, enabling data-driven decisions that enhance planning and resilience.

Why SMI Anomalies matter: Transformative benefits across industries

SMI Anomalies allows industry users to interpret the data against the climatic backdrop, providing context by highlighting deviations from long-term soil moisture norms. This is critical for identifying extremes, such as early warnings for droughts or floods, and understanding their severity and duration.

SMI Anomalies offers critical insights across multiple sectors. For example:

• Agriculture: Farmers gain an edge with early warnings of soil moisture deficits and monitoring of the Agricultural Drought Index, enabling precise irrigation planning and early responses to drought conditions that threaten crop yields
• Water resource management: Authorities can identify regions with persistently saturated soils and flood-prone areas, helping optimize reservoir management and disaster preparedness
• Commodity trading: Traders can incorporate soil moisture anomalies as leading indicators for crop yield, influencing commodity pricing
• Insurance: Insurers can use anomaly metrics to assess risk and adjust coverage strategies for weather-dependent sectors

From detecting flood risks to enhancing financial strategies, SMI Anomalies empowers stakeholders with precise weather and climate intelligence tailored to their needs.

The Agricultural Drought Index shows the number of dry days from January 1 to June 1, 2021, for a location in California south of the Bay Area (marked by the blue dot on the global map) during a major Western US drought. The 10-year median serves as the climatological reference. Upper subplots compare 6 km resolution data (left) with 500 m resolution data (right), highlighting broader regional analysis and field-level detail for agricultural practices. The data reveals long-lasting drought conditions with more than three months of dry days, depicted by red shading in the north.

Flexible resolutions for diverse applications

SMI Anomalies are available at 6 km and 500 m, providing flexibility to support a range of use cases across industries.

• 6 km resolution: Ideal for identifying large-scale soil moisture trends and anomalies; this supports applications such as climate analysis, drought prediction, commodity trading, and insurance risk assessments, where broad-scale insights are essential for understanding potential financial impacts of droughts or floods
• 500 m resolution: Designed for local and field-level insights, this resolution is particularly valuable for precision agriculture, irrigation management, and flood monitoring; granular details optimize decision-making

Seamless access through API and advanced visualization

End users can access SMI Anomalies through the Soil Moisture Insights API and the DeepInsights™ Cirrus visualization solution, offering flexibility for diverse applications.

• API access: Retrieve soil moisture anomalies as point or raster data for location-specific or regional insights
  • Point requests: End users can extract time series of soil moisture and anomalies at specific locations with a single API request, enabling quick analysis of historical and current conditions
  • Gridded data: Regional insights into deviations from climatic norms can be assessed using raster data, supporting broader-scale analysis and visualization
• DeepInsights Cirrus visualization: Within Cirrus, users can explore anomalies through interactive regional maps, providing spatial context for deviations in soil moisture; for detailed temporal insights, meteograms allow users to analyze soil moisture trends and anomalies over time at specific locations

This combination of granular data and broad-scale visualization ensures users have the tools they need to make informed decisions quickly.

Coffee prices surged to a 47-year high in late November due in part to adverse weather disrupting crop production in Brazil, the world’s largest producer of arabica beans. Brazil faced its worst drought in 70 years, followed by heavy rains since October. Spire’s Soil Moisture Anomalies show slightly above-average soil moisture conditions in Minas Gerais, Brazil’s primary growing region for arabica beans, in late December.

Unlock the power of context

With the release of SMI Anomalies, Spire Weather & Climate contextualizes soil moisture data against long-term climate records. These insights help industry users anticipate risks, optimize resources, and remain resilient in a changing climate.

Explore the possibilities of SMI Anomalies today and experience how Spire’s technology can empower your decisions.

What is Radio Occultation?

Radio Occultation (RO) is an advanced remote sensing technique that uses signals from Global Navigation Satellite Systems (GNSS) to measure critical atmospheric variables such as temperature, pressure, and water vapor. These measurements are obtained by tracking how GNSS signals bend as they pass through different layers of the atmosphere from the planetary boundary layer to the top of the stratosphere. The data collected by Spire’s low-Earth orbit satellites offers unparalleled vertical resolution and long-term stability, making RO a cornerstone for improving weather forecasts and monitoring climate change.

How Spire is transforming Radio Occultation

Spire Global has emerged as a leader in RO technology, deploying the world’s largest commercial GNSS-RO constellation. Utilizing nanosatellites equipped with proprietary STRATOS receivers, Spire delivers thousands of high-quality RO atmospheric profiles daily. This remarkable output exceeds many publicly funded missions, such as COSMIC-2*, and offers a similar level of quality to these missions. Spire’s achievement represents a breakthrough in scalability and efficiency, providing critical atmospheric data to enhance weather forecasting and climate research.

*COSMIC-2, a publicly funded satellite mission managed by NOAA, provides global atmospheric data through GNSS Radio Occultation, supporting weather forecasting, climate monitoring, and space weather research with high-quality profiles from six advanced satellites.

Key advancements of Spire’s technology include:

• Multi-constellation tracking: Spire’s receivers can track signals from GPS, GLONASS, Beidou, and Galileo satellites, doubling the profile collection rate compared to older systems
• Cost-efficient nanosatellites: Compact satellites reduce production costs while maintaining high performance, enabling rapid deployment and innovation
• Global coverage: With satellites in diverse orbits, Spire achieves comprehensive geographic and temporal coverage, vital for both weather forecasting and climate studies

The impact of RO on weather forecasting

RO data plays a critical role in improving Numerical Weather Prediction (NWP) models. Studies show that assimilating Spire’s RO profiles into weather models significantly enhances forecast accuracy, especially for extreme weather events. During the early stages of the COVID-19 pandemic, when aircraft-based observations plummeted, Spire’s RO data filled critical gaps, supporting reliable forecasts.

For example, integrating Spire’s data has been shown to:

• Improve short- and medium-range weather forecasts
• Enhance predictions of hurricane paths and intensities
• Provide consistent benchmarks for monitoring climate trends over decades

Spire’s RO data ranks among the most impactful data sources for enhancing weather forecasting metrics globally after microwave radiance and infrared data, according to sources such as ECMWF and NASA.

“Accurate and reliable weather forecasts are crucial to cope with the impacts of weather hazards and climate change and to help businesses thrive; these forecasts depend on high-quality observations of the atmosphere. Spire’s impressive satellite constellation provides important observations across the globe that enhance our forecasting capability,” Alan Thorpe, of the UK Met and a Scientific Advisor and Spire Global Board Member, said.

Spire’s RO data and additional datasets from its satellite constellation, combined with other data sources, feed into Spire’s proprietary weather prediction models, including the Spire High-Resolution Forecast, the backbone for many of Spire’s weather products.

Pioneering possibilities

Spire’s innovation doesn’t stop at traditional RO. The company is exploring exciting new applications of GNSS-RO, Reflectometry, and Hyperspectral Microwave, including:

• Polarimetric RO: Detecting ice clouds and liquid precipitation, estimating precipitation intensity, and monitoring cloud properties (e.g., thickness and altitude) by separately measuring the GNSS signal polarization components (horizontal and vertical)
• Grazing angle GNSS-R: Leveraging reflected GNSS signals to measure sea ice thickness, ocean winds, and soil moisture, enabling large-scale monitoring for agriculture, drought assessment, and hydrological studies among other industry and weather prediction enhancement applications
• Hyperspectral Microwave: Observing the Earth in multiple microwave frequency bands, capturing detailed atmospheric measurements, including water vapor and temperature
• Ionospheric observations: Real-time monitoring of the ionosphere to mitigate disruptions in GNSS-based navigation and communication

Future collaborations, such as the Radio Occultation Modeling Experiment (ROMEX), aim to quantify the impact of large-scale RO data assimilation further, setting new standards for forecasting and climate research. ROMEX is a collaborative initiative led by the International Radio Occultation Working Group (IROWG) to advance global weather and climate forecasting by improving the use of Radio Occultation data in Numerical Weather Prediction models. A key focus of ROMEX is determining how much RO data is sufficient to generate the most accurate forecasts, ensuring optimal integration into weather prediction models.

Leveraging RO data for weather prediction and research

Radio Occultation is more than just a technology; it is a transformative tool for understanding and predicting our planet’s complex systems. By enhancing weather forecasts, mitigating climate risks, and supporting groundbreaking scientific research, RO is paving the way for a safer, more sustainable future. Spire Weather & Climate integrates this powerful data into every product, delivering unmatched precision and insights for businesses.

Whether you’re a business reliant on accurate forecasts or a researcher delving into climate phenomena, now is the time to harness the power of RO. Spire Global invites you to explore how its cutting-edge data solutions can empower your mission and make a lasting impact.

Learn more about how Spire’s Radio Occultation capabilities can elevate your weather intelligence and business operations.

Key updates available today

Improved 100-meter wind predictions

For energy and commodity customers who rely on wind forecasts to optimize energy trading strategies, our model now delivers improved 100-meter wind predictions. This enhancement incorporates new source code and additional static datasets, enabling the model to better account for atmospheric drag under specific conditions.

New variables: Effective cloud fraction and maximum hail size

Responding to customer requests, our team implemented model updates, now generating effective cloud fraction and maximum hail size data. These parameters are critical for solar energy forecasting and insurance risk assessments. Soon, these variables will be accessible via API and in Cirrus, our customer interface.

An unprecedented, expanded data assimilation domain has been extended to a Transatlantic domain, assimilating more Spire RO data and other datasets. The two previous data assimilation domains are shown for comparison.

Unified Transatlantic data assimilation domain

We’ve transitioned from separate data assimilation domains for the continental US (CONUS) and Europe to a unified Transatlantic domain. This innovation brings:

• Improved forecasts through enhanced data assimilation (including more Spire Radio Occultation data)
• Increased consistency across all high-resolution domains
• Reduced engineering complexity, allowing for quicker future upgrades

Assimilation of new satellite datasets via EUMETCast

New capabilities at Spire’s Glasgow office allow us to assimilate a vast array of additional public weather satellite data in real-time, including infrared and microwave observations from multiple satellites. This significantly enriches additional datasets that inform our forecasts.

A testament to innovation and teamwork

This ambitious rollout is the result of relentless dedication and collaboration across teams. Dr. Tom Gowan, Spire’s Director of Weather Prediction and AI, expressed his pride in the team:

“This release reflects our focus on customer feedback, rapid innovation, and delivering the best forecasts possible. It showcases the exceptional talent and expertise of the engineers and scientists on our team, who have pushed the boundaries of what’s achievable in weather prediction to provide our clients with accurate and reliable weather insights.”

Empowering customers with advanced forecasting tools

These updates reflect Spire’s mission to empower businesses with actionable, space-powered weather intelligence. Whether it’s optimizing wind energy production, assessing hail risks, or navigating Transatlantic weather challenges, the Spire High-Resolution Forecast continues to set a new standard for precision and reliability.

Discover how the Spire High-Resolution Forecast can elevate your operations – reach out today to begin your 30-day evaluation.

Hurricane Beryl: Early insights, strategic advantage

Hurricane Beryl; the second named storm of the season and the earliest-ever Category 5 hurricane in the basin; proved how a tropical system can cause significant disruption. Intensifying at a historic rate over unusually warm Caribbean waters, Beryl weakened before making landfall in Texas with maximum sustained wind speeds of 80 mph and leaving a trail of economic and operational challenges.

The storm caused at least $2.5 billion in direct damages, according to Moody’s estimates, with widespread power outages affecting nearly 3 million customers in Gulf Coast states. For energy traders, Beryl’s impact resulted in a 15% spike in natural gas prices due to disruptions in supply chains and increased demand for cooling in the aftermath of power losses.

Lesser-known business impacts

Inland, Beryl’s wind field brought widespread outages and logistical hurdles for businesses unaccustomed to hurricane-force winds. Power restoration efforts were hampered by blocked roads, delaying recovery timelines and increasing costs for utility companies. Retail and service sectors in affected regions reported losses exceeding $300 million due to extended closures.

How Spire’s forecast excelled during Beryl

The Spire High-Resolution Forecast model provided early warnings about Beryl’s strength and track, giving grid operators who leverage Spire risk and forecasting data, as well as energy traders, a critical 48-hour lead time to prepare. The forecast accurately pinpointed the landfall zone within a 25-mile margin more than three days in advance and 10-20 miles within 30 hours, far exceeding the accuracy of the world’s most widely used models. Probabilistic risk metrics highlighted the highest-impact areas, enabling utility operators to pre-position crews, which could have reduced average restoration times by 20%. These insights also allowed energy traders to anticipate market volatility, mitigating financial risks during the event.

The Spire High-Resolution Forecast provided early insights into Hurricane Beryl’s track toward the Texas coastline twelve hours before other models. The image on the left shows the Spire High-Resolution Forecast position for Beryl at 12z on July 8, initialized at 06z on July 5. The image on the right shows Hurricane Beryl’s actual position at 12z July 8 as indicated by radar.

Fast facts: Hurricane Beryl’s impact

• 80 mph: Sustained winds at landfall
• $2.5 billion: Total estimated damages
• 3 million: Total power outages
• 15%: Natural gas price increase
• $300 million+: Retail & service sector losses
• 10-20 miles: Accuracy of landfall prediction within 30 hours
• 75-90 mph: Gusts near landfall, as forecasted
• 60-80 mph: Gusts predicted in Houston, verified by observations

These data points showcase the storm’s widespread economic impact and scope of damage, as well as the accuracy of Spire’s forecasting tools in providing critical lead times for business preparation.

Hurricane Helene: Flooding, wind, and the role of soil moisture

Hurricane Helene made landfall with sustained winds of 140 mph, delivering devastating impacts across Florida, Georgia, and the Carolinas. Helene’s economic toll surpassed $41 billion in direct damages in North Carolina alone, driven by prolonged power outages, flooding, and infrastructure damage. Inland areas experienced the most significant impacts, with up to 30 inches of rainfall causing catastrophic river flooding and landslides in the mountains of North Carolina and South Carolina. This led to road closures, delayed recovery operations, and increased restoration costs for utilities.

Key business impacts

For energy traders, the storm created unprecedented volatility in electricity prices as power plants were forced offline, resulting in rolling blackouts across parts of the Southeast. Electrical utilities faced $1.4 billion in repair and recovery costs, compounded by labor shortages and challenges accessing damaged areas. Soil moisture levels, already elevated from prior rain events, played a critical role in intensifying flooding impacts, underscoring the need for integrated hydrological and meteorological data in forecasting models.

Wider implications for businesses

Helene’s extensive wind field downed trees and damaged energy infrastructure in areas far inland. The cascading impacts led to prolonged outages, with 265,000 customers remaining offline three days after landfall. Businesses reliant on just-in-time supply chains saw delays of 5-7 days, further impacting the regional economy.

Spire’s High-Resolution Forecast for Helene

Spire’s models provided exceptional accuracy, predicting Helene’s landfall location within a 25-mile margin days in advance and capturing the storm’s rainfall distribution with precision. By identifying areas of 20-30 inches of rainfall 36 hours ahead of other models, Spire’s forecasts enabled utilities and energy traders to plan resource allocation effectively. Paired with Spire’s Soil Moisture Insights, an enhanced understanding of flood risk made early warnings of catastrophic flooding possible. This led to a significant reduction in response times for grid repairs and improved decision-making for energy traders managing price swings.

It’s equally important to identify areas of lower impact risk to minimize unnecessary operational disruptions and maximize cost savings. Spire’s High-Resolution Forecast, for example, consistently projected that Tallahassee would avoid eye-wall core winds, which were expected to remain east of the metropolitan area. Pinpointing and communicating areas with statistically lower risk can save businesses thousands—or even millions—depending on their operational footprint.

Spire’s High-Resolution Forecast model run initialized at 12z on September 26, the last official run available before landfall, depicts the composite radar reflectivity as Helene at landfall. The pink line shows the NHC official centerline track. The image in the red box in the upper-right corner shows actual radar as Helene made landfall.

Fast facts: Hurricane Helene’s impact

• 140 mph: Sustained winds at landfall
• $41 billion+: Total estimated damages in NC
• 30.78 inches: Observed maximum rainfall in NC, accurately forecasted by Spire’s forecasts
• $1.4 billion: Electrical utilities’ recovery costs
• 25 miles: Landfall prediction accuracy within 3 days
• 36 hours: Lead time of rainfall forecasts of 20-30 inches, outperforming other models

These figures highlight the storm’s devastating impacts and the remarkable precision of Spire’s advanced weather forecasting in aiding business preparation and response efforts.

Hurricane Milton: Complex impacts, historic records

Hurricane Milton caused widespread destruction, making landfall near Siesta Key, Florida, as a Category 3 hurricane with sustained winds of 120 mph. The storm’s impacts were multifaceted, with storm surge, rainfall, damaging winds, and a prolific tornado outbreak creating widespread disruption. Milton’s economic toll is estimated between $20-$100 billion, with insured losses accounting for the majority of costs. Inland rainfall totals reached over 20 inches in some areas, causing flash flooding and major disruptions to transportation and energy infrastructure.

Key business impacts

Power outages during Hurricane Milton peaked at nearly 3.5 million customers across Florida. Adding to the devastation, a historic tornado outbreak produced 46 confirmed tornadoes, including three rated EF3, which inflicted severe damage on infrastructure and industrial facilities. However, Tampa Bay experienced a rare reverse storm surge, with offshore winds temporarily lowering water levels, ultimately saving an estimated $500 million in potential damages in the region’s most vulnerable areas.

Underreported impacts

The storm’s extensive rain bands caused logistical bottlenecks for supply chains reliant on Florida’s major ports. Major industrial hubs reported a 20-30% drop in operational efficiency for weeks after the storm, exacerbating economic losses.

Spire’s forecasting excellence during Milton

Spire’s High-Resolution Forecast model accurately predicted Milton’s landfall location within 30 miles in 67% of model runs — all accurately south of Tampa Bay, outperforming traditional forecasting tools. Spire’s rainfall forecasts were equally accurate, matching observed totals within a 1-2-inch margin in high-impact areas. The insights enabled utilities to deploy repair crews effectively, reducing power restoration times by up to 20%, and helped energy traders stabilize pricing through early awareness of storm impacts.

Spire’s High-Resolution Forecast model run initialized at 12z on October 7, days ahead of Milton, depicted the composite radar reflectivity at Milton’s landfall. The pink line shows the NHC official centerline track at the time. The image in the red box in the upper-right corner shows actual radar as Milton made landfall.

Fast facts: Hurricane Milton’s impacts

• 120 mph: Sustained winds at landfall
• $20-$100 billion: Estimated total economic toll
• 3.5 million: Customers affected by power outages
• $500 million: Potential damages saved due to a reverse storm surge in Tampa Bay
• 126: Tornado warnings issued, the most ever recorded in a single day in FL
• 30 miles: Landfall location prediction accuracy within 3 days
• 90th percentile: Rain forecasts (in 90th percentile of QPF* distribution of models) closely matched observed totals in high-impact areas

*QPF stands for Quantitative Precipitation Forecast

These statistics summarize the storm’s significant impact and Spire’s advancements in forecasting that helped mitigate potential damages.

The Spire advantage

The 2024 Atlantic hurricane season underscored the increasing frequency and complexity of extreme weather events. For utility operators, grid managers, and energy traders, resilience depended on timely, accurate weather insights. Spire’s High-Resolution Forecasts provided a critical advantage, enabling stakeholders to mitigate risks, optimize resource deployment, and adapt to rapidly evolving conditions.

As weather risks continue to challenge businesses, Spire Weather & Climate remains committed to delivering clarity through chaos. With our space-powered weather intelligence, we empower industries to anticipate, adapt, and thrive in the face of uncertainty.

Learn more about the Spire High-Resolution Forecast

Introduction to data assimilation

Behind these predictions lies weather modeling, a sophisticated process powered by data assimilation, which integrates vast amounts of observational data into computer models to improve forecast accuracy.

This article examines the critical role of data assimilation in numerical weather prediction, showing how it enhances forecast accuracy to meet the needs of industries like utilities, logistics, energy trading, and insurance.

Exploring data assimilation’s role in weather modeling

Weather modeling is complex, using mathematical equations to simulate atmospheric behavior by analyzing variables like temperature, pressure, and humidity across different elevations and regions. However, to transform these simulations into actionable forecasts, they must be anchored in real-world data. Data assimilation bridges this gap, merging diverse observational data sources—such as satellites, radar, ground-based instruments, and previous forecasts—into weather models. This integration provides a snapshot of the best possible estimate of current atmospheric conditions, setting a foundation for reliable forecasts.

For those in high-stakes industries, the difference between an accurate or inaccurate forecast can mean millions in losses or gains. Here’s how data assimilation works to elevate forecast accuracy for informed business decision-making.

A snapshot of the Spire High-Resolution Forecast depicting radar reflectivity, 2-meter temperatures, and 10-meter winds as viewed in Cirrus, a Spire data visualization solution.

Key benefits of data assimilation

1. Enhanced forecast accuracy
   The primary goal of data assimilation is to refine forecast models by incorporating real-time observations. By adjusting initial conditions in models with current data, meteorologists can significantly improve forecast accuracy, supporting timely, data-driven decisions across sectors that rely on precise weather predictions.
2. Error correction and bias reduction
   Models are not immune to error, and data assimilation corrects these errors by dynamically adjusting model parameters based on observed data. For businesses, this means access to more reliable forecasts that minimize risk by accounting for known model biases.
3. Seamless integration of diverse data sources
   Effective data assimilation techniques manage vast, varied datasets collected from multiple sources, formats, and time intervals. This adaptability ensures that weather models remain resilient and robust, equipped to integrate data from an expanding array of high-tech observational tools. At Spire, for example, we utilize a hybrid method that blends ensemble approaches—statistical solutions—with deterministic forecasts to maximize accuracy and adaptability.
4. Deeper understanding of atmospheric dynamics
   Integrating observational data not only improves forecast quality but also enhances meteorologists’ understanding of atmospheric processes. This knowledge is key to advancing weather science, leading to models that are better equipped to handle complex phenomena relevant to industries like insurance, where the stakes are high when assessing climate risk.
5. Short – and long-term forecasting accuracy
   Data assimilation is essential for both immediate and extended forecasts, improving accuracy from daily weather reports to seasonal and extreme-event predictions. For logistics and energy sectors, this means better alignment of resources and optimized strategies in response to upcoming weather patterns.

Data assimilation vs. data science: Clearing up the confusion

Data assimilation is sometimes mistaken for data science, but they serve different purposes. Data science typically involves analyzing historical data to uncover trends, while data assimilation is a mathematical process focused on integrating real-time observations into predictive models. In weather forecasting, data assimilation combines information from satellites, ground stations, radar, and ocean observations to form an accurate “initial state” of the atmosphere. This accurate starting point is essential because it determines the trajectory of future forecasts.

Spire’s approach to data assimilation

At Spire Weather & Climate, our commitment to high-resolution weather forecasting is bolstered by innovative data assimilation techniques. We use a hybrid approach that merges ensemble and deterministic methods, ensuring our forecasts are robust and adaptable. Quality control (QC) processes further refine our data inputs, enhancing the reliability of real-time weather insights that our clients depend on.

As Spire Data Assimilation Expert Sanita Vetra-Carvalho explains, “As long as you can model it and observe it, you can apply an appropriate data assimilation technique. These techniques vary depending on the type of data you have, the model you’re using, and what outcome you’re aiming for.”

“The critical piece is setting the initial condition and keeping the system on track, especially because weather is such a chaotic system,” Vetra-Carvalho continued. “For instance, in the ionosphere, you still need to know the initial condition, but it’s not as chaotic. There, it’s more about correcting the drivers that influence the outcome, rather than managing chaos.”

“Similarly, in flood forecasting, it’s less about correcting model chaos and more about adjusting for biases or inflow errors. So, there’s a range of different techniques depending on the system you’re working with,” she added.

Spire’s approach to data assimilation supports clients across various industries, providing forecasts that account for the unique dynamics of each system.

Conclusion

Data assimilation stands as a cornerstone of weather modeling, enabling highly accurate and reliable forecasts for industries where timing and precision are everything. As observational technologies advance, data assimilation will continue to enhance the ability to predict and respond to weather events. For businesses in sectors like utilities, logistics, energy trading, and insurance, the benefits of precise weather forecasting are clear: optimized decision-making, reduced risk, and competitive advantage.

Incorporating data assimilation into weather modeling allows us to respond more effectively to a changing climate and the growing demand for timely, accurate weather forecasts. By setting a strong foundation with a well-defined “initial state,” data assimilation not only supports today’s forecasting needs but also strengthens our ability to navigate the uncertainties of tomorrow.

Learn more about Spire’s High-Resolution Forecast

Reference

Evensen, G., Vossepoel, F., & Van Leeuwen, P. J. (2022). Data Assimilation Fundamentals: A Unified Formulation of the State and Parameter Estimation Problem. 10.1007/978-3-030-96709-3

A mission rooted in accessibility and sustainability

LatConnect 60’s co-founders set out with a vision: to democratize access to high-resolution satellite data and prioritize sustainability-focused sectors. Unlike many observation companies in Australia and Southeast Asia, LatConnect 60 focuses on areas complementary to defense and security, including agriculture, land use, carbon monitoring, and other commercial applications that benefit the planet.

“I come from the space industry in North America, where I’ve worked with notable companies, and during my business development work in Australia and Southeast Asia, particularly, I noticed a general lack of awareness about the value of Earth observation data and how it could be accessed or analyzed. Specifically, the role of high-resolution imaging satellites in sectors beyond defense and security was often overlooked,” said Venkat Pillay, CEO and Founder of LatConnect 60.

“Our drive has been around how to make Earth observation data sets more usable, more accessible, not so restrictive as well in terms of end-user licensing,” Pillay added.

Five years in, LatConnect 60 has downstream clients that understand the value of Earth observation data and its robust applications. One data gap that remained was soil moisture to layer on top of LatConnect 60’s data from satellites using optical imagery and shortwave infrared.

“That’s where we see a tremendous synergy with Spire moving forward,” Pillay said.

Using the latest technology, even more value can be derived for businesses and governments.

“Australia relies heavily on external data sources due to a lack of sovereign observation satellites,” Rueben Rajasingam, LatConnect 60 Co-founder and COO, explained. “Our platforms bridge this gap by integrating satellite data with AI-powered insights to support critical industries like agriculture and resource management.”

Lot Analytics with NDMI Readings: Normalized Difference Moisture Index (NDMI) assesses water content in vegetation to monitor moisture stress and overall crop health across lots.

Spire’s GNSS-R technology: Building on Soil Moisture Insights for advanced applications

One standout collaboration is the integration of Spire’s Global Navigation Satellite System Reflectometry (GNSS-R) technology into LatConnect 60’s platforms. Soil moisture monitoring—critical for arid regions like Western Australia—benefits immensely from the synergy between Spire’s daily soil moisture data and LatConnect 60’s advanced visualization tools.

With these insights, stakeholders can track water use, manage crop health, and optimize biomass forecasting at scales ranging from national to farm-level granularity. Users can access dynamic dashboards, perform day-by-day statistical assessments, and apply tailored data layers to meet their specific needs.

“The current thrust for LatConnect 60 and understanding clients in the areas of agriculture and sustainability, there definitely is an ongoing need for understanding moisture,” Rajasingam said. “Ultimately, what’s critical is moisture in the biomass.”

Lot Analytics with NDVI Readings: Normalized Difference Vegetation Index (NDVI) gives insights on crop health by indicating the density of vegetation across lots. Tracking the changes over time helps to identify trends in crop vitality.

“For the prediction aspect of things, if you understand what’s happening with soil, then there’s forward understanding of what’s going to be happening with the biomass itself, whether that’s for forests or whether that’s for your broadacre crops,” Rajasingam continued.

Besides Spire’s Soil Moisture Insights being updated daily, the LatConnect 60 team noted that another game-changing aspect is the fact that the GNSS-R data is not affected by cloud cover or whether it is day or night. That’s particularly important due to cloud cover issues in the rainy, tropical environment of Southeast Asia. Other alternative methods like flying drones and Synthetic Aperture Radar (SAR) imagery are relatively costly.

Additionally, LatConnect 60 is working to utilize multi-spectral satellite data for even more granular soil moisture details.

Lot Analytics with NPK Readings during the growth stage: Soil nutrient levels like Nitrogen, Phosphorus, and Potassium (NPK) data are useful to support targeted fertilization and soil management for optimized crop growth.

Closing crop yield gaps and addressing food security

LatConnect 60 uses Spire Soil Moisture Insights as a baseline and factors in other elements like soil type and agronomic methodologies to create yield trending, yield forecasting, and crop stress insights, not only helping with food security but also cost savings in terms of water, fertilizer, and pesticide usage.

“A lot of Southeast Asian countries export rice, but yet they still don’t have enough for their own local consumption. And that yield gap is sometimes over 40%. So that’s pretty significant,” Pillay explained.

“The challenge is how do you get some of the local farmers who may not have the capacity to build up smart farming insights up to the speed and level of some of the more sophisticated farmers who are achieving the yield targets,” Pillay said. “That’s where we come in.”

Satellite-enabled solutions offer a more cost-effective and a less invasive alternate to traditional smart farming systems such as IoT sensors or flying drones, bringing significant value for a broader impact.

Yield Trending: By combining a time-series of historical yield data with remote sensing readings like NDVI, NDMI, NPK, and soil moisture data, it can generate crop yield trends and yield prediction for improved agricultural outcomes.

Revolutionizing emergency preparedness

The benefits of this collaboration extend beyond agriculture. Soil moisture data also plays a vital role in bushfire monitoring and water management. By combining Spire’s GNSS-R readings with biomass data, LatConnect 60 enables more accurate fire risk predictions—critical for improving emergency preparedness in vulnerable regions like Western Australia.

“Governments are beginning to recognize the importance of proactive data collection,” Rajasingam said. “Our partnerships with state and federal agencies focus on building predictive models that align environmental and emergency response efforts.”

Driving innovation in the Asia-Pacific and Australia

The partnership between Spire and LatConnect 60 aims to address unique challenges in agriculture, resource management, and climate resilience.

Upcoming events, such as a November 26 showcase in Malaysia with representation from the Malaysian Space Agency, the Thai Space Agency, and others, highlight the growing interest in these solutions. By offering demos of their integrated platforms, LatConnect 60 and Spire hope to demonstrate the value of their partnership to an even broader audience.

Yield Trending: By combining a time-series of historical yield data with remote sensing readings like NDVI, NDMI, NPK, and soil moisture data, it can generate crop yield trends and yield prediction for improved agricultural outcomes.

A partnership poised for growth

LatConnect 60’s modular platforms, now standardizing Soil Moisture Insights across deployments, underscore the flexibility and scalability of its approach. The LatConnect60 team customizes platforms for client needs with agility and speed.

“We take the heavy lift away from the client. We do the data processing of the GNSS-R with Spire and layer that into our platform along with complementary datasets,” Pillay explained. “And the client at the end of the day just gets a better, more precise service.”

By integrating Spire’s data and leveraging AI-powered analytics, these solutions provide actionable insights for industries ranging from agriculture to emergency management.

“Our partnership with Spire has strengthened our ability to deliver comprehensive, user-friendly solutions that meet the needs of diverse markets, particularly agriculture and governments,” said Pillay. “We’re excited about the potential to expand these unique capabilities and drive even greater impact across the Asia-Pacific region and Australia.”

Spire and LatConnect 60 are bridging gaps in data access, delivering critical insights, and empowering industries and governments to thrive in an ever-changing world, including addressing some of the most pressing issues of our time such as food security and climate change.

Learn more about Spire and LatConnect 60

World class assimilation of GNSS-R data

The GNSS-R project involved developing a forward operator to assimilate GNSS-R L2 data, which provides ocean wind speed measurements critical for improving forecasts in regions where accurate data was previously scarce. By assimilating GNSS-R Level-1 DDM or Level-2 ocean wind speed retrievals, Spire’s DA team demonstrated that near-surface wind forecasts could be improved significantly.

GNSS-R ocean observations enhanced Spire’s High-Resolution Forecast for 2-meter temperature, 10-meter wind speed, and precipitation, boosting high-impact weather predictions.

Validation against METAR station data during Storm Babet in 2023 revealed that both L1 and L2 GNSS-R observations enhanced 10-meter wind speed predictions, with GNSS-R L1 DDM proving most impactful in shorter-term (0-19 hour) forecasts and L2 data excelling in increasing accuracy beyond 37 hours.

10-m winds root mean square deviation (RMSD) due to the assimilation of GNSS-R ML DDM and L2 ocean wind speed.

10-m bias reduction due to the assimilation of GNSS-R ML DDM and L2 ocean wind speed.

For energy traders, utilities, and logistics firms, this leap in forecast accuracy presents new opportunities to optimize resources, anticipate demand changes, and improve efficiency across their operations.

Spotlight on the GNSS-R innovators

This project’s success is due in no small part to the dedication of three exceptional women in the field of data assimilation.

Kari Apodaca-Martínez joined Spire after over 10 years of experience at NCAR, Colorado State University, and the University of Miami’s NOAA-cooperative institutes. Her previous experience leading satellite data assimilation projects helped her master the theoretical and computational aspects of advanced data assimilation.

She has expertise in developing algorithms for satellite instruments like GOES-GLM, EUMETSAT-Aeolus, NASA-CYGNSS, and Spire GNSS-R. Kari earned her PhD from Howard University and a Bachelor of Science in Physics and Mathematics from the University of Texas at El Paso.

Her leadership and problem-solving skills have been crucial in tackling GNSS-R data integration challenges. Kari’s extensive background in managing research-to-operations projects funded by NOAA, NASA, and the Navy has played a key role in Spire’s achievements in this R&D project for NASA.

“I’m excited to be part of a team that’s at the forefront of weather forecasting technology,” Apodaca-Martínez said, underscoring her commitment to making GNSS-R data assimilation a success for Spire and its clients.

NOAA has now included the assimilation capability in their 2024 upgrade to their operational DA system, and they’re currently testing it—not with CYGNSS data, since it’s not real-time, but with near real-time Spire data.

“By collaborating with NOAA’s team [and other agencies], we can demonstrate the best way to assimilate this data,” Apodaca-Martínez said. “This could potentially lead them to purchase Spire data, as they wouldn’t need to develop the capability from scratch—we’ve already done that. It’s also a way for us to give back, with the ultimate goal being to improve weather prediction, help businesses thrive, and protect life and property. Those are the most important outcomes.”

Sanita Vetra-Carvalho pursued her passion for data assimilation by earning her PhD in the field at the University of Reading, which has a longstanding partnership with the Met Office UK and ECMWF.

Reflecting on her journey, Vetra-Carvalho noted, “Data assimilation holds the power to deepen our understanding of anything that can be modeled and observed, leading to more accurate predictions and insights.”

“My interest in applied mathematics, that led me to data assimilation, stemmed from my love of both logic and creativity,” she added. “I wanted to find answers through solid, logical methods, but I also wanted the freedom to be creative. Applied math offered that balance.”

Her background in ocean and atmospheric models enabled her to develop algorithms that integrated GNSS-R data effectively into Spire’s High-Resolution Forecast model, contributing to the project’s success.

Kristen Bathmann, with a PhD in applied mathematics from North Carolina State University, brought her experience from NOAA’s National Centers for Environmental Prediction (NCEP) Environmental Modeling Center (EMC), specializing in satellite data assimilation and algorithms for the GFS model.

“Among other things, I worked on bringing new radiance and radio occultation (RO) instrument observations into the GFS model, and worked on improving assimilation algorithms for these observations,” she said.

“I have extensive experience implementing satellite observations to weather prediction models,” Bathmann explained. While this project was her first experience with practical machine learning, her background in mathematics and deep understanding of tackling difficulties that can arise when using new satellite observations prepared her for this R&D project.

Bathmann played a key role in building the machine learning FO that allowed Spire to assimilate GNSS-R data, marking a groundbreaking achievement in the field.

Impact by sector: Leveraging enhanced forecast accuracy with GNSS-R data

Energy trading

• Improved solar forecasting: GNSS-R data enhances the accuracy of cloud cover and solar irradiance predictions, helping energy traders optimize solar power generation forecasts. Ultimately, this leads to more informed trading decisions and energy purchase and sale strategies.
• Wind energy forecasting: By refining wind speed and direction data, traders gain more reliable insights to adjust wind farm output predictions and trading positions.
• Demand response optimization: With more accurate temperature forecasts, energy companies can manage resources more efficiently, reducing costs and boosting profitability.

Utilities

• Enhanced grid management: Accurate temperature extremes help utilities balance energy loads and prevent outages during peak demand.
• Infrastructure planning and maintenance: GNSS-R can provide insights into precipitation patterns and flood risks, aiding utilities in planning for infrastructure maintenance and upgrades and reducing service disruptions.
• Storm preparedness: Enhanced weather forecast accuracy allows utilities to prepare more effectively for severe weather events, such as hurricanes, by minimizing the potential for outages and improving response times.

Logistics

• Route optimization: Accurate weather forecasts can help logistics companies better plan delivery routes, avoiding severe weather to cut fuel costs and improve customer satisfaction.
• Supply chain resilience: Precise weather forecast data aids companies in adjusting inventory levels and minimizing disruptions in the supply chain.
• Real-time decision making: Enhanced weather data supports real-time operational decisions, increasing efficiency and reducing expenses.

Looking ahead: Advancing machine learning in data assimilation

Spire’s DA team continues to push the limits of what’s possible in data assimilation. The success of GNSS-R data integration paves the way for further innovations, including machine learning-based radiance bias correction and soil moisture assimilation from GNSS-R observations.

By continuously enhancing data assimilation capabilities, Spire Weather & Climate aims to deliver even more accurate forecasts, benefiting industries that rely on precise, real-time data to drive decisions.

“Looking ahead, I’m excited about the potential to keep pushing the boundaries of weather forecasting. There’s so much innovation happening at Spire, from leveraging machine learning to enhance predictions to expanding our satellite data capabilities. I feel fortunate to be part of a team that’s committed to advancing the field and making a difference,” Apodaca-Martínez said.

With this pioneering work in GNSS-R data assimilation, Spire has solidified its position as a leader in weather prediction, delivering unparalleled insights with its high-resolution weather forecast model to clients in industries, including energy trading, utilities, and logistics.

“The unique advantages of Spire’s data include global coverage,” Apodaca-Martínez explained. “The NASA mission is focused on the tropics, but Spire’s proprietary fleet of satellites offers increased coverage, improving weather predictions not just in the US or Europe but also in other regions like Southeast Asia.”

The global scale of Spire’s satellite coverage and data is particularly important for the Southern Hemisphere.

“Wind patterns vary significantly closer to the poles, where there’s far more ocean area and fewer surface observations available, especially in the Southern Hemisphere,” Vetra-Carvalho said. “As we continue to build our fleet of satellites in sun-synchronous orbits, the observations will significantly enhance forecast accuracy. This impact will contribute to saving lives, protecting property, and reducing the economic losses associated with disasters and business interruptions.”

As industries look to weather data to optimize resources, protect assets, and drive profitability, the Spire Weather & Climate team continue to innovate, ensuring that our forecasts are more accurate and actionable than ever.

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US winter forecast highlights

A weak La Niña is expected to develop between November and January, and it will play a role in shaping winter weather conditions across the United States. NOAA has given the odds of La Niña taking shape at 75%.

La Niña impacts jet stream patterns and thus influences storm tracks across the US, affecting temperature and precipitation trends.

Seasonal precipitation outlook

Valid: Devember, January, February 2024-25
Issued October 17, 2024
Credit: NOAA

The greatest chances for above-average precipitation will be across the Great Lakes region of the US, according to NOAA. The map, based on the NOAA seasonal outlook, shows projected precipitation departures from normal for December through January.

This winter is expected to bring above-average precipitation from the Northwest to the Great Lakes, as La Niña is predicted to drive a northern storm track, favoring more active winter storms in the northern US. Below-normal temperatures are predicted from the Northwest to the northern Plains.

In contrast, drier-than-average conditions are forecast for the southern US, from the Southwest to the Gulf Coast, which may worsen existing droughts, especially in the central and southern Plains. Warmer-than-average temperatures are also likely in the southern US and along the East Coast.

Seasonal temperature outlook

Valid: Devember, January, February 2024-25
Issued October 17, 2024
Credit: NOAA

The greatest chances for cooler-than-average conditions will be in the Pacific Northwest of the US, according to NOAA. The map, based on the NOAA seasonal outlook, shows projected temperature departures from normal for December through January.

Businesses across utilities, logistics, and insurance sectors can proactively plan for winter conditions to manage risks and capitalize on potential opportunities, while helping traders anticipate market trends and energy supply dynamics.

Business preparedness for winter weather

1. Winter preparedness for utilities

With La Niña driving wetter conditions across the northern US, utilities should focus on strengthening infrastructure and ensuring efficient power distribution during potential storms.

Storm readiness: Secure critical infrastructure to handle increased precipitation and lower temperatures in northern regions.

Deploy smart sensors for real-time monitoring: Using IoT sensors to monitor load fluctuations, line sag, and ice accretion in real-time helps identify potential weaknesses, allowing operators to act before small issues lead to failures.

Trim trees proactively: Snow-laden branches and ice can damage power lines. Conducting extra tree trimming in the fall minimizes the risk of downed lines, especially in areas where heavy snow or ice is expected.

Monitor snow loads on solar panels: Snow buildup on solar panels not only reduces power output but can also lead to structural damage. Having a strategy to clear or monitor snow on panels helps maintain optimal power generation from solar installations.

Drought management: Prepare for increased power demand in drought-prone southern areas where temperatures are expected to be warmer.

Customer communication: Develop clear communication plans to notify customers of potential weather impacts and power disruptions.

2. Logistics: Navigating winter storms and supply chain disruptions

For logistics providers, the combination of wetter, stormier conditions in the north and drier, warmer weather in the south means adapting quickly to shifting routes and potential delays.

Optimize route planning: Monitor winter storm paths and adjust routes to minimize disruptions in northern areas expecting increased precipitation. Spire leverages proprietary data to help organizations mitigate risk for fixed and moving assets worldwide. With DeepVision™, our premier weather risk solution, decision-makers gain 24/7 access to expert meteorologists, ensuring timely and informed responses to weather-related challenges.

Stockpile essentials: Ensure warehouses in affected areas have necessary supplies, especially where drought impacts could affect inventory levels.

Enhance fleet preparedness: Equip vehicles with winter safety kits and educate drivers on handling adverse weather conditions.

3. Energy traders: Strategic positioning for weather-driven volatility

Energy traders should brace for winter’s potential impact on heating demands, particularly with regional shifts like cooler conditions in the north and warmer-than-average temperatures in the south.

Anticipate price shifts: Watch for demand spikes in heating oil and natural gas in cooler northern areas, where wetter conditions might lead to increased energy needs.

Monitor drought impacts: Drought-stricken regions in the south could see changes in energy demand, affecting power generation and consumption patterns.

Manage market volatility: Prepare for price fluctuations driven by temperature swings and demand shifts.

4. Grid management for utilities facing La Niña’s effects

Utilities serving the Pacific Northwest to the Great Lakes regions should prepare for wetter conditions and impacts from winter storms, which could affect power reliability and demand.

Increase storage capacities: Store additional fuel and energy reserves for higher power demand, particularly in regions prone to colder temperatures.

Invest in snow removal: Anticipate the need for frequent snow and ice removal, especially as northern storm tracks are predicted.

Ensure substations are winterized: Protecting critical substations against ice and snow, including insulating pipes, securing ventilation systems, and installing heating elements, can prevent disruptions from equipment freezing.

Pre-position repair crews strategically: When severe winter weather is forecast, position crews in high-risk areas ahead of time to speed up response and reduce the duration of outages.

Emergency response planning: Prepare for rapid response to outages or grid disruptions due to heavy precipitation and storm activity.

5. Fleet operators: Winter weather adaptation

Fleet and transportation companies should prepare for logistical challenges posed by La Niña’s winter storm paths and potential for increased snow and ice in northern regions.

Safety first: Provide snow chains, winter tires, and safety kits for drivers operating in the northern US.

Flexible scheduling: Implement contingency plans for potential delays caused by heavy precipitation.

Route diversification: Develop backup routes to avoid storm-impacted regions, minimizing delays and ensuring timely deliveries.

6. Southern utilities: Managing demand in warm, dry conditions

Utilities in the southern US, where warmer and drier conditions are anticipated, should focus on strategies to manage energy demand fluctuations. In general, lower heating demand is likely given the trend toward above-normal temperatures in the southern US.

Monitor demand surges: Prepare for potential surges in power usage as warmer-than-average temperatures are likely to influence heating and cooling needs.

Promote energy efficiency: Encourage conservation efforts to control peak demand.

Collaborate with local authorities: Coordinate with local governments to optimize resource management.

7. Drought resilience strategies for businesses

Drought persistence will be a significant issue in the central and southern Plains, affecting resource availability for various industries. Additionally, businesses in the energy and utility sectors should be prepared for drought-driven increases in energy use for irrigation systems.

Drought impact planning: Prepare for operational impacts from reduced water resources and potential energy shortages.

Local supplier relationships: Partner with regional suppliers to address possible water and resource constraints.

Conservation initiatives: Develop and promote conservation strategies among staff and customers to manage resource use effectively.

8. Trading and hedging for winter volatility

Energy traders should be aware of possible price shifts due to winter weather’s impact on supply and demand dynamics across the nation.

Hedge against price spikes: Position contracts to account for potential energy demand increases in colder northern areas.

Diversify energy sources: Consider alternative sources or imports to mitigate supply issues from drought-impacted regions.

Real-time weather monitoring: Use advanced weather forecasts, such as the Spire High-Resolution Forecast, to stay updated on weather patterns that could influence energy markets. Our precise, space-powered model outputs hourly forecasts at 3 km resolution, extending out six days, providing critical short and medium-range forecasts with advanced, space-powered accuracy.

9. Insurance claims readiness

Insurers should brace for an uptick in property claims related to severe winter storms, especially in the northern US.

Streamline claims processing: Prepare ahead to handle increased claim volume from winter storms, especially where an active storm path will deliver above-normal precipitation from the Northwest to the Great Lakes.

10. Wildfire risk prevention

Insurance and utility companies in the southern US should prepare for heightened fire risks due to drier-than-normal conditions.

Proactive planning: Encourage policyholders in dry southern areas to adopt fire-prevention strategies.

Risk management: Use high-resolution forecasts to monitor and manage wildfire risks effectively.

Conclusion

With La Niña predicted to influence winter patterns, businesses across industries should prepare for a season of contrasts, from cooler, wetter conditions in the north to persistent and worsening drought in the south. Spire Weather & Climate offers advanced weather solutions, such as DeepVision™ and DeepInsights™, powered by proprietary, space-derived weather data. Our cutting-edge technology provides businesses critical short- and medium-range forecasts, while our upcoming AI subseasonal model will deliver insights into the long-range forecast.

By leveraging these tools, businesses can proactively manage winter risks, streamline operations, and seize opportunities.

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Hurricane Milton by the numbers:

Spire accurately predicted Hurricane Milton’s landfall and impacts

The Spire High-Resolution Forecast model provided valuable insights into Hurricane Milton’s landfall, strength, and related impacts. The model successfully predicted the landfall position and high-end wind gusts with a high degree of accuracy, allowing businesses to properly allocate resources, make smart decisions, and mitigate risks.

Spire’s High-Resolution Forecast model run initialized at 12z on October 7th, more than two days ahead of Milton, depicted the composite radar reflectivity at Milton’s landfall. The pink line shows the NHC official centerline track at the time. The image in the red box in the upper-right corner shows actual radar as Milton made landfall.

Accurate track forecasts: Within three days of Hurricane Milton’s landfall, two-thirds of Spire’s forecasts accurately predicted its landfall location within 30 miles. Half of the model’s forecasts came even closer within 20 miles of the actual landfall location, adding even more confidence in decision-making for businesses with operations in Milton’s path.

Additionally, Spire’s forecasts were consistently south of Tampa Bay ahead of other models and the National Hurricane Center’s centerline track.

Accurate strength forecasts: The Spire High-Resolution Forecast accurately predicted Milton’s major hurricane strength at landfall and the scope and intensity of the most damaging winds, helping electric companies properly allocate resources and reduce downtime.

Spire’s High-Resolution Forecast model run initialized at 12z on October 7th, more than two days ahead of Milton, depicted hurricane-force wind gusts expanding across central Florida at landfall. The forecast shows tropical-storm-force winds extending well beyond that, as was witnessed when Milton hit.

By correctly identifying areas at highest risk, utilities improved response times by up to 30% and reduced average downtime by 20-40%, compared to previous years without similar forecasting tools. Additionally, Spire’s forecast accuracy helped save millions in operational costs by pre-positioning repair crews in the right locations, avoiding costly delays in emergency response efforts.

A wind gust map at 1:30 am ET October 10th captured from DeepVision™, our premier weather risk solution.

Precipitation: Spire’s High-Resolution Forecast model predicted extreme rainfall (more than 16 inches), with a high degree of accuracy, especially from northeast of Orlando to Daytona Beach, providing advance notice on flooding threats and emergency management response needs. Spire’s model was in the 90th percentile of Quantitative Precipitation Forecast (QPF) distributions among multiple models analyzed in the Daytona Beach area, correctly pinpointing amounts.

Why did Spire forecasts perform better for Hurricane Milton?

Spire’s satellite network helps close weather data gaps, particularly in remote areas and over oceans. This proprietary data provides reliable initial conditions, boosting forecast accuracy.

Using Radio Occultation (RO) technology, Spire captures detailed atmospheric data, especially over the oceans, which significantly improved predictions of the forces steering Hurricane Milton. Unlike traditional, limited weather balloon launches, RO is automated and globally accessible, delivering continuous, scalable insights.

Spire’s High-Resolution Forecast predicted Milton’s track and landfall with remarkable precision, allowing sectors like energy, utilities, and power trading to make timely decisions. The model’s superior performance was also due to its ability to capture fine-scale atmospheric processes.

Spire’s model provided early insights into Milton’s weakening ahead of landfall due to dry air and wind shear, demonstrating the critical value of high-resolution forecasting in capturing intricate atmospheric interactions that drive hurricane intensity and movement. High-resolution models can better capture the dynamics and physics, resulting in better and more detailed forecasts.

“Our forecasts of Hurricane Milton once again highlight the accuracy of Spire’s High-Resolution Forecast model,” said Dr. Tom Gowan, Spire Director of Weather Prediction and AI. “The integration of proprietary data and fine grid spacing allows us to capture the small-scale processes that define a hurricane’s track and intensity.”

Conclusion and key business takeaways

Spire’s High-Resolution Forecast model proved essential in accurately predicting Hurricane Milton’s landfall, wind speeds, and rainfall. Businesses across energy, utilities, and power trading were able to make informed decisions with confidence. Spire’s advanced satellite data and Radio Occultation technology enabled more accurate insights into Milton’s path, intensity, and impacts, setting it apart from other models.

The model’s reliability and precision not only enhanced operational efficiency but also mitigated risks. Spire’s forecasts for Hurricane Milton once again demonstrated the model’s ability to deliver world-leading accuracy in the face of severe weather, proving it a critical resource for managing hurricane impacts.

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Heavy rain event before Helene left the southern Appalachians more vulnerable to flooding

An atmospheric river, fueled by moisture from Helene funneled ahead of a cold front, driving unprecedented water vapor into the region ahead of the storm’s arrival. Integrated vapor transport (IVT), a measure of atmospheric river strength, reached 3,000 kg/m/s in western North Carolina, more than 1.5 times the previous record, according to meteorologist Ben Noll. In other words, the atmospheric river delivered a torrent of tropical moisture into the southern Appalachians.

Atmospheric rivers—narrow corridors of concentrated moisture—often bring excessive rainfall, especially when air is forced upward by mountains, as was the case in the Carolinas. These “rivers” of water vapor are some of the largest freshwater conveyors on Earth, surpassing the flow of the Amazon River. When combined with saturated soil, as in the case of Helene, the flood potential is greatly intensified.

Rainfall amounts of 8-12 inches were recorded in the southern Appalachians before rainfall directly associated with Helene arrived.

A regional Soil Moisture Insights map valid September 27, 2024, indicating wet soil due to Helene’s heavy rainfall across much of the Southeast US. The darkest blue shading from northern Georgia to western portions of the Carolines and eastern Tennessee correlate with the corridor of heaviest rainfall from the tropical system.

Soil Moisture Insights analysis for Hurricane Helene

Spire’s Soil Moisture Insights reveal a crucial piece of the puzzle in understanding how Hurricane Helene’s historic flooding unfolded in western North Carolina and surrounding states.

A chart of 500 m soil moisture data over time for a location just northeast of Asheville, North Carolina, including before, during, and after Helene’s flooding. Note the change from the baseline of around 0.3 up to ~0.4 m3 /m3 prior to the hurricane, and then spiking at around 0.6 m3 /m3, while falling down to a much higher temporary baseline as the communities began picking up the pieces.

“In the days leading up to the catastrophic flooding caused by Hurricane Helene in North Carolina, soil moisture levels rose significantly, especially around Asheville. These increases, first observed on September 25th and peaking by the 27th, meant that the soil was already completely saturated when the hurricane struck. When soil is saturated, it can’t absorb additional rainfall, greatly increasing the risk and severity of flooding,” Dennis Quick, Spire Remote Sensing Data Analyst and Sales Engineer, said.

As Quick further explained, saturated soils left little room for excess rainfall, causing floodwaters to rise more rapidly in rivers and streams. While the water levels in waterways peaked and receded relatively quickly, on land, the effects were more prolonged, with floodwaters lingering due to the slower drainage across the saturated terrain.

If the soil takes a while to dry out, the region will be more susceptible to future power outages and wind damage such as falling trees due to abnormally moist soil.

A chart of 500 m soil moisture data for the same location just northeast of Asheville, North Carolina, but zoomed out further on the timeline to show data for roughly four months (June – September 2024). This highlights the more typical spikes in surface soil moisture from routine precipitation events, in contrast with the much larger spike of Helene’s precipitation.

“That’s something to watch out for the remainder of the hurricane season and into the fall months when synoptic scale systems tend to have stronger winds,” Spire Director of Product Management and Meteorologist Chris Manzeck said.

Historic flooding event involving a tropically fueled atmospheric river

A similar event occurred in early October 2015, when South Carolina and parts of North Carolina endured historic flooding. Hurricane Joaquin became an intense Category 4 storm — just shy of Category 5 force – well off the US East Coast. While Hurricane Joaquin never made landfall in the United States, it contributed to the event by sending tropical moisture toward the Carolinas. The tropical moisture interacted with a non-tropical storm system that developed over the Southeast US, dumping rain for days on end.

Over the course of five days, more than 20 inches of rain fell in some areas, with Mount Pleasant, South Carolina, recording nearly 27 inches. The extreme rainfall overwhelmed infrastructure, breaching 18 dams, and causing widespread destruction. This flooding, like Helene’s, was worsened by already saturated conditions and tropical moisture surges, proving that even a hurricane that doesn’t make landfall can cause catastrophic impacts.

Lessons learned from Hurricane Helene and past flood events

The devastating impacts of Hurricane Helene and similar past events underscore the importance of monitoring soil moisture ahead of extreme weather events like landfilling hurricanes. By tracking these factors, meteorologists, governments, and emergency managers can better anticipate flood risks and help communities and businesses prepare for the most severe outcomes.

Spire’s Soil Moisture Insights solution is now available in Cirrus, Spire Weather & Climate’s data visualization platform, with 6 km and 500 m soil moisture data that can be visualized in charts for any location around the world. Additionally, soil moisture maps are viewable for regional trend analysis.

Recap of Hurricane Helene’s US impacts

Hurricane Helene underwent rapid intensification, becoming a large and powerful storm over the eastern Gulf of Mexico, making landfall as a Category 4 storm with maximum sustained winds of 140 mph, about 10 miles west-southwest of Perry, Florida, at 11:10 pm ET on Thursday, September 26^th. It was the first major hurricane to strike the United States in the 2024 Atlantic hurricane season. Helene unleashed a damaging storm surge, destroying 90% of homes in Florida’s Keaton Beach and leaving debris, sand, and rocks piled up and other small Florida beach communities “unrecognizable,” according to the Pinellas County Sheriff’s Office.

The deadly storm’s fast forward motion, massive wind field, and torrential rainfall caused widespread devastation as it moved inland over the Southeastern US. Catastrophic flooding unfolded in the southern Appalachians as 20-30 inches of rain fell. Flash flood emergencies and high-water rescues ensued in Asheville, North Carolina, rural parts of Tennessee, where two dams nearly failed, and Atlanta. Some communities were left entirely isolated by floodwaters as roads crumbled in spots, adding to the recovery challenges.

Helene knocked out power for over 4 million customers, with Florida, Georgia, and South Carolina suffering the brunt of outages. The hurricane’s significant damage caused tens of billions in estimated economic losses, although exact figures are still being assessed.

Helene is the fourth hurricane of the season to make landfall along the US Gulf Coast, and the third hurricane to strike Florida’s Big Bend in 13 months, including Hurricane Debby in August 2024 and Hurricane Idalia in August 2023.

Hurricane Helene by the numbers:

Spire’s early insights into Helene’s eastern track toward Florida’s Big Bend

Spire’s High-Resolution Forecast model accurately predicted Hurricane Helene’s landfall location, timing, and intensity, providing valuable forecasting insights for industries such as energy, commodity trading, utilities, and grid operators. The enhanced model performance contributed to improved operational decision-making, resource allocation, and risk mitigation during this impactful weather event.

Spire’s High-Resolution Forecast model run initialized at 12z on September 26th, the last official run available before landfall, depicts the composite radar reflectivity as Helene at landfall. The pink line shows the NHC official centerline track. The image in the red box in the upper-right corner shows actual radar as Helene made landfall.

Accurate track forecasts: Within three days of Helene’s landfall, Spire’s forecast accurately predicted Helene’s landfall location within 25 miles in two-thirds of its model runs. Three out of the six final runs came within 10 miles of the actual landfall location, adding even more confidence in decision-making for businesses with operations in Helene’s path.

Spire’s forecasts were consistently east of the NHC’s centerline but still within the cone of uncertainty. Ultimately, Spire’s forecast was spot-on with Helene making landfall east of the NHC’s centerline.

Accurate strength forecasts: Spire’s forecasts accurately predicted Helene’s rapid intensification into a Category 4 storm leading up to landfall, pinpointing high-end winds in northern, central, and western portions of Florida and capturing the storm’s large wind field in the Southeastern US.

Utility impact: Accurate predictions of minimal power outages and wind gusts in the eastern Florida Panhandle helped utilities with resource planning, while Spire’s High-Resolution Forecast precisely indicated the location and intensity of the most damaging winds.

Precipitation: Spire’s High-Resolution Forecast model accurately predicted extreme rainfall (up to 30 inches) in the southern Appalachians days in advance, providing early insights into flooding threats and emergency management response needs.

Spire’s High-Resolution Forecast model identified potential rainfall extremes 24-36 hours earlier than other models, allowing for more effective messaging regarding flood risks and providing earlier guidance for flood preparation measures. Spire’s model was in 99th percentile of Quantitative Precipitation Forecast (QPF) distributions among multiple models analyzed, which turned out to be the correct forecast.

Spire’s High-Resolution Forecast model run initialized at 12z on September 24th, two days ahead of landfall, depicted rainfall amounts from 26 inches to locally 30 inches of rain in the southern Appalachians.

Why did Spire forecasts perform better?

Spire’s extensive satellite network plays a vital role in closing critical weather data gaps, particularly in hard-to-reach regions such as remote areas and over vast ocean expanses. This proprietary data provides reliable initial weather conditions, a crucial factor in increasing the accuracy of forecasts.

Spire’s Radio Occultation (RO) technology allowed for more comprehensive sampling of atmospheric conditions, especially over the oceans. This capability improved the forecast accuracy regarding the forces steering Hurricane Helene. RO technology is a revolutionary method that retrieves vertical profiles of the atmosphere, much like data from weather balloons. However, unlike traditional balloon launches, which are manual, expensive, and limited to land-based operations, RO is automated, scalable, and globally accessible.

Spire’s High-Resolution Forecast offered critical insights into Hurricane Helene’s trajectory toward Florida’s Big Bend well ahead of other models. The high-resolution model forecasted Helene’s exact track and landfall location with remarkable precision, enabling timely decisions across sectors like energy and utilities.

The last six Spire High-Resolution Forecast model runs for the continental US (September 24th initialized at 06z through September 26th initialized at 12z) landfall locations (green squares), model positions at September 27th at 03z (yellow targets), all NHC official centerline tracks (black lines), and 10 mile (red), 20 mile (yellow), 30 mile (green), and 50 mile (white) range rings surrounding the official landfall location (red star). September 27th 03z modeling positions were captured as that was the official landfall time of Helene.

Spire’s network of satellites achieves this precision by analyzing signal distortions from GPS/GNSS satellites caused by atmospheric factors. This results in unparalleled global coverage, delivering essential weather data from polar regions to remote oceanic locations, helping fill the significant gaps that exist in traditional observation methods.

Hurricane Helene rapidly intensified leading up to landfall and wobbled to the right in its final hours over the Gulf of Mexico, which presented challenges in precisely predicting landfall and the location of Helene’s greatest wind impacts. In addition to superior initial weather data, Spire’s High-Resolution Forecast model offered deeper insights into fine-scale atmospheric processes, proving invaluable for those managing risk in the face of such a powerful storm.

High-resolution forecasting models are essential for capturing detailed atmospheric interactions, such as convection and ocean surface processes, that determine the intensity and movement of hurricanes. Spire’s model brought a new level of clarity and accuracy to forecasting Hurricane Helene, providing significant value to industries that rely on precise weather data.

“As shown by our forecasts of Hurricane Beryl and Helene, Spire’s High-Resolution Forecast model excels at forecasting tropical systems,” Dr. Tom Gowan, Spire Director of Weather Prediction and AI, said. “The assimilation of our proprietary data, including RO, accurately initializes storms over the open ocean, while the fine grid spacing of our model enables the small-scale processes that govern hurricane development, track, and strength to be resolved. Ultimately, this results in forecasts with world-leading accuracy that enables communities and companies additional time to prepare for the devastating impacts of hurricanes.”

Spire’s High-Resolution Forecast model run initialized at 12z on September 24th, two days ahead of landfall, depicted hurricane-force wind gusts across the southern Appalachians.

Conclusion and key business takeaways

Spire’s High-Resolution Forecast model proved to be an invaluable tool in the accurate prediction of Hurricane Helene’s landfall, wind speeds, and precipitation. The model’s ability to provide early, accurate forecasts allowed businesses in industries like energy, utilities, and commodities to make informed, confident decisions. Spire’s superior performance demonstrated the model’s robustness and reliability, making it a key resource for enhancing operational efficiency and mitigating the impacts of severe weather events.

Explore Spire’s High-Resolution Forecast

A journey rooted in cloud analysis: ‘Another level of realism’

Steve Albers’ journey to Spire was shaped by his 32 years of work with NOAA and Colorado State University, where he developed an initial version of cloud analysis.

Prior to that, he earned an M.S. in Atmospheric Science at the University of Oklahoma and a B.S. in Physics at SUNY Albany.

“The cloud analysis has three dimensions,” Albers explained. “It shows all the hydrometeors and some aerosols in the atmosphere. I’ve always been interested in getting clouds into models because that’s one way to drill down into the fine details and see if the model represents reality.”

For Albers, who has been with Spire since 2018, the cloud analysis has always been an “acid test” for models—checking if they can reproduce cloud formations visible in the real world.

This depth of realism goes beyond just breathtaking imagery and “taking the temperature” of the atmosphere; it offers a higher level of accuracy in weather modeling, especially as we move towards higher resolution models that can depict cloud density, type, and precipitation.

At Spire, Albers’ work on cloud analysis has been paired with a complementary cloud ingestion system.

Full disk Earth view. On the left, a simulated view from Spire’s analysis is shown for October 7, 2023, at 00:45 UTC. On the right, the observed view for the same date and time is shown, courtesy of DSCOVR.

The pivotal role of cloud ingestion: Going beyond ‘predictability barriers’

Gustavo Carrió’s career, spanning 16 years at Colorado State University and eight years at Spire, has been focused on simulating cloud behavior over time. His work has involved developing numerical schemes to improve how models simulate cloud evolution.

Carrió, who holds an M.S. and PhD in Atmospheric Science from the University of Buenos Aires, said, “The idea is to determine exactly where the clouds are with global 3D snapshots. That is Steve’s job, and we need to help the model to rapidly and accurately develop what is needed to retain them. It’s not just putting them in; retaining them is a big challenge.”

The cloud ingestion system at Spire plays a critical role in ensuring that models can develop responses consistent with cloud snapshots.

“Models cannot necessarily generate storms exactly where they happen. It is very close to a predictability barrier,” Carrió explained. “But it’s a great help to say, ‘OK, they are exactly here, and they have exactly these shapes,’ and therefore, we go beyond that predictability barrier.”

This complex, multi-dimensional process, which factors in numerous data points simultaneously is a crucial function at the initial stage to ensure that the Spire High-Resolution Forecast responses align with the actual cloud data being ingested.

“The benefit is not restricted to the position of storms,” Carrió added. “There are thinner clouds that cover large areas. Mapping them in a very accurate way improves how the model performs. For instance, low-level temperatures, especially for those very close to the ground, and wind forecasts are more accurate with cloud analysis and ingestion.”

More accurate forecasts of these variables translate to better insights for renewable energy production and other industries reliant on precise predictions.

This capability means the Spire High-Resolution Forecast will better predict evolving weather patterns. This system has been a significant step forward in weather prediction, enabling more accurate, short-term forecasts.

Infrared satellite simulations over Europe on November 16, 2023, at 03:00 UTC. On the left, the WRF model first guess is shown. The middle image shows observed conditions from Meteosat. On the right, Spire’s cloud analysis is shown.

The game-changing impact of hot-start modeling

One of the most groundbreaking aspects of Spire’s High-Resolution Forecast is the hot-start technique, which significantly reduces the model spin-up time.

“Our system is unique because right from the initial time, it almost totally eliminates what we call the model spin-up,” Albers explained. Essentially, the technique provides granular forecast details right away unlike other models, which can take a couple of hours to depict short-term weather forecasts such as convectively driven pop-up thunderstorms.

The top row shows precipitation rates at 06:00 UTC on May 3, 2024. The left image represents observed conditions, the middle shows the Spire High-Resolution Forecast without Cloud Ingestion, and the right displays the forecast with Cloud Ingestion. The bottom row presents infrared satellite brightness temperatures: observed conditions on the left, the six-hour forecast that was initialized at 00:00 UTC without Cloud Ingestion in the middle, and the six-hour forecast that was initialized at 00:00 UTC with Cloud Ingestion on the right.

This capability is a game-changer for short-term weather forecasting, setting Spire apart from other models that take up to six hours to spin-up. Spire’s High-Resolution Forecast delivers critical insights and precise weather details in the short- and medium-range by offering hourly forecasts out to six days at 3 km resolution.

Spire’s in-house cloud ingestion and analysis systems allow us to hot-start our High-Resolution Forecast model, enabling accurate now-casts and short-range forecasts. This provides immense value to clients in energy trading, utilities, and other industries by helping them to maximize efficiency and operations.

Spire’s differentiated data gathered from its fully deployed satellite constellation is coupled with data from government partners, offering comprehensive visible and infrared data.

“That allows us to get more information about how dense the clouds are and how tall they are,” Albers said. “Geosynchronous data is very nice because it’s very high resolution down to about a kilometer or so in the daytime and about 2 kilometers at night. Also, it’s very high temporal, very frequent data.”

The geosynchronous satellite data combined with the Spire High-Resolution Forecast “first guess” and frequent radar data provides another level of precision.

“In theory, we could actually look minute by minute in the forecast model and have a good cloud and precipitation rate forecast,” Albers said.

The Spire High-Resolution Forecast for the continental US for July 30, 2024, is shown without Cloud Radar Data Assimilation on the left. In contrast, the Spire High-Resolution Forecast for the continental US for the same date and time is shown with Cloud Radar Data Assimilation in the middle. Actual radar is shown to the right.

Continuous advancements of our Spire High-Resolution Forecast

Spire’s use of space-derived data, AI, and machine learning further enhances the accuracy of its weather predictions.

Carrió noted that aerosols are another area of focus. These particles, such as dust and smoke, can significantly affect visibility and solar radiation, making their accurate modeling essential for reliable forecasts critical to industries such as energy.

“Features like pollution change the ways clouds behave and how radiation heats differentially with altitude, and therefore also condition how clouds will evolve due to the availability of energy and so on,” Carrió explained.

Looking ahead, both Albers and Carrió are excited about the potential to enhance Spire’s weather prediction capabilities. They’re particularly interested in improving the way models interact with environmental factors like pollution, which can influence cloud behavior and weather patterns.

“I’m continually impressed by the breadth and depth of expertise across our scientists, like Steve and Gustavo, at Spire Weather and Climate. This knowledge enables us to build unique, differentiated systems that extend well beyond simply processing public data,” Dr. Tom Gowan, Spire Director of Weather Prediction and AI, said. “By developing proprietary tools in-house, such as our cloud analysis and ingestion system, we can deliver more accurate and tailored forecasts, offering a significant advantage to our customers in the energy, commodities, and utilities markets.”

As Albers and Carrió, along with other scientists on the Spire Weather & Climate team continue to refine and expand these capabilities, the future of weather forecasting looks brighter—and more accurate—than ever before.

Unlock the power of unequaled insights into Earth’s most fundamental resource: its soil.

Discover Spire’s Soil Moisture Insights

What are the risks heading into peak hurricane season?

The National Weather Service Climate Prediction Center (NWS CPC) highlighted the concern for tropical cyclone development from the Gulf of Mexico to the central Atlantic during mid-to-late August. The chances will grow north of the Greater and Lesser Antilles during the middle of August and shift toward the central Atlantic by late August.

“Atmospheric and oceanic conditions have set the stage for an extremely active hurricane season that could rank among the busiest on record,” a recent NOAA Atlantic hurricane season update stated.

There are indications that tropical activity will increase heading into the heart of the season due to an uptick in tropical wave formation over Africa and the main development region of the Atlantic Ocean.

For instance, Ernesto developed from a tropical wave pressing westward across the Atlantic, becoming a tropical storm 10 days ahead of the climatological average for the fifth named storm of the season. After impacting the northeastern Caribbean islands, Ernesto is expected to continue strengthening as it nears Bermuda. It will likely lose some wind intensity before brushing Atlantic Canada with heavy rainfall.

Other systems could follow in Ernesto’s wake forming in a similar area of the tropical Atlantic, and Spire meteorologists are keeping a close eye on tropical waves emerging from Africa.

“Atlantic maritime interests should take note of the increased tropical activity potential,” Spire Meteorologist and Weather Risk Expert Jared Allen said.

Business interests in the US and Caribbean will likely face additional landfalls and threats from tropical storms and hurricanes in the coming weeks and months.

“While above-normal ocean temperatures and low wind shear environments can aid the likelihood of rapid intensification with a favorable weather pattern expected for strengthening during the peak season, winds and storm surge are not the only hazards of concern. Inland flooding typically causes fatalities, infrastructure impacts, and supply chain interruptions,” Allen explained.

“According to the National Hurricane Center, a significant number of fatalities are caused by freshwater flooding, regardless of storm intensity and hurricane category,” Allen added. “Therefore, it is critical to know your personal and business vulnerability to flooding, even hundreds to a thousand miles inland from landfall.”

What are the factors behind peak hurricane season activity?

Sea-surface temperatures continue to run historically high across critical areas of the Atlantic basin, remaining at near-record levels from the Caribbean to the main development region of the tropics.

Above-average sea-surface temperatures can support more hurricane formation and intensification since warm ocean water fuels warm-cored tropical cyclones.

In addition to water temperatures favoring an active peak hurricane season in the coming weeks, other atmospheric conditions are likely to be primed for robust tropical cyclone behavior.

The El Niño-Southern Oscillation (ENSO) is currently neutral, known as an ENSO neutral phase, but anticipated changes during the peak season could set the stage for more hurricanes.

La Niña, defined by cooler-than-normal waters in the central and eastern Pacific near the equator, is favored to return between September and November – recently adjusted to a later timeframe than previous projections. The CPC predicted La Niña’s return within that period at a 66% chance. The climate pattern is favorable for tropical development in the Atlantic since it reduces vertical wind shear over the basin.

Vertical wind shear can inhibit the development and strengthening of tropical storms by displacing the upper-level and lower-level low-pressure centers so that they are no longer aligned vertically. Weakening circulation occurs similarly to how a top’s spin can unravel when it becomes tilted.

“Multiple dynamical model ensemble members in the medium to long range highlight the potential for a more favorable Madden-Julian Oscillation (MJO) phase aiding easterly tropical wave formation over Africa and in the main development region of the Atlantic basin,” Allen said. “However, nuanced details of easterly wave positioning, strength, and wind-shear dynamics will need to be monitored for overall impact potential to land.”

Saharan dust can inhibit or delay the development of tropical systems, especially early in the season, according to Sherrod. Pockets of dust were still visible over parts of the Atlantic in early August.

Historical trends and analog years

According to research complied by Colorado State University (CSU) in an August 6 update, analogous years for the 2024 hurricane season are 1886, 1926, 1933, 1995, 2005, 2010, and 2020 based on global oceanic and atmospheric patterns. These patterns were based on El Niño conditions in the previous winter with ENSO neutral or La Niña conditions during the peak of hurricane season. These years were also selected due to above-average sea-surface temperatures relative to long-term averages in the tropical Atlantic.

Based on these analog years, there was an average of nearly 20 named tropical storms per season, six above the historical average of 14. Additionally, these years averaged 5.7 major hurricanes (Category 3 storms or higher) compared to the long-term average of three major hurricanes. Lastly, the average ACE for these years was nearly 218, well above the long-term average of 123 (1991-2020 climatology).

According to CSU, additional dynamic models and statistically based output suggest that 2024 could be an active to hyperactive season. The analysis, compared to the analog years, found many predictive parameters to be even higher, thus further increasing confidence in an above-average hurricane season.

“It is noteworthy that much of CSU’s analysis uncovered higher ACE values than the hyperactive 2005 season that brought severe and devastating impacts to the US mainland,” Allen said. “While it is way too early to compare 2024 to 2005, and it would be presumptive to do so, vigilance and preparation is key, for possible maritime, landfall, and inland tropical cyclone impacts.”

“It should be noted that an active or hyperactive year does not guarantee significant land impacts, as was the case in another analogous year of 2010,” Allen explained. “There were 19 named storms, 12 hurricanes, and five major hurricanes in 2010, but no hurricane landfalls occurred in the US mainland.”

However, a couple of tropical depressions and one tropical storm impacted the US, with effects including inland flooding and tornadoes. Large and powerful Hurricane Earl unleashed damaging storm surge, near hurricane-force winds, and heavy rainfall as it passed about 100 miles east of North Carolina, but it never made a direct US hit.

What can businesses do to stay prepared during hurricane season?

Download our checklists below for ways that your business can safeguard your people, property, and profits before, during, and after a storm.

Here at Spire Weather & Climate, we’re committed to empowering businesses and traders using one of the world’s largest multi-purpose satellite constellations. We capture exclusive data and enhance its value through sophisticated assimilation, artificial intelligence, and machine learning processes.

We also leverage our proprietary data to help organizations mitigate weather risks worldwide. With DeepVision™, our premier weather risk solution, decision-makers gain 24/7 access to the Spire DeepVision™ Weather Support team ensuring timely and informed responses to any weather-related challenges during hurricane season.

Download business guides on hurricane preparation before, during, and after a storm
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Before and after Hurricane Beryl: Soil Moisture Insights for the US

Hurricane Beryl made landfall near Matagorda, Texas, on Monday, July 8 as a Category 1 hurricane with maximum sustained winds of 80 mph. Widespread damaging winds resulted in power outages to nearly 3 million customers in the US at its peak. The Houston, Texas, area was most significantly affected, with outages lasting for weeks for some.

Flooding occurred along the hurricane’s path, but Spire’s Soil Moisture Insights also highlight some benefits from Beryl.

“Beryl certainly improved the overall surface soil moisture in Southeastern Texas into Arkansas, Missouri, and Illinois as it moved inland,” Spire Meteorologist and Weather Risk Expert Jared Allen said.

Spire’s Soil Moisture Insights (shown left) and soil moisture anomaly (shown right) on July 10, 2024, depict wetter surface soil moisture conditions across portions of the central US after Hurricane Beryl’s impacts.

“To go from -1.5 or -2 standard deviations to a +1.5 to +2 standard deviations would be significant in only happening with tropical cyclone landfalls or unique heavy rainfall patterns. While not unprecedented, this type of turnaround in soil moisture certainly doesn’t happen often, even for flood-prone Southeastern Texas,” Allen added.

The US Drought Monitor echoes significant changes in dry conditions across areas impacted by Beryl in the two weeks from July 2 to July 16. Notably, within that period, moderate drought conditions vanished across parts of Arkansas, Missouri, and Illinois, with only two small pockets of abnormally dry conditions persisting in northern Arkansas and central Illinois.

“The rainfall, especially in the goldilocks areas on the storm’s periphery, likely mitigated agricultural industry spending by limiting irrigation use for crops and refilling of wells and stock animal ponds and other agricultural needs given how dry it was before Hurricane Beryl,” Allen explained.

Meanwhile, some fields were likely flooded or too wet for tractor access for a week, which may have resulted in some losses where soil moisture was highest.

Soil Moisture Insights for Mexico

The soil moisture signature was more muted across the Yucatan Peninsula, as Beryl crossed the region in a weaker state and the main precipitation core shifted towards the northern coast. After Beryl made landfall near Tulum, Mexico, as a Category 2 storm with maximum sustained winds of 110 mph early on the morning of July 5, rapid weakening occurred as it moved inland across the Yucatan.

Rain and wind brushed the eastern tip of the Yucatan Peninsula as the storm moved through the region, but there were no reports of fatalities or widespread damage. Beryl emerged over the southwestern Gulf of Mexico as a tropical storm with maximum sustained winds of 60 mph that evening.

Spire’s Soil Moisture Insights show the most significant change in soil moisture conditions over the far northeastern tip of the Yucatan Peninsula. The soil moisture anomaly maps before and after Beryl depict a change from -1.5 or -2 standard deviations to a +1.5 to +2 standard deviations in that small zone.

Farther west, soil moisture conditions became drier over an area in the central Yucatan Peninsula, likely signaling the area affected by subsidence, or sinking, dry air after Beryl’s influence. This area of dry soil aligns well with the local precipitation minimum observed. NASA satellite-derived data estimates indicated only 0.05 to 0.20 of an inch of rain fell in parts of the western Yucatan. Additionally, hot and dry conditions typically follow in the wake of many tropical cyclones. Analysis of Spire’s Soil Moisture Insights data depicted the dryness of the soil in this region likely due to these factors.

Despite warm Gulf of Mexico waters and low wind shear, both factors favorable for hurricane intensification, it took some time for Beryl to become more organized again likely due to the weakened storm’s poor organization. When it moved over the Gulf, the low-level center of circulation had become displaced from the upper-level low-pressure area. For tropical systems to become better organized and stronger, meteorologists look for the structure of a storm to be vertically stacked.

Spire Soil Moisture Insights and business applications

Spire Global recently announced its advanced Soil Moisture Insights, leveraging its fully deployed constellation of satellites combined with AI and machine learning technologies. This innovative solution offers high-resolution, precise soil moisture data updated daily, up to a 500-meter resolution. Users can access a comprehensive 40-year archive of soil moisture data worldwide, providing invaluable insights for trend analysis, climate research, and data science applications.

The product is designed for a wide range of users and applications, including risk management in insurance, agriculture commodity price forecasting, drought forecasting, irrigation and crop management for precision agriculture, flood and wildfire prediction, environmental monitoring, construction and civil engineering efforts, hydrological modeling, weather modeling, and as input to a variety of machine learning applications.

The critical role of soil moisture in environmental and economic stability is well recognized, impacting agriculture, water resource management, and environmental hazard mitigation. With global accessibility and effortless integration via an easy-to-use API, Spire’s Soil Moisture Insights empowers businesses, researchers, and government agencies to optimize operations and make informed decisions.

Reflecting on 2023’s wildfire season

To look ahead, we must begin by looking back. The National Interagency Fire Center’s report for 2023 showed that last year was one of the least active fire seasons on record, with the fewest number of acres burned at 2,693,910 and the third-lowest number of individual fires at 56,580. However, individual wildfires were still massively destructive and costly, despite the overall reduced risk across the nation.

The Gray Fire and Oregon Road Fire in Spokane County, Washington, destroyed a combined total of 366 residential homes and resulted in the deaths of two people, according to the Washington Department of Natural Resources. The devastating Maui wildfires destroyed over 2,200 structures, killed more than 100 people, caused major economic losses estimated at about $5.5 billion in damages, and impacted tourism, the US Fire Administration said in a report.

The 2024 fire season has already been destructive, with the Park Fire in northern California ranking among the top five largest wildfires in the state’s history. As of early August, it continued to grow. According to the National Interagency Fire Center (NIFC), 2024 has recorded more than 28,000 wildfire incidents, burning about 4.5 million acres. Compared to 2023, more acres have burned this year despite having about half the number of fires, indicating a higher occurrence of large or difficult-to-contain fires.

US wildfire statistics for the last 10 years:

Data for the number of wildfires and acreage burned across the US over the past decade. (National Interagency Coordination Center)

Impact of above-normal precipitation and carryover fuels

Above-normal precipitation in 2023 is attributed to the reduced number of wildfires, especially for Western regions. This increased precipitation, however, has meant that some places, especially parts of Idaho, Nevada, and Utah, are going into the 2024 fire season with a high amount of carryover fuels, or exceptionally dense brush and grass, which is now available for burning in 2024.

Surface soil moisture data (left) from September 1, 2023, showed dryness in parts of the Western and Central US, with a small dry area in the Northeast. The anomaly map (right) highlighted significant below-average soil moisture levels, depicted in deep red, in the Upper Midwest and along the Northeast coast. Soil moisture anomalies for the West Coast and Southeast were near normal to above average.

Comparing soil moisture from 2023 to 2024, significant differences emerge in the anomaly maps, which compare the soil moisture levels relative to the 10-year historical average. By September 2023, soil moisture levels in the West and Southwest were generally near normal to below normal. In contrast, 2024 shows many more areas with below-normal soil moisture, especially in the Pacific Northwest and northern California.

Additionally, the Southeast exhibits far below-normal soil moisture this year, whereas, by late summer 2023, much of this region had near-normal to above-normal soil moisture conditions. In the Great Plains and Midwest, soil moisture anomalies are less noteworthy this year despite conditions remaining generally dry. Notably, Hawai’i displays much drier anomalies and surface soil moisture this year, particularly on the leeward sides of the islands, raising concerns given the magnitude of the 2023 wildfires in Maui.

Adding fuel to the fire

Drought is an indicator of heightened fire risk. Parts of northern Idaho have been in a long-term drought, which has contributed to above-normal fire risk this summer. A lack of rainfall not only increases the amount of dried vegetation, which makes excellent fuel for fires, but can also make containment of fires much more difficult, resulting in larger and more destructive wildfires. Mountainous regions, such as northern Idaho, present an additional challenge as the terrain can make access to ongoing fires difficult, which in turn can result in increased fire risk.

Climate change is increasing the intensity and frequency of flash drying of fuels. For instance, the Maui fire in 2023 was driven by the flash drying of fuels and an extreme wind event. It should be noted that the types of fuels available for burning play a significant role in wildfire behavior. Also, nearly 85% of wildfires are caused by humans in the US, according to the National Park Service. Additionally, the escalation in destructive wildfires is due to increased building and populations in wildland areas, known as the Wildland Urban Interface. Wildfires are a big part of Earth’s natural cycle, but if we continue to build and live in areas that are prone to wildfires, it will only increase the risk of being impacted by wildfires.

Of course, the opposite is true also. Areas where drought is non-existent due to above-normal precipitation totals will face a lower risk of wildfires. This was the case for places such as northern California, which was not experiencing drought or abnormally dry conditions in the spring and early summer, resulting in wildfire risk being below normal into July. However, an expected drier end to summer will continue to elevate the fire risk to near normal or perhaps slightly above normal for parts of the northern Central Valley of California and into portions of the northern Sierra Nevada.

Additionally, record July heat in northern California and the Pacific Northwest has set the stage for more wildfire vulnerabilities in the coming weeks.

Winter snowpack and its influence on fire season

For mountainous regions, winter snowfall, and the rate at which it melts can be a defining factor in the following summer’s wildfire risk. The Cascades this past winter saw lower-than-average snowpack development, however, the snowpack that did develop was slow to melt. That has resulted in a slightly delayed start to the fire season across parts of Washington, Oregon, and Idaho, as green-up, or new plant growth, was delayed due to snow cover. A summer continues, and this growth begins to dry out as above-normal temperatures are expected late this summer, fire risk will increase for these regions.

The North American Monsoon’s role on wildfire season

The North American Monsoon (NAM) is also a contributing factor to wildfire development, especially across the southwestern US, as this helps to fuel the majority of summer rainfall for places like Arizona, New Mexico, and parts of Colorado. A weaker-than-average monsoon will result in drier soil and more dry fuels, and any fires that ignite will be harder to contain without rainfall to help out. On the other hand, a stronger-than-average monsoon season will do the opposite and help reduce the risk of wildfire development. Although the NAM impacts several states, it accounts for more than 50% of the annual rainfall in New Mexico and Arizona. With the Climate Prediction Center season outlook predicting below-normal rainfall and above-normal temperatures from August to October, wildfire risk may be elevated across Arizona and New Mexico.

One other risk to consider is the fact that thunderstorms triggered on the periphery of the NAM moisture can sometimes produce frequent lightning with little rainfall, and these dry thunderstorms often ignite wildfires.

El Niño-Southern Oscillation transition and its effects

Meanwhile, a transition is occurring in the El Niño-Southern Oscillation (ENSO). El Niño ended earlier in the summer, and ENSO-neutral conditions now prevail. La Niña conditions are likely to develop between August and October. Some of the climatological changes associated with the development of La Niña may lead to localized impacts on wildfires.

Wind events are a major driver for wildfire spread and can make existing fires incredibly difficult to contain. La Niña may enhance trade winds, which increases the risk factor in places such as northern California and Hawai’i, increasing fire development risk in the late summer.

Santa Ana winds in Southern California can be a driver of wildfires from September to March, although research has shown that El Niño, rather than the predicted La Niña, tends to increase the intensity of these wind events. Still, Santa Ana winds can especially influence wildfire spread as they are characterized by their dry nature, originating from the deserts of the Southwest, and incredibly high speeds. Combined with the warmer and drier weather associated with La Niña in the Southwest, heightened wildfire risk in the fall and winter combined with the arrival of Santa Ana winds could result in very fast moving and destructive fires.

Across parts of the Southeast, especially across higher terrain, the transition period to La Niña has often resulted in warm and dry falls and winters, which could increase wildfire risk. However, the National Interagency Fire Center (NIFC) says long-term model guidance is mixed on what this fall could look like for the region.

In the Northwest, a transition to La Niña is typically associated with cooler and wetter ends to the fire season, but there can be exceptions. One such exception was in 2016. In both the Northwest and the Southeast, the NIFC reports similarities to that 2016 season, and a comparison to that year may give us an idea of what to expect this fire season. There was also a delayed start to the 2016 monsoon season, which may occur again this year with below-normal precipitation across New Mexico and Arizona.

To put it in context, 2016 was, like 2023, a year considered below average for wildfires. NIFC reported that the US saw 92% of the 10-year average of reported wildfires, and 79% of the 10-year average of acres burned in 2016. That year, Alaska and the Southwest endured an above-normal number of wildfires, while the Rocky Mountains, Southern California, and the South saw above-normal acres burned.

Surface soil moisture data (left) from September 1, 2016, indicated dryness in the interior Northwest, California, the northern Plains, and parts of the Eastern US. The anomaly map (right) showed significant below-average soil moisture levels in a few zones of the East, depicted in deep red.

Comparing the soil moisture anomalies for 2024 and 2016 reveals some clear similarities. The most notable similarity is the below-normal anomalies across the Southeast and along the East Coast. Although these anomalies are stronger this year, this pattern correlates with the NIFC’s assessment that the fire season in the Southeast may resemble that of 2016. In 2016, the Great Plains and Midwest had larger areas of above-average soil moisture conditions compared to both 2023 and 2024, which could explain the lower-than-normal wildfire statistics that year. Meanwhile, the below-normal anomalies in the West and Southwest this year appear stronger than those in 2016.

Wildfire risk outlook for late summer to fall

Overall, the wildfire risk is expected to shift through the remainder of summer and into the fall. August will bring the most widespread above-normal fire risk, mainly situated over southern Oregon, Idaho, northern Nevada, and Utah, where high amounts of vegetation will be ready to burn once they dry out and above-normal temperatures are expected. Parts of Arizona, New Mexico, and southeastern Colorado are also expected to see above-normal fire risk in August, as rainfall is expected to be below average. These same regions will continue to see increased fire risk in September, with fire risk in California shifting southward to the southern coastline, where above-normal fine fuel loading is expected as well as above-normal temperatures and drier conditions. Elsewhere in September, the fire risk will return to normal across much of the country, with the exceptions of Southern California, Arizona, New Mexico, and parts of Virginia, and West Virginia at above-normal risk.

Wildfires can be quick to spark, fast to spread, difficult to contain, and potentially present extreme danger to homes and businesses. Where you are located can change your wildfire risk level, but on the back of a quiet 2023, there is a lot of unburned dense shrubbery on tap.

Since the Western US is generally expected to be warmer and drier, and slight impacts from a transition from ENSO neutral to La Niña are anticipated, there are several spots where wildfire risk will be heightened heading into late summer and fall. Any business owners and homeowners in areas prone to wildfires should always be prepared to take action quickly when the situation arises.

Using Spire’s Soil Moisture Insights to assess wildfire risk for businesses

There is a strong correlation between the timing and location of low soil moisture conditions and an increase in fires. In general terms, fires are more likely to occur in drought-affected areas and during dry seasons. Spire’s Soil Moisture Insights can be leveraged as a tool to weigh potential wildfire risk.

Dry soil is linked to more fires, but fires can also cause dry soil, affecting soil water availability for agriculture, and negatively impacting crop health and production. Satellite-based soil moisture and fire observations can aid local governments, response agencies, and other businesses in better anticipating and preparing for an active fire season, and aid in tracking the potential impact of fire on soil water availability and crop production.

Explore Spire’s Soil Moisture Insights

Hurricane Beryl by the numbers:

The storm forced thousands of flight cancellations and temporarily caused disruptions to oil production.

Beryl was also a prolific tornado producer, ranking second behind Hurricane Ivan from 2004 in terms of the number of tornado warnings triggered in the United States from a tropical system.

The economic impact is estimated to be in the billions of dollars, although specific figures are still being assessed.

Floodwaters inundated Buffalo Bayou Park in Houston, Texas, as Hurricane Beryl hit.

Advanced notice from the Spire High-Resolution Forecast allowed our customers to make informed business decisions with confidence ahead of Hurricane Beryl’s landfall. Early and precise forecasts are critical for energy, utility, insurance, and trading interests among other industries as hurricanes approach.

The Spire High-Resolution Forecast is the only 3 km resolution model, with hourly forecast outputs extending to six days over the entire continental United States. This model accurately predicted Beryl’s Texas landfall location before most other models.

Read on to learn more about Spire’s High-Resolution Forecast performance on Hurricane Beryl.

Spire’s early insight into Hurricane Beryl’s northward track toward Texas

The Spire High-Resolution Forecast came within 25 miles (40 km) of Hurricane Beryl’s actual landfall location 78 hours in advance. The 06Z Spire High-Resolution Forecast from Friday, July 5 was the first to indicate a northward trend, or right turn, in Hurricane Beryl’s track toward the Texas coastline twelve hours before other models.

The advanced notice and consistency in model runs provided confidence in the forecast for Spire customers, allowing more time for better decision-making.

Spire High-Resolution Forecast for Maximum Composite Radar Reflectivity 78 hours before Beryl’s Texas landfall. The National Hurricane Center’s forecast cone at 78 hours is pictured in light blue shading, Beryl’s observed track is shown in red, and the NHC’s forecast track 78 hours out is shown in black.

Our three-day Spire High-Resolution Forecast showed Beryl making landfall between Corpus Christi and Galveston, Texas, at 7:00 am CT on Monday, July 8. ECMWF’s forecast for the same cycle and valid time had a track much farther to the south in Texas. However, in subsequent runs, it began picking up on the northward track trend.

Successive runs of the Spire High-Resolution Forecast homed in further on the landfall location, coming within 10-20 miles with a lead time of 30 hours. Additionally, the model precisely captured impacts from the hurricane’s most powerful winds along the coast and inland at least two days ahead.

“The Spire High-Resolution Forecast pinpointed the risk of winds of 60 mph and greater through the Houston, Texas, metroplex 48 hours out, providing higher confidence to impacts and timing when and where it mattered the most,” Spire Meteorologist and Weather Risk Expert Jared Allen explained. He added that the model accurately depicted the front right eyewall core passing over Houston with wind gusts up to 80 mph at least 40 hours in advance.

Maximum wind speeds occurred near where Hurricane Beryl made landfall along the northern Texas coast and inland to Houston, Texas, according to the National Weather Service. A wind gust of 97 mph was recorded in Brazos, Texas, and widespread 70 and 80-mph wind gusts occurred along the coast and inland, including in downtown Houston, on the right front quadrant of Beryl’s eyewall core.

Why should you consider a high-resolution forecast?

Energy and commodity traders, utilities, and insurance providers are among the industries that should consider improved hurricane forecasts from a precise and high-resolution forecast.

Discover Spire’s comprehensive weather intelligence and solutions for businesses.

Explore Spire Weather & Climate

Why did Spire forecasts perform better?

Our fully deployed satellite constellation helps to fill critical weather data gaps, especially in under-observed remote areas and over the oceans. The proprietary data that Spire gathers allows for better initial weather conditions, which are a major driver of forecast accuracy.

Spire’s Radio Occultation (RO) data provided an improved sampling of atmospheric conditions, especially over the ocean, enhancing the accuracy of forecasts for steering influences on Hurricane Beryl.

RO is a groundbreaking technique that allows for the retrieval of vertical atmospheric profiles similar to those generated by measurements gathered from a weather balloon. However, whereas weather balloon launches are costly, manual, and mainly over land, RO is scalable, automated, and can be performed anywhere globally.

The Spire High-Resolution Forecast provided early insights into Hurricane Beryl’s track toward the Texas coastline twelve hours before other models. The image on the left shows the Spire High-Resolution Forecast position for Beryl at 12Z July 8th, initialized at 06Z on July 5th. The image on the right shows Hurricane Beryl’s actual position at 12Z July 8th.

Spire’s constellation of satellites can accomplish this feat by analyzing the bending of signals from GPS/GNSS satellites due to weather elements. Because of that, Spire offers unparalleled coverage, filling in weather data gaps and providing invaluable data from the poles to the remote oceans.

Hurricane Beryl’s rapidly fluctuating strength and structure and weak steering influences created a complex forecasting scenario. Besides improved weather data for initial conditions, which has been proven to be among the top means for increasing weather forecast accuracy, our high-resolution forecasting capabilities added value for our customers.

High-resolution, convection-allowing forecasts are critical for capturing the fine-scale convective processes and ocean surface interactions that influence the intensity and track of tropical systems.

Learn more about Spire’s comprehensive weather intelligence and solutions for businesses

Explore Spire Weather & Climate

Key takeaways from Cyclone Freddy

The record for Cyclone Freddy was confirmed by a WMO international committee of experts from the Weather and Climate Extremes Archive, including scientists from Australia, France, Spain, Canada, Hong Kong, and the United States.

Prior to this confirmation, NASA had confirmed that Cyclone Freddy held the record for all-time accumulated cyclone energy (ACE), which is a measure of a tropical cyclone’s intensity over its lifetime, in the Southern Hemisphere.

Unprecedented longevity

Tropical Cyclone Freddy maintained its status as a tropical storm or stronger for 36 days. It crossed the Indian Ocean in February and March of 2023 after developing near the coast of Northwest Australia and charted a course toward southern Africa. That longevity surpassed the previous world record of 29.75 days held by John in 1994. Freddy peaked with the equivalent intensity of a Category 5 hurricane on the Saffir-Simpson Hurricane Wind Scale.

Prior to John, Hurricane Tina’s 24-day duration in the 1992 season, and Hurricane San Ciriaco’s 28-day duration in the 1899 Atlantic season were the longest-lived tropical cyclones, according to the WMO.

John became a hurricane over the eastern Pacific before tracking across the dateline into the western Pacific, where it was designated as a typhoon. Before its journey was over, John ventured back into the central Pacific. The cyclone was one of only a handful to be designated as both a hurricane and a typhoon.

At peak intensity, John reached Category 5 strength, the strongest category on the Saffir-Simpson scale. Despite its lengthy journey for 31 days meandering around the basin, John did not have major impacts to land. It affected the Hawaiian Islands and the United States military base on Johnston Atoll, and its remnants later impacted Alaska.

On the other hand, not only was Cyclone Freddy a long-duration event but also one with devastating impacts. Madagascar and southeastern Africa were hit particularly hard during Freddy’s onslaught.

Cyclone Freddy devastated crops in southern portions of Malawi, causing hunger concerns in the region.

Extensive journey

Freddy traveled 7,945 miles (12,785 kilometers), or about one-third of the Earth’s circumference, making it the second-longest in terms of distance traveled by a tropical cyclone. In comparison, John navigated 8,177 miles (13,159 kilometers) across the Pacific Ocean in 1994.

There is potential for vast area of impact with such long-lived storms with extensive paths, as destructive storms like these could affect multiple countries and regions.

Significant human and economic impact

Cyclone Freddy caused devastation in Madagascar, Malawi, and Mozambique. In Malawi alone, more than 1,200 people were reported dead or missing, and over 1.3 million people in Mozambique were affected. The economic toll was substantial, with damages estimated at $481 million USD, according to the African Risk Capacity’s Tropical Cyclone Explorer (TCE) model.

Key statistics on Cyclone Freddy

Implications for businesses of Cyclone Freddy

1. Risk assessment and preparedness

The prolonged duration and extensive reach of Cyclone Freddy highlight the importance of robust risk assessment and preparedness plans for businesses. Companies operating in cyclone-prone areas must ensure they have updated emergency response strategies, supply chain contingencies, and employee safety protocols.

2. Insurance and financial planning

The economic losses caused by Freddy emphasize the need for adequate insurance coverage against natural disasters. Businesses should review their policies to ensure they are protected against prolonged disruptions and significant damages resulting from extreme weather events.

3. Sustainability and climate action

The increasing intensity and longevity of tropical cyclones are closely linked to climate change, but there are several other atmospheric factors that also need to be taken into account. Businesses have a critical role to play in mitigating climate change by adopting sustainable practices, reducing carbon footprints, and supporting global climate initiatives. Proactive climate action can help curb the future impact of such devastating weather events.

The role of climate change

The record set by Cyclone Freddy is not an isolated incident but rather part of a broader trend of more intense and longer-lasting tropical cyclones. Climate change is among the factors behind these changes.

“The warming climate translates to warmer ocean temperatures, and warm water acts as fuel for tropical cyclones. We are not confident yet that there will be an increased number of tropical cyclones developing each year due to climate change. Of the storms that form, we do believe we will see an increase in intensity and longevity as warm waters allow these systems to thrive,” Spire Meteorologist James Van Fleet said.

Above-average ocean heat content can also contribute to the rapid intensification of hurricanes, when atmospheric conditions such as upper-level winds are favorable for explosive strengthening. Additionally, higher sea levels contribute to more severe storm surge and flooding, and more moisture in the atmosphere due to climate change leads to heavier rainfall.

Other atmospheric factors at play

“The Earth’s systems of absorbing, transferring, and releasing energy are complex. You have interactions between the atmosphere and Earth’s oceans. Sun cycles. Global teleconnections. Geological phenomena that play a role, and the list goes on,” Van Fleet explained. “By the very nature of its definition, climate change is a long-term shift in temperatures and weather conditions, and so it is important to have a comprehensive view into what is driving more intense tropical storms, especially when considering a single storm and its behavior.”

“However, we also know that increasing temperatures due to human-caused greenhouse gases play a role in adding heat to Earth’s oceans as well,” Van Fleet said.

Hurricane John developed amid the 1994-95 El Niño, characterized by above-average sea-surface temperatures in the central and eastern Pacific Ocean near the equator.

Other meteorological teleconnections similarly to the El Niño/Southern Oscillation, including the Madden Julian Oscillation and the Indian Ocean Dipole, are among other factors that can influence the formation and behavior of tropical systems around the world.

Geological events such as volcano eruptions can play a role since gases from eruptions can reach the stratosphere and cause global cooling events in certain cases.

Attribution science organizations such as World Weather Attribution and Climate Central analyze scientific methods for measuring and quantifying the influence of climate change on weather events.

Monitoring and Early Warning Systems

The WMO’s confirmation of Freddy’s record underscores the importance of accurate monitoring and early warning systems. These systems are crucial in providing advance advisories, allowing disaster management and humanitarian efforts to mobilize effectively. Businesses should stay informed about advancements in weather forecasting technology and integrate these tools and insights into their operational strategies.

Spire Global has a fully deployed constellation of satellites to gain in-depth insights into the weather and more.

Conclusion

Tropical Cyclone Freddy’s record-breaking longevity is a stark reminder of the growing challenges posed by escalating weather events. For businesses, this event underscores the necessity of comprehensive risk management, robust insurance coverage, and proactive climate action. By understanding the implications of such extreme weather events and taking decisive steps to mitigate their impact, businesses can better safeguard their operations and contribute to a more resilient and sustainable future.

“The abundance of exclusive space-powered data that Spire gathers using its fully deployed constellation of satellites provides unmatched insights into the complexity of the Earth system,” Van Fleet said. “That together with our proprietary data assimilation, computer modeling, and AI and machine learning techniques, culminates in unique and precise weather predictions that can aid in smarter and faster business decisions.”

Incorporating accurate forecasting tools can greatly benefit business operations, safety, and profits. Having a team of meteorologists to interpret model predictions and explain confidence levels is invaluable for making key business decisions. Spire has a team of expert meteorologists, the DeepVision™ Weather Support team, available 24/7 to offer guidance and consultation around any weather uncertainties.

The escalating trend of weather disasters

From the 1980s to the 2020s, the number of billion-dollar weather and climate disasters and their associated costs dramatically increased.

Billion-dollar weather disasters by decade:

This graph shows the number of billion-dollar weather events (bars) and the total cost of disasters (line graph) in the United States by decade. Data is courtesy of the National Oceanic and Atmospheric Administration (NOAA) and is valid through June 10, 2024

Last year, 28 billion-dollar weather and climate calamities set a new annual record, exceeding the previous record of billion-dollar disaster events, which was 22 set in 2020, according to the National Oceanic and Atmospheric Administration’s (NOAA’s) National Center of Environmental Information (NCEI). Severe storms topped the list in terms of frequency with 19 events, followed by four flooding events, two tropical cyclones, one wildfire, and one winter storm. The losses due to drought and heat also factored into the record-shattering year of costly disasters, ranking second in terms of cost and top in terms of deaths.

In total, these disasters cost the US $94.8 billion in 2023. The total of 387 billion-dollar disasters recorded by NCEI from 1980 into 2024 have cost the US more than $2.7 trillion.

A decade-by-decade analysis of weather disasters

Hurricanes are the most destructive and costly natural disasters in the US, averaging $22.8 billion per event. However, severe thunderstorms are the most frequent weather disasters on the billion-dollar disaster list, with the lowest-average cost at $2.5 billion per event on average. Growing populations, homes, businesses, and other infrastructure in vulnerable areas compound the losses due to the increased severity and frequency of extreme weather events.

Read on to explore how weather and climate disasters have surged in recent decades.

1980s: The beginning of the surge

• Number of events: 33
• Total cost: $218 billion

The 1980s saw the beginning of a noticeable uptick in weather-related disasters, with droughts, flooding, and severe storms being the most frequent and costly.

Intense heat and drought plagued the United States from the Midwest to the Great Plains, turning deadly and causing significant economic hardship in 1980

1990s: The rise continues

• Number of events: 57
• Total cost: $333 billion

The 1990s experienced nearly double the number of billion-dollar disasters compared to the previous decade, demonstrating the growing impact of climate change on weather patterns.

2000s: Costs skyrocket

• Number of events: 67
• Total cost: $618 billion

The financial toll of weather disasters surged in the 2000s, with severe storms, tropical cyclones, and other extreme events contributing to significant economic losses.

Hurricane Katrina approaching Louisiana as seen from space. The devastating hurricane caused tremendous loss of life and economic losses during the historic 2005 Atlantic hurricane season

2010s: A decade of devastation

• Number of events: 131
• Total cost: $988 billion

The 2010s were marked by an unprecedented number of high-cost disasters, further emphasizing the urgent need for effective risk mitigation strategies.

2020s: An alarming trend

• Number of events (as of June 2024): 88
• Total cost: $561 billion

With the decade not even halfway through, the US is already outpacing the frequency of disasters witnessed during the 2010s. This trend highlights the increasing threat posed by climate change.

Destroyed homes in Florida following Hurricane Ian, which made landfall as a Category 4 storm in southwestern Florida on September 28, 2022

The impact on the energy sector

As severe storms and other weather disasters become more frequent, the reliability of the electricity grid is increasingly jeopardized. Climate-exacerbated weather disasters particularly put a strain on aging energy infrastructure.

• 92% of major US power outages in 2023 were due to weather-related events, according to the U.S. Department of Energy.
• $5 billion: Potential damage claims against Hawaiian Electric for the deadly and devastating 2023 wildfire, nearly eight times its insurance coverage.
• $87 billion: US power grid investment in 2023, with a significant portion focused on storm resilience.

A report from Climate Central, a non-profit organization of independent scientists, found that 80% (1,755) of all major US power outages from 2000 to 2023 were caused by weather. The majority of weather-related outages were triggered by severe weather (58%), winter storms (23%), and tropical cyclones including hurricanes (14%). In the same period, the following states ranked highest for weather-related power outages: Texas (210), Michigan (157), California (145), North Carolina (111), and Ohio (88).

The impact on the insurance industry

With the increasing frequency and severity of weather disasters, the insurance industry faces increasing claims and financial strain.

According to The Conversation, the insurance industry is particularly concerned about extreme weather events since they cause significant damage and destruction that require financial compensation. Hurricanes and severe tropical cyclones are especially noteworthy due to the widespread wind and flooding impacts. Between 2018 and 2022, tropical systems led to economic losses surpassing $450 billion, with less than half of that amount covered by insurance, The Conversation reported.

While hailstorms are considered a secondary hazard in the insurance industry, these damaging events happen more frequently than primary hazards like hurricanes. Insurance companies pay out billions of hail claims annually in the US, and as these weather events intensify, insurers are being hit harder.

This emphasizes the crucial role of the insurance industry in managing the financial fallout from such devastating weather events.

Explore Spire’s Weather & Climate solutions:

Learn more about Spire’s DeepVision™ Weather Support team
Discover Spire’s High-Resolution Forecast
Explore Spire’s Soil Moisture Insights

Preparing for the future

Given the growing impact of weather disasters, it is imperative for businesses and communities to adopt proactive measures to mitigate risks.

1. Invest in resilient infrastructure: Strengthening infrastructure to withstand extreme weather events can significantly reduce economic losses.
2. Implement advanced weather monitoring support: Utilizing cutting-edge technology to monitor weather in real-time allows for better preparedness and response.
3. Develop comprehensive risk mitigation plans: Establishing detailed plans for responding to various weather scenarios ensures that businesses can quickly and effectively address potential disruptions.
4. Promote sustainable practices: Reducing carbon footprints and adopting sustainable practices can help mitigate the long-term impacts of climate change.
5. Enhance communications with employees and clients: Establishing clear, timely communication channels ensures that all stakeholders are informed and prepared, minimizing confusion and enhancing coordinated responses before, during, and after extreme weather events.

These strategies are crucial for businesses looking to safeguard their operations and financial stability against the increasing frequency and severity of weather disasters. At Spire Weather & Climate, we are committed to helping our clients navigate these risks and building a more resilient future.

We’ve collaborated with industry leaders to bridge the weather data gap in energy and insurance services. From Soil Moisture Insights to an extended High-Resolution Forecast, Spire’s proprietary data gathered from our fully deployed constellation of satellites provides comprehensive insights in a rapidly changing climate landscape. Additionally, our DeepVision Weather Support team is available for consultation in the face of any weather uncertainties.

For more information on how we can assist you in weather risk mitigation, please don’t hesitate to reach out.

The shocking truth: lightning fatalities in the US from 2006 to 2023

Lightning fatalities have significantly decreased in the United States since the early 2000s when annual national lightning awareness campaigns began. In 2001, the first-ever Lightning Safety Awareness Week was held, and each year during the last week of June, the campaign continues.

“When we began our lightning safety effort in 2001, the U.S. had a 10-year average of about 55 lightning deaths per year,” John Jensenius, Meteorologist and Lightning Safety Specialist with the National Lightning Safety Council, told Spire Weather & Climate. “That 10-year average is now about 21 deaths per year. For the past five years, the U.S. has averaged about 16 deaths per year.”

“Throughout these years, leisure activities have contributed to about two-thirds of the deaths,” Jensenius added.

Fishing (9%), beach (6%), boating (5%), camping 23 (5%), farming or ranching (5%) are among the activities that contributed most to lightning deaths in the US between 2006 and 2023, according to analysis from Jensenius.

However, between 2006 and 2023, more than six dozen work-related lightning deaths were recorded in the US.

“Farming, ranching, and roofing have contributed to the greatest number of [work-related] fatalities,” Jensenius said. Construction, lawn care, and military deaths were also noted in Jensenius’ study.

Lightning fatalities – work-related activities

Lightning fatalities broken down by work-related activities based on 94 cases from 2006-2023 analyzed by the National Lightning Safety Council.

According to the National Lightning Safety Council, Florida had the highest number of lightning fatalities with a total of 88 deaths being reported from 2006 to 2023. Texas’ lightning fatalities ranked second, with a tally of 39 deaths, followed by Colorado with 24, and Alabama and North Carolina with 22 each.

July is by far the most dangerous month for deadly lightning strikes in the US based on historical data, followed by June then August. Not only are thunderstorms more numerous, often a daily occurrence across portions of the Southeast US during the sultry summer months, but people also tend to spend more time outdoors and partake in outdoor activities and organized events during these warm months.

Notably, the data points to more males being struck than females, with 80% of the deaths being male, Jensenius explained.

The National Lightning Safety Council estimates that the odds of any person being struck by lightning in a given year is 1 in 1.6 million, but lightning tragedies can be avoided with proper awareness and preparedness.

The importance of preparedness: insights for safer outdoor events and worksites

Lightning poses a significant threat to workers in outdoor environments, and it is often underestimated as an occupational hazard. According to the Occupational Safety and Health Administration (OSHA) and the National Oceanic and Atmospheric Administration (NOAA), understanding the risks associated with lightning and implementing proper safety protocols is crucial for protecting workers. Employers and supervisors must proactively monitor weather conditions, educate employees, and provide adequate shelter to minimize the dangers posed by lightning.

Lightning can strike ahead of and after a storm’s rainfall, making it essential for outdoor workers to be vigilant. The key to safety is recognizing the early signs of thunderstorms and seeking shelter immediately.

Employers should establish a comprehensive Emergency Action Plan (EAP) that includes a lightning safety protocol, ensuring workers are informed and can respond quickly to weather warnings. Proper training and the use of lightning detection systems can further enhance workplace safety and reduce libel exposure by providing timely alerts and detailed weather forecasts.

Two critical aspects of employer lightning risk mitigation, include:

• Implementing an Emergency Action Plan (EAP): Ensure your EAP includes specific lightning safety protocols and that all workers are trained on these procedures.
• Using Lightning Detection Systems: Utilize commercial lightning detection services for real-time alerts and detailed strike information.

Lightning safety procedures should account for several considerations, and defining safe shelter should be high on the list.

“To be safe a person must be inside a substantial building (one with wiring or plumbing) or a hard-topped vehicle when a thunderstorm is in the area (within 10 miles of the location),” Jensenius explained.

The following safety tips are recommended by experts ahead of any type of outdoor activity or work:

• Monitor Weather Conditions: Regularly check weather forecasts before starting outdoor work and continue to monitor conditions when outdoors. Keep an eye on the sky and use phone apps to monitor radar and lightning data, if available.
• Consider Canceling or Postponing Work Activities or Events: Pay attention to the forecast and consider altering work or event plans when thunderstorms are expected, especially if it will be difficult to reach a safe place quickly.
• Plan Ahead: Determine where you will go for safety when a thunderstorm develops or approaches.
• Seek Safe Shelter: Heed signs of developing or approaching storms. When thunder is heard or lightning is seen, immediately move to a fully enclosed building with electrical wiring and plumbing or a hard-topped metal vehicle.
• Avoid High-Risk Areas: Stay away from isolated tall objects, open fields, water bodies, and metal structures during thunderstorms.
• Remain inside for 30 minutes after the last clap of thunder is heard.

By taking these proactive measures, employers and employees can significantly reduce the risk of lightning-related injuries and fatalities at outdoor worksites.

Mitigating lightning risks in the workplace and beyond

Businesses have a responsibility to provide a safe work environment for employees, and there are tools and solutions that can help organizations make better decisions, prepare and mitigate thunderstorm risks such as lightning.

“Real-time monitoring systems like radar and lightning detection play an important role in monitoring weather conditions and alerting to the possibility of lightning. Equally important is monitoring weather conditions with your eyes and ears. Darkening skies or the sound of thunder should serve as a warning of the lightning danger,” Jensenius explained.

Spire’s DeepVision™ is a superior visualization platform for comprehensive weather risk management for businesses. This image from the platform displays a radar image and lightning strikes (color-coded based on the time since the strike). Lightning strikes can be seen far away from rainfall associated with the thunderstorms in this image.

How businesses benefit from monitoring, alerting with Spire DeepVision™

Spire DeepVision™ offers radar visualization for North America and Europe and includes lightning strike and lightning density features. The tool is a fully customizable solution, including weather alerting and monitoring specific to your business and assets.

Spire’s 24/7/365 team of expert meteorologists, the DeepVision Weather Support team, provide tailored forecasts and real-time, on-demand updates delivered by phone, chat, video, and/or email when you need it to support your operations and logistics.

Our Spire High-Resolution Forecast can help meteorologists diagnose environments that may support thunderstorms or severe weather with more lead time to allow for better business and event preparation. Our model outputs include precise hour-by-hour forecasts up to 1 km extending six days to provide more advanced notice on potential weather hazards like thunderstorm threats.

Implementing safety recommendations and leveraging advanced forecasting tools can help businesses mitigate lightning risks effectively. By staying informed and prepared, employers can protect their workers and ensure a safer work environment.

For more detailed insights and to explore how Spire can help your business with weather risk mitigation, contact us.

Tornado Alley: The epicenter of tornado activity

Regarding tornado hotspots, few areas are as infamous as Tornado Alley in the United States. Stretching from the southern Plains to the Midwest, Tornado Alley encompasses parts of Texas, Oklahoma, Kansas, Nebraska, South Dakota, Minnesota, Iowa, and arguably parts of Illinois. Tornado Alley typically experiences more than 500 tornadoes on average annually due to the convergence of warm, moist air from the Gulf of Mexico with cool, dry air from the Rocky Mountains. The clash of these air masses creates the ideal conditions for supercell thunderstorms, which often spawn tornadoes.

The average annual number of tornadoes per state (CONUS, 2003-2022) based on data from the National Weather Service Storm Prediction Center

The Southern US tornado corridor

In addition to Tornado Alley, the Southeastern United States is another hotspot for tornado activity with this area experiencing nearly 300 tornadoes per year based on the 20-year average from the National Weather Service Storm Prediction Center (SPC). States like Alabama, Arkansas, Mississippi, Tennessee, and Georgia regularly experience tornado outbreaks, particularly during the spring months. Unlike Tornado Alley, where tornadoes are often produced by supercell thunderstorms, tornadoes in the Southeast are more commonly associated with squall lines and mesoscale convective systems (MCSs). Annually, the United States experiences about 1,248 tornadoes on average based on SPC data from 2003-2022.

The catastrophic April 2011 Super Tornado Outbreak, during which over 360 tornadoes struck the Southeast, serves as a stark reminder of how devastating these natural events can be when numerous tornadoes occur in quick succession.

A snapshot of the Spire High-Resolution Forecast depicts severe weather in the heartland of the United States, showing both maximum composite radar reflectivity (dBZ) and winds at 100 m (mph)

Another tornado capital of the world: Bangladesh

While tornadoes in the United States tend to garner the most attention, Bangladesh holds the dubious distinction of being the deadliest tornado capital of the world. Bangladesh experiences a relatively high number of tornadoes compared to its size and population density. On average, approximately 5 to 10 tornadoes touch down in Bangladesh each year.

Notably, the number of fatalities due to tornadoes is relatively high in comparison to the US, according to a report from the University of Colorado. These tornadoes primarily occur during the pre-monsoon season, typically from March to May, when atmospheric conditions are conducive to tornado formation.

The unique geographical and meteorological features of the Bengal Delta contribute to the relatively high frequency of tornadoes in Bangladesh, making it one of the most tornado-prone countries in the world. This atmospheric setup creates favorable conditions for tornado development, with devastating consequences for the densely populated and vulnerable region.

The deadliest tornado ever recorded worldwide struck Bangladesh on April 26, 1989. According to the World Meteorological Organization (WMO), the tornado hit the Manikganj District in central Bangladesh, killing an estimated 1,300 people and injuring another 12,000, leaving 80,000 individuals homeless, and causing catastrophic damage.

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Other tornado hotspots around the globe

Beyond the United States and Bangladesh, tornadoes occur in various other regions globally. Canada’s Prairie provinces, Argentina’s Pampas region, and parts of Australia, including the southeastern states of Queensland and New South Wales, and New Zealand are all known for their tornado activity. Each of these regions has a unique combination of geographical features and atmospheric conditions that contribute to favorable atmospheric conditions for tornadoes.

In Europe, some of the highest tornado frequencies are found in countries like Germany, Italy, and England. Germany, for instance, sees a noteworthy number of tornadoes, with many occurring in the northern and central parts of the country. Italy also experiences tornadoes, particularly in the northern and coastal regions, with some causing significant damage.

Greece is among the Mediterranean countries that have experienced significant tornado events. Additionally, hundreds of waterspouts occur each year in the Mediterranean region, and when these move ashore, they can cause damage.

Destruction left behind after an EF5 tornado struck Moore, Oklahoma, in May 2013

Understanding and mitigating tornado risk

While tornadoes are a natural part of the Earth’s atmospheric system, their impact on human lives, livelihoods, and infrastructure can be devastating. Understanding tornado hotspots and the factors that lead to tornado formation is crucial for effective risk mitigation and disaster preparedness efforts. Through investing in early warning systems, community education, and resilient infrastructure, we can minimize the loss of life and property damage caused by these powerful storms.

Precise and reliable weather forecasting information is critical for severe weather preparedness and business resilience amid increasing severe weather concerns.

Our Spire High-Resolution Forecast offers 3 kilometer resolution forecasts for the entire continental United States (CONUS) with hourly outputs extending up to six days. Powered by Spire’s advanced data assimilation system and proprietary Radio Occultation (RO) and reflectivity data, including soil moisture and ocean wind measurements, our High-Resolution Forecast delivers unprecedented accuracy and detail, addressing the critical need for medium-range convective-scale forecasts.

This significant enhancement sets a new industry standard, providing detailed forecasts essential for predicting extreme weather events such as severe thunderstorms and localized flash flooding. Available via API or Spire’s display system, DeepInsights provides High-Resolution Forecasts that empower meteorologists, energy traders, utility managers, and more with the insights needed to make informed decisions, optimize resource management, and enhance safety protocols.

Additionally, Spire has a team of meteorologists available 24/7 for consultation by phone, chat, video, or email and can provide expert analysis and weather support for your business.

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The climatic challenges to Brazil’s coffee legacy

Brazil’s position as a global coffee powerhouse has been historically supported by its ideal wet and dry seasons. Yet, today’s climate change-induced erratic weather patterns, manifesting as severe droughts and excessive rainfall, pose significant threats. These conditions stress coffee plants, exacerbate diseases like coffee leaf rust, and demand innovative farming practices for the sustainability of coffee production.

Spire’s surface soil moisture at a 6-km resolution across South America for February 13, 2024 (left) illustrating varied moisture levels. On the right, a rainfall distribution map of the same region, capturing the intensity of precipitation at the time indicated. This juxtaposition highlights the relationship between rainfall and soil moisture levels in different areas.

Adapting to the extremes: From droughts to downpours

• Soil moisture variability directly affects coffee plant health and bean development. Optimal soil moisture can increase bean size and improve quality, whereas conditions of either extreme (too dry or too wet) can degrade these attributes.
• Research indicates that adequate soil moisture can enhance the resilience of coffee plants to pests and diseases, such as coffee leaf rust, which thrives in warmer and wetter conditions.

The resilience of Brazil’s coffee sector is being tested by the extremes of climate. The adaptation strategies, such as drought-resistant coffee plant varieties, advanced irrigation techniques, and the practice of agroforestry, have become essential. These innovations not only mitigate the adverse impacts but also enhance the sector’s sustainability.

Spire’s Soil Moisture Insights: A beacon for precision agriculture

• Precision agriculture technologies, including soil moisture monitoring systems like Spire’s, are growing at a 13% annual rate.
• These technologies help farmers reduce water usage by up to 20% while maintaining or increasing crop yields.
• The World Bank says investments in climate-resilient agriculture could yield benefits 3-8 times the costs.

In this context of climatic unpredictability, Spire’s Soil Moisture Insights emerges as a crucial tool for farmers and agricultural decision-makers. By providing accurate, real-time data on soil moisture levels, these products help in identifying areas of moisture and drought with precision. This information is invaluable for optimizing irrigation practices, effectively conserving water, and ensuring the health and productivity of crops, especially during critical transition periods from drought to wet conditions.

Learn more about Soil Moisture Insights

Beyond coffee: A climate nexus in agriculture

• NOAA data shows the past five years as the warmest on record, worsening climate extremes affecting South American agriculture.
• Future models predict more frequent and intense droughts and heavy rainfalls in South America, underscoring the need for precise climate data in agriculture.

The narrative of climate impact extends beyond coffee, affecting a wide range of crops in Southern Brazil and Uruguay. The interconnectedness of agriculture and climate change underscores the need for adaptive strategies and technological innovations. In this regard, Spire’s Weather Data APIs play a pivotal role by offering global weather modeling enhanced with unique space data. This capability enables decision-makers to stay ahead of climate and weather impacts, making informed decisions to safeguard agricultural outputs and economic stability.

Comparison of surface soil moisture metrics over South America in February 2024: On the left, the monthly mean surface soil moisture content at a 6-km resolution, indicating overall moisture levels. On the right, the soil moisture anomaly map, highlighting deviations from long-term averages, both based on proprietary Spire data. Notably, there is significant soil dryness in regions including the La Plata River Basin.

Embracing technological solutions for future resilience

The integration of Spire’s cutting-edge technologies in agricultural practices promises not only to enhance the resilience for coffee and other crops to climatic stress but also to ensure that the rich agricultural heritage of regions like Southern Brazil and Uruguay continues to thrive. The journey towards climate adaptation in agriculture is complex, yet with tools like Spire’s Soil Moisture Insights and Data APIs, it’s a step closer to sustainability and productivity in the face of a warming climate and more extreme and variable weather.

History of hurricane forecast accuracy

“In 1980, the average hurricane forecast error for the landfall location was 125 miles just 24 hours ahead of time. The two-day forecast was off by an average of 275 miles, and the three-day average error was a whopping 400 miles,” Michael Eilts, General Manager of Spire Weather & Climate, explained. “Today, because of better models, satellite data, faster computers, and better understanding of hurricanes, the National Hurricane Center forecasts are far better.”

For example, the three-day forecast of hurricane location is now off by less than 100 miles on average. This is noteworthy since more accurate landfall forecasts can result in a better understanding of impacts facing different coastal communities, including storm surge, flooding rainfall, damaging winds, and even tornadoes.

“Hurricane intensity forecasts have not made quite the same advances,” Eilts added.

In the future, Eilts breaks down two of the most encouraging opportunities for progress in hurricane track and intensity forecasting.

“The first is more and better data collected by satellite, for example, Spire’s constellation of over 100 satellites that measure profiles of temperature and humidity directly in and around hurricanes,” Eilts said. “And second is AI forecasting that will allow us to assimilate satellite data and other data and, because these models can be run very quickly on 1 GPU, we can create hundreds of ensembles, allowing probabilistic distributions that cover all of the forecast possibilities.”

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How will AI weather models help to reshape hurricane prediction?

AI modeling has the potential to bring evolutionary progress to hurricane forecasting, and studies are reaffirming the benefits.

“AI models are showing promise at improving the hurricane track forecasts relative to traditional physics-based numerical weather prediction (NWP) models. This is likely because AI models do a phenomenal job at predicting large-scale atmospheric features which are the main driver in determining the track of hurricanes,” Dr. Tom Gowan, Spire Global’s Machine Learning, Modeling, and Data Assimilation lead, said.

“Better individual hurricane track forecasts, combined with the ability to run massive AI forecast ensembles, will allow coastal communities to have much more confidence in a hurricane’s forecasted track and, ultimately, more time to prepare,” Gowan added.

Hurricane strength prediction may be a bigger hurdle, even for AI weather prediction models, but there are favorable prospects for enhancing skill in this aspect.

“In general, pure AI weather models have been found to under-predict the intensity of hurricanes and strong synoptic storms. It’s still an open research question as to why, but it may be due to the way most AI models are trained. They are trained to reduce error, specifically mean squared error, in forecasts which ultimately leads to some smoothing in the forecasts. This smoothing may mean extremes are under-predicted,” Gowan explained. “However, recent research suggests that the use of diffusion models in AI weather models may ameliorate this issue.”

SEE ALSO:

• Top 3 insights to help businesses stay ahead of a hyperactive hurricane season
• AI weather modeling: Spire and NVIDIA’s partnership presents true evolution in weather prediction

For example, Google released an early prototype called GenCast that rather than trying to predict the mean of a distribution, it samples individual instances from a distribution, according to Gowan.

“Ultimately, this leads to sharper forecasts that are likely to better capture extreme events,” he explained.

What are the core insights for businesses?

In a world where the destructive force of hurricanes continues to take a heavy toll on lives and livelihoods, the promise of AI-driven advancements in hurricane prediction brings a ray of hope. As we navigate the challenges posed by climate change and the increasing intensity of storms, the enhancements offered by AI modeling provide a beacon of resilience for businesses and communities alike.

“Any industry that can take advantage of more accurate medium-range hurricane forecasts will benefit from AI models,” Gowan said. “Ultimately, I believe that those who embrace this new technology and understand its strengths and limitations will experience the greatest benefits.”

Spire’s unparalleled space-powered data provides an unmatched advantage by enhancing the data that AI models will train on and providing much more accurate initial conditions for weather conditions worldwide. A technique known as radio occultation that Spire utilizes for generating precision atmospheric profiles globally, based on measuring the bending of GPS/GNSS satellite beams through Earth’s atmosphere, is among the top methods for improving the accuracy of weather predictions.

Besides developing AI weather modeling, Spire continues to innovate and expand on its High-Resolution Weather Model, which extends out six days with hourly forecasts up to 1-km resolution, providing exceptional detail. In addition, Spire’s Weather Risk Communication Team provides businesses with 24/7/365 guidance on how the weather forecast will impact operations and assets.

Embracing technological leaps and harnessing their potential will not only enhance preparedness but also empower us to safeguard what matters most in the face of nature’s fury.

Together, let us embark on this journey towards a safer, more resilient future.

Discover Spire’s AI Weather Forecasting

Understanding the Fujiwhara effect

The Fujiwhara effect, named after Japanese meteorologist Sakuhei Fujiwhara, occurs when two cyclonic vortices — such as tornadoes or hurricanes — come close enough to each other, causing them to rotate about a common midpoint. This interaction can result in a variety of outcomes, including the merging of the two storms into a single, larger system or the rotation of the storms around each other before eventually separating.

This rare phenomenon unfolded in Oklahoma, a US state known for its turbulent weather patterns and frequent tornado activity. On the night of April 30^th, 2024, residents watched in awe as a pair of tornadoes, one spinning counterclockwise (cyclonic) and the other clockwise (anticyclonic), approached each other.

As they approached, their synchronized movements caused them to orbit each other, creating a spectacle that captivated both onlookers and meteorologists.

“The more data I look at the wilder this storm gets. Volumetric data shows a vortex hole from the ground up into the mesocycle [sic]. Centrifuging debris and hydrometeors away from the center of the circulation,” WCNC Charolette’s Chief Meteorologist Brad Panovich explained on X as he was immersed in studying the scenario. His analysis offered a glimpse into the complexity of the storm system.

Unraveling nature’s complexity

The swirling dance of the cyclonic-anticyclonic tornado duo defied conventional understanding, challenging scientists to unravel the intricate dynamics at play. While tornadoes typically repel each other due to their opposing rotational forces, the Fujiwhara effect brings them together in a rare embrace.

What causes this unusual phenomenon? The answer lies in the complex interplay of atmospheric conditions, including wind shear, pressure gradients, and the Coriolis effect, a force caused by the Earth’s rotation. When these factors align in just the right way, tornadoes become locked in a gravitational tango, defying the chaos of their destructive power.

From late April 2024 into early May, severe weather broke out for eight consecutive days across the central US. Intense thunderstorms spawned tornadoes and damaging winds. Officials have confirmed more than 100 tornadoes during a deadly stretch of severe weather that began Thursday April 25th and ended Monday April 29th. The strongest confirmed tornado was an EF4 that devastated Marietta, Oklahoma. Storm surveys are still being conducted by the local National Weather Service offices in the area.

The pattern of severe weather was attributed to a combination of factors including atmospheric instability, strong wind shear, and the presence of a potent storm system moving across the region. The resulting tornadoes and storms caused significant impacts, including property damage, power outages, and sadly, loss of life.

The Fujiwhara effect provides a compelling example of the intricate dynamics of storm systems and the interconnectedness of weather phenomena. Studying this case not only enhances our understanding of atmospheric science and mesoscale meteorology but it also helps improve weather forecasting and preparedness efforts in regions prone to severe weather events.

An animation of Spire’s High-Resolution Weather Model captured on Monday, April 22, depicts the predicted composite radar reflectivity for April 26-27, 2024, showing severe storms erupting across the Great Plains.

Enhancing weather preparedness

Events like the cyclonic-anticyclonic tornado tango serve as stark reminders of nature’s power and complexity, and the need for awareness and preparedness in the face of severe weather dangers. At Spire Global, our Weather Risk Communication Team is hard at work, 24/7 to bring situations such as this to light. Our team of expert meteorologists helps businesses prepare for and understand weather risks, empowering businesses to protect their people and assets during extreme weather events.

Additionally, Spire’s High-Resolution Weather Model, enhanced by satellite data that fills weather observation gaps worldwide, plays a vital role in improving forecast accuracy and preparedness. With precision up to 1-km resolution, our weather predictions extend out six days with detailed weather forecasts for every hour, providing ample lead time for businesses to mitigate weather risks. By leveraging cutting-edge technology and data-driven insights, we can better anticipate and respond to severe weather threats, minimizing their impact on lives and livelihoods.

Learn more about Spire’s High-Resolution Weather Forecast

What to know about the US cicada invasion

A dual emergence of these broods is rare, happening every 221 years, according to cicadasafari.org. This double brood of periodical cicadas will coincide in the United States for the first time since 1803, when Thomas Jefferson was the US President. Brood XIII is a 17-year cicada that will surface in northern Illinois, and Brood XIX is a 13-year cicada that will emerge in parts of the Midwestern and Southeastern US.

The biggest overlap of the two broods will occur toward central Illinois, well to the south of Chicago. While Brood XIII we be fairly confined to eastern Iowa, northern Illinois, and southern Wisconsin, the Brood XIX outburst will be more widespread, spanning from Missouri and Louisiana to Maryland and Georgia.

Learning when the cicadas will arrive in different areas is the first step to managing them in agricultural settings, and understanding their lifecycle is another vital aspect of taking precautions.

After cicada nymphs — or immature cicadas — dig tunnels and surface, they molt, leaving exoskeletons behind, often attached to trees, and mature into adults. These adults then court and mate in trees and shrubs. Subsequently, female cicadas lay their eggs on tree branches. Roughly six weeks later, nymphs hatch from the eggs and descend to the ground where they burrow into the soil, feed on the roots of trees and shrubs, and initiate the cicada lifecycle anew.

Spire’s Soil Moisture Insights: A map of the US showing surface soil moisture data as of April 25, 2024, in locations with emerging cicada broods.

Weather factors behind cicada emergence

Periodical cicadas emerge during odd years as an adaptation to satiate predators while still allowing the survival of many adult cicadas. The timing of their surfacing is tied to weather factors as conditions warm up in late spring and early summer.

Cicada surfacing is most closely linked to the temperature of the soil at a depth of about 20 cm (8 inches). Nymphs emerge when soil temperatures reach 18ºC (64ºF).

Studies have also shown that an increase in soil moisture can also be an indicator that cicadas will soon appear.

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Cicada damage

Some trees are more susceptible to damage caused by female cicadas laying eggs. Oaks, Maples, Hawthorn, Redbud, Cherry, and other fruit trees are among the most vulnerable, according to the University of Maryland.

Cicada management

Managing cicadas effectively during their short above-ground period involves understanding their behavior and taking appropriate precautions. Experts do not recommend spraying pesticides as it is generally ineffective and unnecessary, the EPA states. Cicadas are harmless insects that do not bite, sting, or pose any significant threat to humans, pets, or plants. Moreover, pesticides can harm beneficial insects, pets, and other organisms, making them an impractical solution for cicada control.

For young trees susceptible to cicada damage, simple protective measures can be utilized. Covering them with mesh or netting with small openings (¼-inch or smaller) can prevent cicadas from depositing their eggs in the branches, thus avoiding potential damage. However, established mature trees typically do not require control measures, as cicadas do not pose a significant threat to their health.

It’s also essential to understand that cicadas will naturally go away after their above-ground period, typically lasting for 6-8 weeks. During this time, adult cicadas primarily feed on small amounts of sap from trees and shrubs and do not consume leaves, flowers, fruits, or garden produce, according to the EPA. Therefore, there’s usually no need for special precautions or additional insecticides in gardens or agricultural settings.

For those planning to plant trees or shrubs during a cicada emergence year, delaying planting until the fall when cicadas are gone may be advisable. However, if planting during the emergence period is necessary, covering small ornamental trees, shrubs, or fruit trees with insect netting can provide protection from cicada damage, according to the University of Maryland. It’s crucial to use netting with appropriate openings to prevent trapping of wildlife, and to remove the barriers once the cicadas are gone to avoid hindering plant growth or other potential issues.

With advanced Soil Moisture Insights, users can expect:

• High-resolution precision: Updated daily, our product delivers precise soil moisture insights down to 500-meter resolution, enabling optimized operations across diverse sectors.
• Global accessibility: With worldwide availability, our solution empowers international and local businesses, researchers, and government agencies with comprehensive soil moisture data.
• Rich historical insights: Dating back to 1978, our product provides over four decades of data for trend analysis, climate research, and data science applications. These data are gap-filled spatially and temporally, offering a unique, continuous 40-year time series of soil moisture history from past to present.
• Effortless integration: Our soil moisture data is available through an easy-to-use API, facilitating smooth integration and analysis within existing systems and applications.
• Holistic weather insights: Combine our soil moisture data with Spire’s predictive weather analytics to gain a full view of current soil conditions and detailed forecasts for precipitation, temperature, and humidity, enhancing decision-making across various industries.
• Quality, consistency, and reliability: From data collection to delivery, we control the entire value chain.
• Daily updates: We provide daily updates, offering more timely and relevant data for informed decision-making.

Comparison of surface soil moisture metrics over South America in February 2024:

The critical role of soil moisture in environmental and economic stability

Soil moisture is recognized by the World Meteorological Organization as an Essential Climate Variable, crucial to environmental sustainability. It plays a vital role in the management of water resources across diverse ecosystems. Soil moisture information is pivotal for evaluating crop and vegetation health, forming the bedrock of practices aimed at optimizing agricultural output and environmental stewardship. Beyond agriculture, soil moisture information underpins essential services like risk reduction in insurance, trading agricultural commodities, and proactive management of environmental hazards like droughts, floods, and wildfires. Additionally, industries reliant on stable soil conditions, such as construction, mining, and civil engineering, rely on detailed soil moisture information to optimize operations.

Soil Moisture Insights represents the forefront of technology in this field. Offering high-resolution data updated daily, it provides precise soil moisture insights for any location globally. This product is poised to become a valuable asset across a wide range of industries and applications.

Join us in transforming industries

Join us as we transform industries with cutting-edge technology and data-driven insights. Stay tuned for updates and success stories showcasing the impact of Spire Global’s soil moisture monitoring solution across diverse sectors.

Learn more about Soil Moisture Insights

FAQ: Spire’s Soil Moisture Insights product launch

Understand your risks

Atlantic waters are unusually warm, with sea-surface temperatures rising above the historical average. Ocean temperatures observed in late March were more on par with levels typically reached in late April or early May, according to Spire Weather Risk Communicator Tyler Sherrod.

That is raising red flags among meteorologists since warm ocean waters act as fuel for budding and strengthening tropical cyclones and could signify the potential for tropical development ahead of the official start of the season. However, tropical storms and hurricanes outside of the hurricane season; which runs from June 1 to November 30; are “uncommon” due to disruptive winds driven by the subtropical jet stream that often inhibit early-season systems from forming.

Meanwhile, other signs also point toward a busy tropical season, including the potential for La Niña to return by summer. La Niña, the cooler counterpart to El Niño and marked by below-average water temperatures around the equator in the central and eastern Pacific Ocean, has implications on weather patterns worldwide.

“The probability of a very active Atlantic tropical cyclone season for 2024 is likely to be quite high, both in volume of storms and in hurricane strength,” Levi Blanchette, Spire Weather Risk Team Lead, said. Not only will storms be fueled by above-average water temperatures but La Niña also tends to lessen disruptive winds and stability, two variables that hinder tropical development across the Atlantic Ocean.

An average Atlantic hurricane season produces 14 named tropical storms and seven hurricanes, including three that strengthen into major hurricanes – Category 3 storms with maximum sustained winds of 111 mph or greater.

Develop and implement an emergency action plan

“Ultimately, whether a hurricane season is expected to be below or above average, businesses and residents of regions that are the most susceptible to tropical impacts should be prepared for hurricanes or tropical storms every year,” Spire Weather Risk Communicator Rhiannon McDermid said, underscoring the importance for preparation in mitigating risks ahead of each hurricane season.

“An overactive hurricane season will increase the risk of any one area seeing impacts, but ultimately it can take just one storm to bring significant impacts,” she added.

Hurricanes can unleash flooding rain, destructive winds, tornadoes, and storm surge. The National Hurricane Center (NHC) identifies storm surge as the greatest threat to life and property along coasts. Heavy rainfall can also lead to extensive flooding, responsible for more than 50% of hurricane-related deaths each year. Additionally, hurricane-force winds and windblown debris pose significant risks to buildings and people.

“Businesses can prepare in advance by making sure they have the tools they need to prepare for a storm situation quickly to not only reduce the risk of their operations and assets taking hits, but also so employees have enough time to prepare their own homes and families for the storm or evacuate if the situation calls for it,” McDermid explained.

Proactive measures, such as securing important documents, maintaining generators, and developing evacuation and redundancy plans are critical steps in ensuring business resilience in the face of disasters like hurricanes.

“Businesses can be proactive in risk mitigation by being aware of what the biggest risks to them would be. If storm surge is a concern, then proactively keeping important documents or equipment (that cannot be removed from the premises entirely) on a higher story or in an attic could help reduce the potential for water damage,” McDermid advised. “If electricity is imperative to operations, whether to keep servers running, or if goods need to remain refrigerated, then make sure any generators are in good working condition before hurricane season, so there is time to make repairs or replacements before they’re needed.”

Other factors to consider in business preparation are the cost and availability of supplies ahead of a season versus during the season when storms are developing and approaching. The cost of lumber to board up and repair businesses, for instance, skyrocketed during the COVID-19 pandemic, and that complicated business resilience during hurricane seasons that significantly impacted the US, particularly the Gulf Coast.

“Hurricanes cannot be stopped in their tracks, but knowing what the highest risks to your business would be, and already having a plan in place, and making sure the tools you need to quickly and efficiently prepare for those risks are already available and in good working condition, can help you quickly and efficiently prepare for an approaching storm,” McDermid said.

While businesses in coastal areas along the US East Coast and Gulf Coast stand the greatest chance of tropical impacts in any given season, inland businesses are also urged to remain vigilant due to the risk of inland flooding that hurricanes can trigger.

Know what’s coming

Research has shown that hurricane intensity is increasing due to climate change. Not only are hurricanes growing stronger, but they are also producing heavier rainfall, which enhances the risk of major flooding.

Rising sea levels due to a warming planet and sea ice melt contribute further to storm surge, the deadliest danger from hurricanes along US coastlines, making awareness, preparedness, and risk mitigation even more critical.

Businesses can tap into Spire’s accurate forecasts, with the advantage of space-based data from Spire’s constellation of more than 100 satellites in orbit, track weather concerning their assets for precise and timely warnings, and gain access to expert meteorologists for 24/7/365 support.

“Emerging technologies and methodologies in hurricane forecasting offer promising avenues for providing more precise and timely warnings to businesses, enabling them to better manage risks associated with these natural disasters,” Spire Weather Risk Communicator Nicole LoBiondo explained, adding, “These advancements include remote sensing and satellite technology, numerical weather prediction models, artificial intelligence, machine learning, and high-resolution weather forecasting techniques.”

DeepVision™ by Spire offers unparalleled weather risk management, empowering businesses with weather insights they can act upon, precision monitoring, and live 24/7 weather guidance from expert meteorologists, helping to enable proactive decision-making to optimize operations and prioritize safety.

“By integrating these technologies into their risk management strategies, businesses can enhance their preparedness and resilience in the face of hurricanes,” LoBiondo added. “Leveraging these tools and services, businesses can monitor and track hurricanes in real time, access accurate forecasts, and assess the potential impacts on operations, minimizing the impact on business continuity before, during, and after impactful events.”

Key business takeaways

Understanding hurricane risks is crucial for organizations, especially those in vulnerable areas. Developing a preparedness and mitigation plan is essential for protecting employees, customers, and assets, and ensuring business continuity in the aftermath of disasters.

By implementing preparedness and mitigation strategies, businesses not only enhance their own resilience but also contribute to their community’s ability to recover from disasters. Ensuring business continuity is paramount, as it allows operations to continue after a disaster, ultimately strengthening the overall recovery efforts and minimizing disruptions to the economy and society.

Learn more about Spire’s AI Weather Forecasting and how businesses can utilize it

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Unraveling the weather behind Death Valley’s transient lake

The significant rainfall event that helped form this attraction triggered California’s first-ever tropical storm warnings, extending from the border with Mexico to north of Los Angeles. Hurricane Hilary escalated to an intense Category 4 hurricane on the Saffir-Simpson Hurricane Wind Scale with maximum sustained winds exceeding 135 mph over the East Pacific in August, then weakened as it approached land. It made landfall as a tropical storm with sustained winds exceeding 55 mph in Baja California, Mexico, on August 20, 2023.

Although it weakened, Hurricane Hilary unleashed historic rainfall totals, causing catastrophic flooding in parts of the Baja California peninsula and the southwestern United States. Death Valley National Park measured 2.2 inches of rain, more than   total annual rainfall, from this storm alone.

Hilary persisted over Southern California at tropical storm strength, an unusual occurrence for the region. The last system to maintain tropical storm status while traversing Southern California was Hurricane Nora in September 1997. NOAA’s historical hurricane tracks reveal that only five systems have been recorded passing over California at tropical storm force.

The rainfall from Tropical Storm Hilary resulted in the temporary lake in Death Valley National Park, albeit only forming a shallow reflecting pool in Badwater Basin, as noted on the park’s website.

Months later, an atmospheric river delivered another dose of heavy rain in early February, with a total of 1.66 inches being measured for the month, compared to the monthly average 0.5 of an inch of rain. An atmospheric river is a long plume of tropical moisture, which extends deep into the tropical Pacific Ocean, and can fuel significant rainfall along the West Coast.

The intense rainfall raised water levels of Lake Manly, with water depth reaching up to a foot (0.3 meters) in some spots, the park said.

The history of Lake Manly

Lake Manly, an ancient inland lake that once filled the Badwater Basin, vanished through evaporation tens of thousands of years ago. Since the lake had no outlet, sediment and salt deposits remained as the lake dried up.

“Today, fascinating geometric salt polygons form on the flats as groundwater rises up through these deposits and evaporates,” the park explains on its website.

According to Death Valley National Park, sufficient rain falls in the parched park every couple of years to cover the salt flat and create a temporary lake. However, it typically remains only a couple of inches deep, unlike this year’s event.

Death Valley National Park’s notorious extreme weather

The park is known for its extreme weather conditions. It holds the title of the hottest place on Earth, alongside being the driest location in North America. On July 10, 1913, the world’s highest air temperature of 134ºF was recorded at Furnace Creek, according to the World Meteorological Organization.

During summer, monsoon thunderstorms can lead to flash flooding, while winds stirred by storms or approaching cold fronts can trigger sudden dust storms.

Death Valley’s annual average rainfall of nearly 2 inches is exceptionally dry, even by desert standards, yet it surpasses the precipitation in the world’s two driest deserts, the Atacama Desert of Chile and the McMurdo Dry Valleys of Antarctica.

Discover more about our Weather APIs

Did you know?

In 2022, international shipping alone accounted for nearly 3% of the world’s greenhouse gas emissions. And if nothing changes, it could be responsible for 17% of global emissions in 2050. Staggering, isn’t it?

Thankfully, the maritime industry is taking action.

Intrigued by how weather can impact a ship’s fuel efficiency and carbon footprint?

We recently sat down with avid pro kitesurfer Alex Caizergues, who not only holds several speed records on the water but also serves as CEO and co-founder of Syroco, a Climate Tech startup harnessing the power of physics, data, and AI to revolutionize maritime sustainability. In our conversation, Alex shed light on the immense influence of weather and sea conditions on fuel consumption and how Syroco’s game-changing product empowers operators to leverage weather data for optimal routes, reduced emissions, and reliable scheduling.

What specific challenge in maritime sustainability did your experience in kitesurfing make you particularly passionate about tackling?

My time on the water underscored the immense power of wind, waves and currents, and it frustrated me to see how traditional shipping often ignored these forces, wasting fuel and polluting the very environment that sustains their business. That’s why I co-founded Syroco – to leverage these natural forces through advanced technology and empower these giant ships, responsible for 90% of global trade and a significant share of emissions, to navigate more efficiently and sustainably.

How does weather volatility affect your ability to deliver fuel efficiency and scheduling improvements for your customers? What are the biggest headaches they face when dealing with unpredictable seas?

Weather can swing fuel consumption on the same route by up to 50%, depending on wind, waves, and currents. This historically translated to higher costs and tradeoffs to maintain strict schedules for shipping companies. Syroco turns weather from a foe into a friend. Imagine a bulk carrier battling 20-foot swells – our AI predicts the optimal route that harnesses tailwinds and currents and avoids fighting rough seas, saving 10% or more on overall fuel consumption and arriving on time. This is the kind of impact we bring to our customers, reducing their fuel costs, emissions, and scheduling anxieties.

How does Spire Voyage Optimization, powered by Theyr, amplify the power of your digital twins, unlocking the hidden potential that leads to even greater value for your customers?

Spire Voyage Optimization takes our digital twins to the next level, unlocking a powerful combo for our customers. Through this integration, we unleash the magic of AI-powered route optimization, letting our digital twins virtually explore millions of possibilities. The result is tailored routes, speed profiles and vessel settings that slash fuel costs by double digits, and significantly shrink carbon footprints. Imagine arriving at your destination exactly on schedule, saving 15% on fuel, and all while leaving a lighter footprint on the planet – that’s the power of Spire Voyage Optimization harnessed by our digital twins, delivering tangible benefits for every ship operator we serve.

Why did you choose Spire to be your data partner?

Selecting the ideal partner for Syroco’s digital twin technology was critical. Our priority was to find a routing solution that ensured highly dependable models, offering the flexibility to tailor our objectives. Equally important was access to precise weather and sea condition data. Spire emerged as the standout choice. Their advanced AI-driven, satellite-based weather tracking and forecasting met our stringent criteria. Additionally, Spire’s technology is engineered for seamless integration with various software platforms, simplifying the process for us.

Daily Forecast Error (Root Mean Square Error, smaller is better)

Why is the maritime industry looking for solutions like Syroco’s?

The International Maritime Organization (IMO) recently updated its strategy to significantly curb greenhouse gas emissions from international shipping. This roadmap has huge implications for shipping companies, who are on a fast track to improve their energy efficiency. Among the levers identified by the IMO, there are two that we know we can activate with Syroco: improve ship & fleet operations with smart ship technologies and better leverage wind propulsion for vessels that are equipped with wind assistance devices.

Do you have some specific examples of how digital twins, combined with simulation and routing, can help shipping companies achieve their goals?

Upon analyzing the initial deployments our customers have made, we are seeing an increase in energy efficiency of 10% or more without increasing voyage time. This is achieved through a combination of weather routing and ship configuration adjustments (engine, propeller, autopilot, trim, ballast, rudder, etc.) to optimize overall ship efficiency. Taken together, this is what we call real-time voyage optimization – it reaches well beyond legacy routing.

To put things in perspective, a large merchant ship (containership, tanker, cruise ship, etc.) can burn upwards of 300 tons of fuel daily. With Syroco helping increase efficiency by 10%, this avoids 25,000 tons of CO2 emissions per year while saving €3-5m on the fuel bill.

Learn more about Voyage Optimization through Deep Navigation Analytics™

The probabilty of a white Christmas in Colorado

Across Colorado, the highest historic probability of seeing an official white Christmas is across the Rocky Mountains, where the probability is near 100%, and westward all the way to the Colorado-Utah state line. East of the mountains, including Pueblo, Colorado Springs, Boulder, and Denver, the chances of a white Christmas are lower, ranging from 10-25% in southeastern Colorado to 25-50% in central and northeastern Colorado.

The last white Christmas in Colorado

Christmas 2022 was the first white Christmas in 5 years for Denver, with 2″ of snow on the ground on Christmas morning. However, this was a case where no snow fell on Christmas Day itself, or even Christmas Eve. The snow that was on the ground Christmas Day had actually fallen mostly overnight between December 21^st-22^nd. The high temperature that day was well above freezing at 49 degrees.

A white Christmas in 2023?

Currently, it appears the Christmas 2023 may have an opportunity for a second white Christmas in a row for the Denver area, with snow potentially falling on both Christmas Eve and into Christmas Day itself, although the best chances look to be from Saturday, December 23^rd and into Christmas Eve. Two storm systems are expected to work their way into Colorado over the weekend, and while there is uncertainty in how they might interact with each other, it is currently expected that snow will fall over portions of western Colorado and the mountains through the weekend.

Total snowfall expected through the weekend as of the morning of Monday, December 25th

Whether this activity will bring snow into the foothills and the plains is still uncertain, however confidence is growing in the potential for at least some snow in the urban areas, with different models bringing impacts from the weather system to different parts of the state. Temperatures through the remainder of the week preceding Christmas are quite seasonably warm, with highs through Saturday expected to be above freezing. If the ground retains that heat, it could limit how much snow is able to accumulate before melting, or if temperatures are slow to fall, could even result in more of a wintry mix event, with a mix of both snow and rain falling.

The different weather models have struggled to come into a consensus over precipitation chances and snow totals overall, keeping the highest snowfall over the mountains and western Colorado. The Spire model however has gradually increased the amount of snowfall anticipated through the weekend in the lead up to Christmas, with 1-3″ now forecast around the Denver area, however this may not be the total accumulation due to the warmer temperatures in front of the weather systems, that could result in any initial snowfall melting as it reaches the ground.

Overall, who in Colorado will see a white Christmas is still fairly uncertain. Certainly, across the highest elevations where snow has already fallen, and is unlikely to melt before Christmas, the official definition is likely to be met, and it looks likely that these systems will bring additional snowfall to parts of the state, but where exactly that additional snow will fall, how much will fall, and how much will accumulate is still fairly low confidence.

Whether the larger metro areas see an official white Christmas is especially uncertain, but there is a increasing chance of at least a few snow showers in and around Denver and Boulder, and further south towards Colorado Springs and Pueblo in the lead up to Christmas, even if less than an inch is on the ground Christmas morning.

This raises the question: how will the weather impact the F1 event?

Indeed, places such as the Sahara experience some of the world’s most extreme heat, where summer averages exceed 40°C and occasionally reach near 50°C. In the northern Mojave Desert’s Death Valley, located in Nevada, USA, the highest summer temperatures have been recorded, including the hottest day of summer 2023 at 53.9°C, observed in Saratoga Spring.

Not all deserts are hot, dry and arid

Surprisingly, the largest desert in the world is Antarctica, a place far from being associated with warm summers. Contrary to popular belief, deserts aren’t solely characterized by scorching heat but by their average annual precipitation levels. Typically, a region is classified as a desert if it receives an average of 25 cm or less of precipitation annually, leading to barren landscapes with minimal vegetation.

The dearth of moisture and resulting dryness notably amplifies the extreme summer temperatures in locations such as the Sahara Desert and Death Valley. With limited moisture, fewer clouds form, crucial for moderating Earth’s temperature. As a result, equatorial and mid-latitude deserts face intense heat due to minimal barriers between the sun and the heated surface, intensifying the soaring temperatures.

During the night, the absence of cloud cover produces an inverse effect, often resulting in extreme cooling. Clouds act as a thermal blanket; at night, when the Earth emits more radiation than it absorbs from the sun, clouds reflect a substantial portion of that energy back towards the surface, effectively retaining heat and maintaining warmer nights. In deserts, lacking this natural insulation, emitted radiation escapes directly through the atmosphere, leading to exceptional nighttime cooling.

Heated tires impact strong road grip during Formula One races

With the highly anticipated return of the Formula One world championship to Las Vegas this coming Saturday night on November 18th, the Mojave Desert’s nighttime temperatures during late fall and winter have sparked discussions among both motorsport enthusiasts and journalists.

The coldest Formula One Grand Prix on record stands at the 1978 Canadian Grand Prix in Montreal, where temperatures plunged to 5°C. Considering the November average low of 8°C, speculations have arisen about the 2023 Las Vegas Grand Prix possibly nearing this record. However, it’s worth noting that these low temperatures typically occur in the early morning just before sunrise. Despite the Las Vegas Grand Prix taking place late at night, with both the qualifying session and the race concluding between midnight and 1 am on Saturday and Sunday mornings respectively, it’s probable that the air temperatures during track action won’t reach their lowest.

Low temperatures predicted for the Formula One race

During the midnight Saturday qualifying session, the Spire forecast indicates a temperature of 57.2°F (14°C), with the lowest point of the night, around 55.3°F (12.9°C), expected near 7 am. The Grand Prix kickstarts a bit earlier, at 10 pm local time on Saturday, with Spire’s forecast suggesting a 58.1°F (14.5°C) temperature at the start, gradually dropping to about 54°F (12.2°C) by the race’s end. The coldest temperature, approximately 51.5°F (10.8°C), is anticipated a few hours later, around 7 am Sunday morning. Although noticeably cooler compared to the Brazilian Grand Prix’s 23°C two weeks ago, it appears that Montreal 1978 will retain its record a while longer.

McCarran International Airport, Las Vegas, air temperature and dew point temperature chart over Grand Prix weekend

Cloudy skies and occasional showers will be the rule through the early to middle parts of next week as another storm eyes the Northern Californian coast. This storm is expected to be more potent and has the potential to bring inches of rain to areas around and north of San Fransico. Although the storm’s track is not yet definitive, residents and travelers are advised to stay vigilant and monitor the forecast closely.

This same storm is expected to swirl just off the California coast until late next week and may bring a few showers to Big Sur along the central coast to Santa Barbra, California. For context, Santa Barbara reported a trace of rainfall on September 22nd and saw no rain throughout October, despite the usual average of nearly an inch for the month.

The stormy pattern is set to persist across California and the Pacific Northwest into the following weekend. A significant surge of Pacific moisture could heighten the risk of mudslides, flash flooding, and heavy mountain snow across major passes. This storm has the potential to be Southern California’s first major rainmaker in months and could mark the first significant snowfall for the Sierra Nevada. Travelers and residents are urged to stay informed and exercise caution in the face of potentially challenging weather conditions.

The windstorm is expected to bring damaging wind gusts to coastal communities along the Bay of Biscay in northwestern France and along the English Channel late Wednesday night onto early Thursday morning.

Wind gusts of 130 to 145 km/h (80 to 90 mph) may cause power outages and significant disruptions to ports, air travel and motorists throughout the region. Some locations along the English Channel could experience winds to 161 km/h (100 mph). Widespread gusts of 96 to 129 km/h (60 to 80 mph) are expected to sweep across a large portion of northern Spain, western and northern France into southern portions of the United Kingdom.

Travel by road, rail and air will be impacted along with the potential for disruption or closure of ferry services. Dangerous crosswinds threaten to overturn high-sided vehicles.

Ciarán’s powerful winds will also churn up dangerous seas across the Atlantic, as well as in the Celtic Sea, English Channel and Bay of Biscay Wednesday night into Thursday. Seas are expected to exceed 10 meters (34 feet) in the Bay of Biscay and 5 meters (18 feet) in English Channel.

Ciarán is expected to bring heavy rainfall as well across the region where downpours can total 25-50 mm (1-2 inches) into Thursday. The storm is expected to stall and become stationary through the remainder of the week where additional rain could lead to potential road closures and dreary conditions.

Unlike hurricane Patricia, Otis did not weaken before making landfall. Otis is the strongest landfalling Pacific hurricane on record, battering the resort city of Acapulco.

Most weather models missed the rapid intensification, leaving those in its path unprepared. Spire’s analysis reveals that our global forecasts powered by our proprietary radio occultation data produced a stronger hurricane than other models.

Spire continues to build on our robust and industry-setting radio occultation to improve global forecasting models. Our emerging microwave sounders will only help make forecasts better for the industry in a world of climate change driven rapid intensification of storms.

Spire, ECWF, and GFS weather models. Spire’s showing the rapid intensification of hurricane Otis.

“Spire’s emerging microwave sounders will only help make forecasting better for the industry in a world increasingly impacted by climate change,” adds Tom Gowan, Lead of Data Assimilation and Modeling at Spire.

Improved energy modelling accuracy by 20% through advanced data and modelling techniques

In a recent conversation with Karl Thunell, we delved into the critical role of weather data in energy model​l​ing. As the transition to green energy gains momentum, the reliance on renewable sources like Solar PVs and ​Wind power continues to grow. However, these ​assets​ are inherently intermittent and highly weather dependent. To seamlessly integrate them into a broader energy grid, accurate ​power generation predictions​ become imperative.

Rebase, a pioneering energy platform​ that promotes open-source and enhanced collaboration for data scientists​, is at the forefront of this transformation. Rebase distinguishes itself by being ‘open,’ with algorithms that are predominantly open-source and accessible to all businesses and stakeholders eager to deploy or enhance weather forecast technology. Their platform comprises three fundamental components: the Application or Interface, the Open-source model, and Data.

Effective energy modelling hinges on the availability of accurate weather data, making its role pivotal in this domain. The principle seems straightforward: the more data at Rebase’s algorithm’s disposal, the more precise their forecasts should be. However, reality paints a more intricate picture.

“The weather can vary quite a lot when we look at the geography, especially in the short term. Since we wanted to launch internationally from the start, it was about finding the best source for each geography. We wanted to apply as much data as possible, but since that was not the case, we had to settle for using the best data sources to run the best models at each specific location.”

In an ideal scenario, Rebase would possess an exhaustive repository of weather data, providing them with the resources needed to attain a perfect 100% accuracy rate. However, the current landscape presents a contrasting reality. Despite employing advanced data analytics and modelling techniques, the company currently attains a commendable 20% accuracy rate. This 20% accuracy, although not flawless, represents a substantial enhancement. It underscores Rebase’s strategic methodology of fine-tuning data sources according to specific geographical regions, an approach that proves effective even in the face of elusive complete data coverage.

Access to AI-driven energy forecasting for all energy stakeholders

rebase.energy collaborates with a diverse range of partners, including energy traders, distributed energy resources management companies, aggregators, District Heating Operators, and Energy Service Providers. Each of these entities benefits uniquely from Rebase’s energy modelling expertise and platform. Here’s a structured overview of their specific use cases:

Energy Traders:

Energy traders rely on Rebase’s forecasting tool to remain competitive and build robust portfolios while managing the inherent risks associated with renewable energy investments. Centralizing data at Rebase streamlines the process, saving them time and money on independent projections. They leverage machine learning models to obtain forecasts for their local markets.

Distributed Energy Resources (DER) Management Companies:

DER management companies use energy modelling to estimate the reliable daily, weekly​​ energy output of renewable assets such as solar farms. This data informs their bids in markets like the Frequency Containment Reserves. Rebase’s modelling allows them to increase profitability through well-informed bids, relying on good data and rigorous testing.

Leveraging AI for Enhanced Energy Forecasting

Artificial intelligence and machine learning are key drivers behind Rebase’s advanced energy modelling. Clients with access to third-party datasets can conduct comparative analyses and integrate results from diverse high-level resources to achieve more accurate forecasts. Additionally, the models are trained on historical forecast data from global sources, enabling users to obtain region-specific forecasts worldwide. This capability allows stakeholders to identify the most suitable weather provider for specific regions and seasons, ensuring precision in their energy forecasts.​ Rather than replacing humans, AI augments their capabilities, enabling professionals to work more efficiently​​​.​​

​​In the end, a forecast is just a forecast, but with great quality data and bringing white-box thinking to the algorithms, the belief is that the empowering of data scientists will enable more robust, accurate, and faster decisions – all needed to mitigate climate change.​

Source: rebase.energy

The world’s current energy system operates in a linear fashion, with power flowing from fossil fuel-based plants like coal, fire-based, or nuclear, through power stations, distributors, and ultimately to homeowners and EV stations. In this model, power and influence are concentrated at the top, held by large corporations and governments.

However, the emerging energy system takes a different approach. It’s decentralized, allowing energy generation and sharing at multiple points along the distribution chain. Solar PVs and wind turbines are accessible to both major corporations entering the renewable energy market and individual users seeking cleaner energy options. They can generate their power and even sell excess energy back to the grid.

Rebase is playing a pivotal role in facilitating this transition from the traditional centralized model to the new decentralized energy system through its software solutions.

Passing through a busy shipping lane between China, Japan, and North America has likely offset some traffic as it’s footprint can be seen in Spire’s Maritime tracking data. 

A map of Spire’s shipping data showing Typhoon Bolaven’s impact on ship traffic.

At the same time, September has continued an unfortunate trend of being another month of record-breaking heat and ranking as the “warmest September in NOAA’s 174-year global climate record,” since global records began in 1850.

NOAA reports that multiple climate anomalies impacted the globe in September. Heat records continued and New York City experienced heavy rainfall creating floods that brought the city to a halt. Heatwaves hit across the Americas, United Kingdom, Europe, Africa, and Asia. The Arctic experienced its fifth-lowest on record while the Antarctic sea ice hit a fifth consecutive month of record lows.

This dynamic septet joined forces to establish METIS Cyberspace Technology S.A., a hub dedicated to harnessing the transformative power of the Fourth Industrial Revolution for the maritime sector.

Their motivation sprang from observing the adverse effects of delayed digitization on profitability and service quality within the maritime industry. They also recognized the inadequacies of quick-fix solutions that failed to effectively address long-standing challenges. METIS’s core mission centers around the conversion of raw data into actionable intelligence to drive industry growth.

Through collaboration with Spire, METIS facilitates secure and efficient maritime operations for its clients. This strategic partnership empowers ship operators and navigators to strategize routes that optimize fuel consumption, reduce voyage durations, and enhance safety in open waters.

Sea-farers are vulnerable to the forces of nature out on the high seas. Knowing what the coming weather will be like is paramount to maintain safety of crew, cargo and vessel. Weather data assumes a pivotal role in identifying favorable wind and current patterns, allowing vessels to harness natural meteorological events for propulsion, resulting in cost-efficiency and a reduction in greenhouse gas emissions.

Beyond cost considerations, the prioritization of weather data is indispensable for the welfare of both crew and cargo. The integration of weather information into voyage planning and execution provides the maritime transportation sector with the capacity for informed real-time decision-making and efficient route adjustments, culminating in an overall enhancement of operational performance.

Moreover, METIS assumes a crucial role in calculating the impact of weather conditions on fuel consumption, a pivotal factor in the evaluation of vessel performance. Weather data also finds utility in Charter party Agreements, enabling precise comparisons between agreed-upon performance and actual outcomes.

Maintaining zero blind spots for increased global weather coverage

METIS utilizes weather forecasts from Spire in conjunction with AIS and historical weather data. Historical weather data are essential for voyage simulations, allowing for algorithm adjustments and the evaluation of optimization performance and proposed routes. The ability to run such simulations based on accurate historical data, rather than forecasts, empowers the engineering team to refine algorithms and approaches effectively.

Furthermore, METIS receives AIS and weather data (historical and predictive) from Spire, with the partnership occasionally operating in a bidirectional fashion. METIS employs onboard sensors to provide real-time vessel weather data, including SpeedLog data for current verification, anemometer data for wind force confirmation, and wave radars for swell and wave validation. This two-way collaboration allows both Spire and METIS to enhance the quality and transparency of weather forecasts through performance review projects.

Charting efficient courses with advanced maritime tech solutions

The heart of METIS is its in-house automated Data Acquisition System, which holds prestigious certifications: ‘Lloyd’s Register Type Approval Certificate’ for marine, offshore, and industrial applications, and a Cyber Resilience Type Approval by BV. These certifications assure clients of a reliable platform adhering to recognized Industry Quality Standards and International Conventions.

METIS’s impact on the maritime industry has been significant given the short time it has been in operation:

• Over 350 vessels are currently registered on the METIS platform, demonstrating widespread adoption (METIS Cyberspace Technology S.A. internal data, 2023).
• The platform processes more than 10 billion performance data points monthly, highlighting its robust data-handling capabilities (METIS Cyberspace Technology S.A. internal data, 2023).
• METIS generates specialized analytics for various roles, departments, and management levels, showcasing its versatility in catering to diverse maritime needs (METIS Cyberspace Technology S.A. internal data, 2023).

Navigating ships safely, cost-effectively, and with minimal environmental impact demands a precise balancing act reliant on timely, well-informed decisions. In cases where the power of raw data, on its own, falls short of delivering actionable insights is where artificial intelligence steps in to transform the maritime landscape.

In the realm of ship efficiency, objectives such as cost savings on fuel and environmental responsibility are not conflicting but rather complementary. Achieving both requires a comprehensive understanding of the multifaceted factors, both internal and external, influencing vessel performance.

Data, spanning machinery performance, the vessel’s physical condition, weather forecasts, and charterer expectations, has assumed paramount importance. However, the true value lies in harnessing this data to bolster decision-making that prioritizes vessel safety, profitability, and a reduced carbon footprint.

This is the heart of what METIS embodies. The AI-driven METIS platform seamlessly integrates real-time vessel-performance analysis with proactive decision support, offering shipping companies the means to transform raw data collected from onboard IoT devices into invaluable insights.

Leveraging advanced Machine Learning and Artificial Intelligence techniques, METIS empowers shipping companies to:

• Assess Past Performance: Gain a reliable assessment of their vessels’ historical performance.
• Monitor Real-Time Operations: Keep a vigilant eye on current operations in real time.
• Predict Future Behavior: Accurately anticipate vessel behavior in the future.

Ultimately, METIS’s technology empowers customers to minimize costs, optimize operational efficiency, streamline maintenance processes, and ensure unwavering regulatory compliance.

While data in shipping is more abundant and accessible than ever before, a lack of standardization in onboard equipment makes it difficult to leverage. The METIS solution is helping to bring together data from multiple sources and reveal the ‘big picture’ on ship performance.

For example, the ability to model ‘what-if’ scenarios enables users to determine the route that best combines safety, voyage time, fuel efficiency and minimum possible carbon footprint.

Another METIS software module provides a different angle on ship efficiency, allowing operators to monitor performance in line with the terms stipulated in charter party agreements (CPAs). With analysis drawing on data points including weather, maneuvering and speed, the module offers a complete representation of a vessel’s CPA compliance – to the benefit of both operator and charterer.

Meanwhile, personnel and stakeholders onboard and ashore have immediate access to real-time insights and interactive support through the METIS Virtual Personal Assistant.

As shipping’s first chatbot, the Assistant communicates with users in plain English, sharing vessel performance analyses, informing of machinery malfunctions and assisting with voyage planning and maintenance scheduling. Thanks to its underlying machine learning technology, the chatbot also refines its insights and recommendations over time.

METIS aggregates maritime weather data in real-time such as wind, swell, wave, seawater and ice, and delivers forecast insights, significantly increasing the accuracy and the value to the end customer.

Shaping the future of digital shipping

METIS envisions a future where technology plays a pivotal role in transforming the industry into a highly digitized and technologically savvy industry.

The convergence of various technologies, data analytics, and digital solutions will bring about significant changes and benefits. Most importantly, data availability and specialized weather intelligence will be an integral part of this transformation since the relation of weather with safety, risk, optimization, and efficiency is as old as shipping.

Also, one of the key drivers of digitalization in the maritime industry will be the widespread adoption of the Internet of Things (IoT) and sensor technologies. Smart sensors placed throughout vessels and maritime infrastructure will enable real-time data collection on various parameters, equipment performance, fuel consumption, cargo status, and vessel health. This data will provide valuable insights to optimize operations, enhance safety, and reduce costs.

With the vast amounts of data generated from IoT sensors and other sources, advanced data analytics and artificial intelligence (AI) will be crucial in making sense of the information. Machine learning algorithms can analyze historical data, weather patterns, and vessel behavior to predict potential challenges, optimize routes, and improve fuel efficiency. AI-powered predictive maintenance will also help prevent breakdowns and reduce downtime.

To fully realize the benefits of digitalization, collaboration among industry stakeholders will be essential. The establishment of common standards and data-sharing protocols will facilitate interoperability and seamless integration of various digital solutions across the maritime ecosystem.

In conclusion, the future of the maritime industry will be shaped by digitalization, reliance on weather data, and technological advancement. Embracing these changes will enhance efficiency, safety, sustainability, and profitability, ushering in a new era of innovation and progress for the maritime sector.

Changing climate conditions can harm renewable offshore energy production

The oceans contribute immensely by producing 50% of the world’s necessary oxygen for human survival. Additionally, they take in 25% of global carbon dioxide emissions and skilfully trap up to 90% of the excess heat released into the environment. This unparalleled capacity designates the oceans as the planet’s primary carbon sink, playing a crucial part in mitigating the impacts of climate change.

The ocean plays a fundamental role in influencing and regulating Earth’s climate, acting as a crucial component of the planet’s intricate systems. Ocean currents are responsible for distributing essential heat and moisture globally, similar in function to the circulatory system in the human body. Ocean currents are vital not only for influencing climate patterns but also for offshore wind projects, as they can significantly affect wind speed and direction, making it essential for optimizing the efficiency and viability of renewable energy generation at sea.

This is why equipping companies such as north.io with its leading TrueOcean marine data platform with powerful and accurate marine and meteorological insights is essential to harnessing our Earth’s oceans in a sustainable manner.

Harnessing marine big data to maximize offshore wind energy success

In the pursuit of climate protection and renewable energy, offshore wind farms have emerged as vital components in the global decarbonization efforts. With governments setting global ambitious targets for offshore renewable energy (from 34 GW in 2020 to 330 GW by the end of the decade), the world is witnessing a surge in offshore wind projects. However, executing multiple projects simultaneously within limited resources and shorter timelines presents a significant challenge. One key factor that plays a pivotal role in the success of offshore projects is the acquisition and management of marine data. As the “eyes of the sea,” sensors generate vast amounts of complex marine data which must be effectively harnessed to drive sustainable solutions.

In this context, TrueOcean Marine Data Platform [TrueOcean MDP], the leading cloud-based platform for managing data for offshore wind projects worldwide, offers a comprehensive solution to overcome the challenges associated with big data. TrueOcean MDP empowers users to gain a better understanding of marine data, make informed decisions, enhance project efficiency, reduce costs, secure data storage and protection, and benefit from a scalable solution that adapts to evolving project needs and the exponentially growing number of projects.

Unlocking the ocean’s untapped treasures with weather insights

TrueOcean MDP has also been recently upgraded to include MetOcean data forecasts natively. This enhancement empowers marine survey, energy, and offshore contractor users to enhance data quality control from diverse marine sensors, such as multibeam echo sounders and sub-bottom profilers.

“We are starting to use our oceans in a totally different way. We are moving from simple fishing to a world where we are transforming our oceans into giant energy generators, hubs for modern connectivity, CO2 storage and resource providers.”, shares Jann Wendt.

80% of our oceans remain largely uncharted and unmapped but are vital for our fight against climate change since they are playing a key role in global climate dynamics. Thus, empowering the world with accurate weather insights becomes an imperative step in shaping a more sustainable future.

Jann Wendt, the CEO of north.io and an environmental geographer with a passion for all things people and the planet, sheds insights on the unfolding value of oceans and the indispensable role that weather occupies in this narrative.

TrueOcean MDP: Revolutionising data management with weather insights for offshore wind

“We relate to everything that has ocean data included. Data acquisition from the ocean is growing in scale, as the demand for it is growing,” states Wendt.

TrueOcean MDP offers an additional module, empowering customers to contribute valuable data to global weather forecasts, especially pertinent within offshore domains. This module provides customers with a comprehensive display of critical weather data. TrueOcean envisions a future seamlessly integrating this data into a diverse range of large-scale computations. Consider the scenario of a wind farm owner contracting data collection services. The prevailing approach involves agreements with shipping companies, potentially limiting measurements to a 1.5-meter wave height parameter. While the present method relies on subjective claims, the future promises a revolutionary shift. Leveraging weather data and harmonizing it with sensor data could potentially validate data acquisition within the specified 1.5-meter parameter. TrueOcean’s utilization of meteorological data ensures robust quality control and assurance for data procured from oceanic sources.

As TrueOcean delves deeper into optimizing wind farm potentials, accurate weather insights become indispensable for both operations and maintenance. This crucial element propels the world towards an interconnected and sustainable future.

How Spire Global uses NOAA’s GOES-R and Himawari Datasets

NOAA’s GOES-R in combination with the JMA Himawari datasets serve as critical inputs for Spire’s Cloud Analysis (CA) product. The CA product generates three-dimensional microphysical fields, including cloud liquid, cloud ice, rain, snow, and water vapor data.

These fields are primarily used internally within Spire’s Cloud Ingestion (CI) package. The CI package, in turn, helps initialize the Spire Operational Forecast-Deterministic (SOF-D) model, which enables more accurate forecasts of clouds, precipitation, and other meteorological variables.

Spire’s Operational Forecast-Deterministic (SOF-D) is an advanced weather forecasting system developed by Spire Global. It is designed to provide accurate, and highly detailed weather forecasts for various regions across the globe. SOF-D utilizes a combination of cutting-edge numerical weather prediction models, innovative data assimilation techniques, and Spire’s extensive satellite observations to generate precise and reliable global weather predictions.

The system incorporates a range of data sources, including satellite observations, NOAA’s datasets, ground-based weather stations, and atmospheric models, to capture a comprehensive view of the atmosphere. Spire’s constellation of small satellites, equipped with instruments like radio occultation receivers and GPS receivers, plays a crucial role in collecting crucial atmospheric data that significantly enhances the accuracy of the forecasts.

Also, SOF-D employs advanced data assimilation algorithms to merge the collected observations with the underlying atmospheric models, allowing for the optimal representation of weather patterns and phenomena. This process results in advanced global weather forecasting capabilities, empowering various industries and sectors that rely on accurate weather information for decision-making.

Additionally, the SOF-D model, driven by the integrated NOAA data, offers medium-term forecasting capabilities of up to 15 days. This integration allows Spire to provide advanced weather solutions that meet the diverse needs of their customers.

Building customer-focused innovative weather data solutions

Furthermore, Spire Global uses the GOES-R and Himawari datasets, provided on NODD , to build its innovative Current Weather Conditions (CWC) product.

By integrating these datasets into Spire’s system, the company enriches the CWC product with near real-time and highly detailed information about atmospheric conditions. The GOES-R and Himawari datasets serve as essential sources of satellite imagery, offering high-resolution visual insights into cloud cover, precipitation patterns, and other key weather indicators.

Spire Global’s data processing algorithms merge this satellite imagery with other meteorological inputs to generate up-to-the-minute and accurate assessments of current weather conditions. This integration of NOAA’s datasets ensures that Spire Global’s CWC product provides meteorologists, weather enthusiasts, and various industries with a comprehensive snapshot of the prevailing weather conditions, enabling them to make informed decisions and take appropriate actions in response to changing atmospheric dynamics.

The Current Weather Conditions (CWC) products, which utilize the Cloud Analysis (CA) data, are generated on a high-resolution grid and are sent directly to customers via Spire’s Product Team API. These CWC products provide up-to-date information on current weather conditions, catering to short-term forecasting needs, including hourly and daily predictions.

Accessing weather data from the ‘cloud’: Accelerating innovation and improving collaboration

Spire Global’s ability to access NOAA’s weather datasets through a cloud-based platform represents a significant advancement in democratizing access to critical data and driving innovation within the weather industry.

NODD enables Spire Global to leverage the wealth of near real-time satellite observations and atmospheric models via the cloud, in a seamless and efficient manner.

By breaking down barriers to data access, NODD empowers researchers, scientists, startups, and other stakeholders to tap into this invaluable resource and unleash their creativity to develop new applications, models, and tools that further enhance weather forecasting and analysis.

NODD’s democratization of data and products not only fosters collaboration and knowledge-sharing but also sparks accelerated innovation. With increased access to NOAA’s datasets, researchers and developers can explore new avenues, test novel hypotheses, and fuel advancements in meteorology and climate science. Ultimately, partnerships drive the weather industry forward, leading to improved forecasts, enhanced preparedness for severe weather events, and a more resilient and sustainable future. Working with partners such as NOAA strengthens Spire’s mission to contribute to a brighter, better, and greener world.

Co-authors:

Jenny Dissen – NOAA Open Data Dissemination (NODD) Engagement Lead
Kate Szura – NOAA Open Data Dissemination (NODD) Communications Lead

What does it mean for you?

The mid-troposphere low pressure over the West Coast and the ridge of high pressure in the plains allowed this storm to come North. As well, the current heat wave warnings for the Midwestern United States will become more extreme and have the potential to put a strain on energy grids as staying indoors and air conditioning will be necessary. Spire’s DeepVision™ dashboard is already showing heat warnings for the energy grid in Texas and heat warnings across the Midwest.

The remnants of Hilary will likely ride the ridge Northward into Canada and help to develop a cold front that will help to move that ridge out and bring a bit of heat relief to the Midwest by late next week into next weekend, according to Levi Blanchette from Spire’s Weather Risk Team.

The National Weather Service in Phoenix, Arizona has issued the following High Risk rain warning:

Anomaly measures from NAEFS mean output are still off the charts, and almost unbelievably more extreme than previous iterations. Essentially every standardized field measure is pegged at a climatological extreme for this time of year at multiple time scales. Most impressive is IVT measuring better than 14 normalized standard deviations from average and rivaling anything experienced in moisture flux during the cool season. Considering a large reservoir of 2.0-2.5″ PWATs will be tapped by a 60-70kt meridional wind in the H8-H7 layer, this poleward moisture advection persistent through the Saturday night through Monday morning time frame should bring recurring periods of moderate to heavy tropical rainfall to the western CWA. RAW GEFS output still highlights extreme accumulations across SE California with almost no members below 1″ in El Centro and greatest clustering in a 2-5″ range. If data for Palm Springs is indicative of surrounding higher elevations around Joshua Tree NP, almost no member advertises anything under 2.5″ with the best clustering in a 4-7″ range. Thus, it comes as no surprise that WPC has painted a rare High Risk in the excessive rain outlook (ERO) along the western CWA border during the Sunday morning through Monday morning time frame.

Hurricane Hilary was a Category 4 storm, with recorded winds up to 65 Knots (almost 75 mph). It’s now a low pressure system heading inland.

The Spire Weather data is showing up to 7.02 inches of rain in Southern California for early next week

Impact on infrastructure

As noted above, the storm is causing flooding, and an associated increase in the heatwave will put strain on energy grids. Spire’s ShipView dashboard showing cargo ships (red) and tankers (black) taking a wide course around the Category 4 storm on Friday.

Spire Weather‘s Wind Gust data layered over Spire Maritime’s ShipView data showing cargo (red) and tanker (black) ships taking a wide course to avoid Hurricane Hilary on Friday.

Inland, Spire’s DeepVision™ dashboard shows weather warnings around electricity grids and base stations across the U.S.

A map of the U.S. from Spire’s DeepVision™ dashboard showing weather warnings around power grids in Nevada on Friday.

What is clear-air turbulence?

Sometimes referred to as “air pockets”, clear-air turbulence forms where two layers of air meet while moving at different speeds. The movement of air between these masses causes erratic wind patterns. Typically, turbulence can be seen in cloud patterns, giving pilots and their onboard instrumentation the ability to detect these pockets of erratic air and adjust their course for a smoother flight. Unlike that turbulence that forms with clouds, clear-air turbulence remains invisible to onboard instruments and visible sight, making it a hidden danger during flights.

Why does clear-air turbulence matter?

Clear-air turbulence is common around the Jet Stream, so flights are more effected as they transit the jet stream and encounter these invisible wind patterns. It also can occur at lower altitudes around rough terrain and mountains.

Researchers found a 55 percent increase in severe turbulence from 1979 to 2020, suggesting that climate change is playing a role. Papers from Nature and Advances in Atmospheric Sciences have looked at the effects of increasingly warm air masses turbulent air patterns between the upper and lower atmosphere. This means that unfortunately for uneasy fliers, turbulence is likely to continue increasing.

A 2023 paper cites that the cost of turbulence was estimated to be around $200 million annually in the US alone in 2003. That’s primarily from increased strain to the airframe, causing fatigue and damage requiring repairs and lost productivity. As well, injuries suffered by passengers and crew requiring costly hospital visits and compensation. This year alone, severe turbulence has been in the news for causing injuries worldwide.

Is clear-air turbulence actually invisible?

To pilots and their current onboard instruments, yes. While it isn’t visible to on-board radar and satellite imagery, it is detectable through Spire’s radio occultation data that can detect small changes in wind patterns, as Spire’s data shows below. As we advance our understanding and technology, addressing this hidden threat becomes increasingly essential for safer – and more pleasant – air travel.

Clear-Air turbulence around Munich, Germany

Interact with the map to see the relative Clear-Air Turbulence (rcat) measurement at different altitudes.

At the same time, NASA notes that hurricanes form – and are sustained – when sea surface temperatures reach above 82’F. A warming sea means more potential for sustained hurricanes.

In the United States, ground moisture levels are alarmingly depleted, hinting at a challenging year for harvests and placing additional strain on crop growth.

Spire’s weather dashboard showing heatwaves and severe weather patterns overlayed with power grid reports. Source: Spire Weather

Concurrently, the strain on power grid systems in heatwave-battered US states persists . Arizona has been especially hard hit with record high temperatures putting a strain on their power grid.

Spire’s weather dashboard showing the current heatwave impacting Arizona. Source: Spire Weather

There’s no easing of extreme weather in the foreseeable future with El Niño building in the pacific, floods, and more heatwaves forecasted for the summer.

As severe environmental patterns continue, extreme weather alerts are more important than ever for communities around the world.

The United Nations has made a commitment to ensure that one-third of the world’s population – currently without severe weather warning systems – has access to alerts within the next five years. This is vital for the 680 million people living in low-lying coastal zones where a 24-hour warning could reduce damages by 30% according to the United Nations.

Innovative companies like OroraTech are partnering with Spire to leverage our expertise in manufacturing, launching and operating satellites. This allows OroraTech to focus on their core business of providing thermal space-based intelligence for wildfire detection purposes as well as other solutions.

OroraTech uses thermal intelligence to help build a more sustainable future. Recently, OroraTech has ordered Spire to build, launch, and operate an eight-satellite constellation dedicated to global temperature monitoring. Once operational, it will represent the first and largest constellation of satellites dedicated to tracking and monitoring wildfires.

Mantle Labs is another partner that leverages Spire’s data for AI to streamline farming. Mantle Labs is leveraging Spire’s unique weather data to train AI and create risk assessment models for crop protection and agricultural commodity companies that use Mantle Lab’s own Geobotanics platform. Farmers worldwide can use the platform to monitor crops and prevent losses.

Spire’s Weather dashboard showing storm warnings that may impact infrastructure and power lines across Florida.
Source: Spire Weather

Spire empowers our customers with the ability to predict weather events with heightened precision and accuracy, meaning early warnings for severe weather phenomena are more reliable. This allows first responders and resources to be allocated and positioned, ready to act, before hazardous weather impacts resources or operations.

One-third of the world’s population do not have access to early warning systems for extreme weather. With over 680 million people living in low-lying coastal zones and on small islands, even a 24-hour warning can reduce the damage of climate disasters by 30 percent. The United Nations has made it its mission to address this within the next five years so everyone is safeguarded by early warning systems for extreme weather.

Spire’s Weather dashboard showing rain warnings across the Pacific Ocean north of Australia.
Source: Spire Weather

Lives would be saved, and damage from natural disasters minimized through AI’s proactive planning and swift actions.

Extreme weather conditions at sea increase operational risks for the global maritime industry

To put this into perspective, according to a recent study by Allianz, ‘bad weather accounted for one in five losses, and issues with car carriers and roll-on/roll-off (ro-ro) vessels remain among the biggest safety issues.’ Also, the same study highlights that out of 24% of the 54 shipping accidents that occurred in 2021, happened due to extreme weather conditions. Even more, a report published by The World Shipping Council reveals that the average number of containers lost overboard increased by 400% due to the intensity and frequency of extreme weather events.

It is evident that making decisions and predictions based on accurate maritime weather data sets the foundations needed for a sustainable and safer maritime industry.

Explore Spire’s maritime weather data solutions

Esgian’s data-driven approach to making the maritime shipping industry sustainable

Esgian uses Spire’s weather data to power parts of its Shipping Analytics, Greenpact Rigs, and Wind Analytics products. Specifically, the company leverages Spire’s satellite-powered current weather conditions data, available globally in high 3km resolutions.

For shipping, the company has developed advanced analytics software that analyzes the activity of the global RoRo fleet through a map and user-friendly platform. This allows users to compare operators’ performance in a range of parameters versus segment averages and turn data into actionable insights.

Plus, Esgian uses Spire AIS datasets to match each vessel to a commercial operator and geofence ports. With such insights, Esgian’s clients have the advantage of being able to observe RoRo trading patterns and schedules, as well as port activity and port-pair service performance with a 98% accuracy rate.

On the platform side, Shipping Analytics analyzes carbon emissions in the shipping industry which measures the carbon footprints of individual vessels, voyages, and shipping fleets, both in absolute terms and in terms of carbon intensity. Additionally, the platform compares the emissions between individual ships, fleets, operators, and countries. It also tracks the Carbon Intensity Indicator (CII) rating for individual vessels, operators, or defined fleets. Spire’s weather data is ingested into the algorithm to correct for the actual weather conditions surrounding the vessel, giving a much more accurate estimation of the vessel’s required power to maneuver.

“Weather has a direct effect on a vessel’s performance and can add resistance to its movement. Environmental factors such as wind speed and direction, ocean currents and wave heights impact a ship’s resistance which can increase its fuel utilization and its carbon footprint. Factoring in the vessel’s speed is important as well that can be retained from AIS data. However, to achieve 90% accuracy in the estimation of carbon emissions, Spire’s granular weather datasets are key,” commented Omli.

Measuring the carbon footprint of vessels not only assesses their environmental impact but also enables the evaluation of the cost and benefits of making improvements to a specific ship or contract. This evaluation helps determine whether it’s worth investing in upgrading the technology. Such upgrades can aid in calculating the total cost of offsetting ship emissions and ultimately lead to tax benefits for ship owners.

Onshore, port managers allocate their resources and assign their docks based on vessel traffic, available equipment for cargo management, and personnel. Esgian is also leveraging Spire’s AIS data to monitor the duration it takes a vessel to enter and exit a port, including the time it takes to load/unload cargo onto it.

By understanding such insights, Esgian is equipped to design and data-driven maritime products that will improve ports’ operational efficiencies. Companies such as Esgian are bolstering the smooth flow of global supply chains by helping shipping companies deliver faster, minimize delays, reduce costs and decarbonize.

Esgian’s maritime solutions for offshore oil rigs

For offshore oil rigs, the company created a robust platform that provides users with live drilling rig market data. The platform offers accurate data and analysis tools that cater to the needs of drilling rig owners, offshore rig service providers, equipment manufacturers, oil companies, shipyards, banks, and even investment funds.

These tools are specifically designed to keep stakeholders up-to-date with the latest trends and developments in the rig market, enabling them to support tendering, contracting, business development, and investment decisions. Specifically, users can compare oil rigs based on technical specifications and features, as well as do improved forecasts on demand and day rates among other benefits.

Also, Esgian leverages Spire’s hyper-localized Point-Optimised Forecast, covering over 10K locations around the world with a 1-hour refresh rate, to measure weather variables on the specific locations of its oil rigs.

Esgian’s maritime solutions for the global offshore wind market

Lastly, the company has built a bespoke solution for the global offshore wind market, providing global coverage on contracts, target and leasing, vessel activity, floating technologies and more. This market intelligence gives investors and stakeholders the opportunity to anticipate fluctuations in demand and to support contracting, business development, and investments.

Overall, Esgian’s innovative solutions are helping to make the global maritime industry more sustainable and safer for everyone involved. By reducing environmental impacts, improving safety, and ensuring compliance with regulations, Esgian is helping to create a more responsible and efficient industry for the future.

Talk to our team to learn more about our data solutions

Satellite-powered weather and AIS data fueling a sustainable maritime industry

The increasing risk and frequency of extreme weather events at sea make access to advanced global maritime data more urgent than ever.

Collecting maritime data from remote ocean areas has posed a challenge for the maritime industry for a long time. Even when such data is available, it is often collected from buoys and moving vessels which results in inaccurate, delayed, and oftentimes not AI-ready data that require large computing power to assimilate and run through models.

Accurate and real-time readings of current ocean weather conditions such as wind and wave height are crucial in making reliable forecasts. With weather intelligence, shipping companies can learn to avoid a certain route to mitigate a storm, oil rigs can prepare for rough sea waves by halting operations and even evacuating the crew, and offshore wind farms can better anticipate the flow of wind.

Also, weather and AIS data play a direct role in the way ports operate. If a vessel was delayed due to unfavorable weather conditions, then it will ultimately use more fuel to arrive on time to avoid paying penalties, increasing its carbon footprint in the process. Managing vessel traffic around a port needs reliable AIS data, to know when to expect a vessel to arrive and unload/load.

Download our whitepaper on how weather and AIS data optimize port operations

An analysis conducted by SeaIntel in 2023 revealed that the average delay for late vessel arrivals had been dropping consistently since the turn of the year, a great trend to observe particularly as there has been a global increase in demand for goods and services after the pandemic. However, arrival delays remain at an average of 6-7 days throughout the year.

The underlying problem that causes these delays remains unresolved. The problem with vessel delays is that they have a widespread ripple effect, resulting in increased costs, additional risk, and more emissions as ships attempt to arrive or depart on time amidst a constant flow of ships coming and going from ports. This is a reality that cannot be ignored.

Climate change has created a new financial and environmental imperative for businesses. For example, artificial reefs made of defunct oil rigs are breathing new life into oceans, supporting marine life growth, and reducing disposal efforts. The offshore wind farms industry is also growing, with increasing investments in alternative offshore energy sources, requiring reliable maritime data to succeed.

With satellite-powered weather and AIS data, the global maritime industry now has access to near real-time data, making the journey from data to insights more streamlined. Spire builds and manages a constellation of 100+ nano-satellites in low-Earth orbit that are able to collect AIS and maritime weather data. Researchers and meteorologists now have better data to plan around all the moving elements surrounding the maritime industry: weather, vessels, ports, wind farms, oil rigs, submarines, sea ice, marine life, and more.

Working together for more than a year, Spire and Esgian share a natural synergy and vision which is to build more sustainable maritime operations. Spire’s continuous ability to collect rich, granular data from space across all points on the globe that include the open oceans puts it in a unique place to create a positive impact on Earth and solve real-world problems.

Storm Izzy halted operations at busy south-eastern American airports

The above animation depicts Spire’s weather forecast model’s prediction that a strong, comma-shaped low-pressure system would strike the southeast US. This forecast animation was for 48 hours of the composite radar and indicates the potential reach and intensity of the forecasted precipitation. It reflects that certain geographical areas in this vicinity would experience severe thunderstorms and tornadoes (as Florida actually did). As stated, some of the busiest air hubs lie within this region and include:

• Memphis, a large cargo shipping center utilized by global entities such as FedEx as a primary distribution point
• Atlanta, the busiest airport in the United States by passenger traffic
• Charlotte ranked as the fifth busiest national airport in 2022

Powerful winds hindered aircraft takeoff and landing safety

However, there was another component to Storm Izzy that compounded the negative weather effect at these large airports – the threat of sustained high winds. Spire’s weather forecast anticipated heavy thunderstorms and sustained high wind speeds. The map below denotes Spire’s 48-hour forecast with sustained wind speeds as shown. All three airports highlighted were forecast to be struck by sustained wind speeds near or greater than 40 km/h.

Alone, these wind speeds would probably not have been powerful enough to affect air traffic so notably. However, when these sustained high wind speeds converged with heavy precipitation, the forces unleashed caused the cancellation and delay of thousands of flights across the three significant airports within the region: Memphis, Atlanta, and Charlotte. In addition to the winds, the storm system created a prolonged period of Low Instrument Flight Rules (LIFR) conditions.

All airports pay critical attention to wind speed, gust, and wind direction to make optimal decisions regarding runaway configurations for inbound/outbound aircraft operations. The authorities responsible for airport functionality define specific safety thresholds for such weather parameters that permit planes to land and take off safely. For Storm Izzy, wind speeds were predicted to be high enough to obstruct airports from operating at full capacity, thus stranding thousands of travelers and delaying/canceling over 7000 flights nationally.

Uncovering the effects of severe weather on air freight operations

Understanding the consequences of extreme weather events on air cargo operations is crucial to empower businesses to be able to make data-driven decisions and develop contingency plans to alleviate the risks. To shed more light on the impact of Storm Izzy on air traffic, here’s an analysis of Spire’s aviation data that compares flights during the week of the snowstorm and the week after. The visual below depicts the impact of the storm at each of these respective airports: Memphis, Atlantis and Charlotte.

Apart from thousands of flights being canceled throughout the south-eastern region of America, a 3% decline in cargo flights was detected at Hartsfield–Jackson Atlanta International Airport whilst the Memphis International Airport witnessed a 6% drop in flights. Venturing towards the northern-eastern heart of the USA, Storm Izzy impacted  the Newark Liberty International Airport and Louisville Muhammad Ali International Airport yet not as negatively as its southern counterparts.

Studying the combined number of cargo and passenger flights scheduled over the same period, it’s observed that flight density declined between 6%-14% across Memphis International, Hartsfield–Jackson Atlanta International, and Charlotte Douglas International Airport. The latter has been notably hit the hardest by Storm Izzy. Charlotte is a primary air and passenger hub with over an average of 1400 arrivals and 118,000 people traveling through per day.  Storm Izzy affected more than 74 million people as it canceled thousands of flights whilst delaying hundreds of others. Similar to passenger flights, the winter storm disrupted air cargo operations as well by grounding several aircrafts and postponing delivery timelines.Leading global logistics and transport service providers experience a 30% decrease in aircraft utilization.

To truly gain an overall understanding of the impact of winter storms on air cargo daily operations, Spire’s team analyzed the top five cargo operators from Memphis, Atlanta, and Charlotte airports as well as the aircraft types commonly utilized by these operators to grasp the effect of Storm Izzy on the global air supply chain.

Major carriers experience 30% drop in air cargo flights

Let’s understand that global trade logistics is a highly complex and interconnected ecosystem. A weather-related delay at one point would require subsequent actors (ranging from trucks, warehouse, ports, railway services) to adjust their operational schedules accordingly. They would also have to ensure that they have the correct capacity to store the incoming cargo and have it available for the next stage of transport. Therefore, when a winter storm with the intensity equivalent to Storm Izzy left icy roads that were deemed dangerous to drive upon, it naturally hindered the transportation of goods from main cargo hubs that serviced international and domestic operations.  The delays  were further exacerbated by fallen trees and power lines that blocked primary road arteries and highways.

Putting the above into perspective, extensive air, road and rail services to main cities in the country that included port facilities link to the Hartsfield–Jackson Atlanta International Airport that connects cargo carriers with six different continents. During the stormy week of January 2022, three out of five operators, FedEx, Korean Air and Qatar Airways, experienced the consequences of Storm Izzy on their aircraft utilization. Korean Air and Qatar Airways operations were negatively impacted with cargo flights declining by over 30%. Considering that the Hartsfield-Jackson airport processes an average of 56,000 metric tons of cargo and mail on a monthly basis, even the most minute delays will have far-reaching effects down the air supply chain.

Soaring over to the Memphis and Charlotte airports, a similar trend is evident amidst cargo aviation operations at both the Memphis International Airport and at the Charlotte Douglas entity. The Memphis International Airportis the busiest cargo airport in North America and the second-busiest in the world. Home to major global logistical service providers, Storm Izzy  had a particularly strong effect on the daily operations of two of the airport’s major cargo players: UPS and Atlas Air. Both cargo carriers respectively witnessed their daily operations within that week fall by almost half of their usual capacity.

Meanwhile, at the Charlotte Douglas International Airport that  caters to over 30 airlines for domestic, regional and international passenger/cargo services, cargo operators felt the brunt of the winter storm with a 22% average decline in airport usage.

When examining the influence of weather conditions on aircraft utilization, it is also necessary to analyze the impact on particular aircraft types. When factoring that in for vital air cargo players, it’s evident that the storm effected the longest-range twin-engine aircraft B777-200 freighter the most. Its utilization fell by over 20% at both the Atlanta and Memphis International Airport. Secondly, the American three-engine wide-body airliner McDonnell Douglas MD-11F was impacted the least.

Storms do not only cause loss in airport revenue yet cause infrastructural damages worth thousands of dollars. Often, it can take days, weeks or even up to months to rebuild. Apart from impacting flight schedules and safety, hurricanes can also cause power outages that add further chaos to the existing tumultuous environment. Factor in seasonal holidays and peak travel times under extreme weather conditions, it’s imperative for air supply service providers to be equipped with global, accurate weather and aviation insights to quickly assess the impact of these disruptions on their operations and make adjustments to minimize the damage, and ensure flight schedules are optimized and goods are delivered on time.

Get customized weather data for your business Explore space-based flight data and aviation insights

The importance of maritime weather data

Maritime weather data is used to provide information about the current and forecasted weather conditions in the oceans and coastal areas. These insights can be used to plan safe and efficient routes for ships, as well as to make decisions about cargo and ship loading. Additionally, accurate weather data can help ships avoid dangerous conditions such as tropical cyclones, severe thunderstorms, and rough seas, which can lead to damage to the vessel or cargo and even loss of life.

According to Allianz’s Safety and Shipping Review 2022 report, around 90% of global trade is transported by the maritime transportation sector, making vessel safety essential. The global shipping fleet was losing 200+ ships a year in the early 1990s. During the past four years, the number of ship losses has decreased to about 50-75 vessels a year. This statistic is impressive especially as there are an estimated 130,000 ships in the world’s fleet (over 100 gross tonnage), up from around 80,000 thirty years ago.

In 2021, the maritime industry maintained its positive safety trend with 54 reported total losses as opposed to 65 losses the year before. Annual shipping losses have decreased by 57% (127) since 2012, and 2021 saw a significant improvement over the rolling 10-year loss average (89). The decrease in shipping-related accidents is a direct impact of the implementation of safety measures in recent times. Regulations, improved ship design and technology, and developments in risk management and mitigation have all contributed to increasing the safety of the industry. 

Plus, using maritime weather data has several hidden cost savings for shipping companies. For example, shipping companies might be able to benefit from lower insurance premiums, saving on crew overtime pay due to inefficiencies, and avoiding penalty fees from port operators due to delays in arrival and schedule. 

Most importantly, leveraging accurate and reliable maritime weather data helps the shipping industry become more environmentally friendly and compliant with regulations. It has become mandatory for all maritime operators to calculate their attained Energy Efficiency Existing Ship Index (EEXI) and to initiate the collection of data for the reporting of their annual operational Carbon Intensity Indicator (CII).

The reason for these regulations is to ‘reduce the carbon footprint of ships by 40% by 2030 compared to the 2008 baseline‘. Decarbonizing the shipping industry requires a holistic approach involving data-driven efficiencies, policies, automation, smart ports, and cleaner fuels, to name a few.   

Reach your compliance goals with our maritime weather forecast API

Types of maritime weather data

There are several types of maritime weather data available, including data on sea winds, waves, currents, temperature, and precipitation.

Wind data

Most vessels would like to avoid windy conditions as it, depending on the direction, often negatively impacts the ship’s efficiency or the safety of crew and cargo. Wind data is therefore an important ingredient in any voyage optimization algorithm.

Wave data

Just like wind, most ships would like to avoid rough sea conditions as it negatively impacts the ship’s efficiency or the safety of crew and cargo. Wave data is strongly correlated with the wind data. However, both data sets are needed because not all waves are generated by the local wind conditions. A ship can experience treacherous waves that were generated many days ago and thousands of miles away. Wave data is a critical component in any voyage optimization algorithm.

Ocean currents

Although often not dangerous by themselves, insight into ocean currents is crucial for any ship optimization calculation. It can also be used to predict the movement of floating debris, including icebergs. 

Temperature and precipitation

These two weather parameters are used to forecast weather conditions that may affect the transport of bulk cargo and reefer containers

Maritime weather data can also be used to improve shipping operations. For example, wind data can be used to optimize the speed and fuel consumption of ships. Wave height data can be used to ensure that ships are not at risk of capsizing. Additionally, weather data can be used to optimize the scheduling of ship maintenance and repairs, which can help to minimize downtime and increase efficiency in the long run.

Request a demo of maritime weather data 

How to collect and use maritime weather data

Maritime weather data can be obtained from various sources such as satellites, buoys, vessels and ground stations. Once collected, the data is then distributed through commercial companies or government agencies like NOAA (National Oceanic and Atmospheric Administration) or the Maritime & Coastguard Agency (MCA) branch of the Met Office in the UK which provides maritime weather forecasts and alerts to the general public. 

Many private companies also provide weather data, often with a focus on specific regions or shipping routes. Some ships also have their own weather monitoring equipment, which can be used to provide real-time data.

Climate change is increasing the need for complex and accurate weather forecasting data. As a result, maritime shipping companies’ needs have evolved to require a single source of information that is reliable, accurate, robust, and centralized.

Spire has one of the largest private constellations of nano-satellites in orbit, comprising more than 100 Low Earth Multi-Use Receiver (LEMUR) satellites and collecting a vast amount of weather observations. The LEMUR measures key parameters like temperature, humidity, and pressure through a technique called radio occultation.

Radio occultation is the process of measuring the amount of bending that radio signals undergo while traversing between the ionosphere and Earth’s surface as a result of the temperature, atmospheric pressure and humidity. 

Once the data is collected, it is then incorporated into Spire’s proprietary weather forecasting model which goes out up to 15 days into the future. The forecast is delivered to Spire’s clients through an API that offers multiple types of weather data in various formats. 

This flexibility ensures that our customers are able to leverage Spire weather data depending on their needs. For example, a user can download current wind speed data for the entire Pacific Ocean in Grib2 format. Via that same API, another user can retrieve the ocean temperature of predefined points in a planned route of its vessel. Even more, a user can receive maritime weather data for specific destinations such as ports.

Some of the use cases for maritime weather data include:

• Optimizing shipping routes to avoid extreme weather events and become more environmentally friendly and cost-effective
• Optimizing port operations and other points of interest 
• Gaining a competitive advantage over other shipping companies
• Complying with environmental regulations in regards to the Carbon Intensity Indicator (CII)

To put this all into perspective, watch this webinar to learn more about why the shortest maritime route isn’t always the most fuel-efficient. Chris Manzeck, Meteorologist and Product Marketing Manager, had a discussion with Luc Terrral, cofounder of BluePulse, one of the global leaders in AI-powered predictive maintenance for the maritime industry. During their chat, Chris and Luc discussed how BluePulse takes advantage of Spire weather data to develop a routing algorithm for reefer container transport. Voyages for ships carrying refrigerated containers can be further optimized by looking at parameters like air temperature, cloudiness and precipitation. 

After using Spire weather data combined with their in-house artificial intelligence algorithms, BluePulse was able to save 297 MWh reefer energy per crossing, reduce their carbon footprint by 90,000 tons eqCO2, and ultimately offer the world the potential to save €20M in operational costs.

Watch the webinar on demand now

To use maritime weather data, ships and shipping companies can employ weather analytics, routing, and voyage optimization software, which can help to make sense of the data and make informed decisions quickly and easily.

Maritime weather data adds a layer of safety in a world of uncertainty

In conclusion, maritime weather data is essential for the safe and efficient operation of ships. Accurate and up-to-date information about winds, waves, currents, temperature, and precipitation can be used to plan safe and efficient routes, make decisions about cargo and ship loading, and optimize the operation of ships. Shipping companies can take full advantage of the available weather data and technology to improve their operations and keep their ships and cargo safe.

Talk to one of our experts now to learn more about our maritime weather forecast API and solutions.

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What is the Spire Point Optimized Forecast?

The Point Optimized Weather Forecast system relies on a few different types of technology to produce a highly accurate, rapidly updating weather forecast for surface weather conditions from the next hour out to day 15. This is an advanced forecast ecosystem that uses multiple global and regional forecast models, including Spire’s unique global forecast model. Each forecast model opinion is considered and compared against the surface conditions from actual weather station readings. As each hourly surface conditions update is published at the weather station, the forecast ecosystem considers the performance of each model and uses machine learning techniques to correct the overall forecast based on that performance. The evaluation of each forecast model within the ecosystem is continually updated to ensure that any seasonal biases in forecast models are accounted for.

What are the benefits of this type of local weather forecast?

The end user benefits of Spire’s Point Optimized Weather Forecast are primarily two-fold. First, using multiple forecast models and comparing their performance against surface sensor data allows for this forecast to continually outperform any individual forecast model. If forecast accuracy is the most critical factor, generally speaking, the Optimized Point Forecast will be the best choice. 

The second benefit of this forecast is the rapid update cadence. Not all forecast models update on an hourly basis, but we are still able to produce an hourly updating forecast because the local sensor data updates that frequently. 

Consider a scenario where most of the individual forecast models were predicting a temperature drop of 5 degrees C between 12 and 13 UTC, which is +6 hours from “now”. However, the local sensor actually indicates the temperature drop has just occurred now (6 hours earlier than predicted). Despite the fact that no forecast models have updated between those two hours, the Point Optimized Weather Forecast will still notice that temperature drop has happened at the local sensor and forward-correct the forecast to account for the change that occurred. In this way, the Point Optimized Forecast is truly continually updating, even if the forecast models haven’t quite caught up to any rapidly evolving weather event.

Where is the forecast available and what weather variables are included?

The Point Optimized Weather Forecast is readily available today for roughly 10,500 predefined global locations, for which we also retain the forecast history. Our customers can access any of these locations through an easy to use weather API which produces JSON or CSV formatted output. If you require a set of custom locations, we can also add those to the ecosystem and allow access to those new ‘virtual weather station’ locations within a short time. 

The output from this weather forecast API includes over 25 unique variables and includes parameters describing the forecast temperature, dew point temperature, wind speed, cloud cover, precipitation, and probability of thunderstorm among many others. Please reach out to your Spire representative for more information on how to gain access to this highly accurate weather forecast.

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How can Spire’s Point Optimized Forecast minimize supply chain disruptions?

Advanced weather forecasts enhance airport functionality

This is of particular interest to strategic stakeholders in the global supply chain network, such as airports and ports. Pilots require accurate weather insights during landing and takeoff to ensure the safety of their crew and passengers. Fog, rain and low hanging clouds can obstruct visibility at and around the airport whilst thunderstorms can hinder both flight and airport operations. Weather variables such as wind speed and wind direction determine the directional landing and take off of airplanes and which flight routes to utilize. Armed with high quality location-specific weather forecasts, airports can ensure that their loading/unloading baggage & cargo operations, personnel and passenger safety, along with fuel optimization is maximized.

Advanced weather forecasts optimize operational efficiency for ports

Port authorities need the right weather information available at the right time. Despite their individualistic characteristics, business model and location, all ports are impacted by weather and have to execute their operations accordingly.

A location-specific forecast designed just for that specific port will facilitate decision making and help design contingency plans.

For instance, if high winds are expected to blow at dangerously high speeds, then that would halt port operations. Knowing this possibility in advance would empower the relevant authorities to plan for downtime and warn other players in the supply chain of the expected delays.

Wildfires average 7 million acres of burnt land annually

The Analytical Moose provides GIS consulting services and drone imagery to customers from Wyoming to California. The past twenty years have seen an average of 7 million acres of land burning annually due to wildfires.

The Analytical Moose™ is the brainchild of Rachel’s vision for greater predictability around wildfires. To this end, her company, which provides GIS consulting services and drone imagery to its customers, is releasing a mobile wildfire notification application, Wildfire Aware™ this month (November 2022). The application will allow users to monitor locations near areas of interest and provide timely notification of fires that start. Serving the Western United States from Wyoming to California.

Download wildfire use case

The figure above highlights a newly formed wildfire where the boundary is either unknown or so small that an individual point is used to represent the current location, while Spire current weather conditions are overlaid onto the map to give an indication of which direction the fire may spread. Further down the page, the application provides the user with additional weather information that contributes to the volatility of a wildfire.

Wildfires can either crackle and hiss out quickly or can extend their damages within a heartbeat to thousands of acres of land. When uncontrolled, the destruction and chaos occurs within mere hours. However, three variables influence the severity and movement of the wildfire: geography, weather and fuel.

The chemical composition, moisture levels and density will define the speed, spread and temperature of such a conflagration. If the land has low moisture levels and is dry in nature, then it will burn faster as there’s no water to fight the fire’s heat. For example, grass burns quicker and doesn’t create as much heat as trees and other similar fuel sources. A detailed understanding of weather parameters  such as humidity, wind and temperature will help to model the wildfire’s path. Under windy conditions, wildfires will obtain additional oxygen and flare across the earthen floor at an accelerated rate.

Fueled mission to be a fire expert and GIS specialist

Rachael, the co-founder of the Analytical Moose, has personally lived through multiple wildfire events in Northern California (Bully, Carr, Zogg, etc.) whereby she has had to rush to get her friends and family out of the way of the fast moving fire. As a former member of the California Department of Forestry and Fire Protection, Rachael spent six years as a dispatcher. She was responsible for resource allocation during emergencies and maintained the supporting GIS database, followed by an additional seven years as a Research Data Specialist at CAL FIRE’s regional office.

Rachael fulfilled many roles in the CAL FIRE Northern Region office. She helped manage the database where CAL FIRE tracked all fuel reduction projects. She assisted with serial arson investigations, even winning the USGIF Government Achievement Award for her work. When fire activity was heavy in California, she would routinely provide GIS support for airspace coordination and regional coordination. Rachael is also an Infrared Interrupter and would quickly map fires based on nighttime flights by specialized aircraft, in 2018 she provided the first fire perimeter of the Camp Fire and had the first look at the widespread devastation from the air.

A collaborative effort between organizations like AM and Spire, with strong governmental support, offers a sustainable solution to this ongoing problem. A small fire, whether unintentional or created on purpose, when pushed by strong winds, is what essentially creates the need for real time, technology enabled tracking of weather and wildfires alike. The cumulative data will make or break any efforts put forward to mitigate future fire events.

Download wildfire use case

Economic downturn will impact consumer demand

The International Monetary Fund expects worldwide inflation to hit 8.8% this year. That would be the highest rate since 1996. In the US, consumer prices were up 9.1 percent over the year ended June 2022. This was the largest increase in 40 years according to the U.S. Bureau of Labor Statistics. In Europe, it is worse. Preliminary data from October 31st – reported Eurozone inflation running at 10.7%. This is the highest ever monthly reading since the euro zone’s formation. Five countries experienced triple-digit inflation rates during 2022. These countries are: Zimbabwe (269%), Lebanon (162%), Venezuela (156%), Syria (139%) and Sudan (103%). Argentina (88%), Turkey (85.5%) were not far behind.

Basically, driven by the Coronavirus and then the still ongoing Russia-Ukraine war, energy inflation is pushing up the cost of living around the planet. This means people will focus more on essentials and less on frivolous spending, translating to people trying to hold on to their cash. Thus, supply chain executives can work to reduce forecasts for 2023 and accordingly reduce stockpiles for the year.

Central banks respond to high inflation by continuing to raise interest rates – and thus slow economic growth – until inflation is back to acceptable levels. With the increased interest rates, borrowing at the corporate and individual level is expected to see a dive. This in return will affect capacity to produce and buy respectively.

Deeper visibility into N-tier suppliers will be priority

At one point in time, keeping dibs on Tier-1 suppliers was sufficient to ensure the smooth flow of goods across different layers of the supply chain network. However, in today’s age, with the exponential growth of external complications, supply chain strategists have to delve deeper and map out every stage taking into account distribution, warehousing, manufacturing support, repair options, transportation variables from land, air or sea and put it in against its corresponding matrix of cost, risk, revenue, time and carbon footprint.

In 2021, McKinsey did a survey in which just under half of the surveyed business entities stated their understanding of the locations of their tier-one vendors and their critical risks. A bare 2% reported that they had supplier visibility beyond tier 3 and beyond. As every stage of the supply chain is inter-connected and impacts the other, it’s essential to comprehend what pressing issues are occurring. Becton Dickinson, like most other companies, had many supply chain problems because of COVID. Around 80% of this global medical technology company’s disruptions were the result of problems in the n-tier supply base, not their Tier 1 suppliers.

Traditionally, it’s been challenging and time-consuming to identify who the N-tier vendors are as it constituted a manual process dependent on collaboration between upstream and downstream suppliers. Viewed with suspicion, upstream vendors were not comfortable with sharing data. Fortunately, technology has provided an efficient solution by combining large oceans of data, databases and AI.

Extreme weather will continue to plague supply chain efforts

Forty years ago, when scientists first warned of a possible climate catastrophe, it was a problem for the future. 2022 showed that that perilous future has arrived. Once rare, extreme weather incidents have now become a modern norm. Europe experienced record heat waves that burned forests and dried up rivers. Pakistan endured a similarly brutal heat wave that was followed by epic monsoons that left as much as one-third of the country under water. The U.S. southwest endured a record drought that shrank reservoirs like Lake Mead and diminished crops yields. These events, and more, are fueling the global supply chain challenge.

Technology will have to be at the forefront of all supply chain efforts, from the first mile to the last. We live in an era where companies can enjoy real time updates of their supply chain movements from literal eyes in the sky.

This same technology can also be used to plan supply chains routes, regardless of the route being by air, road or sea. This works by tracking global weather patterns and putting together forecasts with high levels of accuracy. To learn more, visit spire.com to discover how the company is reforming the way data is collected and utilized via its state-of-the-art satellites.

Wildfires burn 700,000 hectares of European land

High temperatures and dry weather conditions created the perfect environment for fires to blaze across France, Italy and Romania in August 2022. It was reported that 700,000 hectares of land, three times the size of Luxembourg or Azerbaijan, burnt uncontrollably amd worsened Europe’s energy dilemma as this lengthy drought reduced hydropower generation by almost a fifth across the entire continent. Nuclear plants were unable to function at complete capacity as rivers did not overheat by the cooling water released from the plants. Italian farmers reported losses over 60% as the drought had an adverse impact on crop production, especially on rice.

Record-breaking droughts prevail in the UK, the US and Asia

Central/Eastern China experienced droughts and record-breaking heat waves leading to water restrictions. This caused crop shortages that added to the rising costs of food around the world. Scorching heatwaves and drought plunged the southwestern Chinese province of Sichuan into an energy security crisis that relies on dams to generate approximately 80% of its electricity. In Italy, the former “King of Rivers”, known as the Po, is flowing at one tenth of its usual rate. These droughts and their significant impacts are forecasted to continue for the foreseeable future. 

Record-breaking heat has also been recorded in Japan, the central US and in the UK, where temperatures exceeded 40℃ for the first time. UK residents experienced such high temperatures which brought flights and the transport system to a standstill. This occurred only a few months after temperatures soared in the Indian sub-continent to 50°C ahead of the monsoon rains in northern India and Pakistan.

Storm Ana hits five African nations

The year had barely begun as a tropical storm formed in the Indian Ocean in the last week of January 2022 and began to move westwards towards Madagascar, eventually leaving destruction in its wake across 5 African countries. It caused rivers to overflow, landslides, floods and such that damaged public infrastructure such as healthcare facilities, roads and homes. Killing over 88 people across the affected African region, this extreme weather event was also attributed to heating waters with rising sea levels due to climate change.

Floods in Pakistan displace 33 million people

The latest in this sequence of extreme weather events is the unprecedented floods that have left one-third of Pakistan, the world’s sixth most populous nation under water. Pakistan contributes less than 1% of global greenhouse emissions that warm our planet but its geography makes it extremely vulnerable to climate change. The floods have been caused by a combination of heavy monsoon rains and melting glaciers.

Global warming is making air and sea temperatures rise, thus leading to further evaporation. Warmer air can hold more moisture that causes an increase in the intensity of monsoon rainfall. Pakistan recorded, in several bursts from mid-June to late August, a 500%-700% increase of its usual August rain. Pakistan also has something else making it more susceptible to climate change effects – its immense glaciers.

The country’s region is sometimes referred to as the ‘third pole’ – it contains more glacial ice than anywhere in the world outside of the polar regions. Glaciers located in the northern regions of Pakistan’s Gilgit-Baltistan and Khyber Pakhtunkhwa regions are melting rapidly and creating more than 3,000 lakes. Out of all these lakes, 33 lakes are at the risk of bursting suddenly. Now, if that happens, that will unleash millions of cubic meters of water and debris, putting 7 million people at risk.

Hurricane Ian causes second-largest insured loss on record

A category 4 Atlantic hurricane, Hurricane Ian, hit Florida and South Carolina earlier last year turned out to be the most expensive weather-related disaster within the USA in 2022 and became the second greatest insured loss after Hurricane Katrina in 2005.

Estimated to have caused havoc between $50-65 billion in insured damages, Hurricane Ian landed in the western region of Florida at the end of September 2022, bringing along with it high winds and severe downpour.

A report published stated that insurance losses from extreme weather events had  estimated damages of $115 billion, higher than the 10-year average of $81 billion. This number has been on the rise as extreme weather events become a frequent norm around the globe with climate change as the primary driver.

Extreme weather events are the watermark of climate change

According to a report by Centre for Science and Environment and Down To Earth magazine, India, the world’s third largest carbon emitter, recorded “extreme weather events on 241 of 273 days” in the first nine months of the year. Thunderstorms, persistent rains, cyclones, droughts, heat waves, lightning, floods and landslides ravaged India’s geography. Overall, these disasters claimed about “2,755 lives, affected 1.8 million hectares (ha) of crop area, destroyed over 416,667 houses and killed close to 70,000 livestock.” The CSE report describes these disasters as “the watermark of climate change.”

There was a string of largely unreported extreme weather events in Africa in 2022 as well. From deadly floods in Nigeria to devastating drought in Somalia, Africa has faced a run of severe – and sometimes unprecedented – extreme weather events since the start of 2022 which have resulted in over 4,000 deaths and affected a further 19 million people. Despite being the world’s second largest continent, Africa contributes only 4% of global carbon emissions combined.

Pakistan, the world’s sixth most populous country, with only 1.4% contribution to global carbon emissions, witnessed unprecedented extreme weather events. One-third of the nation was left under water following record monsoons and glacier melting due to high temperatures. The record flooding has killed over 1,500 people, destroyed a million homes and displaced 33 million people. With the latest damage estimates exceeding USD 30 billion that includes the destruction of essential crops, further disruption to the country’s economy and critical food production is inevitable.

The need to invest in accurate global weather data is greater than ever. Unfortunately, not all countries have the means to invest in robust weather observation infrastructure – which creates inconsistencies in the quality of observation collections. This is where space technology plays a critical  role in fulfilling this gap and companies such as Spire are able to provide high quality, reliable weather observations through its constellation of space satellites.

As the hustle and bustle to work begins, a young woman coughs into her mask as the smoke in the air triggers her asthma. She gets into her car and wonders whether the temperature will drop below 32 degrees Celsius.

Luckily, we’re just transitioning into 2023 and we still have a chance to paint a better picture of our future. To ensure that the world does not look like this due to climate change, companies like DeepSea are tapping into the power of artificial intelligence to help the maritime industry sail more sustainably with reduced carbon emissions.

Using the space frontier to drive maritime performance routing

“Weather routing is not something new. It has been done for 20 or 25 years,” says Symeon Chatzigeorgiou, Business Director at Deepsea Technologies. “We’re taking it to the next level by collecting and combining vessel behavior information and weather components to optimize data-driven decision making.”

He went on to share that the industry norm is to categorize the vessel under standard geometry rules or as an undefined object that simply seeks to avoid poor weather conditions. However, by collecting high frequency ship data for analysis and creating performance profile models that take into account engine data, fuel consumption data and more- Deepsea’s AI-powered algorithm is able to create a vessel-customized route and speed plan based on weather forecasts.

For instance, if a ship is enroute to its destination and faces a current – the natural response of a traditional weather routing system will be to route around it beyond a certain threshold, regardless of the actual effect of the current on the vessel – which is always different. This ‘one-size-fits all’ model of routing a vessel leads to significant inefficiencies. On the other hand, Deepsea’s technology accesses the vessel’s DNA and assesses its operating conditions. If it identifies that the ship has a clean hull, the recommendation may be to sail right through the current (as a ship with a clean hull will perform differently than one with a fouled hull under the same weather patterns).

But of course, all this intelligence is reliant on accurate data inputs – especially weather forecasts.

Adding the value of accurate maritime weather insights for environmental compliance

The foundation of an accurate weather forecast is based on the quality of weather observations input into it. Known as the initial starting conditions, this is a critical component. Our planet’s land mass is more than 510 million square kilometers, out of which, unfortunately, a massive chunk is unobserved. Developed countries tend to own the resources that can be allocated to researching, producing and launching the biggest satellites into space. It’s only natural that they will choose to direct the coverage focus within their own topographical districts and not incorporate other parts of the globe, hence leading to inconsistent weather monitoring.

On top of that, tapping into a pool of reliable ocean weather observations is also a complicated process. The surface area of all oceans is 140 million square miles and the majority of it is too remote for wide-band communications. Other elements also interfere in the transmission process such as storms, saltwater and breaking waves. As we’re not able to access each and every point of the high seas, it becomes hard to accumulate a sufficient level of data to create accurate weather forecasts.

Over 71% of the Earth’s surface is covered in water and out of that, 80% is unobserved, unmapped and unexplored. This is why Deepsea is partnering with space entities such as Spire, which has eyes that monitor even the most under-observed regions. This includes but is not limited to appraising the oceans to the expanse of the Southern Hemisphere plus other remote territories. This way, we’re able to fill many of the gaps in the accumulation of weather observation data and generate reliable global weather forecasts that will open a whole new world of cost predictability between departure and destination points.

The value of data in the fight against climate change

Climate change – and the response of governments at home and abroad to it – will affect businesses financially, both over shorter horizons and the longer term. Since it influences key economic variables such as output and inflation, climate change matters.

This means that climate change is everybody’s business. While government delegates from around the world meet at COP27 to deliberate on how the world can slow climate change, the private sector has a role to play too. The need for new ideas has never been higher. Old formulas need to be rethought.

Developing a culture of innovation at the governmental and business level is required. By recognizing that managing the impact of climate change and its financial costs is a shared responsibility, countries and businesses can come together to present unified solutions based on innovative thought and data-sharing.

Making wise, data-driven, and scientifically sound decisions is the only viable course. It will depend on collecting granular data on a global scale to build an information matrix that can be plugged into computer-aided analysis, machine learning, and artificial intelligence solutions. This is where companies such as Spire, come into the picture to cater to this urgent, growing need for global, accurate data. Such processes will bring a myriad of practical and theoretical methodologies that can alleviate the climate change impacts that cannot be avoided while concurrently dialing back dire risks that are now in the realm of the possible. This may sound difficult, but there are tech companies dedicated to the collection and dissemination of weather data.

Studies show fiscal gain in sustainable business practices

To incentivize private companies’ governments and specialist companies to work more collaboratively together in this arena, especially for nations that don’t have the capacity, governments can formulate economic policies to set up offices so as to kickstart the economy, provide more jobs etc and build their financial position.

The private sector also needs to be more serious about climate change and its impact on business. The pursuit of short-term gains tends to make the people at the top disregard the danger.

A recent study by Ernst & Young New challenges earlier arguments that there is a trade-off between financial and non-financial impacts of climate change investments. As per the study, comprehensive transformational approaches to sustainability return more value — financial, customer, employee, societal and planetary — than companies anticipate.

This challenges the perception that there is a trade-off between financial and nonfinancial impact. To the contrary, for a subset of “pacesetter” companies taking the boldest steps, comprehensive climate action helped boost customer value (such as brand perception and purchasing behavior) as well as employee value (such as staff recruitment and retention), which in turn led to improved financial value. These pacesetters are 2.4 times more likely than companies taking few climate actions (observers) to report significantly higher-than-expected financial value as a result of their climate initiatives. They’ve also achieved higher emissions reductions to-date.

By putting climate action at the heart of business strategy, value is delivered across a range of vital measures. The sooner companies get started, the more they learn and the more value they receive.

He shared that Gale Force’s technology is built on the system source code and performance engine developed over the past decades by the Swedish Meteorological and Hydrological Institute SMHI and has been further refined by Gale Force.

Love for the ocean

Having spent warm summers and weekends on the edge of his family boat, gazing at pink-hued sunset streaked skies, Tom literally grew up on the water. He had an uncle that worked on the wheat trade on sail ships between Europe and Australia and would enthral young Tom with his tales of the high seas. Tom’s love for the ocean grew with every story that he heard as did his passion to protect them. Knowing from the age of five, Tom knew that he would live his life as a Master Mariner.

And that’s exactly how his career unfolded after.

Working his way up from small archipelago passenger ships in Stockholm, attending seamen’s school to retaining his Master Mariner’s graduate at the age of 23 as well as his unlimited license at 25, Tom decided to dip his toes into other spheres of the maritime industry. With a career spanning over 35 years’ that delved into fleet/vessel operations, hub & port agency, business development, sales, weather routing and vessel navigation, Tom has a strong grasp of all maritime disciplines and that is what inspired him to launch Gale Force.

Routing through safe, fuel-efficient passages

There are 940 million tonnes of CO2 annually that constitutes 2.5% of the world’s total CO2 emissions.

Gale Force’s technology is contributing to significant bunker costs and savings through its intelligence platform and increasing the parameters of safety across cargo, crew and vessel. Applying different performance models and digital twins based on the type of vessel, Gale Force’s platform will deliver an eco-friendly safe route along with the predicted time of arrival.

Weather data is a key ingredient in identifying such maritime pathways not only from a safety point of view but also to identify when and where to utilize the force of the current in the ship’s favour to consume less fuel. That’ll ensure a minimal cost impact on the subsequent stages of the supply chain and allow the next round of stakeholders to plan and allocate their resources accordingly.

“Gale Force’s strength comes from its powerhouse combination of internal marine expertise and its robust maritime technology. Partnering with experts in nearby domains such as Spire only enhances our competitive ability to steer the maritime industry towards sustainability,” says Tom.

Tom shares that so far they have helped the maritime industry to save 500,000 metric tons of C02 annually. Avoiding coral damages, vessel breakdowns, cargo loss and such will also reduce the pollution in the sea and keep expenses for all players above the surface.

Digitization of the maritime sector is an important element in the fight against climate change and with time, Gale Force hopes that its technology will grow smarter and truly help shipping companies achieve the Paris Agreement 2015 goals of reducing greenhouse gas emissions.

World GDP to shrink by 18% if temperatures rise by 3.2°C

As per an ongoing temperature analysis led by scientists at NASA’s Goddard Institute for Space Studies (GISS), the world has witnessed a rise in global average temperature by at least  1.1° Celsius (2° Fahrenheit). The bulk of these temperature increments have occured since 1975 at a rate of roughly 0.15 to 0.20°C per decade. Climate change is not just changing the fabric of our atmosphere but is threatening our way of life. The Swiss RE reported that the world’s GDP could diminish by 18% if global average temperatures increase by 3.2°C. Rising temperatures and sea levels are causing extreme weather events such as wildfires, droughts, floods, storms et cetera to occur more frequently.

Different parts of the world are already suffering from the repercussions of climate change. Western Europe and Central/Eastern China experienced droughts and record-breaking heat waves leading to water restrictions. This has caused crop shortages, adding to the rising costs of food around the world. Throw in an energy security crisis within the southwestern Chinese province of Sichuan that relies on dams to generate approximately 80% of its electricity. Italy’s longest river is flowing at one tenth of its usual rate. These droughts and their significant impacts are forecast to continue for the foreseeable future. Severe downpours have caused floods in Dallas, Texas (USA) and Seoul, South Korea, which experienced its heaviest torrential rain in a century.

Record-breaking heat has also been recorded in Japan, the central US and in the UK, where temperatures exceed 40℃ for the first time. It has also only been a few months since we saw temperatures reach 50°C ahead of the monsoon rains in northern India and Pakistan.

To understand the context, it’s important to know that in 1750, there were 280 parts per million of carbon dioxide in the air. To date, it’s 421 ppm in the atmosphere. Since then, we’ve emitted over 1.5 trillion tons of CO2. When released, CO2 lingers around for a very long time: between 300 to 1000 years. Therefore, the action we take today based on weather forecasts to reduce carbon emissions will impact generations to come.

One-third of Pakistan is under water

The latest in this sequence of extreme weather events is the unprecedented floods that have left one-third of Pakistan, the world’s sixth most populous nation, under water. Pakistan contributes less than 1% of global greenhouse emissions that warm our planet but its geography makes it extremely vulnerable to climate change. The recent floods have been caused by a combination of heavy monsoon rains and melting glaciers.

While Pakistan is no stranger to flooding, the impact of these recent floods is beyond what the country has dealt with before. Over 1,300eople have died, a million homes are destroyed and 33 million people have been displaced. With the latest damage estimates exceeding USD 12.5 billion that includes the destruction of essential crops, further disruption to the country’s economy and critical food production is inevitable.

It is predicted that inflation is projected to go up to the range of 24% to 27%  and will touch 30% for the current fiscal year as per the country’s largest news channel). Moreover, poverty and unemployment are expected to increase from 21.9% to over 36%. Some 37% of the population was hit by poverty after floods in 118 districts, as estimated by the Pakistan government.

With the clear economic and human impact of these floods, it beckons the question: why did this happen? Is it Pakistan’s unique geographical structure?

“The floods in Pakistan are driven by unusually heavy and persistent monsoonal rains. A group of international scientists from World Weather Attribution are currently investigating whether this ‘monster monsoon’ can be linked directly to climate change. However, the intensification of the water cycle is something to be expected due to climate change,” explains Gerald van der Grijn,  Meteorologist and Technical Customer Success Leader at Spire Weather.

He goes on to further explain that on a global scale, climate change causes increased evaporation. In addition, a warmer atmosphere can contain more water vapour. As a result, the probability for intense precipitation and subsequent flooding is increased. Some regions in the world are expected to become on average dryer, other regions to become wetter. Pakistan is located in a region where the probability of extreme precipitation is expected to increase due to a warming climate.

Melting glaciers put 7 million at risk

Global warming is making air and sea temperatures rise, thus leading to further evaporation. Warmer air can hold more moisture that causes an increase in the intensity of monsoon rainfall. Pakistan recorded, in several bursts from mid-June to late August, a 500%-700% increase of its usual August rain. Pakistan also has something else making it more susceptible to climate change effects – its immense glaciers.

The country’s region is sometimes referred to as the ‘third pole’ – it contains more glacial ice than anywhere in the world outside of the polar regions. Glaciers located in the northern regions of Pakistan’s Gilgit-Baltistan and Khyber Pakhtunkhwa regions are melting rapidly and creating more than 3,000 lakes. Out of all these lakes, 33 lakes are at the risk of bursting suddenly. Now, if that happens, that will unleash millions of cubic meters of water and debris, putting 7 million people at risk.

If you’d like to further understand the connection between weather and its role in climate change, download our white paper here and unlock new insights that could help us all build a better, cleaner and greener planet.

To ensure that other parts of the world do not witness life-threatening floods on the scale that Pakistan has, it’s imperative that the world comes together to do its bit to build more sustainable global business practices and renew its commitment to reducing greenhouse gas emissions. This is why we at Spire are dedicated to equipping strategic international verticals with accurate, reliable weather datasets to help them make informed, optimal decisions. This way they can anticipate what is to come and how to safeguard their assets, their infrastructure and their surrounding communities.

Why is it essential to track marine debris?

All this accumulated debris swimming is harming marine wildlife. To put this into context, it’s estimated that fish consume an estimated 12000-14000 tons of plastic annually that’s causing intestinal injury and death. In the end, it’s a vicious food chain as it comes back to us only. A study from the University of California, Davis discovered that more than 25% of fish sold at markets contained plastic debris in their guts.

It’s not just fish that is being impacted by the plastic pollution crisis- seabirds are susceptible to this danger as well. As they eat plastic, it takes up storage space in their stomachs and causes them to starve. By 2050, it’s predicted that 99% of all seabirds will have consumed pieces of plastic as compared to the current 60%. Sea turtles consider floating pieces of plastic to be food and eat it. This causes them to either choke, suffer internal injuries or die from starvation. Marine mammals are not safe from this either.

With over 267 species affected globally, that spans 44% of seabirds, 43% of all marine mammals and 86% of seabird species, it’s imperative that marine debris be tracked so as to understand the impact on sea life. The Japanese coast witnessed a ten fold increase in the volume of pelagic plastic particles between the 1970-80s. This is also the time when international production of plastic fibers shot up by four times. Autopsies conducted on the body of a washed up California gray whale on the shores of the Puget Sound revealed more than 20 plastic bags, a golf ball, surgical gloves and even a pair of pants.

This is why like-minded space enterprises such as Amanogi Space and Spire Global are coming together to address this very challenge: tracking marine debris along the Japanese coast (to start with).

Harnessing the power of space technology

Amanogi Space, a leading Japanese entity, is developing solutions for the collection and analysis of satellite imagery by using methodologies such as machine learning and artificial intelligence to detect marine debris and hope to help clean up our oceans.

Spire Global, as you may know, has the largest constellation of nanosatellites in close orbit to Earth that collects atmospheric data 24/7 for all points across the globe. Partnering with Spire, Amanogi has utilized Spire’s historical weather data to train its simulation algorithm so as to improve its accuracy level in forecasting the flow of marine debris.

Challenge

Amanogi Space aims to identify a statistical correlation between the movement of marine debris against the ocean currents around the Japanese coastline. To achieve this, Amanogi Space required historical weather data to simulate local debris advection to compare against global models generated from satellite-based imagery.

Solution

Spire’s comprehensive historical weather datasets powered Amanogi’s predictive analytics to understand how ocean currents influence the direction of debris.

To test its hypothesis, Amanogi Space will incorporate Spire’s historical weather data to train its AI model so as to enhance its capability to analyze and predict debris advection.

Testing Methodology

Spire Weather wave height data: the validation benchmark

Amanogi is aiming to use wave height data for interpreting the global ocean current situation. They are currently in the process of analyzing other datasets to validate this theory.

Ocean significant wave height distribution chart

Preliminary Results

Amanogi Space is developing the technology to detect the coastlines that are contaminated by debris via satellite imagery. Having achieved 87% accuracy levels in their prediction models, Amanogi Space (as shown in the images below where the red dots signify the debris-filled areas) hopes to utilize Spire’s historical weather data to train their algorithm to attain higher quality results in terms of accuracy and granularity.

The red represents debris that was detected whilst the blue represents the undetected portion of the debris.

The way forward

Amanogi will be using Spire Weather Data to continually train their marine debris algorithm and improve its accuracy in forecasting the direction that debris will flow. The end vision here is to discover the correlation between debris advection and ocean currents. Once this is identified, Amanogi will further train its AI-powered models with satellite images. Amanogi hopes to take this on to a global scale and help countries predict where marine debris may wash up so they can take action beforehand and optimize costs accordingly.

Sinay gathers massive volumes of data from eclectic sources such as vessel position, weather, currents, wildlife, and much more. This includes Spire’s historical and real-time automatic identification system (AIS) data. Inputting Sinay’s AI-powered algorithms is helping to generate more accurate ETAS, efficient maritime routes, and reduce overall risks.

Sinay is now looking at integrating Spire’s maritime weather insights for cargo tracking by modeling weather conditions and ETA’s that employ machine learning to define optimal routes for cargo delivery. “One of the most critical aspects, when you are out on the sea, is what kind of weather will I encounter? How can I deal with it? How can I adapt my ship, my cargo, and my route to minimize the impact of weather?” says David.

Weather is an essential component for any maritime business to consider when planning such operations. Spire provides a complete portfolio that delivers highly accurate and reliable weather data that can be leveraged for trusted decision making.

Adding value to the maritime world

When asked what sets Sinay apart from other digital maritime companies, David says, “You find quite a lot of companies which are aiming at monitoring, improving, predicting environmental impacts of various maritime activities, and I think that’s quite unique. What you may not find is a business that wants to combine both and offer a 360-degree, correlated view on all those aspects.”

Partnering with Spire, Sinay is enjoying increased visibility across the maritime operational spectrum and has access to real-time insights into the ocean world. In addition, Spire’s historical AIS data is used to maintain and improve Sinay’s AI and machine learning models.

Using all this data, Sinay is able to provide its customers with a truly holistic view of the open seas that includes but is not limited to air quality, water quality, noise, ETA, route planning, and fuel efficiency.

Working together, Sinay and Spire are tapping into the magic of big data and steering the maritime world towards sustainability. As the industry slowly moves towards digitization, David is confident that more and more companies are realizing the importance of technology in enhancing safety and decarbonization efforts.

“We see this changing happening now almost on a day-to-day basis and our goal, role, and ambition is really to help them to materialize this transformation,” he says.

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Predicting Wildfires and Protecting Firefighters

Spire’s weather data supports critical wildfire management from long-term planning to immediate tactical responses. With weather data and forecast models, firefighting can begin before flames turn into runaway forest fires. Our customer Quiron Digital is showing success at wildfire prediction using weather data collected by Spire’s constellation of 100+ satellites. Historical weather data helped train Quiron’s wildfire models and Spire’s forecasts feed the ongoing predictions, leading to a 30% increase in accuracy of fire risk zoning.

As the threat grows with climate change, solutions that help protect firefighters and communities are more critical than ever – especially tools that help stop fires before they turn into life-threatening events.

Monitoring Our Oceans For Illegal Fishing

Today, nearly three million fishing vessels operate across the seas, with 60,000 commercial vessels broadcasting communication signals known as Automatic Identification Signals (AIS). Tracking this fleet outside the range of terrestrial receivers is spotty and infrequent. Our customer, Global Fishing Watch is applying advanced data analytics and machine learning capabilities to Spire’s AIS tracking data to promote ocean sustainability and expose illegal, unreported, and unregulated fishing.

Data increases transparency of human activity at sea to promote fair and sustainable use of our ocean. Spire’s satellites provide continuous monitoring of vessels across the globe, illuminating activity in the most remote points of the ocean. With this level of insight, operators and regulators can enhance their actions with data-based decisions that support food security and human health.

Sea Ice Seen from Space

Declining levels of sea ice are an unmistakable sign of climate change’s impact on our planet. Record low levels of sea ice are leading to warming temperatures which affect sea level rise, ocean circulation, and weather patterns. As climate related opportunities and challenges arise in the Arctic and Antarctic regions, abundant and accurate insights on sea ice, sea surface temperatures, and weather patterns are critical.

Over 65% of Spire’s satellites are in polar orbit, meaning they have high revisit rates in the polar region and provide more accurate weather and climate insights. With data observations including sea ice age, extent and height, and weather forecasts for temperature, wind and other ocean variables, Spire is able to greatly enhance Arctic and Antarctic weather forecasts.

No matter what the mode of transport is, it’s the “last mile” that determines the final leg of the journey of the goods in question. It’s imperative that the last mile be flexible as it influences customer experience and satisfaction.

Trade is one of the oldest professions in the world and can be traced back to ancient civilizations such as the Greeks, the Romans and the Indus. From the time when the Silk Route connected the East to the West – where spices, perfumes, silk cloth and much more were exchanged – to the present day, trade blurs national boundaries and connects people with similar interests. However, while we live in a period where access to convenience and luxury is abundant, we also have to understand the challenges that come with it.

What are the threats to supply chain security?

The COVID-19 pandemic and its adverse impact on international economies, businesses, and communities has tested the resiliency of mankind. Sprinkle in climate change and several geopolitical events and it is clear just how imperative it is for organizations to strategically plan their operations in a manner that can effectively anticipate disruptions and make necessary adjustments to keep the supply chain engine running smoothly.

1. Sociopolitical forces

International relations influence foreign, trade, and economic policies. Consider an on-going example: the current war in Ukraine. Since Russia invaded Ukraine, there has been a direct negative effect on the global food network. Ukraine is the number three exporter of wheat and number four for grain. On February 24, 2022 Ukraine’s military suspended commercial shipping at its ports to protect the local food supply, which caused prices to rise globally. Grain is one of the most essential yet underrated commodities in the world. It’s critical to ensure that grain shipment deadlines are met, but the impact of port slowdowns on global supply chains extends even further. Vessel charter agreements specify an allotted time for loading and unloading and if rain isn’t taken into account during negotiations, then it can quickly affect the charterer’s bottom line. Even vessels carrying other commodities that are stuck at anchorage while berthed cargo ships wait to discharge or load grain can mean the difference between a successful voyage and a delayed one.

It’s not just grain exports that are impacted by this particular crisis. The international community has slammed sanctions on Russia and this has exposed vulnerabilities in the global supply of oil. It’s important to note that Russia is the largest oil exporter in the world. The International Energy Agency warned that over 3 million barrels of oil per day could be cut off from global oil markets, resulting in one of the biggest supply shortfalls since the 1970s. Spire’s AIS data reflected a declining number of Russian vessels moving through the Bosphorus strait (the only warm water exit point to the Mediterranean Sea from Russia) in March 2022 as a result.

Sample vessel positions by the Bosphorus

Then there’s the USA-China trade tensions to consider. In 2018-19, America increased Chinese import tariffs, primarily on metals and machinery. China counter-acted by not only adding tariffs on American goods but also lowering tariffs on imports from other nations. These moves were in stark contrast to the tariff liberalization taking place at the time across the globe. Interestingly, China’s exports to America fell by 8.5% but rose to the rest of the world by 5.5%. US exports to the Chinese economy fell by 26.3% but only increased by a modest 2.2% to other countries. With import and export flows being increased and reallocated, world trade rose by 3%.

2. Pandemic

Even as the world slowly trickles back to a semblance of pre-pandemic life, we still experience the impact of a stressed international trade network. Ships continue to remain on standby for berth space off the coast of Los Angeles. It was recently reported that approximately 101 ships are anchored 150 miles away from the shoreline as per the new regulations enforced by the busy Southern California port. A similar pattern resonates half-way across the world at the Port of Shanghai, one of the busiest hubs in the trading sphere. Due to a strict lockdown, about 300 sea-faring vessels are waiting to load or discharge. It also shut down in September 2021 due to Typhoon Chanthu – a by-product of the warming climate. Recently, a rise in COVID cases also had China place Shenzhen, its local tech hub, under lockdown. Home to the world’s third largest port that receives a majority of China’s electronic goods, Spire’s AIS data reflected a sharp fall in vessel traffic within the Yantian port due to the lockdown.

Daily count of unique vessels detected

Even when COVID-19 sent the world into its first lockdown back in early 2020 and grounded airline fleets, there became a dearth of weather data. Our satellites continued to encircle in space and perform their job, providing crucial weather data.

You’ll very well remember how in early 2020 the pandemic grounded airplanes all over the world. While air passenger traffic has suffered losses worth $200 billion up to March 2022, freight forwarders and air cargo subsectors enjoyed an upsurge in revenue. Air cargo carriers earned a 9% profit while freight forwarders gained 4%. This can be attributed to the expedited need for personal protective equipment, masks, and medicine.

3. Climate change and weather impact on the entire supply chain (air, sea, land)

It’s not just ports that can cause delays in subsequent stages of the supply network. Near the end of 2020, the Apus One embarked on its journey from China to Long Beach, California and lost almost 2,000 containers due to gale force winds and massive ocean swells. This took place 1,600 nautical miles northwest of Hawaii and incurred losses of approximately $200 million. In 2020 alone, approximately 3,000 containers fell overboard. Whilst shipping companies and their crews do their best to secure their cargo, poor weather conditions and waves may flood vessels causing damage to cargo items or even submerging them into watery depths.

In spring 2021, the world watched as the mighty 200,000 metric-ton vessel Evergreen was run aground due to strong gusts of wind and blocked the strategic Suez Canal waterway for almost a week. The grounded vessel was blocking trade worth $9.6 billion a day. Spire forecasted these weather conditions the day before the collision. Spire’s weather forecast issued at 00:00 UTC on March 22nd predicted wind gusts at speeds of 13 meters per second (30 miles per hour) and above. Knowing about these kinds of hazardous conditions by having access to accurate, reliable weather forecasts in advance could potentially mitigate such costly delays.

This WMS visualization illustrates 48 hours of wind activity in the Suez Canal region, from March 22nd (00:00 UTC) until March 24th (00:00 UTC). The speeds are measured in meters per second.

Let’s anchor sea-faring trade stories for a moment and venture on-shore.

Last November, the Canadian province of British Columbia experienced major rainfall that caused mudslides and floods and blocked strategic road routes that linked to the nation’s largest port. Canadian exports constitute one-third of the country’s GDP and journey through the Pacific Ocean to reach Asian markets. However, due to Canada’s topography, only two rail lines and a few highways have been carved through the Rocky Mountains and jagged British Columbian land to get to the Port of Vancouver. Hence, such disturbances choke up the entire supply chain. Earlier in the summer, the local town of Lytton was destroyed by wildfires that spread to the railways, disrupting the export of lumber distribution to key markets. This pushed up international prices as there was a dearth in supply and negatively impacted the American economy as it depends on over a quarter of its lumber demand to be fulfilled by its northern neighbor.

Scientists predict that the repercussions on the international supply chain caused by climate change will only amplify in the coming years. The entire supply chain infrastructure will be subject to threat from extreme weather events due to sea levels rising by two to six feet.

Hurricane Ida, one of the most intense storms to ever hit the USA, wreaked havoc across Louisiana in August 2021, leaving many without power for the next 30 days or more. It took 50 lives and cost $65 billion in damages. The question that arises is: to what extent could we have minimized these consequences if we’d known that such a powerful natural disaster is coming? Take a look at Spire’s weather data to track activity around offshore supply vessels and see how they prepared and reacted to storm warnings in the region.

The visualization above compares the tracking of strong low pressure systems in the Spire Weather and two other popular weather forecast models, compared with the actual hurricane track data from the National Hurricane Center (NHC) to show the accuracy of the three models (using 6 day forecasts from all 3 models).

Below is the Spire Weather’s track and model-derived reflectivity of the hurricane.

When you club Hurricane Ida, Texas ice, British Columbia floods, American tornadoes, Australian wildfires, and typhoons at Chinese ports together – you’ll understand the magnitude of the challenge that supply chain managers are facing today.

If you’d like to understand more why port authorities need the right data at the right time, download our port weather forecasts webinar now and see for yourself!

View webinar

In GRAVITY Challenge 03, which ran from March to December of 2021, three different teams of innovators won their respective challenges with the help of Spire’s data and technical insights. While all of the participating groups deserve recognition for their brilliant contributions, Spire would like to specifically recognize these three winners. Below are details on these innovations as described by their creators:

Frazer-Nash Consultancy

Gravity Challenge:

The challenge was to help the Australian electricity transmission company ElectraNet by accurately detecting electricity line sag to ensure public and environment safety and enable greater renewable energy output.

The Solution using Spire’s Data:

Frazer-Nash Consultancy has developed a new way for South Australia’s electricity transmission network operator, ElectraNet, to accurately predict transmission line-sag to ensure better public safety and enable greater efficiencies across the network. Known as PowerMET (Prediction  Optimisation for Weather Effects on Ratings Monitoring & Evaluation Tool), it estimates the local weather conditions along line corridors to maximize line capacity and more accurately determine  the network’s operational risk profile.

By combining space-derived meteorological data provided by Spire Weather and local topography modeling, an accurate microclimatic model predicts temperature, wind speed and wind direction.  This hyper-local data can be used to more accurately determine the line temperature and allowable current in each span of the transmission line, and hence the allowable current for the entire line.

ElectraNet owns and operates more than 5,600km of transmission lines in South Australia and this innovative micro-climate modeling tool is positioning them as industry leaders in network optimization in decarbonization with advanced modeling.

This digital innovation initiative is a catalyst for many other trusted digital solutions in renewable energy and wildfire mitigation with space data.

About Frazer-Nash:

Frazer-Nash is a leading systems, engineering and technology company. We help organizations deliver innovative engineering and technology solutions to make lives safe, secure, sustainable, and affordable. Read more.

Tenchijin, Inc.

Gravity Challenge:

The challenge was to help improve crop health by reducing soil degradation while also addressing the challenge of carbon sequestration.

The Solution using Spire’s Data:

Soil degradation is an increasingly important issue worldwide because of adverse climate change effects. Consequently, yield and revenues plummet while prices skyrocket. Tenchijin is contributing to soil health enhancement through intercropping by designing Carbon-Health, an A.I powered solution. Carbon-Health analyzes satellite data and recommends growing the companion crop that has the highest carbon sequestration potential and synergy with the existing orchard. The platform matches the growth condition of the crops (temperature, soil, humidity) with the Bx orchard environment (temperature, rain, solar irradiance, soil moisture).

In this respect, Spire Weather‘s data is of paramount importance as they are instrumental in enabling Tenchijin to deliver reliable, granular and accurate insights and metrics to Bx. With the intuitive Carbon-Health solution, agribusinesses can quickly visualize their land’s key performance indicators and enhance their income through carbon-driven ancillary revenues. Ultimately, mankind will live in a healthier environment and have access to healthier food at a fair price as purchasing power increases.

About Tenchijin:

Tenchijin, Inc. is a start-up company that utilizes big data captured in space to revolutionize land assessment and provide a fuller evaluation of land. We develop business solutions using high-precision, high-resolution earth observation satellite data and our proprietary land evaluation engine. We are recognized as a JAXA (Japan Aerospace Exploration Agency) STARTUP that conducts projects using JAXA’s intellectual property and knowledge. Our company was also established by JAXA staff and developers with expertise in the agricultural IoT field. Read more.

Helyx SIS Ltd.

Gravity Challenge:

The challenge was to deconflict cetacean (whale and dolphin) distribution with vessel traffic to alleviate ship strikes.

The Solution using Spire’s Data:

Helyx developed a flexible, customisable workflow to create hazard and vulnerability zones around the world, to assist in deconfliction through shipping regulations and awareness of the issues.

We utilized Spire Maritime‘s AIS data in the first phase of the challenge. It provided a useful granular record of vessel tracks in our areas of interest. We were able to easily filter the records by vessel size and speed, which are known to be directly linked to the risk of vessel strikes. The data provides a risk layer in our model that assists those in the maritime community to know which areas are most pressured over time. We combine this with our vulnerability models to provide a comprehensive view.

About Helyx:

Helyx is a professional services company specializing in the provision of information management, exploitation, assurance, and geospatial information systems services and solutions. We provide access to a wealth of expertise to facilitate informed decision making. Our range of services encompass technical consultancy services and solutions, remote sensing, data analytics, training design, development and delivery, to name but a few disciplines, and we are at the forefront of a number of innovative research and development programmes. Read more.

Spire is happy to continue supporting the Deloitte Gravity Challenge in 2022

From this number, 289 ports would be at a relatively higher risk to exposure. This can include overflooding of docks, on-loading & off-loading operations and rising temperatures.

It’s more imperative than ever for the maritime industry to have access to timely, reliable weather insights for effective ship arrival/departure schedules, cargo transfers, and labour and equipment planning. Fortunately, location-specific weather forecasts can aid ports to plan for a better future. If you’d like to understand how weather forecasts for ports can facilitate operations, have a read here.

Not all weather forecasts are created equal

The truth is that an immense chunk of the Earth is unobserved and causes gaps and uncertainties in the art of weather forecasting. Whilst specific parts of the globe can generate a consistent, authentic supply of weather observation data, other regions may not be able to match the same level of high quality and coverage.

Another barrier that the forecasting community faces is gaining verified ocean weather insights. The surface area of all oceans is 140 million square miles and the majority of it is too remote for wide-band communications. Other elements also interfere in the transmission process such as storms, saltwater and breaking waves. As we’re not able to access each and every point of the high seas, it becomes hard to accumulate a sufficient level of data to create accurate weather forecasts. It’s not just challenging to aggregate accurate weather observation data at the ground or ocean level – the atmosphere itself creates obstacles.

Now, it is clear that errors in weather forecasting occur as we don’t know what every small molecule in the atmosphere is up to. The truth is, even if we did, we don’t have the capacity to craft a complete digital twin of our entire planet. Not all is grey and gloomy. The good news is that now mankind has been able to reach the seven skies and has eyes from the best vantage point: from space.

Spire’s Port Optimised Forecast

Dedicated to facilitating the maritime industry to face the complex challenges of the modern world, constant innovation lies at the heart of Spire’s business model. As of January 2022, Spire Global has 150 satellites in orbit that are collecting millions of messages per day. As a one-stop weather and maritime insight hub, Spire will continue to provide more data and insights to provide more accurate and actionable weather forecasts for the maritime industry. Spire launched its Port Optimised Forecast that can help ports remain profitable despite the climatic events occurring.

The Port Optimized Forecast delivers data beyond air temperature readings and includes dew point temperature, relative humidity, 24-hour minimum, and maximum temperature, precipitation probability, surface wind speed and direction, surface visibility, cloud coverage percentage, ice and thunderstorm probability, and more. It’s truly comprehensive data focused on a specific area, so you have all of the weather variables to make data-driven decisions you can count on.

Spire’s Port Optimised Forecast can support port authorities in managing vessel traffic during poor weather conditions such as strong winds, swells and currents. Depending on the exact location, characteristics and business model of the port of interest, Spire’s port solution will facilitate operational scheduling and maintenance downtime as it’ll provide up-to-date regional weather insights. The maritime industry can allocate its resources more effectively to manage ETAS, enable smooth cargo loading/off-loading operations and keep all stakeholders safe.

How can a balance between on-time delivery, safety and fuel consumption be achieved?

Facilitates network and voyage planning

We live in a complex atmosphere where the only constant is its change and flux. The world is still struggling to comprehend the mysterious forces that influence weather patterns and related events. The smallest change can cause a ripple effect that may echo from one point of the globe to the other. This is one of the reasons why weather forecasts after ten days can be unreliable and cannot serve as a guide for your network planning efforts beyond this time period.

Historical weather data

The network planning team studies historical weather data to identify any potential underlying weather abnormalities in regions that have a high risk sailing factor. This is dependent on the season as well. For instance, the weather in the North Atlantic differs based on whether it’s summer or winter. If the wave is in favour of pushing your vessel towards your targeted location, then you’ll utilise less fuel and effectively reduce your carbon footprint.

Achieves a balance

Container ships sell the promise to deliver precious goods on time. Now, to be true to their brand message, container shipping lines need to calculate the right sailing speed and route.

Their biggest expense is fuel consumption and can range from $50,000 – $200,000 per vessel per day. When added across a fleet of seafaring vehicles, the number can escalate into a mind-boggling, massive figure. Historical weather data can assist in cracking this puzzle and unveiling optimal velocities along with favourable destination paths.

It’s important to note that the way you choose to apply historical weather data will also matter. The shipping sphere has seen an increase in the number of containers lost at sea. In 2020, the One-Apus, a 14000 TEU ship, sailed up the Japanese Kuroshio current and upon entrance into the Pacific, ventured close to a developing depression. This toppled the massive vessel and sent over 1800 containers sinking to the bottom of the sea and fiscally translated into losses worth $200 million.

Minimise global supply chain disruptions

Recent global port bottlenecks have only worsened with ports having to close down in Southern China, such as in Yantian & Hong Kong, due to a cyclone, dubbed Kompasu.This is the second major storm to interrupt port operations in southern China in the last month.

In mid-September, Typhoon Chanthu impacted the world’s busiest container port, Shanghai, as well as the Ningbo port complex. Although the storm did not make a direct impact on Shanghai, the port along with others in the region and the airports were all closed. This caused upheaval in the subsequent supply chain as delays in arrivals meant postponing off-loading, cost differentials for freight transport, warehouse storage and store deliveries along with more.

Reflecting back in time on such sites to comprehend if there are related atmospheric triggers or, is there a seasonality to it can help container ships make decisions in advance to ensure cargo, passenger and ship safety. Analysing historical weather data along a route of waypoints, i.e., high risk trajectories, will pave the way for fuel optimisation as well as reducing carbon emissions.

Paints the truth

Unfortunately, like the rest of the world, the shipping industry is prone to conflict. Maritime insurance service providers can use historical weather data to understand if extreme weather related events impacted a ship disaster or what truly led to it. They can also use it to define their products by assigning premiums on high-risk regions where hurricanes occur or wave heights can thrash cargo and send it into the deepest depths of the sea.

Trains AI and weather models

As a spin-off from Maersk Tankers and a leader in its industry, ZeroNorth is paving the way to provide real-time weather voyage optimisation and aims to deliver a reliable, transparent solution straight to your fingertips. Spire’s maritime historical weather data contributes to the benefit customers can gain from ZeroNorth’s routed voyages helping them get from A to B more optimally.

Companies such as ZeroNorth are tapping into the power of historical weather data to train their fuel optimisation and voyage routing softwares to deliver more accurate results and help the maritime industry to become more sustainable through diminished carbon emissions.

It’s simple: the more data points you collect, the more equipped you are to understand the forthcoming potential impact of weather on your business.

However, with meshing infinite, eclectic sources of data into weather models and algorithms can be an exhausting, time-consuming exercise. Why, you may ask? Data gathered across the entire planet may be inconsistent in quality and be delivered in differing layouts.

To allow you to focus your energy on your business, Spire steps in to provide unique, rich historical weather datasets that have been through the process of data assimilation and run through machine learning algorithms to increase accuracy. The accuracy of our data is enhanced as we collect data from across all corners of the Earth and reduce the gap of low quality in weather data as we have eyes right in the heavens. With one of the world’s largest nanosatellite constellations in orbit, we’re able to collect observations from the most under-observed regions- including the open oceans.

Even if we stop draining peatlands, it looks as if a warming climate will continue to threaten bogs and accelerate emissions. Scientists at the Oak Ridge National Laboratory found that warmer and drier conditions could change bogs from carbon sinks into carbon emitters. The researcher enclosed several peatland plots in northern Minnesota and exposed the ecosystems to a range of temperatures and carbon dioxide levels higher than current averages. After three years, the scientists found that the peatlands lost carbon about five to 18 times faster than rates of accumulation.

“Urgent action worldwide is required to protect, sustainably manage and restore peatlands,” the IUCN wrote.

In Scotland, restoration projects are already underway. Since 2012, Peatland ACTION has been working to revitalise 25,000 hectares. And last year, the government pledged £250 million ($344 million) over a decade to recovery as part of efforts to become a net-zero society by 2045. Projects involve the construction of peat dams to close drainage ditches, allowing water levels to rise and peat-building vegetation to return. The programmes remove encroaching trees and minimise grazing and burning. Revegetation helps manage extreme cases of erosion.

But as Professor Davy McCracken, Head of the Department of Integrated Land Management at SRUC, pointed out during the round table, work on the ground is only one step towards meaningful change.

“We need to actually know whether what we’ve actually done is working,” he said. “It all comes down to data.”

At the moment, many restoration projects rely on field surveys to monitor how well peatlands are recovering. But sending researchers out into remote corners of bogs is costly, time-consuming, and requires specialist expertise.

Experts may have found an effective alternative. The method uses satellites and a remote-sensing technique called Interferometric Synthetic Aperture Radar, which measures changes in the altitude of land surfaces. It may be possible to use the method to detect the expansion of peatlands that can occur during restoration, said Mark Reed, who is also the research lead for IUCN U.K.’s Peatland Program.

Think of it like breathing, Reed explained. When the peatland is degraded, it loses moisture, the peat contracts, and the land sinks. The bog is breathing out. When the bog is rewetted during restoration, the water table climbs, the peat expands, and the land rises. It is breathing in.

“If you can measure these topographical changes over the course of years,” Reed said, “you can track the restoration of a bog, whether it is working or not.”

Satellites can measure changes over large tracts of land, opening the door to wide-scale monitoring of peatland conditions and restoration projects. There is also a robust relationship between a peatland’s water table level and its greenhouse gas flux, making it possible to track emissions changes over time. And the remote-sensing technique could even identify areas at risk of instability, fire, and erosion, NatureScot found.

This is the tip of the iceberg of what is possible with nanosatellites.

For example, Spire’s devices monitor soil moisture using a satellite-based sensing technique known as Global Navigation Satellite System Reflectometry. This remote sensing technique gauges moisture levels by studying how signals bounce off the water trapped in the ground. The data could be helpful for mapping wetlands and monitoring their dynamics.

In fact, Spire’s constellation of satellites already measures variables pertinent not just to peatlands but to the health of the global climate. And it could add many more to the list in a short time frame. Spire has a history of bringing ideas from the whiteboard to orbit in under a year.

As the roundtable continued, the experts discussed other ways that existing and future datasets from small satellites could support peatland restoration, like locating optimal locations for projects. The mood became optimistic.

“It’s extraordinarily dumbfounding what people and humanity can do when working together,” said Platzer.

The hope is that as more dams go up, more water will return to the degraded lands. Moss will follow and then the wildlife. Peat formation will begin again and the landscapes will start to resemble the untouched corners of the Flow Country. And above them all, satellites will help ensure the progress continues unabated. Technology allowed us to destroy the peatlands. Now it will help protect them.

Thankfully, humanity began to dabble in the art of weather forecasting as early on as 650 B.C. when the Babylonian civilisation attempted to anticipate short-term weather patterns and optical phenomenon as haloes. Exponential massive strides have been made in the world of weather prediction since then. As a global society, inventions and technology have permitted us to progress at a faster pace than ever before.

With the installation of sensors, weather stations, weather balloons and countless other devices to measure and record current weather data, we’ve gained a stronger understanding of the Earth’s atmosphere. Not just that, we’ve got eyes in the skies with the launch of countless satellites that continuously orbit the planet and record data. Armed with this and super computing power, weather forecasting models are getting better.

With all this innovation and technological expertise, why does the maritime sector still encounter countless challenges?

Managing a fleet of sea-worthy, efficient vessels consists of a complex business model that entails colossal investment and costs. No matter what the class of shipping enterprise, fuel consumption contributes the highest percentage to expenses.

What can historical weather data do for your business?

The complex nature of weather poses as a barrier to create reliable weather forecasts beyond ten days. The further you go ahead in time, the less accurate the forecast gets. Route planning for lengthy voyages requires the utilisation of historical weather data to analyse past weather conditions. This makes it possible to identify potential weather patterns and obtain actionable insights. It really is an integral part of weather routing in order to get the full benefit of the algorithms we develop.

For instance, a container ship that has to reach its destination at an appointed time & date, balancing amidst the eminent factors of fuel optimisation, emissions reduction and remaining on schedule is harder than attempting to walk on a tightrope.

A container shipping company will gain customers based on its ability and reputation to meet its promise of on-time delivery. Global supply chains depend on such ocean carriers to arrive at their destinations at the stated time/dates. The principle of “Just-In-Time” has allowed B2C companies to ameliorate their ROI by minimising inventory management costs, however, at the risk of stock shortages if there is any delay in the supply chain.

Having access to historical weather data can decrease the risks associated with such major disruptions in the supply chain.

What other beneficial applications can historical weather data offer?

Think about it. What better way to learn and improve is there than looking back at history? You can also improve your vessel’s engine performance, optimise fuel, save costs and protect both your cargo plus crew

Whether you’re a member of the on-shore team or the off-shore team, weather data will play a key role in your strategy and plan of action. Having access to accurate historical weather data will support you in your efforts to:

• Optimise weather-based routing
• Assist in proforma scheduling
• Monitor fleet performance

If you’re part of a P&I firm or a maritime insurance service provider, you’ll want to understand the risk dynamics in certain locations for maritime transport. Scrutinising historical weather data on specific trajectories can help you identify high risk regions (in terms of weather) and make decisions accordingly.

Interested to learn more?

With Tom Bebbington, a highly experienced ex-Maritimer and innovation specialist, along with our panel of experts in the industry, learn how you can apply maritime weather data to analyse your trajectory paths, improve your vessel’s performance and optimise fuel consumption.

You’ll also hear from Soren Christian Meyer, CEO of ZeroNorth, about how his company uses historical weather data. ZeroNorth is a company which helps the shipping industry optimise operations through digitalisation.

We will also be joined by Christopher Manzeck, a Meteorologist & Sales Engineer at Spire as well as Simon van den Dries. VP of Business Development at Spire

The truth is that there are terabytes, more terabytes and even more terabytes of countless weather data to swift through. Let us help you cut through this clutter by demonstrating a few, effective methodologies of extracting weather data in a way that’ll save you ample time and help you achieve your business objectives. Let’s find your needle in this vast, infinite data haystack that could make or break your profit margins.

Alongside weather data, experts track vegetative ground cover—or fuel levels—to forecast wildfires. Satellites can help with this, too. It is possible to approximate fuel levels by studying soil moisture readings, explained Cromarty. Until recently, soil moisture has proved difficult to study on a large scale. But now, experts can calculate soil moisture across large tracts of land using satellite-based reflectometry, known as Global Navigation Satellite System Reflectometry or GNSS-R. This remote sensing technique measures how signals bounce off water trapped in the ground. Spire is investing heavily in this kind of soil moisture data. Satellites with this capability are already deployed and fully active with more missions planned.

“Compared to GNSS-R missions of the past, Spire satellites can collect about seven times the quantity of soil moisture measurements per satellite due to advances in tracking more simultaneous GNSS reflections,” said Dallas Masters, Spire’s Earth observations director. “We have long-term plans for sustainable Earth observations, and GNSS-R soil moisture is a key product that will positively impact weather forecasting, drought monitoring, and agriculture.”

Communities around the world have suffered record-breaking wildfires over the last few years. Even forests in Siberia have gone up in flames. As the threat grows with climate change, solutions that help protect firefighters and communities are more critical than ever—especially tools that help stop fires before they turn into life-threatening infernos. Satellites will continue to monitor the weather and environmental variables, and analytics will progress with time. Together, they should offer firefighters ever-improving solutions to predict and prevent wildfires.

“That means lives saved, structures saved, and the ability to get resources to the area to fight fires and minimize its impact,” said Quiron chief executive officer Gil Pletsch.

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1. You can’t sum up ocean weather conditions with an emoji

We all do it, we grab our smartphones and summon the weather app to decide when to go somewhere, what to wear, and what to bring. The weather is volatile, complicated, and rapidly changing which makes it nearly impossible to sum up in one emoji. Ocean weather is often more complicated to forecast than weather in suburban America for example, because ocean forecasts are the sum of many moving parts: ocean currents, wave height, and wind speed to name a few. All of these factors all impact ocean forecasts. Combining these factors and estimating their evolution amounts to a perfect storm of conditions that influence the weather around the planet. To get an accurate view of sea conditions, you need to combine atmospheric forecast data (temperature, pressure, and humidity) and oceanographic forecast models ( currents, waves, etc). In other words, what is happening in the air and what is happening on the ocean’s surface and how each is affected by the other.

2. Remote ocean data is plentiful and if it is very remote, it doesn’t impact the weather near me

A storm brewing in a remote ocean area travels and changes weather conditions far from the remote area where the inclement weather first formed. Weather, like water, is always moving and always changing. So it makes sense that warmer than usual weather in the Arctic, directly impacts weather patterns from the United States to Europe and everywhere in between. Weather data in remote areas is challenging to collect. You can’t rely on weather stations and widespread sensors that make data collection easy. For remote ocean data, remote sensing techniques like satellite radio occultation have become essential for atmospheric data collection.

Radio Occultation (RO) captures detailed temperature, humidity, and pressure information across the entire planet, including vast oceans and under-observed corners. This results in better forecast accuracy everywhere. Before Radio Occultation, maritime models depended on a combination of buoys, sensors on ships, offshore structures, aviation sensors flying overhead, and weather balloons for ocean data. All of these techniques are not accessible in remote ocean locations. RO is quickly becoming the go-to solution for open ocean forecast data.

3. If Meteorology is a science, it should be accurate

This is partly true, but there is an art/science approach to forecasting and meteorology that is essential because of the degree of complication and the constantly changing conditions. There isn’t one exact method of forecasting that works in all situations. Forecasting relies on the science of equations and these equations are what meteorologists use to explain the physical processes occurring in the atmosphere. Yet, what is occurring in the atmosphere is impacted by these physical processes. So you need to understand how certain conditions change certain patterns. And since we’re focusing on ocean forecasts, you need to consider changing ocean temperatures, precipitation, water vapor, wind speed, and more to determine how an incoming weather condition impacts these elements.

Climate change, too, makes these predictions more challenging, as it represents unchartered waters when calculating weather conditions not typically found during certain seasons. The Polar Vortex in November of 2020 for example set into motion strong surface winds from upper atmospheric phenomena that pushed sea ice across the central Arctic Ocean. Arctic wind speed and direction create changing weather patterns and when combined with stratospheric warming events, can result in what is referred to as “atmospheric waves” that create an imbalanced polar vortex. This imbalanced polar vortex can lead to blizzard conditions similar to those seen in 2013 and 2014 across the United States. Forecasters rely on historical data to predict these types of conditions. Before climate change, these incidents didn’t occur as often. The onset of climate change created a renewed demand for historic data because it allowed meteorologists to go back and study patterns from 10 years ago and longer and chart changes and patterns that help identify weather patterns today.

4. Modern data collecting techniques gather enough data to build solid prediction models, so errors shouldn’t happen

Yes, sort of. All weather models are wrong to some extent. Technologies, like Machine Learning, are applied to forecasting to reduce errors, and they are having a big impact on accuracy, but they don’t deliver 100% accuracy. The reality of forecasting is that it isn’t perfect and it isn’t perfect because ocean data is complex and oftentime there isn’t enough ocean data available to build a perfect forecasting model. One way to rectify this data shortage is to diversify the data you’re using. If you pull data from a variety of sources that contribute to weather patterns, you can feed machine learning models to reduce errors. For example, if you incorporate wave data into your forecasting model you can begin building a numerical weather model that digests different variables for weather prediction. Ocean waves affect coastal dynamics and ocean activities and they are indicators of other surface conditions, like high winds. Using data from multiple sources has been shown to lead to better, more accurate weather models. Optimizing your weather data to smaller, data-dense areas is another strategy for building better forecasting models.

Weather forecasts optimized for seaports, for example, is one such scenario that is proving popular among maritime operations. Port weather impacts a variety of port services around the globe and the forecasts need to be accurate to time grain unloading and other types of cargo that are weather sensitive. By focusing on a small area where data is abundant, you can measure many factors to determine a short term weather forecast with greater accuracy.

Hot with a chance of sunspots, solar flares, and coronal mass ejections

Experts disagree about how severe this solar cycle will be. The official Solar Cycle 25 Prediction Panel forecasts below-average activity, while other scientists suggest this could be one of the stormiest cycles ever. Scientists gauge conditions by counting the number of sunspots—the dark patches that appear on the sun’s surface in areas with high magnetic flux.

“Sunspots are a metric of solar activity,” said Matthew Angling, Spire’s director of space weather. “When there are no sunspots, the sun is really quiet. And at the top of the sun cycle, there are lots of sunspots.”

The presence of sunspots indicates a higher chance of extreme events like solar flares. Twisted magnetic fields in sunspots release energy and cause these sudden eruptions, which emit X-rays and ultraviolet light. Flares are often associated with increases in the density of energetic particles around the Earth, which can affect the operation of satellites or harm astronauts.

Other violent explosions, known as coronal mass ejections, hurl billions of tons of plasma away from the sun. These outbursts carry a magnetic field and travel as fast as 3000 kilometers per second. One of the most infamous coronal mass ejections occurred in March 1989 when a cloud of plasma 36-times the size of Earth catapulted into our magnetic field. It sparked a geomagnetic storm that shut down Quebec’s power grid, plunging the province into a 12-hour blackout.

A storm of similar magnitude could be even more devastating today. Fortunately, most solar events miss the Earth, and our magnetic field protects us from the brunt of the ones that do hit. Nonetheless, the effects of minor incidents and daily space weather continually impact modern life by manipulating our ionosphere.

GPS signals sail through space weather

The ionosphere has up to four layers. It begins in the atmosphere’s upper levels at an altitude of about 80 kilometers and reaches into space some 1500 kilometers above the Earth’s surface. These layers contain charged particles created when X-rays and ultraviolet radiation from the sun collide with atmospheric gasses and break atoms into ions and electrons.

Because the amount of X-rays and ultraviolet radiation hitting the planet fluctuates, so does the density and elevation of the ionosphere’s layers. The amount of energy varies from day to night and can increase ten-fold over the sun’s 11-year cycle, NASA explained. Experts recently discovered that weather on Earth also alters the ionosphere, as atmospheric waves from storm systems can propagate up into the charged layers. So, just as the sea swells with regular tides and seasonal storms, the ionosphere is constantly in flux.

The ionosphere’s ebb and flow influence radio frequencies critical for communication and global navigation systems. The density of charged particles affects how signals reflect off and pass through the ionosphere, adding variability into military and commercial operations. In what is known as ionospheric scintillation, signals distort as they travel through pockets of ionospheric turbulence.

Severe scintillation can make it impossible for a GPS receiver to lock onto a signal and determine its precise location, NOAA explained. Even minor scintillation can reduce the accuracy of navigation systems, which not only contribute to critical technologies like cell phones and airplanes, but also transmit time data that underpins vital infrastructures like power grids and financial markets.

With so much relying on these systems, it pays to know what is happening in the ionosphere.

Keeping an eye on the ionosphere

Spire Global monitors the ionosphere using nanosatellites fitted with sensors that receive global navigation satellite system (GNSS) signals. The measurement technique takes advantage of the physics of how the GNSS signals travel through the ionosphere and produces invaluable results.

In general, signals travel slowly through high-density pockets of the ionosphere—just like it is slower to walk through water than on land. The magnitude of a signal’s delay also depends on its frequency. Because navigation systems broadcast more than one frequency, Spire can use its nanosatellites to measure the difference between the delays of various GNSS frequencies and then estimate ionospheric density. The measurements are called radio occultation, and Spire uses a similar technique to monitor weather conditions from the upper levels of the atmosphere down to the surface of the sea.

Ground-based sensors can also measure the ionosphere, but only for areas above land. Also, these observations fail to capture the nuances of how conditions change with altitude. In contrast, orbiting satellites provide both global coverage and vertical measurements through different layers of the ionosphere, which makes it possible to build highly detailed three-dimensional models of conditions, Angling explained.

To better understand the distinction, it helps to think of the difference between standard X-ray imaging and CT scans. A standard X-ray machine is fixed and creates a two-dimensional picture of a bone or organ. This is similar to ground-based sensors. On the other hand, a CT scanner uses a rotating X-ray device to build a three-dimensional representation of the body, much like orbiting satellites that monitor the ionosphere.

Moreover, satellites can continuously monitor the ionosphere while orbiting, helping to ensure observations of the ever-changing environment are up-to-date.

“In a dynamic model, you are constantly collecting data and revising the model based on real observations,” said Carhart.

There is a range of applications for a dynamic model of the ionosphere. For defense users, it can help account for disruptions in navigation systems, correct errors of radar images, improve space situational awareness, and help to pinpoint the location of high-frequency radio transmissions. It is also beneficial for commercial organizations with services that rely on GPS—like autonomous vehicle operators and global logistic companies—or satellite communications.

Researchers can access our unique space weather data now. In 2020, Spire received a contract award for commercial operational Earth observation data from NASA. Through this contract, Spire provides GNSS radio occultation atmospheric profiles, space weather measurements, grazing angle reflectometry used in sea ice measurements, and more. Spire’s contract with NASA was renewed in May 2021, and this data is currently available to support environmental research efforts.

Spire will continue to launch new satellites and ramp up data collection as the sun heads into what could be a record-setting period of activity. And Spire will further hone its space weather solutions so its partners can see the impact of solar events as clear as day.

“We are building the best possible representation of the ionosphere, one that can provide solutions to meet the needs of many different customers,” said Angling.

Sourcing

The weather that disrupts the production or extraction of a raw material in one location can send costly ripples down entire supply chains.

“It is critical that all stakeholders become aware of the potential impact of raw material supplies on their business,” according to a paper from the Massachusetts Institute of Technology. “If those raw materials become difficult to acquire, market forces may shift demand to other goods and therefore other supply chains.”

Take cotton, for example. Last year, anemic rainfall in west Texas cut expectations for the state’s output, the Wall Street Journal reported. At the same time, cotton-producing regions to the southeast were dealing with the repercussions of Hurricane Hanna, which flooded farmlands. The combination of these events contributed to a spike in cotton prices, pushing them to a two-year high.

Droughts can have a similar impact on other global markets. During the summer of 2018, heatwaves and scant rains in the European Union damaged food crops. The weather cut wheat production by 9%, increasing the staple’s price to a four-year high. The drought also drove up the cost of fresh vegetables, with broccoli’s price tag jumping by more than a quarter. Furthermore, animal feed reductions forced cattle farmers to bring forward slaughter, adding nearly 2% more beef than the previous year into the market.

Manufacturing

Manufacturing also falls victim to the weather. Adverse conditions can shut down and limit access to plants, disrupting downstream production and potentially raising prices to both manufacturers and consumers, reported McKinsey.

In late 2011, heavy rains inundated more than 1,000 factories in Thailand, the world’s second-largest producer of hard disk drives. Western Digital Corporation, which produced one-third of all hard disks, lost nearly half of its shipments when its factory flooded, according to a report in the International Journal of Disaster Risk Reduction. Even hard disk drive factories that escaped flooding had to cut production as they ran short on parts.

With production and supplies curtailed, the costs of hard disk drives increased—significantly. Desktop versions jumped 80% to 190%, while mobile ones increased 80% to 150%. Prices remained high for up to six months after the industrial parks drained floodwaters from the factories.

“This clearly shows that the world economy is closely interconnected through a global supply chain network and the indirect damage of disasters now easily affects the consumer market at the global scale in the electronics sector,” the report continued.

Transportation

Networks of planes, trains, trucks and ships form the backbones of supply chains. Raw materials, parts, and goods crisscross the world before a final product lands in a consumer’s hands. Each stage is exposed to weather-related disruption.

For example, tornadoes can knock over trains, mudslides after heavy rains can block highways, heatwaves can cause sun kinks in rail tracks, and freezing temperatures that force planes to de-ice can disrupt flight schedules. Even light showers can increase travel time delay by up to 20%, according to the U.S. Department of Transportation Federal Highway Administration.

“This translates into financial impacts,” said the administration. It found that trucking companies and commercial vehicle operators lose about 33 billion vehicle hours to weather-related congestion each year. These delays cost them about $2 billion to $3.5 billion annually.

The weather also caused about 40% of all flight delays in the U.S. in 2019, according to the Bureau of Transportation Statistics. A single delayed plane can hold up the delivery of as many as 50,000 packages, the National Oceanic and Atmospheric Administration estimated.

Finally, the world saw how heavy winds could disrupt international trade when the 400-meter container ship Ever Given ran aground in the Suez canal. Amid strong gusts and sand storms, the vessels veered off course and collided with the canal’s bank, blocking the critical trade artery, Reuters reported. The blockage that lasted nearly a week disrupted global commerce, delaying $10 billion in trade a day and triggering a spike in oil prices.

From reactive to proactive

A report from the United Kingdom’s Met Office, the country’s meteorological agency, captured the weather’s total influence on supply chains.

“While many may believe that their product portfolio is not weather sensitive, operationally the weather will always have an impact on their logistics and commercial activities,” the agency wrote in Understanding the Role of Weather in the Supply Chain, which surveyed more than 200 industry experts.

This impact, however, does not have to be negative. Supply chain and logistics managers have an opportunity to turn risk into reward with the help of weather data. Retailers and suppliers who responded to the Met Office’s survey listed better on-shelf availability, sales forecasting, and customer service as benefits of using weather data. Both groups also identified less waste as an advantage.

“Using advanced weather data is a significant opportunity for organisations to improve supply chain efficiencies,” the Met Office said.

For example, Oldendorff, one of the world’s largest dry bulk shipping companies, used weather data from Spire Global to help improve its fuel consumption model’s accuracy and plot efficient courses. Similarly, VesselBot integrated Spire’s weather forecast data into digital solutions to help its customers reduce emissions and increase profitability.

Opportunities abound for using weather data to amplify supply chain efficiency, from both the supply side and demand management. Especially when you consider that services like Spire Weather provide data on more than 100 weather variables across the planet.

As the Met Office put it: “Better tracking and understanding of weather conditions is essential to better meet consumer demand, ensure the timely and safe delivery of goods and reduce unnecessary inventory and waste in the face of more seasonal weather extremes.”

Watch our Wildfire Prediction & Observation Use Case:

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Sea ice sets the scene

Declining levels of sea ice are an unmistakable sign of climate change’s impact on our planet. Record low levels of sea ice are leading to warming temperatures which affect sea level rise, ocean circulation, and weather patterns. Climate developments increasingly affect economies, industries, and transportation within the Arctic and around the globe, and pertinent data to help mitigate the effects of these changes is lacking. Critical missions such as search and rescue, safe marine operations, fishing, water quality, and climate change monitoring are all suffering from a lack of Polar observational data and an inability to access remote areas.

Spire is seizing the opportunity to provide more satellite coverage in the Arctic and Antarctic regions to measure the extent and height of sea ice and to monitor new waterways created by the melting ice. Over 65% of Spire’s cubesatellites are in polar orbit, offering high revisit rates in the polar region, thereby providing unprecedented vessel tracking coverage as well as highly accurate weather and climate intelligence. Spire data can provide an optimized Arctic solution to support both environmental and security interests due to the architecture of our satellite constellation and accuracy of our data.

Supporting opportunities and mitigating challenges with climate data

According to the Government Accountability Office, the Arctic holds 13% of the world’s undiscovered oil, 30% of undiscovered gas, and about $1 trillion worth of gold, zinc, nickel, and platinum. Melting sea ice is increasing usage of the Northern Sea, Northwest Passage, and Transpolar trade routes and potentially opening up new waterways to create new trade routes. Flooding and erosion have caused millions of dollars in property damage in Arctic Alaska indigenous villages, posing threats to lives, homes, and infrastructure and putting pressure on hazard mitigation efforts for federal and state agencies.

In-depth, accurate data on melting sea ice and human activity in the Arctic is critical to taking advantage of opportunities and mitigating regional challenges. However, this data is currently lacking and will continue to be elusive as Arctic monitoring satellites reach end of life.

In an open Polar Altimetry Gap Letter of Concern, over 600 scientists signed their names to address their concern over an expected lack of satellite altimetry data in the coming years. The scale and inaccessibility of the Polar Regions call for a collection of space-based observation techniques. Satellite altimetry offers a unique capability to monitor changes in the Polar Oceans and the height of land and sea ice. There are 7 satellite altimeters in orbit, but only two reach polar latitudes. CryoSat-2 and ICESat-2 were launched in 2010 with a design-life of 3.5 years and 2018 with a design-life of 3 years, respectively. CryoSat-2 is projected to reach end-of-life between 2024 and 2026. The European Commission initiated the CRISTAL polar altimeter as a high priority candidate mission, but the earliest launch date is projected for Q4 2027. Considering these factors, there will be a gap of 2-5 years in our polar satellite altimetry capability.

Spire’s earth intelligence capabilities can successfully fill this gap and support efforts to study indicators of climate change and its resulting impacts in the Arctic and Antarctic regions as well as globally. Spire provides a plethora of radio occultation (RO) data in the polar regions, where the low humidity permits the collection of data all the way to the surface. This unique set of near surface temperature measurements greatly enhances Arctic and Antarctic weather forecasts.

To collect measurements for sea ice extent, classification, and altimetry, Spire utilizes a novel GNSS low grazing angle reflectometry technique (GNSS-R) using radio occultation satellites. This technique has the potential to deliver high resolution (approximately 0.5 x 8 km footprint) and fast return rate (less than 24 hours) sea ice measurements.

With various data observations including sea ice age, extent, height, and weather forecasts for temperature, wind, and other ocean variables, Spire can provide an all-in-one Arctic Intelligence solution to meet research and mission needs.

SEA ICE EXTENT

Spire Ice Detection from Grazing Angle GNSS-R in the Antarctic, data from March 2020, gridded at 5 km resolution

SEA ICE EXTENT

Spire Ice Detection from Grazing Angle GNSS-R in the Arctic, data from April 2021, gridded at 5 km resolution.

Spire’s sea ice extent measurements have the capability to distinguish sea ice from open water in order to map sea ice coverage. This also allows us to delineate the marginal ice zone (MIZ), which is a transitional region between open sea and dense drift ice.

SEA ICE CLASSIFICATION

Spire Ice Type Classification from Grazing Angle GNSS-R in the Arctic, data from March 2020, gridded at 5 km resolution.

Spire’s sea ice classification measurements allow for the categorization of ice type, i.e. age of the ice.

As climate related opportunities and challenges arise in the Arctic and Antarctic regions, abundant and accurate insights on sea ice, sea surface temperatures, and weather patterns will be critical. Spire can deliver this data with refined accuracy and abundance.

Researchers can access our unique Arctic data now. In 2020, Spire received a contract award for commercial operational earth observation data from NASA under the Commercial Smallsat Data Acquisition (CSDA) Program. Through this contract, we provide GNSS-RO atmospheric profiles, space weather measurements, grazing angle reflectometry used in sea ice measurements, and more. Spire’s contract with NASA was renewed in May 2021, and this data is currently available to support environmental research efforts.

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Supporting security missions in the Arctic and Antarctic regions

The 2013 DoD Arctic Strategy lays out a framework for the United States to harmonize human and environmental security, highlighting myriad activities in the region such as resource extraction, trade, promoting safe scientific and commercial activities, and national defense, but other countries are also exploring what opportunities the changing climate may bring. Russia, for example, has developed its Northern Sea Route, which the Russian Energy Ministry promoted as comparatively more “reliable, secure, and competitive” during the Suez Canal jam.

Additionally, the United States risks falling behind other countries in regards to icebreaker ship development and deployment. As the U.S., Russia, China, Norway and Finland, among many other nations, continue to increase their presence in the region, critical Arctic data is needed to anticipate world power convergence in search of oil, natural gas, and other strategic advantages.

In The Art of War, Sun Tzu lists Heaven (the weather) and Earth (the terrain) as two of the five main considerations to achieve battle-less victory. Spire’s data can help the U.S. national security community master the weather and terrain in the Arctic and achieve national security goals while promoting U.S. superiority both in space and the Arctic. Spire’s combined weather forecasting and AIS data provide strong support for mastering the weather and terrain for security operations.

Our sea ice data measure the extent, classification, and age of sea ice, and our GNSS-R sensors measure ocean surface height, roughness, wind speed, surface water mapping, and soil freezing and thawing. Spire’s weather forecast bundle offers wind data, incredibly precise weather data for obscure locations, wave height, and maritime waves. We also provide insights on space weather, including Northern Lights, comms and navigation, and temperature.

Spire can also provide national security customers with vessel tracking capabilities in the Arctic through our high-quality satellite, terrestrial, and Dynamic™ AIS data. Spire collects AIS signals from over 200,000 vessels around the Earth and processes these signals into AIS messages to provide real-time vessel tracking data through our API.

Furthermore, Spire maintains extraordinary coverage in high traffic zones (HTZs) such as the North Sea, where the density of vessels is extremely high, and AIS coverage is notoriously lacking. We created a solution addressing the HTZ problem by adding +2,100 dynamically moving AIS receiving stations on vessels throughout all major sea routes and HTZ areas, collecting this data and updating it via communications satellites every 15 minutes. This results in an additional total volume of 10M AIS messages per day and an average 135,000 unique MMSIs per day globally.

Spire is prepared to support the Department of Defense and Department of Homeland Security as their Arctic presence becomes increasingly necessary, being able to provide them with masterful data that gives our warfighters greater confidence in operating in remote areas with uncertain conditions. Our polar focused constellation of CubeSats is increasing maritime intelligence in the Arctic while providing critical weather insights to support remote operations around the world.

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Accurate data means Arctic and Antarctic superiority

Spire offers comprehensive data and weather forecasting services to provide an all-in-one data solution to both civilian and military agencies to promote and protect U.S. interests in the Arctic and Antarctic regions. As great-power competition continues to ramp up in the Arctic and the region becomes more crowded, it is imperative that researchers and service members have access to the most accurate and comprehensive data available. 

Spire can provide this mission critical data in real-time with a tried and tested space-to-cloud data and analytics infrastructure, leveraging small satellites to solve Earth’s biggest problems.

Looking back to see the future of forecasting

The origins of numerical weather prediction reach back to 1904 when Norwegian physicist Vilhelm Bjerknes theorized that it was possible to forecast the weather by solving a set of equations, the National Oceanic and Atmospheric Administration wrote in a history of the technique. A few years later, British mathematician Lewis Fry Richardson put the theory to the test, crunching numbers for six weeks to produce a six-hour forecast—all while working with an ambulance unit in France during World War I.

Today, leading national and international weather institutions use supercomputers instead of slide rules. For example, NOAA plans to upgrade to a system with 40 petaflops of computing capacity, meaning it can do 40 quadrillion (one with 15 zeros after it) operations a second. But the process follows the same basic steps as it did decades ago.

First, experts collect measurements from sensors about the atmosphere’s current state, combining readings of temperature, humidity, pressure, and a range of other variables through statistical techniques. They then feed this initial state into a numerical model that simulates the evolution of the atmosphere, which include physics and mathematics equations. These equations encompass Newton’s laws, thermodynamics, microphysics, and other physical approximations that scientists have created to describe how meteorological variables change with time. Finally, the model’s solutions become the forecasts we see on the daily news or smartphone applications.

“A numerical weather prediction system is like a great wonder of the world,” said Stefanescu. “However, there are many aspects that need to be improved.”

Machine learning can help.

Let the neural net handle that

Machine learning lets computers take a crack at decision-making. Instead of scientists finding equations to explain a phenomenon, neural networks identify patterns in data and develop answers independently. It tends to be ideal for decoding complex scenarios with massive amounts of data—just like the weather.

“Neural networks are very flexible, which means you don’t need to make strong guesses about how weather systems are going to behave,” said Matthew Lennie, a machine learning engineer at Spire Weather. “The flexibility allows the neural network to fit itself to the situation and find the pattern. Think of it like mathematical play-dough.”

These systems show potential in aiding multiple stages of numerical weather predictions. They might help with automated quality control, model errors, faster physics approximations, and improved optimizers. And they could assist engineers with fine-tuning models.

“Informing the neural network with physics constraints holds a great promise in improving the weather forecasts,” said Stefanescu.

Spire is already finding success using a machine learning program called JUNO to boost ensemble forecasting.

In ensemble forecasts, meteorologists combine the results of multiple models into one prediction. Each model has strengths and weaknesses, with some performing better in certain regions than others. By combining them, forecasters hope to get the best of all available forecast options. But determining when and where one model performs better than another is complicated. After all, numerical weather predictions track the evolution of hundreds of variables throughout the atmosphere and into the future.

With JUNO, Spire leaves the complexity for a neural network to sort out. The program compares the various predictions with observed results and then determines how to rank each model’s results. Multiple weather variables are used to correct the forecasts’ biases, Stefanescu explained. For example, JUNO does not just look at the relationship between predicted temperature and measured temperature. It also studies how pressure, wind, humidity, and other conditions impact a temperature prediction. The process is data-driven and makes fewer assumptions than with traditional approaches, said Stefanescu.

“This intelligent voting system starts to work out which predictions are the best in each scenario, creating a better quality prediction than each one alone or an average of the group,” said Lennie.

Bespoke forecasting

One day, machine learning might help tailor forecasts to meet the needs of specific industries.

“Markets have different wishes of what they want from models,” Lennie said. “It helps to have this system so we can customize and build the best version of the forecast that is reliable for that particular industry.”

Take the unique forecasting demands of the renewable wind energy industry, for example. In this industry, over-predicting the wind can lead an organization to sell more power than it can generate, Lennie explained. With machine learning, it should be possible to tailor the ensemble forecast to provide conservative forecasts, which can help customers avoid the risks of over-committing. Lennie said the systems might even help provide wind turbine operators with a probabilistic output to help them further balance risk and reward.

On the other hand, a fire department might want to know about even a slight chance of high winds that could stoke and spread a wildfire. The earlier the warning, the better. In this case, machine learning might prioritize forecasts that show any chance of heavy winds while also honing in on temperatures highs and humidity lows—spotting conditions that make wildfires more likely.

Better yet, these systems will improve as engineers feed them with more data. Spire has no shortage of that. It operates over 100+ nanosatellites that gather observations around the world. These satellites already make radio occultation measurements, collecting detailed atmospheric data that can help reduce weather forecasting errors. As Spire launches more devices and capabilities, the constellation will produce more information.

“We can improve on our best knowledge as time continues,” said Lennie.

Meteorologists and machine learning scientists are sure to discover new ways of using neural networks and data to optimize numerical weather predictions. The fields show the potential of growing together and building on each other’s successes, with the hybrid systems becoming better at predicting unexpected events and nuanced occurrences.

“This is the future no matter what,” said Stefanescu.

Watch our Wildfire Prediction & Observation Use Case:

Predicting accurate energy generation

For all energy producers, it’s important to have estimates of how much energy they’ll be able to generate. Energy producers have contracts with the electrical grid to supply a certain amount of power at a certain time. Some of these contracts are quite short-term, with producers committing to a certain amount of energy a few hours in the future.

The exact downsides of inaccurate energy generation forecasting will depend on the nature of the market and laws in a region, but in general the main risks are:

• Creating less energy than expected: besides making less money, there may be energy-imbalance penalties, which are used to incentivize accurate load forecasts for the grid’s benefit.
• Creating more energy than expected: this may result in the producer having to sell that energy cheaply on the market or, worst case, have it be wasted entirely if the energy can’t be stored or they can’t find a buyer.

Predicting energy production is easy for traditional power plants like coal and nuclear; they can easily control energy production. This is much harder for solar and wind facilities, which are inherently volatile. This is why accurate weather forecasts are so important. (And we’ll look in a little bit about operational differences between wind and solar.)

Interestingly, as wind and solar energy become more ubiquitous, the importance of their ability to forecast production also grows. As wind and solar make up a larger percentage of the grid supply, it’s increasingly important that they forecast well and operate more like traditional non-renewable facilities, so that grid operators can in turn also plan well. It’s also becoming more common to implement energy imbalance penalties on renewable energy operators, which will put additional pressure on these sectors to use more accurate weather forecasts.

Wind farm construction and planning for offshore wind farms

Wind farms are located in remote areas that have consistent, year-round wind. All historical weather data that might affect energy production is examined to arrive at energy generation estimates. Planners look at wind speed, wind consistency, variance in wind (highs and lows), and wind measurements at different elevations.

In some locations, depending on the topography, the wind can vary a lot over very short distances, meaning turbine placement can require in-depth analysis of wind patterns. Unique wind patterns will also dictate unique arrangements of the turbines.

The industry is attempting to do more high-altitude wind energy collection because high-altitude winds are steadier and of greater velocity. These methods can include taller turbines and also airborne wind energy (AWE) devices, like kites or balloons. There is much research being devoted to more efficient ways to harness this wind (for example, this 2017 study). And there is a growing demand for more comprehensive wind forecasts covering larger (higher altitude) regions. One forecasting technology of interest is radio occultation (GPS-RO), which uses satellites to get high resolution measurements of high-altitude atmospheric properties at a better consistency than weather balloons can.

Wind farm operations 

As mentioned, it’s important for both wind and solar to try to accurately forecast energy production. The wind sector has unique challenges because wind is so volatile, and this means operators must keep a close eye on current wind state and near-future wind forecasts. The unpredictability of wind creates many issues for both wind utility operators and grid operators.

Rapid changes in wind speed are called “ramp events”, and these events require operators to ramp generators up or down to try to balance energy creation and not waste it. But due to several factors (e.g., commitments to the grid, inability to ramp down generators quickly), facilities will produce too much energy.

For a great explanation of the many factors in this area, we recommend this 2011 study on wind forecasting by the National Renewable Energy Laboratory. To quote from there:

In short, better wind forecasting means huge efficiencies and savings — increasingly so as wind energy becomes more prevalent. As you’d expect for such a competitive industry, many products and research projects are focused on this area. A couple of examples:

• A 2018 study using machine learning techniques to improve forecasts based on historical wind data.
• A 2020 proposal for improving wind forecasts using machine learning strategies.

For a concrete example of the types of solutions being used by the industry, here’s a Spire Global tutorial on how to retrieve wind forecasts for different altitudes.

A visualization of Spire weather forecasting for wind farm applications.

Wind farm maintenance

For wind farms, there are two main types of maintenance: planned maintenance and emergency maintenance.

For planned, regular maintenance, it’s important to plan it several months or weeks out when weather is expected to be calmest. Extreme weather can mean various costs, including delays in work, lost income from out-of-commission turbines, harm to equipment, and injuries to workers. Planning for calm weather windows is both the safest strategy for workers and equipment and also ensures that work is done when energy production is least.

This is especially important for maintenance being done at offshore wind farms, where the seas present bigger risks. One study estimated that “up to one third of the total cost of energy from offshore wind generation is contributed by operation and maintenance.” Large offshore projects, like replacement of turbines, can take days or even weeks, depending on the facility and weather conditions.

For more emergency-type maintenance, there are more hazards. There can be pressure to fix equipment quickly because every day a turbine is out of commission, money is being lost, and there may not be an optimal calm-weather window in the near future. If maintenance must occur in stormy areas, lightning is the biggest risk, and workers monitor nearby lightning strikes closely. For offshore facilities, the situation is especially dangerous. The better the weather forecasts used are, the more a company minimizes dangers and risks in choosing a good window for maintenance.

Solar farm operations

Just as with wind, it’s important for solar farms to predict their energy output. Solar farms look at seasonal shifts in sunlight, which are well understood. More importantly, they look at the hour-by-hour and day-by-day changes in solar irradiance, which are harder to predict. To do this, they rely on weather data of many types (such as temperature, moisture, cloud cover, air pressure, more) to understand how much sunlight is expected to reach solar panels at a given time.

For example, here is a visualization from Spire Weather’s Web Map Service (WMS) image API showing 10 days of Global Total Cloud Cover (%) focused on the US. In addition to incoming solar radiation which Spire also provides, cloud cover is critical for solar farm applications.

Total Cloud Cover (%) 10 Day Global Forecast shown with Spire WMS

As expected in such a rapidly growing industry, there’s a lot of research and investment in better prediction of solar irradiance. One recent example of this is a technique called SCOPE: Spectral Cloud Optical Property Estimation, described in the Journal of Renewable and Sustainable Energy. This technique uses satellites to measure several cloud properties, including the cloud height, the cloud thickness (vertical height), and the cloud’s optical depth (a measurement of how it modifies light passing through it).

Another example of work being done in this area is the use of machine learning to find correlations between various weather measurements and solar radiation. For example, in a 2011 paper titled Predicting Solar Generation from Weather Forecasts Using Machine Learning, the team found that their machine learning models making 3-hours-in-future forecasts were “27% more accurate” than existing forecast-based models.

For an example of how solar energy companies are using weather data, here’s a Spire Global tutorial on getting a forecast useful for solar applications.

Visualization of Spire weather forecasting for solar application.

As with wind energy, machine learning and artificial intelligence approaches are being applied to forecasting solar energy.

Energy trading

Not directly related to renewable energy operations, but worth mentioning: weather forecasting also has potential for being used by energy traders to predict and take advantage of upcoming swings in energy costs. This is an emerging market that’s still adjusting to the rapidly changing reality of renewable energy and how it differs substantially from traditional markets.

Just the beginning

This has been a brief overview of the main ways the wind energy and solar energy industries benefit from accurate weather forecasts.

At Spire, we are dedicated to staying on the cutting edge of satellite data collection and weather forecasting technology. We operate one of the largest private satellite constellations in the world, which provides a unique global weather observation network including remote regions and oceans. Spire’s unrivaled radio occultation technology powers Spire’s weather models and sets a new benchmark for weather forecasts.

Learn more about Spire Weather

Reading wildfire risks in weather forecasts

“Of the factors that affect the daily changes in fire danger, weather data is the most significant,” explains a handbook on the U.S. fire danger rating system from the National Wildfire Coordinating Group.

Specialists consider air temperature, humidity, and wind speed and direction when they analyze fire danger and behavior. It is important to track temperature because a certain amount of heat is required for ignition and continued burning, according to material from Auburn University. Hotter fuel—grasses, needles, brush, and so on—also burns more readily and quickly. Wind heightens the danger of wildfires by drying out fuels and supplying oxygen to flames. And fires tend to ignite more easily and burn more intensely at lower relative humidities.

“Ask any wildland fire expert about the weather components that lead to difficult fire conditions, and the expert will reply with some combination of ‘hot, dry, and windy,’” wrote U.S. Forest Service experts and researchers in a paper.

If flames ignite, weather data can offer critical insight into a wildfire’s evolution and lifespan. Knowing wind speed and direction is particularly important, as they influence where and how far a fire might spread. Response teams also consider wind speeds at different flight levels to help plan how and when to deploy aerial assets like water bombers, helicopters, and drones.

“In the emergency management sector, resources are constrained,” said William Cromarty, a federal account executive at Spire Global with a background in emergency management. “Weather data allows an incident commander to prioritize resources and anticipate where to deploy support in advance, given you can never have 100% coverage.”

“It’s one of the few unifying threads that span the gap of tactical and longer-term strategic planning,” said Cromarty.

Space data supports land management

Wildfire management teams need to know that the weather data they use is as precise as possible. That is why we recommend using weather forecasts powered by radio occultation data. A leading weather organization recently identified it as a top-five data type for reducing errors in forecasting.

Impacts of Various Data Types on Weather Forecast Accuracy

Spire’s more than 100+ satellites use radio occultation measurements to capture detailed temperature, humidity, and pressure information across the entire planet. Taking exact measurements around the world can help improve local forecasts since weather systems connect globally. It also helps ensure that emergency management professionals and search and rescue teams can have detailed data across their operational regions.

Radio occultation measurements also generate high vertical resolution. Spire’s satellites measure conditions in thin slices of the atmosphere from sea level to the mesosphere, helping create detailed wind profiles for a range of altitudes. Furthermore, Spire also offers flight tracking information from our aviation department.

 
Temperature (2m AGL) and Relative Humidity (2m AGL)

ADS-B Data and Wind Speed & ADS-B Data and Weather Radar

“Spire’s data offers an incident commander the ability to not only monitor localized weather conditions on location but also track the presence of local aviation assets via ADS-B in the affected zone for added situational awareness,” said Cromarty.

Measuring moisture underground to gauge vegetation above

Alongside weather data, fuel levels are a crucial component of gauging wildfire risks. More dry grass and brush buildup means more chance of fire ignition and spread. But until recently, there has been no simple way to estimate fuel quantity across large areas, said Cromarty, especially in remote and inaccessible wilderness areas.

Now there appears to be a method. Experts can approximate vegetative ground cover through soil moisture estimations, explained Cromarty. And they can calculate soil moisture across large, even remote areas, using GNSS reflectometry, a satellite remote sensing technique that measures how GNSS signals scatter off the Earth’s surface. It is particularly adept at evaluating broad areas where it is impractical to deploy people.

Some of Spire’s satellites already collect soil moisture measurements, and coverage will expand as Spire launches more nanosatellites, promising another tool in the wildfire management toolbox.

Dry season versus wet season

“Our upcoming launches will continue to improve soil moisture readings and weather forecasting,” said Cromarty, “ensuring emergency management teams will gain increased insight and detail with every successive launch.”

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