In the insurance world, the “once-in-a-century” storm has become a yearly occurrence. Global insured losses reached $127 billion in 2025,¹ marking the sixth consecutive year that payouts exceeded the $100 billion threshold.²

Perhaps more striking is the frequency of these events. Last year saw 30 separate disasters causing over $1 billion in insured losses each³ — far exceeding the historical average of 17. Traditional risk models built on broad geographic averages are no longer sufficient to address this rising volatility.

Recently, The Weather Company experts Matt McCrary (Insurance Sales Lead) and Matthew Porcelli (Solutions Engineer) discussed this fundamental shift with Insurance Thought Leadership. Their core insight? The industry is reaching an inflection point where hyperlocal weather data must become a dynamic, strategic asset.

What is hyperlocal weather data in insurance?

Hyperlocal weather data in insurance refers to high-resolution atmospheric insights mapped to specific GPS coordinates (often down to a 500-meter to 1-kilometer grid) rather than broad ZIP codes. For insurers, this enables property-level risk assessments for specific perils like hail, wind, and wildfire.

Solving the “over-the-wall” data problem

For years, the primary challenge for carriers hasn’t been a lack of data, but a lack of clarity. Many insurers receive raw weather streams that are difficult to integrate into existing underwriting or claims workflows.

As Porcelli and McCrary highlighted, carriers must bridge the gap between meteorological science and operational strategy. By integrating high-resolution, timestamped data from lightning sensors, radar, and LiDAR, insurers can move from broad regional assumptions to surgical business decisions.

Turning uncertainty into measurable risk via probabilistic forecasting

A major takeaway from our recent discussion is the power of probabilistic forecasting. Unlike a standard deterministic forecast that predicts a general “chance of weather,” a probabilistic model quantifies the likelihood of specific outcomes — such as the exact probability of 2-inch hail hitting a specific cluster of assets.

This level of precision enables:

• Tailored underwriting: Pricing risk based on the true exposure of a specific home or commercial building.
• Claims volume prediction: Anticipating the “First notice of loss” (FNOL) surge before the storm even clears the area.
• Fraud detection: Utilizing forensic meteorology to verify if the weather conditions reported in a claim actually occurred at that specific timestamp and location.

The growth of parametric insurance and “ground truth”

The shift toward hyperlocal data is fueling the rapid growth of parametric (event-based) insurance. Unlike traditional policies that require physical damage inspections, parametric products are triggered by measurable thresholds — such as wind speeds exceeding a specific limit or rainfall totals.

This model offers three distinct advantages:

1. Accelerated payouts: Provides liquidity to policyholders in hours or days, not weeks.
2. Reduced loss adjustment expenses (LAE): Minimizes the need for on-the-ground adjusters for every event.
3. Objective verification: Success depends on “ground truth”—verifiable data from mesonets, satellite, and synthetic aperture radar.

Powering the next generation of weather-resilient insurance

At The Weather Company, we don’t just observe the weather; we provide the programmatic infrastructure that allows insurers to operationalize it. Our suite of weather data APIs and intelligence platforms is designed to integrate seamlessly into existing core systems, from underwriting engines to claims management dashboards.

Our key offerings for the property and casualty sector include:

• Standard and enhanced weather APIs: Access real-time, historical, and forecast data for over 2 billion locations globally. Our APIs deliver 15-minute hyperlocal updates, allowing for precise “nowcasting” of severe events.
• Historical weather data and forensic services: Validate claims with 10+ years of archived atmospheric data. Our forensic tools provide the “ground truth” evidence needed to confirm hail size, wind gusts, and lightning strikes at exact GPS coordinates, helping reduce exposure to fraudulent claims.
• Probabilistic forecasting suite: Move beyond binary “rain or shine” forecasts. Our AI-driven ensemble modeling quantifies the likelihood of specific risk thresholds, providing the data confidence required to trigger parametric insurance payouts automatically.
• Weather alerts and notifications: Enhance policyholder loyalty by delivering targeted, automated alerts. By notifying customers to move assets before a storm hits, you can actively reduce claim frequency while improving your Net Promoter Score (NPS).

Through industry-leading accuracy and enterprise-grade reliability (99.95% uptime), we help carriers turn atmospheric uncertainty into a measurable competitive advantage.

Moving toward climate resilience

The convergence of AI, machine learning, and hyperlocal data is turning insurers into partners in safety. By sending proactive alerts — advising a policyholder to move a vehicle before a hail cell arrives — carriers are preventing claims before they happen.

As we navigate an increasingly volatile climate, the carriers that thrive will be those that treat weather intelligence as the backbone of their resilience strategy.

Try naming a business that isn’t impacted by weather. Go ahead – really pressure test it. Weather touches every corner of the global economy. Whether it’s a farm, a freight company, a fashion brand, or even a software firm with a fully remote team, weather finds a way in.

Yes, even in sectors that feel “weather-proof,” its influence shows up in unexpected ways. That remote software firm? A localized heat wave or severe storm can strain regional power grids, risking the uptime and productivity of a distributed workforce. Your data center? Temperature spikes can strain the cooling systems. Your employees? Sunlight levels can affect human cognition and productivity.

Accepting that weather impacts your business is the first step; building resilience against it is the second. This shift from reactive to proactive requires a sophisticated pipeline that translates atmospheric physics into operational logic.

How do organizations turn weather data into actionable insights?

At The Weather Company, every real-world application starts with a rigorous process that transforms raw environmental signals into strategic intelligence:

1. Collection: More than 75 billion terabytes of weather data are ingested daily, sourced from satellites, radar mosaics, aircraft, government feeds, and a global network of ~390,000 personal weather stations, with dense urban and suburban coverage.
2. Normalization: This raw data is cleaned, quality-controlled, and standardized to maintain consistency across inputs. It’s then structured into formats ready for modeling and distribution.
3. Integration: APIs built for enterprise-scale operations – supporting billions of requests per day – deliver this data into systems such as ERP platforms, IoT networks, digital twins, and custom applications.
4. Application: AI-powered technologies like WxMix synthesize over 100 global forecast models, including The Weather Company’s own GRAF^® system. These models are continuously optimized for every location and weather variable, surfacing predictive insights that businesses can act on in real time. Independent evaluations rank our forecasts #1 in accuracy across both global and regional scales.¹ 

How is weather data driving innovation across industries?

Across industries, businesses are integrating weather intelligence more deeply than ever to unlock value and build long-term resilience:

• Aviation: Weather is responsible for roughly 75% of all flight delays,² and airlines depend on real‑time weather insights to optimize routing, reduce fuel use, and enhance safety. To combat this, more than 44,000 flights in the U.S. alone³ rely on weather forecasts every day to plan safer, more efficient routes, reduce fuel burn, and minimize disruptions.
• Energy & utilities: In summer 2025, U.S. electricity demand across the Lower 48 states set new peak records twice, reaching 759,180 megawatts as hot weather drove up cooling needs – nearly 2% higher than the prior year’s peak.⁴ High‑resolution weather intelligence helps utilities anticipate demand swings, balance renewables, and plan grid operations more effectively under weather‑driven stress.

• Agriculture: Across Europe, extreme weather causes over €28 billion ($31.9 billion) in annual losses for farmers, according to EU-backed analysis.⁵ Flooding, drought, heatwaves, and storms continue to disrupt crop yields, supply chains, and agricultural productivity. To mitigate these risks, producers are increasingly automating their resilience. Today, 35% of global weather API requests support real-time decisions on planting and crop health,⁶ allowing growers to integrate hyper-local soil and atmospheric data into their daily operations.

• Retail: With over $1 trillion in global sales influenced by weather,⁷ brands use seasonal and localized weather signals to optimize promotions, staffing, and inventory, down to the store level.

• Insurance & finance: Global insured losses from natural catastrophes were projected to reach $107 billion in 2025, with the U.S. accounting for a staggering 83% of that total.⁸ As wildfires and severe storms push losses higher, insurers are turning to high-resolution weather forecasts and risk modeling tools to better price policies, reduce exposure, and support more resilient coverage strategies.

• Construction: Weather regularly disrupts construction timelines – damaging materials, delaying crews, and forcing costly rework. In 2024 alone, the U.S. faced 27 separate billion-dollar weather disasters, totaling more than $182.7 billion in losses.⁹ By integrating forecast data into scheduling tools, project teams can plan around conditions like rain, wind, and heat to reduce downtime and stay on track.

• Sports & entertainment: Weather and climate extremes are increasingly disrupting major sports and outdoor entertainment events worldwide. In 2025, severe conditions such as wildfires, high winds, and heat forced cancellations and rescheduling of professional competitions (including PGA golf events and marathons), affecting revenue and the fan experience in an industry valued at $2 trillion.¹⁰ Organizers are integrating real‑time weather intelligence to make safer go/no‑go decisions, adjust schedules, and protect athletes, spectators, and operations.

The rise of the “Shadow CEO”

This cross-industry momentum reflects a fundamental shift: weather is no longer just a background disruption; it is the “Shadow CEO” of the global economy. It quietly influences shipping routes, energy costs, and staffing needs every single day.

This rising awareness is shifting weather from a background disruptor to a boardroom priority.

What’s next for data-driven problem solving in weather and climate intelligence?

As weather volatility intensifies, businesses are moving beyond basic forecasting and embracing climate intelligence – a more comprehensive approach that layers in air quality, environmental data, and AI-driven insights.

• Generative AI is unlocking new ways to simulate risk, test mitigation strategies, and optimize business continuity plans, before disruption occurs.
• Open data collaboration is expanding, with public and private sectors sharing environmental intelligence to advance climate resilience at scale.
• AI-ready datasets from The Weather Company are purpose-built for integration into digital twins, planning tools, and real-time operations systems. These integrations help organizations anticipate disruption rather than simply react to it.

And business leaders are taking note: in a recent study, 100% of surveyed executives agreed that weather intelligence gives their business a competitive edge.¹³ When data becomes both scalable and strategic, weather shifts from a source of risk to a driver of opportunity.

Built for developers: Scalable, high-impact weather data APIs

APIs are at the heart of it all, making it easy for developers and data teams to bring high-resolution weather insights straight into the tools they already use. Add AI into the mix, and suddenly you’re spotting patterns – like a storm that could delay shipments or a cold snap that’ll drive up energy demand – so businesses can stay one step ahead.

The Weather Company offers a robust portfolio of enterprise-grade weather APIs designed to deliver real-time, forecast, and historical weather intelligence at scale. Trusted across industries, our APIs support over 200 billion calls per day with enterprise-grade performance, low latency, and secure integration.

These RESTful APIs enable access to:

• Hyper-local forecasts (hourly, daily, and 15-minute “nowcasts”)
• Historical conditions and almanac data for trend analysis
• Severe weather alerts from trusted government sources
• Environmental and lifestyle indices like air quality, UV risk, pollen, and even use cases for driving difficulty, power disruption, and travel comfort
• Marine and aviation insights, geospatial mapping layers, and current site-based conditions for any latitude/longitude

These APIs are built for flexible implementation – whether you’re powering operational dashboards, IoT platforms, public safety alerts, or mobile apps.

A success story in weather intelligence

Want to see how organizations are already using weather data to solve complex challenges? One example is CAA Club Group, which worked with The Weather Company to improve road safety and operational readiness using real-time weather insights.

For a broader look at how accurate forecasts are driving measurable impact across transportation, energy, and public safety, read our Weather Means Business report.

Ready to build a weather-resilient business?

Don’t just react to the elements — plan for them. Start your free trial to explore our enterprise-grade weather data and start making smarter, data-driven decisions.

Weather is one of the most complex, high-volume data streams organizations can leverage – and one of the easiest to get wrong. For operations leaders in logistics, energy, and agriculture, the gap between an acceptable weather data model and a truly accurate one comes down to the precision, freshness, and validation of the underlying data.

What was once a general prediction must now become a location-specific, real-time decision input. To get there, businesses are turning to proprietary AI forecasting systems layered with human insight — systems capable of delivering resolutions as detailed as 3.5km while keeping pace with rapidly changing conditions.

Understanding how weather data is structured and applied reveals why precision, validation, and granularity now drive competitive advantage.

Why does weather data matter?

Weather’s impact is constant, but how businesses respond to it is changing. Companies are shifting from reactive strategies to proactive planning driven by high-resolution, real-time weather data.

The cost of inaction is steep: In 2023 alone, weather-related disruptions caused over $90 billion in damages across U.S. industries¹ – a number that’s pushing more businesses to focus on resilience through proactive weather planning.

As climate variability increases, highlighted by 28 separate billion-dollar weather and climate disasters in the U.S. in 2023 alone,² so does the need for predictive, adaptable tools. Weather intelligence is now a core component of decision-support tools across sectors like energy, agriculture, and logistics.

How is weather data structured and organized?

Understanding weather data starts with knowing its three main types:

• Real-time data – current observations from radar, satellites, and sensors
• Historical data – long-term climate patterns and trends
• Predictive data – forecast models that simulate future outcomes, including:
  • GRAF^® – A proprietary global model that delivers high-resolution forecasts as often as every five minutes, down to a kilometer level.
  • WxMix – A continuously optimized blend of more than 100 weather models, customized per location, variable, and forecast window to maximize accuracy.
  • HOTL (Human-over-the-Loop) – Oversight from 100+ expert meteorologists who refine AI-generated forecasts based on real-world conditions and operational context.

These tools allow enterprises to create forecasts that are on demand, location-specific, and AI-optimized in real time. That capability is made possible by advances in AI and weather technology.

How is weather data analyzed?

At The Weather Company, forecast accuracy is powered by more than automation. WxMix, our advanced multi-model ensemble, analyzes approximately 100 global weather models. Using AI, it synthesizes and optimizes inputs by location, parameter, and timeframe – maximizing accuracy where and when it matters most.

But it doesn’t stop there. Through Human-over-the-Loop (HOTL) intelligence, our team of over 100 expert meteorologists adds critical oversight so that forecasts are tweaked to reflect real-world complexities algorithms alone might miss. The result is a system that delivers real-time precision with the confidence of expert validation.

What defines reliable weather intelligence?

Not all data is created equal. The most reliable weather intelligence is:

• Accurate – validated against historical and current observations
• Granular – spatially and temporally precise
• Timely – updated continuously (not just 4x a day like legacy systems)
• Validated – tested by third-party accuracy audits

A ForecastWatch study found The Weather Company to be nearly 4x more likely to be the most accurate forecaster compared to the next-best weather forecast provider.³

Standard data vs. precision intelligence: A performance comparison

What turns weather information into intelligence?

Information tells you the weather is changing. Intelligence tells you what that change will cost and how much time you have to act.

At The Weather Company, that transformation happens through a refinement process that filters raw atmospheric data into signals that are specific, validated, and decision-ready. It starts with granularity – moving from broad forecasts to 3-kilometer, 15-minute updates that detect microclimates across a delivery network. Then comes validation, using a blend of over 100 models (WxMix) checked against real-world conditions from sensors, radar, and aircraft.

Contextualization adds historical insight – understanding how past weather patterns affect current risk, like black ice or power outages. Finally, human expertise enters the loop. Our meteorologists don’t just monitor model output; they translate it into actionable guidance, helping enterprises shift from reaction to optimization.

Together, this approach turns noise into signals and weather into a strategic input for smarter decisions.

Weather intelligence is most effective when it connects siloed enterprise systems. By combining high-resolution forecasts with IoT data, live inventory, and ERP platforms, organizations can build a digital twin of their operations. With that visibility, teams can model how future weather may affect supply chains, test response strategies in advance, and shift from reacting to planning.

How is weather data delivered?

Enterprise-grade weather data needs to be accessible, fast, and flexible. That’s why The Weather Company delivers insights via robust, scalable Weather Data APIs built to support real-time decisions across logistics, energy, insurance, and more.

Our APIs give you access to real-time, historical, and predictive weather data with industry-leading accuracy and sub-hourly updates, optimized for integration into your existing platforms. Start a free trial to experience the difference for yourself.

Why near-accurate isn’t accurate enough

If your current provider can’t clearly explain how their forecasts are built, validated, and applied, you may be optimizing against the wrong reality.

As weather becomes more volatile and business cycles more complex, operational success will hinge on forecast intelligence, not just awareness. The next competitive advantage won’t come from knowing the weather, but from engineering around it.

In an age where weather isn’t just small talk but instead, the headline, the impact of changing weather patterns on people and businesses is more significant than ever. From everyday weather conditions to extreme temperatures, the environment is now a critical factor driving strategic decision-making in everything from supply chain management to consumer engagement. As global temperatures continue to rise, businesses need to see the opportunity weather presents. At The Weather Company, we help businesses use weather intelligence to drive business resilience, growth, and competitive advantage.

Adapting at the speed of weather

We’ve all seen it. The world is witnessing unprecedented changes in weather patterns. This intensifying weather volatility is fueling more frequent extreme weather events and economic upheavals.

As a result, keeping tabs on the weather has made The Weather Channel digital properties a habitual touchpoint for over 360 million monthly average users¹ worldwide. This widespread reliance shows the powerful influence of weather on consumer behavior. In 2023 alone, Adobe projected that weather would influence over $13.5 billion (about $42 per person) in U.S. e-commerce sales³ — the equivalent of an extra Cyber Monday.

The message is clear — businesses need to evolve from reactive to proactive, weaving weather data deeply into their strategic fabric.

How do meteorologists predict the weather?

Weather forecasting is the process of combining scientific insights, data, and technology to assess future atmospheric conditions. Meteorologists observe, study, and predict changes in precipitation, temperature, wind, and more.

In today’s data-rich environment, meteorologists combine real-time observations, advanced modeling techniques, and expert interpretation to produce accurate forecasts. But how do weather forecasters predict the weather, and how are weather predictions made?

How a weather forecast is made

Fundamentally, the process begins with gathering data and using that information to feed forecasting models. These simulations help anticipate everything from temperature changes to the path of major storms.

At The Weather Company, we combine human meteorological expertise with advanced AI to create forecasting capabilities that neither could achieve on its own. Our team of over 100 expert meteorologists works in real-time with our AI systems, providing critical oversight and adding invaluable human intelligence to the process – without slowing things down.

Essentially, how to predict the weather is a four-pronged approach:

1. Observe
What is the weather like now? We ingest data from a collection of instruments to observe conditions on the surface and in the upper atmosphere, including:

• Weather radar: Detects precipitation and storm intensity.
• Weather balloons: Measure upper-atmosphere conditions.
• Barometers and thermometers: Monitor pressure and temperature.
• Satellites: Observe cloud cover and storm systems globally.
• Weather stations: Collect ground-level conditions.
• IoT sensors: Deliver hyperlocal temperature, humidity, and pressure data.

2. Model
How will the weather evolve? Numeric Weather Prediction (NWP) models take current atmospheric conditions as a starting point to project a forecast. There are many well-known models, such as the European Centre for Medium-Range Weather Forecasts (ECMWF), the Global Forecast System (GFS), and The Weather Company’s proprietary, hyperlocal Global High-Resolution Atmospheric Forecasting System (GRAF).

Instead of relying on a single model, our AI-driven, multi-model ensemble, WxMix, synthesizes and optimizes over 100 models, ensuring that we always leverage the best available science.

3. Produce
We translate model outputs into actionable insights, such as daily highs/lows, severe weather alerts, and turbulence maps.

4. Deliver
Forecasts are delivered instantly through apps and websites, such as The Weather Channel, Weather Underground, and Storm Radar, which feature APIs that provide real-time and historical data, aviation dashboards, broadcast media systems and displays, as well as mission planning and simulation tools.

Our strength lies in modeling, productization, and delivery – applying advanced modeling techniques, AI integration, and human oversight to produce timely, accurate forecasts.

The role of AI in accurate weather forecasting

AI is rapidly transforming weather forecasting, significantly enhancing its accuracy and speed. This rapid processing enables more frequent forecast updates, which is crucial for quickly evolving weather events, such as severe thunderstorms. In particular, new Deep Learning-based AI models (DL-NWP) are showing promise in improving the accuracy, granularity, and cost-effectiveness of traditional models, while also demonstrating an enhanced ability to depict the range and likelihood of potential weather outcomes, enabling better decision-making.

Long before “AI” became a buzzword, The Weather Company was harnessing the power of sophisticated algorithms, statistical models, and data-driven computational methods to improve weather forecasting and deliver actionable insights to consumers and businesses globally.

Today, we’re working with partners like NVIDIA to actively develop new deep learning approaches and incorporate the latest AI models into our forecasting processes to continuously improve forecast precision.

Who has the most accurate weather forecast?

According to the latest ForecastWatch study, The Weather Company is nearly 4x more likely to be the most accurate weather forecaster than the next closest competitor.⁶

Building on our commitment to proven forecast accuracy, we continue to innovate and challenge ourselves to do even better.

• Consistent #1 finishes: The most 1st place finishes each year since ForecastWatch measurement began.^{7 8}
• Regional accuracy dominance: The most accurate forecast provider is most often in 7 out of 8 regions.⁹
• Leading in longer-range forecasts: Nearly 6x more likely to be the most accurate when measuring a 14-day time horizon.¹⁰

Benefits of accurate weather forecasting

Weather affects nearly every sector — from supply chains and staffing to safety and customer engagement. It impacts an estimated $3 trillion of the U.S. economy annually and influences 30% of global GDP.¹¹ Even a 1ºC temperature shift can cause a 1.2% swing in consumer spending.¹²

Simply, better accuracy means better decisions. Accurate weather forecasting can deliver measurable value across industries:

Aviation: For airlines, accurate forecasts are crucial for planning routes, minimizing delays, and enhancing safety. Weather is responsible for nearly 75% of flight delays,13 highlighting the importance of accurate, proactive forecasting for keeping flights on schedule and passengers safe. Turbulence prediction, wind shear detection, and runway condition forecasts enable flight crews to make informed decisions that protect passengers and optimize fuel consumption.

Advertising: Weather impacts consumer behavior, and accurate forecasts enable brands to align their messaging with what people are experiencing in the moment. The Weather Company’s advertising solutions use real-time weather and location insights to power smarter campaign delivery – reaching consumers when and where it matters most. These insights help brands anticipate shifts in mindset and purchase intent, such as promoting allergy relief ahead of high pollen days or iced coffee on a warmer-than-usual afternoon. With tools like Weather Targeting,  advertisers can dynamically tailor messaging by region, season, or even zip code – improving performance while maintaining privacy-forward practices..

Media: Reliable forecasts built into broadcast media solutions keep viewers informed and engaged. Localized, timely forecasts build trust, improve viewer retention, and support higher ad revenue. Broadcasters can promote their accuracy, backed by The Weather Company, as a differentiator in competitive media markets.

Government & defense: From storm response to mission planning, government and defense agencies rely on accurate forecasts for operational readiness. Whether preparing for hurricanes or managing logistics during winter storms, accurate data helps leaders act decisively and allocate resources efficiently.

Given the ever-increasing reliance on precise weather insights, what’s next for forecasting?

What is the future of forecasting?

Forecasting is evolving to become faster, more personalized, and more precise. Key innovations include:

• Probabilistic forecasting: Instead of offering a single deterministic outcome, probabilistic forecasts show a range of possible scenarios and the likelihood of each one. This helps decision-makers understand risk and uncertainty more clearly – for example, while a deterministic forecast might indicate an expected snowfall amount of 5 inches in the next 24 hours, a probabilistic forecast reveals there’s also a chance of as little as 1 inch or as many as 10 inches of snowfall in that time, which might prompt a user to change plans or prepare alternatives accordingly.
• AI-powered modeling: Artificial intelligence and machine learning are increasingly playing a role in enhancing forecast accuracy. These systems can rapidly process massive volumes of historical and real-time data, identify subtle patterns, and provide a range of outcomes known as ensemble modeling, which supports probabilistic forecasting and gives a more complete picture of the weather’s nuances and variability. AI is particularly useful for refining forecasts in dynamic or hard-to-model environments.
• Street-level resolution: Forecasts are becoming hyperlocal, not just city-wide, but down to neighborhoods and even individual streets. This level of detail supports everything from route planning in logistics to micro-targeted alerts for consumers.

Precision, preparedness, and progress

Ultimately, accurate weather forecasting isn’t just about knowing if it will rain tomorrow; it’s about making smarter, more informed decisions that protect lives, livelihoods, and economies. The synergy of human meteorological insight and advanced AI is pushing the boundaries of what’s possible. Moving forward, our unwavering commitment to precision will continue to empower individuals and businesses to thrive in an ever-changing world.