Market Overview:

The weather forecasting services market is experiencing rapid growth, driven by increased frequency of extreme weather events, rapid advancements in AI and data analytics, and escalating demand from commercial and industrial end-users. According to IMARC Group's latest research publication, "Weather Forecasting Services Market Size, Share, Trends and Forecast by Forecasting Type, Purpose, Organization Size, End User, and Region, 2026-2034", the global weather forecasting services market size was valued at USD 2.5 Billion in 2025. Looking forward, IMARC Group estimates the market to reach USD 4.7 Billion by 2034, exhibiting a CAGR of 7.17% from 2026-2034.

This detailed analysis primarily encompasses industry size, business trends, market share, key growth factors, and regional forecasts. The report offers a comprehensive overview and integrates research findings, market assessments, and data from different sources. It also includes pivotal market dynamics like drivers and challenges, while also highlighting growth opportunities, financial insights, technological improvements, emerging trends, and innovations. Besides this, the report provides regional market evaluation, along with a competitive landscape analysis.

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Our report includes:

• Market Dynamics
• Market Trends and Market Outlook
• Competitive Analysis
• Industry Segmentation
• Strategic Recommendations

Growth Factors in the Weather Forecasting Services Market

• Increased Frequency of Extreme Weather Events

The rising global incidence of severe weather is a critical catalyst for market growth. Climate unpredictability, resulting in more frequent and intense phenomena like wildfires, floods, and powerful storms, necessitates advanced forecasting and early warning systems. Governments and emergency services worldwide rely on these services to mitigate humanitarian and economic damage. For instance, data from the National Oceanic and Atmospheric Administration (NOAA) confirms a surge in billion-dollar weather-related disasters in recent periods. This growing risk pushes governmental agencies and commercial enterprises to invest heavily in resilient infrastructure and sophisticated weather intelligence tools to protect assets, ensure public safety, and maintain operational continuity.

• Rapid Advancements in AI and Data Analytics

The integration of Artificial Intelligence (AI) and Machine Learning (ML) is fundamentally transforming the accuracy and speed of weather prediction. These technologies process massive datasets—including satellite, radar, and ground-based sensor readings—at unprecedented speeds, enhancing the resolution and lead time of forecasts. For example, some AI-powered models, such as Google’s GraphCast, have shown the ability to generate accurate ten-day forecasts significantly faster than traditional, physics-based numerical models, and with less computational cost. This technological leap enables the creation of hyper-local, high-resolution models, which are vital for industry-specific applications, allowing businesses to make more precise, data-driven decisions in real-time.

• Escalating Demand from Commercial and Industrial End-Users

The necessity for precise weather data has extended far beyond public safety and aviation, now deeply penetrating major commercial sectors. The transport and logistics industry, for example, heavily relies on forecasting to optimize shipping routes, manage inventory, and prevent delays caused by adverse conditions. In the United States, the Federal Highway Administration (FHWA) estimates that weather is responsible for a substantial percentage of all roadway delays annually, leading to billions in lost vehicle hours for trucking companies. Similarly, the burgeoning renewable energy sector depends on accurate forecasts of wind and solar irradiance to optimize energy production and manage grid stability, driving a need for specialized and high-fidelity service providers.

Key Trends in the Weather Forecasting Services Market

• Hyper-Local and 'Nowcasting' Services

A key trend is the development of ultra-short-term, hyper-local forecasting, often referred to as "Nowcasting." This trend leverages high-frequency data from sources like localized radar and IoT sensors, combined with deep learning algorithms, to provide minute-by-minute predictions for a specific, small geographical area. A concrete example is the deployment of AI-based systems that provide immediate, high-resolution updates on local precipitation or wind shear, critical for sectors like drone delivery and precision agriculture. This level of granularity allows farmers to optimize irrigation or pesticide application based on conditions for their exact field, and helps construction sites make real-time decisions to ensure worker safety.

• AI-Driven Sub-Seasonal to Seasonal (S2S) Forecasting

The market is seeing a major trend towards reliable long-range prediction, specifically Sub-Seasonal to Seasonal (S2S) forecasts, which cover timeframes from two weeks up to two years. Unlike traditional medium-range forecasts, S2S models use AI to identify long-term climate patterns and anomalies in sea surface temperatures, atmospheric pressure, and more. A real-world application is in the energy trading and utilities sector, where advanced S2S models are used to anticipate temperature and precipitation anomalies for the coming months. This foresight allows energy companies to better manage natural gas reserves, optimize hydroelectric dam operations, and proactively position resources to mitigate risk from extended heatwaves or drought.

• Integration with Decision Support Platforms

Another emerging trend is the seamless integration of raw weather data into broader decision-support and workflow platforms via APIs (Application Programming Interfaces). Rather than a separate weather report, the forecast becomes an embedded input for business intelligence and operational software. For example, a global logistics company can use a weather API to feed real-time route optimization software, which automatically reroutes shipments to avoid severe weather-impacted ports or roads. Similarly, insurance companies are embedding these weather APIs into their risk modeling platforms, allowing them to instantly assess the potential claims exposure of their portfolio to an incoming hurricane or flood event, streamlining preparation and response.

Leading Companies Operating in the Global Weather Forecasting Services Industry:

• AccuWeather, Inc.
• AEM
• Climavision
• CustomWeather, Inc.
• DTN
• Pelmorex
• Spire Global
• StormGeo
• The Tomorrow Companies Inc.
• The Weather Company LLC
• Vaisala

Weather Forecasting Services Market Report Segmentation:

By Forecasting Type:

• Short-range Forecasting
• Medium-range Forecasting
• Long-range Forecasting

Medium-range forecasting leads the market with 29.6% share in 2024, balancing accuracy and planning needs for sectors like agriculture, aviation, logistics, and energy, covering three to ten days.

By Purpose:

• Operational Efficiency
• Safety
• Others

Operational efficiency driven by industries aiming to streamline processes and reduce costs through accurate weather forecasts, enhancing productivity in agriculture, logistics, and energy.

By Organization Size:

• Large Enterprises
• Small and Medium-Sized Enterprises

Large enterprises dominate with 71.2% market share in 2024, requiring high-precision forecasts for critical operations across various sectors, investing in advanced weather monitoring technologies.

By End User:

• Transportation
• Aviation
• Energy and Utilities
• Banking, Financial Services and Insurance (BFSI)
• Agriculture
• Media
• Manufacturing
• Retail
• Others

Transportation utilizes weather forecasts for route optimization and safety, minimizing delays and accidents through proactive adjustments.

Breakup By Region:

• North America (United States, Canada)
• Asia Pacific (China, Japan, India, South Korea, Australia, Indonesia, Others)
• Europe (Germany, France, United Kingdom, Italy, Spain, Russia, Others)
• Latin America (Brazil, Mexico, Others)
• Middle East and Africa

North America holds the largest market share at 28.9% in 2024, driven by technological advancements and reliance on accurate weather data across key industries like aviation and agriculture.

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