The global weather forecasting industry is an essential and rapidly evolving sector, driven by a growing demand for accurate, timely, and hyper-localized weather data. Once a domain primarily for government agencies and academic institutions, the industry has expanded significantly, with private companies now playing a dominant role in providing a wide range of specialized services. This report provides a detailed overview of the industry, including market size, key drivers, emerging technologies, and future outlook.
Market Overview and Size
The global weather forecasting services market is a multi-billion dollar industry that is experiencing steady growth. In 2024, the market was valued at approximately USD 2.55 to USD 2.69 billion [1, 2, 4]. Analysts project a robust Compound Annual Growth Rate (CAGR) of 6.22% to 7.7% from 2025 to 2035 [1, 2, 4]. This growth is expected to propel the market to a valuation of around USD 4.95 billion by 2035 [2].
North America currently holds the largest share of the market, thanks to its well-developed technological infrastructure and high government and private sector expenditure on meteorological research [2, 4]. However, the Asia-Pacific region is poised for the fastest growth, fueled by rapid urbanization, industrialization, and an increasing susceptibility to climate-related disasters [2].
Key Industry Drivers
Several factors are propelling the growth of the weather forecasting market:
- Extreme Weather Events: The increasing frequency and intensity of extreme weather events, such as hurricanes, floods, droughts, and wildfires, directly linked to climate change, have made accurate forecasting indispensable for disaster preparedness, risk mitigation, and public safety [3, 4, 6]. For example, a single-day extreme precipitation event has become substantially more common since the 1980s [6].
- Technological Advancements: The industry is being revolutionized by innovations in computing, remote sensing, and data analytics. Supercomputers and high-resolution numerical weather prediction (NWP) models provide more precise forecasts. The rise of AI and machine learning (ML) is also a significant driver, enabling the processing of vast datasets and improving predictive accuracy [3, 5, 8].
- Growing Demand from End-Use Sectors: The need for precise weather information is expanding beyond traditional applications. Key sectors include:
- Agriculture: Farmers rely on forecasts to optimize crop production, manage irrigation, and mitigate risks from frost or drought [1, 2, 3].
- Aviation: Accurate forecasts are critical for flight planning, ensuring passenger safety, and optimizing fuel efficiency by taking advantage of atmospheric conditions like the jet stream [3].
- Energy: Utility companies use weather forecasts to anticipate energy demand for heating and cooling, while the renewable energy sector (solar and wind) depends on them for efficient power generation and grid stability [2, 3].
- Logistics and Transportation: Accurate weather data helps logistics companies plan routes, avoid delays, and ensure the safety of cargo [4].
Key Players
The weather forecasting industry is a mix of established government meteorological agencies and a growing number of influential private companies [5]. Key players include:
- AccuWeather: A global leader providing a wide range of services to consumers and businesses. The company leverages AI, ML, and big data to offer highly localized forecasts [5].
- The Weather Company (an IBM subsidiary): A major provider of weather data and technology platforms for various industries, including aviation, energy, and media [5].
- DTN: Specializes in providing weather intelligence and decision-support tools for the agriculture and energy sectors [5].
- StormGeo: A Norwegian company offering weather intelligence and advanced forecasting solutions, particularly for the maritime, oil and gas, and renewable energy sectors [5].
- Vaisala: A Finnish company known for manufacturing electronic instruments and measurement systems used in meteorology and other fields [5].
Other notable players include AerisWeather, Fugro, and BMT Group, among others [5].
Emerging Trends and Technologies
The future of weather forecasting is being shaped by several groundbreaking trends:
- Artificial Intelligence and Machine Learning: AI and ML are poised to transform the industry by creating “data-driven” models that can analyze massive datasets much faster and at a lower computational cost than traditional NWP models [8]. These models can identify complex patterns and improve the accuracy of short-term, localized forecasts, though challenges remain in their interpretability and ability to predict extreme events [8, 9].
- The Internet of Things (IoT): The proliferation of IoT devices and distributed sensor networks is creating an unprecedented volume of real-time weather data. This data, when integrated with traditional sources, enhances the resolution and accuracy of forecasting models [7, 8].
- Satellite Technology and Observational Systems: Advancements in satellite technology, including compact satellites and high-resolution sensors, are providing more detailed and accurate data [7]. Private companies like Spire are also launching their own constellations of satellites to collect valuable atmospheric data for commercial use [10].
- Hyper-Localized and Impact-Based Forecasting: The industry is moving beyond general forecasts to provide hyper-localized, street-level predictions that are tailored to a user’s specific location and needs [8]. Furthermore, there is a shift toward “impact-based forecasting,” where the focus is on the effects of the weather (e.g., flood inundation) rather than just the meteorological conditions themselves [7].
Challenges and Opportunities
Despite its rapid growth, the industry faces several challenges. Traditional NWP models are computationally expensive and struggle with short-term, localized predictions, while new AI-based models face hurdles in interpretability and a lack of high-quality training data for all scenarios [8, 9]. Additionally, there is a global disparity in forecast accuracy, with some regions lacking the necessary observational networks and infrastructure [8].
However, these challenges present significant opportunities. The development of more efficient data assimilation systems and the integration of diverse data sources—from drones to commercial aircraft—can fill data gaps [10]. There is also a growing market for providing specialized, high-resolution forecasting services to small and medium-sized enterprises (SMEs) that previously relied on less sophisticated weather information [4]. As the world grapples with a changing climate, the demand for sophisticated weather intelligence will only continue to grow, making the weather forecasting industry a critical component of global economic resilience and public safety.
Citations
[1] IMARC Group. “Weather Forecasting Services Market Size & Forecast 2033”.
[2] Spherical Insights & Consulting. “Top 20 Companies in Weather Forecasting Services Market Worldwide 2025”.
[3] IMARC Group. “Weather Forecasting Services Market Size, Growth & Forecast 2033”.
[4] Research Nester. “Weather Forecasting Services Market size crossed $2.69 billion in 2024 | Eyes $7.06 billion by 2037”.
[5] MarketsandMarkets. “Weather Forecasting Systems Companies -Vaisala (Finland) and DTN (US) are the Key Players”.
[6] Environmental Protection Agency (EPA). “Climate Change Indicators: Weather and Climate”.
[7] Royal Meteorological Society. “The future of weather forecasting”.
[8] ResearchGate. “Challenges and Opportunities in Numerical Weather Prediction”.
[9] MDPI. “Data-Driven Weather Forecasting and Climate Modeling from the Perspective of Development”.
[10] NOAA Institutional Repository. “Challenges and Opportunities in Numerical Weather Prediction”.
