Market Overview
According to DIResearch's in-depth investigation and research, the global Weather Forecasting Technology market size will reach 16,307 Million USD in 2025 and is projected to reach 28,349 Million USD by 2032, with a CAGR of 8.22% (2025-2032). Notably, the China Weather Forecasting Technology market has changed rapidly in the past few years. By 2025, China's market size is expected to be Million USD, representing approximately % of the global market share.
Research Summary
Weather forecasting technology encompasses a diverse array of tools and techniques utilized to predict atmospheric conditions and generate forecasts. Key components include meteorological instruments, such as weather stations, satellites, and radar systems, which collect data on temperature, humidity, pressure, wind speed and direction, and precipitation. Advanced computer models, known as numerical weather prediction models, utilize complex algorithms and physics equations to simulate atmospheric processes and forecast future weather patterns. These models assimilate observational data from multiple sources to initialize forecasts and improve accuracy. Additionally, advancements in remote sensing technologies, data assimilation techniques, and computational power have led to significant improvements in forecast accuracy and lead time. Integration of artificial intelligence and machine learning algorithms is also enhancing forecast capabilities by analyzing large datasets and identifying patterns in atmospheric behavior. Overall, weather forecasting technology continues to evolve, providing invaluable insights to support decision-making in various sectors such as agriculture, transportation, energy, and disaster management.
The major global suppliers of Weather Forecasting Technology include All Weather, Inc. (AWI), Campbell Scientific, Inc, Columbia Weather Systems, Inc., General Acoustics e.K., Gill Instruments Limited, IBM (The Weather Company), Lockheed Martin Corporation, Met One Instruments Inc., MORCOM International, Optical Scientific, Inc., Pulsonic, Skye Instruments Limited, Vaisala, etc. The global players competition landscape in this report is divided into three tiers. The first tier comprises global leading enterprises that command a substantial market share, hold a dominant industry position, possess strong competitiveness and influence, and generate significant revenue. The second tier includes companies with a notable market presence and reputation; these firms actively follow industry leaders in product, service, or technological innovation and maintain a moderate revenue scale. The third tier consists of smaller companies with limited market share and lower brand recognition, primarily focused on local markets and generating comparatively lower revenue.
This report studies the market size, price trends and future development prospects of Weather Forecasting Technology. Focus on analysing the market share, product portfolio, prices, sales, revenue and gross profit margin of global major suppliers, as well as the market status and trends of different product types and applications in the global Weather Forecasting Technology market. The report data covers historical data from 2020 to 2024, based year in 2025 and forecast data from 2026 to 2032.
The regions and countries in the report include US, Germany, Japan, China, France, UK, South Korea, Canada, Italy, Russia, Mexico, Brazil, India, Vietnam, Thailand, South Africa and other regions, covering the Weather Forecasting Technology market conditions and future development trends of key regions and countries, combined with industry-related policies and the latest technological developments, analyze the development characteristics of Weather Forecasting Technology industries in various regions and countries, help companies understand the development characteristics of each region, help companies formulate business strategies, and achieve the ultimate goal of the company's global development strategy.
The data sources of this report mainly include the National Bureau of Statistics, customs databases, industry associations, corporate financial reports, third-party databases, etc. Among them, macroeconomic data mainly comes from the National Bureau of Statistics, International Economic Research Organization; industry statistical data mainly come from industry associations; company data mainly comes from interviews, public information collection, third-party reliable databases, and price data mainly comes from various markets monitoring database.
Global Key Suppliers of Weather Forecasting Technology Include:
All Weather, Inc. (AWI)
Campbell Scientific, Inc
Columbia Weather Systems, Inc.
General Acoustics e.K.
Gill Instruments Limited
IBM (The Weather Company)
Lockheed Martin Corporation
Met One Instruments Inc.
MORCOM International
Optical Scientific, Inc.
Pulsonic
Skye Instruments Limited
Vaisala
Weather Forecasting Technology Product Segment Include:
Monitoring Devices
Communication Devices
Software
Others
Weather Forecasting Technology Product Application Include:
Agriculture
Transportation
Power & Energy
Industrial
Government & Defense
Meteorology & Weather Service Providers
Others
Chapter Scope
Chapter 1: Product Research Range, Product Types and Applications, Market Overview, Market Situation and Trend
Chapter 2: Global Weather Forecasting Technology Industry PESTEL Analysis
Chapter 3: Global Weather Forecasting Technology Industry Porter's Five Forces Analysis
Chapter 4: Global Weather Forecasting Technology Major Regional Market Size (Revenue) and Forecast Analysis
Chapter 5: Global Weather Forecasting Technology Competitive Analysis of Key Suppliers (Revenue, Market Share, Regional Distribution and Industry Concentration)
Chapter 6: Global Weather Forecasting Technology Revenue and Forecast Analysis by Product Type
Chapter 7: Key Company Profiles (Product Portfolio, Revenue and Gross Margin)
Chapter 8: Industrial Chain Analysis, Weather Forecasting Technology Different Application Market Analysis (Revenue and Forecast) and Sales Channel Analysis
Chapter 9: Research Findings and Conclusion
Chapter 10: Methodology and Data Sources
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