The global AI-based climate modelling market was valued at approximately USD 343.2 million in 2024 and is projected to reach USD 1,992.1 million by 2033, reflecting a compound annual growth rate (CAGR) of 21.9% from 2025 to 2033. This growth is expected to be significantly driven by the increasing demand for AI technologies that enhance the accuracy of forecasting climate events such as heatwaves, droughts, and cyclones. These advancements enable timely actions that protect human and animal lives while conserving Earth's resources.

AI's ability to analyze real-time data plays a crucial role in tracking climate-related changes, which can occur at any time and in any location. The growth of the AI-based climate modelling industry is primarily attributed to its capacity to handle, comprehend, and analyze vast and complex datasets from various sources, including satellites, Internet of Things (IoT) sensors, and historical climate records. AI detects subtle patterns and nonlinear relationships that traditional models might overlook, resulting in more accurate and detailed climate forecasts. By automating data collection and seamlessly integrating diverse data streams in real time, AI enhances climate risk analysis and improves predictions of extreme weather events, such as hurricanes, floods, and heatwaves.

Another key factor driving market growth is AI's ability to model subgrid-scale processes and address biases present in traditional climate simulations. AI-enhanced parameterizations and hybrid methods that combine physical principles with data-driven insights improve the realism and accuracy of these models. Moreover, artificial intelligence enhances computer efficiency through substitute modeling and optimization, allowing for quicker climate testing and more effective climate risk management.

Key Market Trends & Insights

• North America led the AI-based climate modelling industry with a revenue share exceeding 40.5% in 2024, fueled by its robust technological ecosystem and strong governmental support and initiatives that foster innovation and large-scale implementation of AI software.
  
  
• The U.S. AI-based climate modelling sector is anticipated to experience significant growth in 2024, leveraging updated data analytics and real-time inputs from satellites, IoT sensors, and weather stations to enhance forecast accuracy and reduce delays, particularly for extreme events such as hurricanes and wildfires.
  
  
• In terms of components, the software segment dominated the AI-based climate modelling market in 2024, capturing a revenue share of 70.7%. This dominance is attributed to the increasing demand for advanced AI tools that provide real-time, high-resolution climate forecasts by integrating large and diverse environmental datasets.
  
  
• By application, the weather forecasting segment represented the largest revenue share within the AI-based climate modelling industry in 2024. This growth is driven by the segment's capability to rapidly process extensive and varied meteorological data from satellites, radar, and ground-based sensors, enabling precise and localized short- to medium-term forecasts.
  
  
• Regarding technology, the machine learning segment held the largest revenue share in the AI-based climate modelling industry in 2024. This is due to its proficiency in processing large and diverse datasets to identify climate signals, allowing for accurate and real-time climate predictions. 

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Market Size & Forecast

• 2024 Market Size: USD 343.2 Million
• 2033 Projected Market Size: USD 1,992.1 Million
• CAGR (2025-2033): 21.9%
• North America: Largest market in 2024

Key Insights into AI-Based Climate Modelling Companies

Several key players in the AI-based climate modelling industry include AccuWeather, Realeyes, Microsoft, IBM, and Tobii.

• AccuWeather specializes in weather intelligence by combining advanced technology, extensive data, and expert analysis to provide highly accurate forecasts and climate insights to over 1.5 billion users globally. The company utilizes vast weather datasets along with cutting-edge AI and machine learning models, supported by a skilled team of meteorologists. This enables AccuWeather to deliver precise and actionable information. Its AI-powered software assists businesses and governments in managing climate risks, enhancing operational efficiency, and improving safety by integrating real-time weather data with analytics on scalable platforms like Databricks and Snowflake.
  
  
• NVIDIA is leading the way in AI-based climate modeling innovation with its Earth-2 platform, which integrates AI, GPU acceleration, and physical simulations to produce high-resolution, energy-efficient climate and weather forecasts at exceptional speed and scale. Utilizing generative AI models like CorrDiff, Earth-2 creates climate simulations that are 12.5 times more detailed and thousands of times faster than traditional models, facilitating rapid and interactive forecasting and visualization. NVIDIA's collaborations with organizations such as G42 and major climate research institutions underscore its commitment to advancing climate science through AI, aiming to mitigate economic losses and support sustainable, data-driven decision-making worldwide.

Key Players

• IBM
• Google
• Microsoft
• AWS
• NVIDIA Corporation
• AccuWeather
• ClimateAI
• Atmos AI
• Open Climate Fix
• Meteomatics AG

Conclusion

The AI-based climate modelling market is poised for substantial growth, driven by the increasing demand for accurate climate forecasting and real-time data analysis. As AI technologies continue to evolve, they will play a pivotal role in enhancing our understanding of climate dynamics and improving our ability to respond to extreme weather events. This market not only offers significant opportunities for technological advancement but also contributes to global efforts in climate resilience and sustainability, ensuring that we can better protect both human and environmental health in the face of climate change.

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