AI-Based Climate Modelling Market

AI-Based Climate Modelling Market Summary

The global AI-based climate modelling market size was estimated at USD 343.2 million in 2024 and is projected to reach USD 1,992.1 million by 2033, growing at a CAGR of 21.9% from 2025 to 2033. The market growth is anticipated to be significantly accelerated by the growing need for AI-based technologies that enhance the accuracy of forecasting climate events like heatwaves, droughts, and cyclones, enabling timely actions that help protect the lives of humans, animals, and conserve the resources of the Earth.

Additionally, AI analyzes real-time data, which is the crucial step in tracking climate-related changes as they can happen at any time and anywhere in the world. The AI-based climate modelling industry’s growth is mainly driven due to its capability to handle, understand, and analyze vast, complex datasets from sources like satellites, Internet of Things (IoT) sensors, and historical climate records. It detects minute patterns and nonlinear connections that basic and traditional models might miss, which results in more accurate and detailed climate forecasts. By automating data collection and seamlessly integrating diverse data streams in real time, AI speeds up climate risk analyzes and improves predictions of extreme weather events such as hurricanes, floods, and heat waves.

The other factor driving the market growth is the advantage of AI for its ability to model subgrid-scale processes and analyze any biases in traditional climate simulations. AI-enhanced parameterizations and hybrid methods that combine both physical principles with data-driven insights help improve the realism and accuracy of these models. Furthermore, artificial intelligence (AI) improves the efficiency of computer functions through substitute modeling and optimization, enabling quicker testing of the climate and more responsive climate risk management.

Climate AI also has a unique role by offering explainability and causal analysis of the climate, allowing scientists to better understand complex climate interactions and the reasons for extreme events occurring. This helps make more informed decisions in areas like climate adaptation, urban planning, and policy-making. Once the model output is received then they are evaluated in practical life for making informed strategies. AI is responsible for sustainable resource management and disaster preparedness. Its integration into climate science is enhancing how we forecast, interpret, and address climate change across various scales of temperature.

Global AI-Based Climate Modelling Market Report Segmentation

This report forecasts revenue growth at the global, regional, and country levels and provides an analysis of the industry trends in each of the sub-segments from 2021 to 2033. For this study, Grand View Research has segmented the global AI-based climate modelling market report based on the component, technology, application, and region:

• Component Outlook (Revenue, USD Million, 2021 - 2033)
• Software
• Services
• Technology Outlook (Revenue, USD Million, 2021 - 2033)
• Machine Learning
• Deep Learning
• Computer vision
• Others
• Application Outlook (Revenue, USD Million, 2021 - 2033)
• Weather Forecasting
• Disaster Prediction
• Climate Risk Assessment
• Carbon Emission Tracking
• Others
• Regional Outlook (Revenue, USD Million, 2021 - 2033)
• North America
• U.S.
• Canada
• Mexico
• Europe
• UK
• Germany
• France
• Asia Pacific
• China
• India
• Japan
• South Korea
• Australia
• Latin America
• Brazil
• Middle East and Africa
• KSA
• UAE
• South Africa

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