IPSL-AID: Generative Diffusion Models for Climate Downscaling from Global to Regional Scales
arXiv:2604.03275v2 Announce Type: replace-cross Abstract: Effective adaptation and mitigation strategies for climate change require high-resolution projections to inform strategic decision-making. Conventional global climate models, which typically operate at resolutions of 150 to 200 kilometers, lack the capacity to represent essential regional processes. IPSL-AID is a global to regional downscaling tool based on a denoising diffusion probabilistic model designed to address this limitation. Trained on ERA5 reanalysis data, it generates 0.25 degree resolution fields for temperature, wind, and
The increasing availability of high-resolution climate data and advancements in generative AI models like diffusion models are converging to enable more precise climate projections.
Accurate, high-resolution climate downscaling is critical for effective planning and adaptation strategies across various sectors, impacting infrastructure, resource management, and economic stability.
This development allows for more localized and detailed understanding of climate impacts, moving beyond generalized global models to inform regional decision-making with greater specificity.
- · Climate scientists
- · Regional planners
- · Insurance industry
- · Agricultural sector
- · Sectors reliant on outdated climate models
- · Regions unprepared for specific climate impacts
Improved regional climate forecasts inform better infrastructure and agricultural planning.
Reduced economic losses from climate-related disasters due to proactive adaptation measures.
Enhanced societal resilience to climate change, potentially altering migration patterns and resource allocation strategies.
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Read at arXiv cs.AI