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#downscaling

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papersSEP 10 04:00 UTC

Conditional diffusion model produces high-resolution temperature maps from sparse station data

Researchers have introduced a conditional diffusion framework that refines coarse ERA5 reanalysis fields into fine-scale air temperature estimates by incorporating sparse ground-station measurements. The approach is designed to capture terrain and land-surface contrasts that coarse products miss, with the goal of improving local heatwave hazard assessment in areas with limited sensor coverage.

diffusion-models/climate/downscaling/research