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og:description: CorrDiff, part of NVIDIA Earth-2, uses generative AI to downscale coarse climate projections (like CMIP6) into high-resolution, bias-corrected data. The model...
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# How to Unlock Local Detail in Coarse Climate Projections with NVIDIA Earth-2

**[NVIDIA Developer](https://daily.dev/sources/nvidiadev)** · 12 min read · 1 upvotes · 0 comments

## Summary

CorrDiff, part of NVIDIA Earth-2, uses generative AI to downscale coarse climate projections (like CMIP6) into high-resolution, bias-corrected data. The model combines spatial super-resolution (11x), temporal downscaling (daily to hourly), and bias correction in one workflow by training on paired datasets—CanESM5 assimilated hindcasts as input and ERA5 reanalysis as target. Training involves a regression model for conditional mean prediction and a diffusion model for residuals. The approach reveals local climate extremes like hurricanes that disappear in coarse data, generates large ensembles for uncertainty quantification, and enables probabilistic climate risk assessment. S&P Global Energy is using this workflow for portfolio-level impact analysis.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://developer.nvidia.com/blog/how-to-unlock-local-detail-in-coarse-climate-projections-with-nvidia-earth-2/>

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