Downscaling weather forecasts from Low- to High-Resolution with Diffusion Models

1. 1Train a diffusion model on reforecast pairs from ECMWF IFS to learn the conditional distribution of finer-scale residuals
2. 2Use the trained model to transform low-resolution ensemble forecasts into high-resolution ensembles
3. 3Evaluate the performance of the downscaling method using metrics such as mean squared error or mean absolute error
4. 4Integrate the downscaling method into the Anemoi framework for global atmospheric downscaling

Data scientists and researchers on a weather forecasting team can benefit from this method to improve forecast accuracy, and software engineers can implement the Anemoi framework to integrate this approach into existing systems

💡 Diffusion models can learn the conditional distribution of finer-scale residuals to downscale low-resolution weather forecasts

💡 Diffusion models can improve weather forecast accuracy by downscaling low-resolution forecasts to high-resolution #AI #weatherforecasting