Model card for granite-geospatial-wxc-downscaling

>>Try it on Colab<< (Please select the T4 GPU runtime)
granite-geospatial-wxc-downscaling is a fine-tuned foundation model for the downscaling of weather and climate data. It is based on the Prithvi WxC foundation model. granite-geospatial-downscaling has been used to downscale both MERRA-2 data as well as EURO-CORDEX climate simulations. The weights for the former are included here.

6x downscaling of MERRA-2 2m temperature

More information: Code, base model, paper (to appear).

Architecture

From an architecture point of view, we embed Prithvi WxC's transformer layers into a series of convolutional layers. That is, we typically increase resolution before and after the pre-trained transformer stages.

Data - MERRA-2

As a reference and baseline how to use Prithvi WxC as well as the downscaling architecture, we have used granite-geospatial-downscaling for 6x downscaling of MERRA-2 2m temperature data. That is, we take MERRA-2 data of 0.5 x 0.625 degrees resolution, coarsen it by a factor of six along each axis and then apply an additional smoothing filter via a 3x3 convolution. Subsequently we fine-tune the above architecture to recover the high resolution data. The weights for this are included here.

Further applications - EURO-CORDEX

In addition, we have used the same architecture with different hyperparameter choices for a 12x downscaling of a subset of EURO-CORDEX climate simulation.