Fine-tuning Prithvi WxC to predict gravity wave fluxes beats an Attention U-Net baseline on one month of ERA5 validation, including in upper stratospheric levels absent from the pre-training data.
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Finetuning AI Foundation Models to Develop Subgrid-Scale Parameterizations: A Case Study on Atmospheric Gravity Waves
Fine-tuning Prithvi WxC to predict gravity wave fluxes beats an Attention U-Net baseline on one month of ERA5 validation, including in upper stratospheric levels absent from the pre-training data.