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Found 3 papers, 1 papers with code
Learning of Sea Surface Height Interpolation from Multi-variate Simulated Satellite Observations
We also introduce a new way to transfer the learning from simulation to observations: supervised pre-training on our OSSE followed by unsupervised fine-tuning on satellite data.
Learning 4DVAR inversion directly from observations
Variational data assimilation and deep learning share many algorithmic aspects in common.
Fusion of rain radar images and wind forecasts in a deep learning model applied to rain nowcasting
The network was compared to a similar architecture trained only on radar data, to a basic persistence model and to an approach based on optical flow.
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