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Found 4 papers, 2 papers with code
An ensemble of data-driven weather prediction models for operational sub-seasonal forecasting
We present an operations-ready multi-model ensemble weather forecasting system which uses hybrid data-driven weather prediction models coupled with the European Centre for Medium-range Weather Forecasts (ECMWF) ocean model to predict global weather at 1-degree resolution for 4 weeks of lead time.
Sub-seasonal forecasting with a large ensemble of deep-learning weather prediction models
Current forecast systems have low skill in predicting one- or 2-week-average weather patterns at S2S time scales.
Improving data-driven global weather prediction using deep convolutional neural networks on a cubed sphere
The cubed-sphere remapping minimizes the distortion on the cube faces on which convolution operations are performed and provides natural boundary conditions for padding in the CNN.
WeatherBench: A benchmark dataset for data-driven weather forecasting
Data-driven approaches, most prominently deep learning, have become powerful tools for prediction in many domains.
