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Found 3 papers, 1 papers with code
A Machine Learning Outlook: Post-processing of Global Medium-range Forecasts
Post-processing typically takes the outputs of a Numerical Weather Prediction (NWP) model and applies linear statistical techniques to produce improve localized forecasts, by including additional observations, or determining systematic errors at a finer scale.
Skillful Twelve Hour Precipitation Forecasts using Large Context Neural Networks
An emerging class of weather models based on neural networks represents a paradigm shift in weather forecasting: the models learn the required transformations from data instead of relying on hand-coded physics and are computationally efficient.
Machine Learning for Precipitation Nowcasting from Radar Images
High-resolution nowcasting is an essential tool needed for effective adaptation to climate change, particularly for extreme weather.
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