506 citations · 520 across the 7 of their papers we have counts for
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physics.ao-ph2020★ 6 cited
Physics-inspired adaptions to low-parameter neural network weather forecasts systems
Sebastian Scher, Gabriele Messori
Recently, there has been a surge of research on data-driven weather forecasting systems, especially applications based on convolutional neural networks (CNNs). These are usually tr…
physics.ao-ph2020
Ensemble methods for neural network-based weather forecasts
Sebastian Scher, Gabriele Messori
Ensemble weather forecasts enable a measure of uncertainty to be attached to each forecast, by computing the ensemble's spread. However, generating an ensemble with a good spread-e…
physics.ao-ph2020★ 506 cited
WeatherBench: A benchmark dataset for data-driven weather forecasting
Stephan Rasp, Peter D. Dueben, Sebastian Scher +3
Data-driven approaches, most prominently deep learning, have become powerful tools for prediction in many domains. A natural question to ask is whether data-driven methods could al…