1.1k citations · 3.5k across the 16 of their papers we have counts for
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physics.ao-ph2018★ 1.1k cited
Deep learning to represent sub-grid processes in climate models
Stephan Rasp, Michael S. Pritchard, Pierre Gentine
The representation of nonlinear sub-grid processes, especially clouds, has been a major source of uncertainty in climate models for decades. Cloud-resolving models better represent…
stat.ML2018★ 536 cited
Neural networks for post-processing ensemble weather forecasts
Stephan Rasp, Sebastian Lerch
Ensemble weather predictions require statistical post-processing of systematic errors to obtain reliable and accurate probabilistic forecasts. Traditionally, this is accomplished w…