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Towards Physically-consistent, Data-driven Models of Convection
Data-driven algorithms, in particular neural networks, can emulate the e...
02/20/2020 ∙ by Tom Beucler, et al. ∙
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WeatherBench: A benchmark dataset for data-driven weather forecasting
Data-driven approaches, most prominently deep learning, have become powe...
02/02/2020 ∙ by Stephan Rasp, et al. ∙
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Achieving Conservation of Energy in Neural Network Emulators for Climate Modeling
Artificial neural-networks have the potential to emulate cloud processes...
06/15/2019 ∙ by Tom Beucler, et al. ∙
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Combining crowd-sourcing and deep learning to understand meso-scale organization of shallow convection
The discovery of new phenomena and mechanisms often begins with a scient...
06/05/2019 ∙ by Stephan Rasp, et al. ∙
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Deep learning to represent sub-grid processes in climate models
The representation of nonlinear sub-grid processes, especially clouds, h...
06/12/2018 ∙ by Stephan Rasp, et al. ∙
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Neural networks for post-processing ensemble weather forecasts
Ensemble weather predictions require statistical post-processing of syst...
05/23/2018 ∙ by Stephan Rasp, et al. ∙
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Stephan Rasp
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Technische Universität München
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Universität München
