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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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Recovering the parameters underlying the Lorenz-96 chaotic dynamics
Climate projections suffer from uncertain equilibrium climate sensitivit...
06/16/2019 ∙ by Soukayna Mouatadid, 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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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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