Representing ill-known parts of a numerical model using a machine learning approach

no code implementations • 18 Mar 2019 • Julien Brajard, Anastase Charantonis, Jérôme Sirven

In numerical modeling of the Earth System, many processes remain unknown or ill represented (let us quote sub-grid processes, the dependence to unknown latent variables or the non-inclusion of complex dynamics in numerical models) but sometimes can be observed.

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