activity
20192024
most citedCombining data assimilation and machine learning to emulate a dynamical model from sparse and noisy observations: a case study with the Lorenz 96 model

206 citations · 594 across the 12 of their papers we have counts for

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physics.ao-ph2021★ 44 cited

Super-resolution data assimilation

Sébastien Barthélémy, Julien Brajard, Laurent Bertino +1

Increasing the resolution of a model can improve the performance of a data assimilation system: first because model field are in better agreement with high resolution observations,…

physics.ao-ph2021★ 166 cited

Bridging observation, theory and numerical simulation of the ocean using Machine Learning

Maike Sonnewald, Redouane Lguensat, Daniel C. Jones +3

Progress within physical oceanography has been concurrent with the increasing sophistication of tools available for its study. The incorporation of machine learning (ML) techniques…