activity
20072026
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 · 966 across the 31 of their papers we have counts for

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Showing 2025 · physics.ao-phShow all

2 papers · 2 filters

physics.ao-ph2025★ 1 cited

Generative AI models capture realistic sea-ice evolution from days to decades

Tobias Sebastian Finn, Marc Bocquet, Pierre Rampal +4

Sea ice plays an important role in stabilising the Earth system. Yet, representing its dynamics remains a major challenge for models, as the underlying processes are scale-invarian…

physics.ao-ph2025★ 1 cited

Hybrid machine learning data assimilation for marine biogeochemistry

Ieuan Higgs, Ross Bannister, Jozef Skákala +2

Marine biogeochemistry models are critical for forecasting, as well as estimating ecosystem responses to climate change and human activities. Data assimilation (DA) improves these…