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Climate
I am part of M2LInES, an international collaborative project with the goal of improving climate projections, using machine learning to capture unaccounted physical processes at the air-sea-ice interface. In collaboration with Alistair Adcroft and Laure Zanna, I have focused on modeling missing physics in the ocean.
Generative data-driven approaches for stochastic subgrid parameterizations in an idealized ocean model P. Perezhogin, L. Zanna, C. Fernandez-Granda. Journal of Advances in Modeling Earth Systems, 15 (10),
e2023MS003681. 2023
Implementation and Evaluation of a Machine Learned Mesoscale Eddy Parameterization into a Numerical Ocean Circulation Model C. Zhang, P. Perezhogin, C. Gultekin, A. Adcroft, C. Fernandez-Granda, L. Zanna. Journal of Advances in Modeling Earth Systems, 15 (10),
e2023MS003697. 2023
Benchmarking of machine learning ocean subgrid parameterizations in an idealized model A. S. Ross, Z. Li, P. Perezhogin, C. Fernandez-Granda, L. Zanna. Journal of Advances in Modeling Earth Systems, 15(1), e2022MS003258. 2023
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