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SamudrACE: Fast and Accurate Coupled Climate Modeling with 3D Ocean and Atmosphere Emulators
Traditional numerical global climate models simulate the full Earth system by exchanging boundary conditions between separate …
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A landscape of mesoscale eddy vertical structure: the influence of bathymetric slope and roughness on kinetic energy
Surface and upper ocean measurements of mesoscale eddies have revealed the central role they play in ocean transport, but their …
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A theory for how the depth of meltwater injection impacts regional sea level evolution
Mass loss from the Antarctic ice sheet is projected to continue over the coming century. The resultant sea level change will have a …
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A fluctuation-dissipation theorem perspective on radiative responses to temperature perturbations
Radiative forcing drives warming in the Earth system, leading to changes in sea surface temperatures (SSTs) and associated radiative …
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Observational constraints imply limited future Atlantic meridional overturning circulation weakening
The degree to which the Atlantic meridional overturning circulation (AMOC) weakens over the twenty-first century varies widely across …
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Design and implementation of a data-driven parameterization for mesoscale thickness fluxes
Mesoscale eddies are a major sink of available potential energy (APE) in the ocean. When these eddies are not resolved or only …
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Addressing Out-of-Sample Issues in Multi-Layer Convolutional Neural-Network Parameterization of Mesoscale Eddies Applied Near Coastlines
This study addresses the boundary artifacts in machine-learned (ML) parameterizations for ocean subgrid mesoscale momentum forcing, as …
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Samudra: An AI Global Ocean Emulator for Climate
AI emulators for forecasting have emerged as powerful tools that can outperform conventional numerical predictions. The next frontier …
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Time-varying global energy budget since 1880 from a reconstruction of ocean warming
Accurately quantifying air-sea fluxes is important for understanding air-sea interactions and improving coupled weather and climate …
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Deep Learning of Systematic Ocean Model Errors in a Coupled GCM from Data Assimilation Increments
We present a novel, data-driven approach to predict systematic model errors in the ocean component of a coupled general circulation …
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