Search

A. Adcroft

Samudra: An AI Global Ocean Emulator for Climate
Addressing out-of-sample issues in multi-layer convolutional neural-network parameterization of mesoscale eddies applied near coastlines
Transfer Learning for Emulating Ocean Climate Variability across CO2 forcing
Machine Learning for Online Sea Ice Bias Correction Within Global Ice-Ocean Simulations
Implementation of a data-driven equation-discovery mesoscale parameterization into an ocean model
Remote Versus Local Impacts of Energy Backscatter on the North Atlantic SST Biases in a Global Ocean Model
Parameterizing Vertical Mixing Coefficients in the Ocean Surface Boundary Layer using Neural Networks
Implementation and Evaluation of a Machine Learned Mesoscale Eddy Parameterization into a Numerical Ocean Circulation Model
Deep learning of systematic sea ice model errors from data assimilation increments
NeverWorld2: An idealized model hierarchy to investigate ocean mesoscale eddies across resolutions