17 citations · 30 across the 14 of their papers we have counts for
4 papers · 1 filter
Samudra: An AI Global Ocean Emulator for Climate
Surya Dheeshjith, Adam Subel, Alistair Adcroft +4
AI emulators for forecasting have emerged as powerful tools that can outperform conventional numerical predictions. The next frontier is to build emulators for long climate simulat…
An Analysis of Deep Learning Parameterizations for Ocean Subgrid Eddy Forcing
Cem Gultekin, Adam Subel, Cheng Zhang +5
Due to computational constraints, climate simulations cannot resolve a range of small-scale physical processes, which have a significant impact on the large-scale evolution of the…
Addressing out-of-sample issues in multi-layer convolutional neural-network parameterization of mesoscale eddies applied near coastlines
Cheng Zhang, Pavel Perezhogin, Alistair Adcroft +1
This study addresses the boundary artifacts in machine-learned (ML) parameterizations for ocean subgrid mesoscale momentum forcing, as identified in the online ML implementation fr…
Transfer Learning for Emulating Ocean Climate Variability across forcing
Surya Dheeshjith, Adam Subel, Shubham Gupta +4
With the success of machine learning (ML) applied to climate reaching further every day, emulators have begun to show promise not only for weather but for multi-year time scales in…