2 citations · 2 across the 3 of their papers we have counts for
7 papers
Harmonic Extension for Multiscale Analysis and Modeling Near Boundaries, with an Ocean Application
Benjamin A. Storer, Mehrnoush Kharghani, Alistair Adcroft +1
Treatment of fields near domain boundaries is a long-standing problem in signal processing that has come into renewed focus following recent efforts in convolution-based multiscale…
A Framework for Hybrid Physics-AI Coupled Ocean Models
Laure Zanna, William Gregory, Pavel Perezhogin +23
Climate simulations, at all grid resolutions, rely on approximations that encapsulate the forcing due to unresolved processes on resolved variables, known as parameterizations. Par…
Advancing global sea ice prediction capabilities using a fully-coupled climate model with integrated machine learning
William Gregory, Mitchell Bushuk, Yong-Fei Zhang +4
We showcase a hybrid modeling framework which embeds machine learning (ML) inference into the GFDL SPEAR climate model, for online sea ice bias correction during a set of global fu…
Generalizable neural-network parameterization of mesoscale eddies in idealized and global ocean models
Pavel Perezhogin, Alistair Adcroft, Laure Zanna
Data-driven methods have become popular to parameterize the effects of mesoscale eddies in ocean models. However, they perform poorly in generalization tasks and may require retuni…
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…