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20242026
most citedCoupled Ocean-Atmosphere Dynamics in a Machine Learning Earth System Model

11 citations · 28 across the 11 of their papers we have counts for

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physics.ao-ph2026

DLESyM-Ocean: A Deep Learning Probabilistic Global Model for Simulating Present-Day Upper Ocean and Sea Ice

Zachary I Espinosa, Nathaniel Cresswell-Clay, William Yik +6

While AI has shown remarkable promise in atmospheric and meteorological forecasting, accurately simulating other components of the Earth system with AI remains an active frontier.…

physics.ao-ph2026★ 1 cited

AIMIP Phase 1: systematic evaluations of AI weather and climate models

Brian Henn, Christopher S. Bretherton, Nikolay Koldunov +18

We present the AI weather and climate model intercomparison project (AIMIP), phase 1. Drawing from the rich tradition of intercomparisons in climate model development, we specify a…

physics.ao-ph2026

Learning Accurate Storm-Scale Evolution from Observations

Jaideep Pathak, Mohammad Shoaib Abbas, Peter Harrington +10

Accurate short-term prediction of clouds and precipitation is critical for severe weather warnings, aviation safety, and renewable energy operations. Forecasts at this timescale ar…

physics.ao-ph2025

Imposing the Fundamental Dynamical Constraint of Hydrostatic Balance to Improve Global ML Weather Prediction

Akshay Subramaniam, Dale Durran, David Pruitt +2

Forecasting weather accurately and efficiently is a critical capability in our ability to adapt to climate change. Data driven approaches to this problem have enjoyed much success…

physics.ao-ph2024★ 8 cited

A Deep Learning Earth System Model for Efficient Simulation of the Observed Climate

Nathaniel Cresswell-Clay, Bowen Liu, Dale Durran +4

A key challenge for computationally intensive state-of-the-art Earth System models is to distinguish global warming signals from interannual variability. Here we introduce DLESyM,…

physics.ao-ph2024★ 7 cited

Kilometer-Scale Convection Allowing Model Emulation using Generative Diffusion Modeling

Jaideep Pathak, Yair Cohen, Piyush Garg +8

Storm-scale convection-allowing models (CAMs) are an important tool for predicting the evolution of thunderstorms and mesoscale convective systems that result in damaging extreme w…

physics.ao-ph2024★ 11 cited

Coupled Ocean-Atmosphere Dynamics in a Machine Learning Earth System Model

Chenggong Wang, Michael S. Pritchard, Noah Brenowitz +5

Seasonal climate forecasts are socioeconomically important for managing the impacts of extreme weather events and for planning in sectors like agriculture and energy. Climate predi…