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20242026
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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

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

Huge Ensembles Part I: Design of Ensemble Weather Forecasts using Spherical Fourier Neural Operators

Ankur Mahesh, William Collins, Boris Bonev +13

Studying low-likelihood high-impact extreme weather events in a warming world is a significant and challenging task for current ensemble forecasting systems. While these systems pr…

physics.ao-ph2024

A Practical Probabilistic Benchmark for AI Weather Models

Noah D. Brenowitz, Yair Cohen, Jaideep Pathak +6

Since the weather is chaotic, forecasts aim to predict the distribution of future states rather than make a single prediction. Recently, multiple data driven weather models have em…

physics.ao-ph2024

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…