works on

From the 1 of 13 linked papers with an AI index.

most citedScaling Storm-Resolving Atmospheric AI Simulation to the Entire Planet

2 citations · 3 across the 2 of their papers we have counts for

collaborators

13 papers

physics.ao-ph20261 cited

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

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

The paper introduces AIMIP Phase 1, an intercomparison framework for AI‑based weather and climate models that evaluates their ability to simulate historical atmospheric conditions…

physics.ao-ph20262 cited

Scaling Storm-Resolving Atmospheric AI Simulation to the Entire Planet

Zeyuan Hu, Akshay Subramaniam, Noel Keen +9

Kilometer-scale convection shapes precipitation extremes, tropical organization, and cloud feedbacks, but most global atmospheric models approximate these processes at 25-100 km re…

physics.ao-ph2026

Towards accurate extreme event likelihoods from diffusion model climate emulators

Peter Manshausen, Noah Brenowitz, Julius Berner +2

ML climate model emulators are useful for scenario planning and adaptation, allowing for cost-efficient experimentation. Recently, the diffusion model Climate in a Bottle (cBottle)…

cs.LG2026

Demystifying Data-Driven Probabilistic Medium-Range Weather Forecasting

Jean Kossaifi, Nikola Kovachki, Morteza Mardani +15

The recent revolution in data-driven methods for weather forecasting has lead to a fragmented landscape of complex, bespoke architectures and training strategies, obscuring the fun…

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…

cs.LG2025

Long-Range Distillation: Distilling 10,000 Years of Simulated Climate into Long Timestep AI Weather Models

Scott A. Martin, Noah Brenowitz, Dale Durran +1

Accurate long-range weather forecasting remains a major challenge for AI models, both because errors accumulate over autoregressive rollouts and because reanalysis datasets used fo…