459 citations · 966 across the 23 of their papers we have counts for
3 papers · 1 filter
Lightning-Fast Convective Outlooks: Predicting Severe Convective Environments with Global AI-based Weather Models
Monika Feldmann, Tom Beucler, Milton Gomez +1
Severe convective storms are among the most dangerous weather phenomena and accurate forecasts mitigate their impacts. The recently released suite of AI-based weather models produc…
Simulating Atmospheric Processes in Earth System Models and Quantifying Uncertainties with Deep Learning Multi-Member and Stochastic Parameterizations
Gunnar Behrens, Tom Beucler, Fernando Iglesias-Suarez +5
Deep learning is a powerful tool to represent subgrid processes in climate models, but many application cases have so far used idealized settings and deterministic approaches. Here…
Stress-testing the coupled behavior of hybrid physics-machine learning climate simulations on an unseen, warmer climate
Jerry Lin, Mohamed Aziz Bhouri, Tom Beucler +2
Accurate and computationally-viable representations of clouds and turbulence are a long-standing challenge for climate model development. Traditional parameterizations that crudely…