From the 1 of 4 linked papers with an AI index.
1 citations · 1 across the 1 of their papers we have counts for
4 papers
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…
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)…
Climate in a Bottle: Towards a Generative Foundation Model for the Kilometer-Scale Global Atmosphere
Noah D. Brenowitz, Tao Ge, Akshay Subramaniam +7
Climate modeling is reaching unprecedented resolution, producing petabytes of data. AI climate model emulators offer a path to computationally cheap analysis, enabling new scientif…
Generative Data Assimilation of Sparse Weather Station Observations at Kilometer Scales
Peter Manshausen, Yair Cohen, Peter Harrington +7
Data assimilation of observational data into full atmospheric states is essential for weather forecast model initialization. Recently, methods for deep generative data assimilation…