Nonlinear Laplacian spectral analysis of Rayleigh-Bénard convection. - Noah D. Brenowitz; Dimitrios Giannakis; Andrew J. Majda (J. Comput. Phys., 2016)

Machine-learned climate model corrections from a global storm-resolving model. - Anna Kwa; Spencer K. Clark; Brian Henn; Noah D. Brenowitz; Jeremy McGibbon; W. Andre Perkins; Oliver Watt-Meyer; Lucas Harris; Christopher S. Bretherton (CoRR, 2022)

ClimSim: A large multi-scale dataset for hybrid physics-ML climate emulation. - Sungduk Yu; Walter M. Hannah; Liran Peng; Jerry Lin; Mohamed Aziz Bhouri; Ritwik Gupta; Björn Lütjens; Justus C. Will; Gunnar Behrens; Julius Busecke; Nora Loose; Charles Stern; et al. (NeurIPS, 2023)

ClimSim: An open large-scale dataset for training high-resolution physics emulators in hybrid multi-scale climate simulators. - Sungduk Yu; Walter M. Hannah; Liran Peng; Mohamed Aziz Bhouri; Ritwik Gupta; Jerry Lin; Björn Lütjens; Justus C. Will; Tom Beucler; Bryce E. Harrop; Benjamin R. Hillman; Andrea M. Jenney; et al. (CoRR, 2023)

Generative Residual Diffusion Modeling for Km-scale Atmospheric Downscaling. - Morteza Mardani; Noah D. Brenowitz; Yair Cohen; Jaideep Pathak; Chieh-Yu Chen; Cheng-Chin Liu; Arash Vahdat; Karthik Kashinath; Jan Kautz; Mike Pritchard (CoRR, 2023)

ACE: A fast, skillful learned global atmospheric model for climate prediction. - Oliver Watt-Meyer; Gideon Dresdner; Jeremy McGibbon; Spencer K. Clark; Brian Henn; James Duncan 002; Noah D. Brenowitz; Karthik Kashinath; Michael S. Pritchard; Boris Bonev; Matthew E. Peters; Christopher S. Bretherton (CoRR, 2023)

A Practical Probabilistic Benchmark for AI Weather Models. - Noah D. Brenowitz; Yair Cohen; Jaideep Pathak; Ankur Mahesh; Boris Bonev; Thorsten Kurth; Dale R. Durran; Peter Harrington; Michael S. Pritchard (CoRR, 2024)

DiffObs: Generative Diffusion for Global Forecasting of Satellite Observations. - Jason Stock; Jaideep Pathak; Yair Cohen; Mike Pritchard; Piyush Garg; Dale R. Durran; Morteza Mardani; Noah D. Brenowitz (CoRR, 2024)

Coupled Ocean-Atmosphere Dynamics in a Machine Learning Earth System Model. - Chenggong Wang; Michael S. Pritchard; Noah D. Brenowitz; Yair Cohen; Boris Bonev; Thorsten Kurth; Dale R. Durran; Jaideep Pathak (CoRR, 2024)

Generative Data Assimilation of Sparse Weather Station Observations at Kilometer Scales. - Peter Manshausen; Yair Cohen; Jaideep Pathak; Mike Pritchard; Piyush Garg; Morteza Mardani; Karthik Kashinath; Simon Byrne; Noah D. Brenowitz (CoRR, 2024)

Huge Ensembles Part II: Properties of a Huge Ensemble of Hindcasts Generated with Spherical Fourier Neural Operators. - Ankur Mahesh; William D. Collins; Boris Bonev; Noah D. Brenowitz; Yair Cohen; Peter Harrington; Karthik Kashinath; Thorsten Kurth; Joshua North; Travis A. O'Brien; Michael S. Pritchard; David Pruitt; et al. (CoRR, 2024)

Huge Ensembles Part I: Design of Ensemble Weather Forecasts using Spherical Fourier Neural Operators. - Ankur Mahesh; William D. Collins; Boris Bonev; Noah D. Brenowitz; Yair Cohen; Joshua Elms; Peter Harrington; Karthik Kashinath; Thorsten Kurth; Joshua North; Travis A. O'Brien; Michael S. Pritchard; et al. (CoRR, 2024)

Kilometer-Scale Convection Allowing Model Emulation using Generative Diffusion Modeling. - Jaideep Pathak; Yair Cohen; Piyush Garg; Peter Harrington; Noah D. Brenowitz; Dale R. Durran; Morteza Mardani; Arash Vahdat; Shaoming Xu; Karthik Kashinath; Michael S. Pritchard (CoRR, 2024)

Stochastic Flow Matching for Resolving Small-Scale Physics. - Stathi Fotiadis; Noah D. Brenowitz; Tomas Geffner; Yair Cohen; Michael S. Pritchard; Arash Vahdat; Morteza Mardani (CoRR, 2024)

Elucidated Rolling Diffusion Models for Probabilistic Weather Forecasting. - Salva Rühling Cachay; Miika Aittala; Karsten Kreis; Noah D. Brenowitz; Arash Vahdat; Morteza Mardani; Rose Yu (CoRR, 2025)