Noah D. Brenowitz

According to our database, Noah D. Brenowitz authored at least 20 papers between 2016 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2026

Demystifying Data-Driven Probabilistic Medium-Range Weather Forecasting.

Jean Kossaifi, Nikola B. Kovachki, Morteza Mardani, Daniel V. Leibovici, Suman Ravuri, Ira Shokar, Edoardo Calvello, Mohammad Shoaib Abbas, Peter Harrington, Ashay Subramaniam, Noah D. Brenowitz, Boris Bonev, Wonmin Byeon, Karsten Kreis, Dale R. Durran, Arash Vahdat, Mike Pritchard, Jan Kautz

CoRR, January, 2026

2025

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

Scott A. Martin, Noah D. Brenowitz, Dale R. Durran, Michael S. Pritchard

CoRR, December, 2025

cuHPX: GPU-Accelerated Differentiable Spherical Harmonic Transforms on HEALPix Grids.

Xiaopo Cheng, Akshay Subramaniam, Shixun Wu, Noah D. Brenowitz

CoRR, October, 2025

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, June, 2025

ClimSim-Online: A Large Multi-Scale Dataset and Framework for Hybrid Physics-ML Climate Emulation.

Sungduk Yu, Zeyuan Hu, Akshay Subramaniam, Walter M. Hannah, Liran Peng, Jerry Lin, Mohamed Aziz Bhouri, Ritwik Gupta, Björn Lütjens, Justus C. Will, Gunnar Behrens, Julius J. M. Busecke, Nora Loose, Charles Stern, Tom Beucler, Bryce E. Harrop, Helge Heuer, Benjamin R. Hillman, Andrea M. Jenney, Nana Liu, Alistair White, Tian Zheng, Zhiming Kuang, Fiaz Ahmed, Elizabeth A. Barnes, Noah D. Brenowitz, Christopher S. Bretherton, Veronika Eyring, Savannah L. Ferretti, Nicholas J. Lutsko, Pierre Gentine, Stephan Mandt, J. David Neelin, Rose Yu, Laure Zanna, Nathan M. Urban, Janni Yuval, Ryan Abernathey, Pierre Baldi, Wayne Chuang, Yu Huang, Fernando Iglesias-Suarez, Sanket R. Jantre, Po-Lun Ma, Sara Shamekh, Guang Zhang, Michael S. Pritchard

J. Mach. Learn. Res., 2025

Adaptive Flow Matching for Resolving Small-Scale Physics.

Stathi Fotiadis, Noah D. Brenowitz, Tomas Geffner, Yair Cohen, Michael S. Pritchard, Arash Vahdat, Morteza Mardani

Proceedings of the Forty-second International Conference on Machine Learning, 2025

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

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

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, David Pruitt, Mark Risser, Shashank Subramanian, Jared Willard

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, Mark Risser, Shashank Subramanian, Jared Willard

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

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

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

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

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, Noah D. Brenowitz, Karthik Kashinath, Michael S. Pritchard, Boris Bonev, Matthew E. Peters, Christopher S. Bretherton

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

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, Savannah L. Ferretti, Nana Liu, Anima Anandkumar, Noah D. Brenowitz, Veronika Eyring, Pierre Gentine, Stephan Mandt, Jaideep Pathak, Carl Vondrick, Rose Yu, Laure Zanna, Ryan P. Abernathey, Fiaz Ahmed, David C. Bader, Pierre Baldi, Elizabeth A. Barnes, Gunnar Behrens, Christopher S. Bretherton, Julius J. M. Busecke, Peter M. Caldwell, Wayne Chuang, Yilun Han, Yu Huang, Fernando Iglesias-Suarez, Sanket R. Jantre, Karthik Kashinath, Marat Khairoutdinov, Thorsten Kurth, Nicholas J. Lutsko, Po-Lun Ma, Griffin Mooers, J. David Neelin, David A. Randall, Sara Shamekh, Akshay Subramaniam, Mark A. Taylor, et al.

CoRR, 2023

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, Tom Beucler, Bryce E. Harrop, Benjamin R. Hillman, Andrea M. Jenney, Savannah L. Ferretti, Nana Liu, Animashree Anandkumar, Noah D. Brenowitz, Veronika Eyring, Nicholas Geneva, Pierre Gentine, Stephan Mandt, Jaideep Pathak, Akshay Subramaniam, Carl Vondrick, Rose Yu, Laure Zanna, Tian Zheng, Ryan Abernathey, Fiaz Ahmed, David C. Bader, Pierre Baldi, Elizabeth A. Barnes, Christopher S. Bretherton, Peter M. Caldwell, Wayne Chuang, Yilun Han, Yu Huang, Fernando Iglesias-Suarez, Sanket R. Jantre, Karthik Kashinath, Marat Khairoutdinov, Thorsten Kurth, Nicholas J. Lutsko, Po-Lun Ma, Griffin Mooers, J. David Neelin, David A. Randall, Sara Shamekh, Mark Taylor, Nathan M. Urban, Janni Yuval, Guang Zhang, Mike Pritchard

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

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

2016

Nonlinear Laplacian spectral analysis of Rayleigh-Bénard convection.

Noah D. Brenowitz, Dimitrios Giannakis, Andrew J. Majda

J. Comput. Phys., 2016