Biography

Noah Brenowitz is a Senior Research Scientist at NVIDIA. He completed a PhD in 2017 in Atmospheric-ocean Science and Mathematics at NYU’s Courant Institute of Mathematical Sciences with Andrew Majda as his Advisor. While there he developed a strong background in applied mathematics. Since then he has focused on improving climate models with machine learning with Christopher Bretherton, first as a Moore/Sloan & WRF Innovation in Data Science Postdoctoral Fellow at the University of Washington (UW) and then later at Vulcan and AI2. Noah has led the publication of several foundational papers in this burgeoning field. He enjoys spending his free-time in the beautiful mountains of the Pacific Northwest during all seasons of the year.

Interests
  • Atmospheric dynamics
  • Tropical moist convection
  • Machine learning
  • High-resolution numerical modeling
Education
  • Ph.D. in Atmosphere-Ocean Science and Mathematics, 2017

    New York University

  • BS in Mathematics and Statistics, 2011

    New York University

Recent Posts

Recent & Upcoming Talks

Recent Publications

(2022). Correcting a 200 km resolution climate model in multiple climates by machine learning from 25 km resolution simulations. J. Adv. Model. Earth Syst..

Cite DOI

(2022). Correcting coarse‐grid weather and climate models by machine learning from global storm‐resolving simulations. J. Adv. Model. Earth Syst..

Cite DOI

(2021). Correcting weather and climate models by machine learning nudged historical simulations. Geophys. Res. Lett..

Cite DOI

(2020). Machine Learning Climate Model Dynamics: Offline versus Online Performance. NeurIPS 2020 Workshop on Tackling Climate Change with Machine Learning.

Cite