Data Science Working Group

The US CLIVAR Working Group on Emerging Data Science Tools for Climate Variability and Predictability was formed in September 2019. The purpose of the Working Group is to help foster the understanding, adoption, and further development of modern data science tools for the analysis of large-to-massive climate data sets. It brings together experts in Earth science, statisticians, and computer scientists with the specific goal of fostering collaboration across these disciplinary boundaries to achieve US CLIVAR's scientific objectives.

The main objectives of the Working Group are:

  1. Identify best practices for interpretability and predictive capacity.
  2. Gather, prepare, and ecourage use of benchmark training data sets.
  3. Provide timely perspectives on emerging data sciences tools.

 

Data Science Working Group
Elizabeth Barnes (co-chair) Colorado State University
Amy Braverman (co-chair) California Institute of Technology/NASA JPL
Pierre Gentine (co-chair) Columbia University
Mike Pritchard (co-chair) University of California, Irvine
Ryan Abernathey Columbia University
Noah Brenowitz Vulcan Inc.
Imme Ebert-Uphoff Colorado State University
Emily Kang University of Cincinnati
Alicia Karspeck Jupiter Intelligence
Vladimir Krasnopolsky NOAA EMC
Bo Li University of Illinois
Paul Loikith Portland State University
Matthew Norman Oak Ridge National Laboratory
Bruno Sansó University of California, Santa Cruz
Richard Smith University of North Carolina
Ying Sun Cornell University
Paul Ullrich University of California, Davis
Laure Zanna New York University