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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 encourage use of benchmark training data sets.
  3. Provide timely perspectives on emerging data sciences tools.
Data Science Working Group
Amy Braverman (co-chair) California Institute of Technology/NASA JPL
Bo Li (co-chair) University of Illinois
Ryan Abernathey Columbia University
Noah Brenowitz Vulcan Inc.
Tom Beucler University of Lausanne, Switzerland
Emily Kang University of Cincinnati
Vladimir Krasnopolsky NOAA EMC
Paul Loikith Portland State University
Mike Pritchard University of California, Irvine
Bruno Sansó University of California, Santa Cruz
Richard Smith University of North Carolina
Ying Sun Cornell University
Laure Zanna New York University