Joint Session 17 AI and Climate: Impact and Opportunities

Tuesday, 14 January 2020: 10:30 AM-12:00 PM
156BC (Boston Convention and Exhibition Center)
Hosts: (Joint between the 19th Conference on Artificial Intelligence for Environmental Science; the 33rd Conference on Climate Variability and Change; the 26th Conference on Probability and Statistics; and the Events )
Cochairs:
Auroop Ganguly, Northeastern University, Civil and Environmental Engineering, Boston, MA and Karthik Kashinath, LBNL, National Energy Research Scientific Computing Center (NERSC), Berkeley, CA

This session will feature applications of AI and machine learning models for analyzing and understanding our climate.

Papers:
10:30 AM
J17.1
Viewing Climate Signals through an AI Lens (Core Science Keynote)
Elizabeth A. Barnes, Colorado State Univ., Fort Collins, CO; and I. Ebert-Uphoff, J. Hurrell, C. W. Anderson, and D. Anderson
Recorded Presentation

11:00 AM
J17.2
Evaluation of Data-Driven Causality Discovery Methods among Dominant Climate Modes
Steve R. Hussung, Indiana Univ., Bloomington, Bloomington, IN; and S. Mahmud, A. Sampath, M. Wu, P. Guo, and J. Wang

11:15 AM
J17.3
Deep Learning Semantic Segmentation for Climate Change Precipitation Analysis
Andrew Lou, LBNL, Berkeley, CA; Univ. of California Berkeley, Berkeley, CA; and E. Chandran, M. Prabhat, J. Biard, K. Kunkel, M. F. Wehner, and K. Kashinath

11:30 AM
J17.4
The Future of Severe Thunderstorms in the United States—Insights from Combining Deep Learning and High-Resolution Modeling
Maria J. Molina, NCAR, Boulder, CO; and D. J. Gagne II and A. F. Prein
Recorded Presentation

11:45 AM
J17.5
Downscaling Climate Model Data for Energy and Crop Modelling Using Self-Organizing Maps
Andrew Polasky, The Pennsylvania State Univ., Univ. Park, PA; and J. L. Evans and J. Fuentes
Recorded Presentation

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