Joint Session 16 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; and the 26th Conference on Probability and Statistics )
Cochairs:
Auroop Ganguly, Northeastern Univ., 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 University, Fort Collins, CO; and I. Ebert-Uphoff, J. Hurrell, C. W. Anderson, and D. Anderson

11:00 AM
J17.2
Evaluation of Data-Driven Causality Discovery Methods among Dominant Climate Modes
Steve R Hussung, Indiana University, 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; University 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 U.S. - Insights from Combining Deep Learning and High-Resolution Modeling
Maria J Molina, NCAR, Boulder, CO; and D. J. Gagne II and A. F. Prein

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

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