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)

Cochairs:
Auroop Ganguly, Northeastern Univ., Civil and Environmental Engineering, Boston, MA and Karthik Kashinath, LBNL, National Energy Research Scientific Computing Center (NERSC), Berkeley, CA

Description:

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


Papers:
10:30 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

10:45 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

11:00 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

11:15 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

Abstract Submissions Closed



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