Themed Joint Session 7 Machine Learning and Climate Studies

Wednesday, 10 January 2018: 10:30 AM-12:00 PM
Ballroom A (ACC) (Austin, Texas)
Hosts: (Joint between the 17th Conf on Artificial and Computational Intelligence and its Applications to the Environmental Sciences; and the 31st Conference on Climate Variability and Change )
Cochairs:
Auroop Ganguly, Northeastern University, Civil and Environmental Engineering, Boston, MA; Kerry H. Cook, The Univ. of Texas at Austin, Geological Sciences, Austin, TX and Gudrun Magnusdottir, Univ. of California, Department of Earth System Science, Irvine, CA

Papers:
10:30 AM
TJ7.1
Deep Learning for Detecting Extreme Weather and Climate Patterns (Core Science Keynote)
William Collins, Univ. of California, Berkeley, CA; and M. Prabhat, E. Racah, Y. Liu, K. Kashinath, C. Pal, J. C. Biard, K. E. Kunkel, M. Wehner, and T. O'Brien
Recorded Presentation

11:00 AM
TJ7.2
Super-Resolution and Deep Learning for Climate Downscaling
Thomas Vandal, Northeastern Univ., Cambridge, MA; and A. R. Ganguly
Recorded Presentation

TJ7.3
Machine Learning Models for Climate Data

11:30 AM
TJ7.4
Automated Detection of Fronts Using a Deep Learning Algorithm
Kenneth E. Kunkel, Cooperative Institute for Climate and Satellites, Asheville, NC; and J. C. Biard and E. Racah
Recorded Presentation

11:45 AM
TJ7.5
Computational Models for Detection and Analysis of Synoptic-Scale Ice Storm Patterns
Ranjini Swaminathan, Central Climate Science Center at Texas Tech Univ., Lubbock, TX; and K. Hayhoe
Recorded Presentation

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