Session: Artificial Intelligence and Climate: Impact and Opportunities (99th American Meteorological Society Annual Meeting)

Wednesday, 9 January 2019: 1:30 PM-2:30 PM

North 124B (Phoenix Convention Center - West and North Buildings)

Hosts: (Joint between the 18th Conference on Artificial and Computational Intelligence and its Applications to the Environmental Sciences; and the 32nd Conference on Climate Variability and Change )

Cochairs:

Carlos F. Gaitan, ClimateAI, San Francisco, CA and Philippe Tissot, Texas A&M University−Corpus Christi, Conrad Blucher Institute, Corpus Christi, TX

The use of machine learning techniques is already widespread in the climate community. Examples include the application of deep learning to characterize climate model outputs, high-resolution climate downscaling, or the use of neural networks for the modeling of climate time series. Submissions are sought for broad contributions that AI can make to climate studies and particularly topics relevant to the work of the National Climate Assessment Committee.

Papers:

1:30 PM

J6.1

Deep Learning Recognizes Climate and Weather Patterns and Emulates Complex Processes Critical to the Modeling of Earth's Climate

Karthik Kashinath, LBNL, Berkeley, CA; and M. Prabhat, M. Mudigonda, A. Mahesh, S. Kim, J. Wu, A. Albert, A. Rupe, A. Fernandez, T. A. O'Brien, M. F. Wehner, and W. D. Collins

Recorded Presentation

1:45 PM

J6.2

A Topology-Based Approach To Characterization and Detection of Weather Patterns in Climate Model Output: Application to Atmospheric Blocking Events

Grzegorz Muszynski, LBNL, Berkeley, CA; and K. Kashinath, V. Kurlin, M. F. Wehner, and M. Prabhat

Recorded Presentation

2:00 PM

J6.3