Session 2A Applications of Machine Learning in Earth System Modeling

Monday, 13 January 2020: 2:00 PM-4:00 PM
156BC (Boston Convention and Exhibition Center)
Host: 19th Conference on Artificial Intelligence for Environmental Science
Cochairs:
Christiane Jablonowski, University of Michigan, Climate and Space Science and Enigneering, Ann Arbor, MI and Christoph A. Keller, GMAO, Greenbelt, MD

This session features applications of machine learning and deep learning to atmospheric, ocean, land, and ice models.

Papers:
2:00 PM
.1
Discovering Novel Eddy Parameterisations with Machine Learning
Laure Zanna, University of Oxford, Oxford, United Kingdom; and T. Bolton

2:15 PM
.2
A Pure Deep Learning Approach to Precipitation Nowcasting
Jason Hickey, Google, Mountain View, CA; and C. Gazen, S. Agrawal, C. Bromberg, L. Barrington, V. Lakshmanan, and J. Burge

2:30 PM
.3
Towards Physics-informed Deep Learning for Spatiotemporal Modeling of Turbulent Flows
Rui Wang, Northeastern University, Boston, MA; and A. Albert, K. Kashinath, M. Mustafa, and R. Yu

2:45 PM
.4
Deep learning for weather prediction: Forecasting globally-gridded 500-hPa geopotential heights on short- to medium-range time scales
Jonathan A. Weyn, University of Washington, Seattle, WA; and D. R. Durran and R. Caruana

3:00 PM
.5
Nonlinear Averaging of Global NCEP Wave Ensemble Using NNs
Vladimir Krasnopolsky Krasnopolsky, NOAA, College Park, MD

3:15 PM
.6
Machine Learning for Parameterization of Moist Processes in the Atmosphere
Janni Yuval, MIT, Cambridge, MA; and P. A. O'Gorman

3:30 PM
.7
Developing the Snow Cover Fraction Schemes for land surface model using Machine Learning Approach
Yuan-Heng Wang, Univ. of Arizona, Tucson, AZ; and H. V. Gupta, P. D. Broxton, Y. Fang, A. Behrangi, X. Zeng, and G. Y. Niu

3:45 PM
.8
A machine learning-based parameterization of OH
M. B. Follette-Cook, Morgan State Univ./GESTAR, Greenbelt, MD; and J. M. Nicely, C. A. Keller, and B. Duncan

- Indicates paper has been withdrawn from meeting
- Indicates an Award Winner