Joint Session 22 Hybrid Machine Learning and Statistical Approaches

Tuesday, 14 January 2020: 1:30 PM-2:30 PM
260 (Boston Convention and Exhibition Center)
Hosts: (Joint between the 26th Conference on Probability and Statistics; and the 19th Conference on Artificial Intelligence for Environmental Science )
Cochairs:
Stephan R. Sain, Jupiter Intelligence, Earth and Ocean Systems, Boulder, CO and Dorit Hammerling, Jupiter Technology, Boulder, CO

Papers:
1:30 PM
J22.1
Using Artificial Neural Networks for Generating Probabilistic Subseasonal Precipitation Forecasts over California
Michael Scheuerer, CIRES, Boulder, CO; and M. B. Switanek, T. M. Hamill, and R. Worsnop
Recorded Presentation

1:45 PM
J22.3
The Long-Term Frontal System Variation for Future Climate Projections with Machine Learning Weather Classifier
Shih-Hao Su, Chinese Culture Univ., Taipei, Taiwan; and T. S. Yo, C. W. Chang, Y. C. Yu, and J. L. Chu

J22.2
Machine Learning calibration of CAM ensemble probabilistic forecasts of convective mode with conditional probabilities of severe weather hazards using the OU MAP ensemble from HWT SFEs.

2:15 PM
J22.4
Statistical–Physical Microphysics Parameterization Schemes: A Proposed Framework for Physically Based Microphysics Schemes That Learn from Observations
Marcus van Lier-Walqui, Columbia Univ. and NASA GISS, New York, NY; and H. Morrison, M. R. Kumjian, K. J. Reimel, O. P. Prat, S. Lunderman, and M. Morzfeld
Recorded Presentation

- Indicates paper has been withdrawn from meeting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