Session 3B High Impact Weather Prediction with AI

Tuesday, 14 January 2020: 8:30 AM-10:00 AM
156A (Boston Convention and Exhibition Center)
Host: 19th Conference on Artificial Intelligence for Environmental Science
Cochairs:
Montgomery L. Flora, University of Oklahoma, CIMMS, NSSL/NOAA, School of Meteorology, Norman, OK and Stephan R. Sain, Jupiter Intelligence, Earth and Ocean Systems, Boulder, CO

Papers:
8:30 AM
3B.1
Generating Ensemble-Derived Next-Day Probabilistic Severe Weather Forecasts with Machine Learning
Eric D. Loken, CIMMS/University of Oklahoma, Norman, OK; and A. J. Clark

8:45 AM
3B.2
Regional High Impact Hail Forecasting using Random Forests
Amanda Burke, CAPS/University of Oklahoma, Norman, OK; and N. Snook and A. McGovern

9:00 AM
3B.3
Using machine learning to advance next-day probabilistic convective hazard prediction with convection-allowing models
Ryan A. Sobash, NCAR, Boulder, CO; and D. J. Gagne II, C. S. Schwartz, and D. A. Ahijevych

9:15 AM
3B.4
Using machine learning to improve storm-scale 1-h probabilistic forecasts of severe weather
Montgomery L. Flora, University of Oklahoma, CIMMS, NSSL/NOAA, Norman, OK; and C. Potvin, P. Skinner, and A. McGovern

9:45 AM
3B.6
Multi-prior LSTM (mpLSTM): predicting visibility with uncertainties from complex background states
Yao xiao, Shanghai Em-Data Technology Co., Ltd, Shanghai, China; and F. Qi, Y. Meng, H. Zuo, X. Guo, Z. Yan, and C. Lu

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- Indicates an Award Winner