Session Applications of Artificial Intelligence for Improved Estimation and Prediction of Extreme Precipitation and/or Drought in Weather and Climate


Description:

This session invites abstracts leveraging AI tools to improve understanding and/or forecasting abilities of extreme rainfall and drought events.


Papers:
Comparison of Regression Algorithms in Multivariable Drought Modeling and Analysis
Maria Chzhen, University of Toronto, Toronto, ON, Canada

High Spatiotemporal Resolution Quantitative Precipitation Estimation over the United Arab Emirates
Vesta Afzali Gorooh, SIO, La Jolla, CA; Scripps Institution of Oceanography, University of California San Diego, La Jolla, CA; and M. Ghazvinian, PhD, W. Hu, Q. Cao, M. Pan, B. Hassan Banimfreg, E. Damiani, A. Sengupta, D. Axisa, and L. Delle Monache

Improving the Forecast of Extreme Rainfall Event “21.7” in Henan Province Base on a Physical Guided RainNet
Qi Zhong, China Meteorological Administration, Beijing, 11, China; and Z. Zhang and S. Hou

A Machine Learning Emulator for West African Monsoon Prediction
Charlotte Merchant, Princeton University, Princeton, NJ; and W. Yang and G. A. Vecchi

A Novel Quantile Regression Neural Network Scheme for Postprocessing Medium-range Ensemble Quantitative Precipitation Forecasts
Mohammadvaghef Ghazvinian, PhD, Center for Western Weather and Water Extremes, Scripps Institution of Oceanography, Univ. of California, San Diego, La Jolla, CA; and S. Candido, L. Delle Monache, V. Afzali Gorooh, A. Sengupta, W. Hu, and F. M. Ralph

Evaluation of Flash Drought Identification with Machine Learning Techniques, Part 1: Standard Machine Learning Algorithms
Stuart Galen Edris, University of Oklahoma, Norman, OK; and J. B. Basara, J. I. Christian, Ph.D., J. C. Furtado, A. McGovern, and X. Xiao

Evaluation of Flash Drought Identification with Machine Learning Techniques, Part 2: Common Deep Learning Algorithms
Stuart Galen Edris, University of Oklahoma, Norman, OK; and J. B. Basara, J. I. Christian, Ph.D., J. C. Furtado, A. McGovern, and X. Xiao

Enhancing Regional Quantitative Precipitation Forecasts Using Machine Learning in Western US Watersheds
Weiming Hu, Center for Western Weather and Water Extremes, Scripps Institution of Oceanography, UC San Diego, La Jolla, CA; James Madison University, Harrisonburg, VA; and M. Ghazvinian, PhD, A. Sengupta, M. Pan, and L. Delle Monache

Submission Deadline: Thursday, 31 August 2023



See more of: 23rd Conference on Artificial Intelligence for Environmental Science
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