Speaker
Prof.
Pedram Hassanzadeh
(University of Chicago)
Description
AI weather models have shown remarkable success in short- and medium-range forecasting. However, major questions remain about their ability to predict the most extreme events, particularly those that are so rare they were absent from the training set (so-called gray swans). There are also already documented challenges for these models in learning multi-scale dynamics. We will show in-depth analyses of these models' shortcomings for learning gray swans and multi-scale dynamics. We will discuss the implications and present a number of solutions for addressing both.
Primary author
Prof.
Pedram Hassanzadeh
(University of Chicago)
