This is an ongoing research project focusing on the use of deep learning for feature detection of mesoscale convective systems (MCSs).
Machine learning training uses PNNL provided labels of MCS objects derived from ERA5.
The trained model will be subsequently applied to CESM high resolution output.
This project entails a collaboration between the National Center for Atmospheric Research, the Department of Atmospheric and Oceanic Science at the University of Maryland-College Park, and the Department of Earth Sciences at the University of Connecticut.