Toward Replacing Current NWP with Deep Learning Weather Prediction and Extensions to a Full Earth-System Model

Presented on November 29, 2023, by

Dale Durran, Professor
Atmospheric Sciences
University of Washington

ABSTRACT

We compare the performance of a global deep-learning weather-prediction (DLWP) model with reanalysis data and forecasts from the European Center for Medium Range Weather Forecasts (ECMWF).

The model is trained using ECMWF ReAnalysis 5 (ERA5) data with convolutional neural networks (CNNs) on a HEALPix mesh using a loss function that minimizes forecast error over a single 24-hour period. The model predicts seven 2D shells of atmospheric data on an equal-area pixelization at resolutions of roughly 200 km.

Notably, our model can be iterated forward indefinitely to produce forecasts at 3-hour temporal resolution for any lead time. We present case studies showing the extent to which the model is able to reproduce the dynamical evolution of atmospheric systems and its ability to learn “model physics” to forecast two-meter temperature and precipitation.

Extensions to a full earth-system model are presented using similar deep learning architecture to forecast sea surface temperatures. The SST model can be stably stepped forward for a year and shows skill in forecasting El
Niños.

Short Bio

Dale Durran is a professor and past Chair of Department of Atmospheric Sciences at the University of Washington. His research foci include atmospheric predictability, mountain meteorology, and numerical weather prediction. Most recently he has been exploring how deep learning can change our current paradigm for numerical weather prediction, sub-seasonal, and seasonal forecasting. He is a fellow of the American Meteorological Society (AMS) and a recipient of the AMS’s Jule Charney Award. He has written over 125 scientific publications, the graduate-level textbook “Numerical methods for Fluid Dynamics with Applications to Geophysics” and “perspective” articles about climate change for the Washington Post. His sculpture was included in the first ArtScience Virtual Exhibit exhibit of American Geophysical Union’s 2022 Fall Meeting.