Please join us Thursday, June 1, 2023 for our Spring Seminar Series with our speaker: Dale Durran. 

Department of Earth System Science 

Seminar Series Spring 2023

12:00-1:00pm 

Thursday, June 1st, 2023 

McCullough Building (Room 115) 

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 100 km Notably, our model can be iterated forward indefinitely to produce forecasts at 6-hour temporal resolution for any lead time. We present case studies showing the extent to which the model can 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 described.

Biography

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 120 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.

Website

https://atmos.uw.edu/~durrand/