Deep Neural Networks Speed Up Weather and Climate Models

Typography

When you check the weather forecast in the morning, the results you see are more than likely determined by the Weather Research and Forecasting (WRF) model, a comprehensive model that simulates the evolution of many aspects of the physical world around us. 

When you check the weather forecast in the morning, the results you see are more than likely determined by the Weather Research and Forecasting (WRF) model, a comprehensive model that simulates the evolution of many aspects of the physical world around us. 

“It describes everything you see outside of your window,” said Jiali Wang, an environmental scientist at the U.S. Department of Energy’s (DOE) Argonne National Laboratory, ​“from the clouds, to the sun’s radiation, to snow to vegetation — even the way skyscrapers disrupt the wind.”

The myriad characteristics and causes of weather and climate are coupled together, communicating with one another. Scientists have yet to fully describe these complex relationships with simple, unified equations. Instead, they approximate the equations using a method called parameterization in which they model the relationships at a scale greater than that of the actual phenomena. 

Read more at DOE / Argonne National Laboratory

Image: Jiali Wang and Rao Kotamarthi were co-authors on the Geoscientific Model Development that focused on the planetary boundary layer. Pictured below is co-author Prasanna Balaprakash. (Image by Argonne National Laboratory.)