Conditional, super-resolution application is bridging the gap between coarse resolution and convective-permitting scale in earth system models using deep learning.
Argonne is employing deep neural networks to replace computationally expensive parameterizations of certain physical schemes in the Weather Research and Forecasting model.
Argonne’s new numerical modeling tool helps researchers better understand a powerful engine that could one day propel the next generation of airplanes and rockets.