NSSL scientists awarded an NSF grant to improve convective-scale weather prediction

IMG_0853NSSL scientists Jidong Gao, David Stensrud and the University of Oklahoma School of Meteorology professor Xuguang Wang have received a significant research grant from the National Science Foundation to develop new techniques that will help improve convective-scale (1km) weather prediction.

Currently, most convective-scale data assimilation rely on techniques that were developed for larger-scale weather, where the rules of the atmospheric dynamics are usually different from those of thunderstorm events. To make convective-scale data assimilation more realistic and able to predict individual storms, they must effectively use Doppler radar data as a jumping off point.

The scientists propose to explore new techniques to feed (assimilate) operational WSR-88D radar data into convective scale models, and evaluate the results. This research will help improve our understanding of storm-scale data assimilation and dynamics, and lead to better detection and prediction of thunderstorm hazards. The award continues to draw upon NOAA’s critical investment in the WSR-88D network, and will provide synergistic support to NOAA’s Warn-on-Forecast project.