Dr. Yunheng Wang received his B.Sc. in Meteorology from the Nanjing Institute of Meteorology (Nanjing University of Information Science and Technology, Now). After receiving his M.S. (2000) in Atmospheric and Oceanic Science from The University of Maryland, he changed his field of study to Computer Science and received his M.S. (2003) and Ph.D. (2007) from the University of Oklahoma, specializing in scientific computing and digital filters. He joined the Center for Analysis and Prediction of Storms (CAPS) at the University of Oklahoma in 2002 as a scientific programmer. While pursuing a doctorate at the University of Oklahoma, he continued working at CAPS as a software engineer. He then joined the Warn-on-Forecast team at the Cooperative Institute for Mesoscale Meteorological Studies (CIMMS) and NOAA National Severe Storms Laboratory (NSSL) in September 2015. He is now a Research Scientist at the Cooperative Institute for Severe and High-Impact Weather Research and Operations (CIWRO) of the University of Oklahoma. His research interest is high-performance computing for numerical weather prediction and data assimilation, especially for high-impact hazardous weather events. He is now mainly involved in the NOAA’s Warn-on-Forecast project (WoF). The purpose of WoF is to increase the lead time and accuracy for hazardous weather and water warnings and forecasts. He developed and is also actively improving a variational and EnKF hybrid data assimilation system for the WoF project.
Dr. Ming Xue holds a B.S. degree (1984) in meteorology from Nanjing University and a Ph.D. degree (1989) in meteorology from the University of Reading. He is the Weathernews Chair Professor, George Lynn Cross Research Professor at the School of Meteorology (SOM), and Director of the Center for Analysis and Prediction of Storms (CAPS), University of Oklahoma. Before joining SOM in 1999 as a faculty member, he was with CAPS for 10 years, starting as a post-doc and ending as a senior scientist and Scientific Director. He became the Director of CAPS in 2006. He was the main developer of the open-source community Advanced Regional Prediction System (ARPS), an end-to-end regional, nonhydrostatic atmospheric modeling and numerical weather prediction system that includes complete data assimilation systems. His research interests include research and development on advanced modeling, data assimilation, and numerical weather prediction techniques and systems, the simulation, prediction, dynamics, and predictability of severe and high-impact weather from synoptic down to microscales (e.g., tornadoes), the assimilation of remote sensing observations from platforms such as radar and satellites, the modeling of environmental processes and regional climate, the modeling of environmental processes and regional climate, and the use machine learning techniques for improving weather forecasting. He is an elected Fellow of the American Geophysical Union and the American Meteorological Society.
