Fuqing Zhang, professor of meteorology, Penn State, will be the sole recipient of the American Meteorological Society's 2009 Clarence Leroy Meisinger Award for promising atmospheric scientists who have recently shown outstanding ability and are under age 40 when nominated.
The Clarence Leroy Meisinger Award is given to an individual in recognition of research achievement that is, at least in part, aerological in character and concerns the observation, theory and modeling of atmospheric motions on all scales. Zhang will receive his award at the Annual Meeting of the American Meteorological Society in January 2009 in Phoenix, Ariz.
Zhang receives his award for "for outstanding contributions to mesoscale dynamics, predictability and ensemble data assimilation." His recent work focuses on the data simulation, dynamics and predictability of tropical cyclones. Over the past summer, he led the implementation of a real-time ensemble analysis and forecasting system for hurricane prediction, which represents the first time that airborne Doppler radar observations from the National Oceanic and Atmospheric Administration reconnaissance aircraft are ingested into hurricane prediction models and the first time that the cloud-resolving ensemble forecasts for hurricanes in real time were produced. Beside providing situation-dependent forecast uncertainty, preliminary tests show that this prototype system out performed the official forecast issued by the National Hurricane Center.
His research has led to the development and implementation of a hierarchy of analytical, numerical and conceptual atmospheric models that along with in-situ and remotely sensed observations provide fundamental understanding of the dynamics and impacts of gravity waves, particularly associated with the atmospheric jet streams.
His research attributes the limit of weather predictability to the rapid growth of small, often undetectable initial condition errors in the atmosphere, with moist precipitative processes playing a key role in the nonlinear error dynamics. His work provides an important understanding of the time and spatial scales at which probabilistic weather forecasts may outweigh deterministic weather forecasts. Also, with cloud-resolving numerical weather prediction models, his work for the first time provides quantitative confirmation of the predictability bounds established by Ed Lorenz over 40 years ago in the context of chaos theory.
Zhang pioneered the effort of directly assimilating airborne and ground-based Doppler radar observations with the ensemble-based approaches that give the promise of initializing cloud-resolving hurricane models. For this, he has successfully developed and implemented the ensemble-based data assimilation technique in several mesoscale atmospheric models for the study of mesoscale weather systems as well as air pollution meteorology.
Zhang earned his B.S. and M.S. in atmospheric science from Nanjing University, China in 1991 and 1994, respectively, and his Ph.D. in atmospheric science in 2000 from North Carolina State University. He came to Penn State in 2008 after spending seven years as an assistant and then associate and then associate professor at Texas A & M University. In 2000, he spent a year as a postdoctoral fellow at the National Center for Atmospheric Research. In 2004, he received a Young Investigator Award from the Office of Naval Research and in 2007 he received the Outstanding Publication Award from the NCAR. He has published more than 50 peer-reviewed articles.
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