Cooperative Institute for Research in the Atmosphere
Colorado State University
1375 Campus Delivery
Fort Collins, CO 80523-1375
CIRA Room 114
Ting-Chi received her BSc and MS in Atmospheric Science in 2007 and 2009 from National Central University in Taiwan. She continued her education at University of Miami in Florida earning a Ph.D in Meteorology and Physical Oceanography in 2014. Her areas of research interest include
data assimilation including ensemble, variational, and hybrid techniques
numerical weather prediction and microphysics process
develop novel techniques for data assimilation and tropical cyclone predictions
Ting-Chi joined CIRA in Fort Collins in September 2014. As a member of the CIRA Data Assimilation Group, she works on the development and application of a data assimilation system (Gridpoint Statistic Interpolation – GSI) for assimilation of precipitation and moisture observations from several satellite instruments using NOAA Hurricane WRF (HWRF) system. Her recent research activities focus on preparing GSI to assimilate all-sky satellite radiances within the HWRF system.
Assimilate TRMM/GPM Hydrometeor Retrievals in HWRF
Wednesday, June 22, 2016
Hurricane forecasting skills may be improved by utilizing increased precipitation observations available from the Global Precipitation Mission (GPM). This study adds to the GSI capability to assimilate satellite retrieved hydrometeor profile data in the operational HWRF system. The newly developed Hurricane GPROF algorithm produces TRMM/GPM hydrometeor retrievals specifically for hurricanes. Two new observation operators are developed and implemented in GSI to assimilate Hurricane GPROF retrieved hydrometeors in HWRF. They are based on the assumption that all water vapor in excess of saturation with respect to ice or liquid is immediately condensed out. Two sets of single observation experiments that include assimilation of solid or liquid hydrometeor from Hurricane GPROF are performed. Results suggest that assimilating single retrieved solid or liquid hydrometeor information impacts the current set of control variables of GSI by adjusting the environment that includes temperature, pressure, and moisture fields toward saturation with respect to ice or liquid. These results are explained in a physically consistent manner, implying satisfactory observation operators and meaningful structure of background error covariance employed by GSI. Applying to two real hurricane cases, Leslie (2012) and Gonzalo (2014), the assimilation of the Hurricane GPROF data in the innermost domain of HWRF shows a physically reasonable adjustment and an improvement of the analysis compared to observations. However, the impact of assimilating the Hurricane GPROF retrieved hydrometeors on the subsequent HWRF forecasts, measured by hurricane tracks, intensities, sizes, satellite retrieved rain rates, and corresponding IR images, is inconclusive. More details can be found in Wu et al. (2016).
Wu, T.-C., M. Zupanski, L. D. Grasso, P. J. Brown, C. D. Kummerow, and J. A. Knaff, 2016: The GSI Capability to Assimilate TRMM and GPM Hydrometeor Retrievals in HWRF. Q. J. R. Meteorol. Soc., Accepted Author Manuscript, doi:10.1002/qj.2867. Available at: http://onlinelibrary.wiley.com/doi/10.1002/qj.2867/abstract