GMAO Seminar Series: Sara Zhang

In the near future the NASA Global Precipitation Measurement (GPM)
Mission will provide new sources of precipitation observations with
unprecedented accuracy and coverage of the globe.  For hydrological
applications, the satellite observations need to be downscaled to the
required finer spatial and temporal resolution precipitation fields. A
WRF ensemble data assimilation system is developed to explore the
potential of using ensemble data assimilation techniques and
cloud-resolving models to dynamically downscale satellite observations.
A high-resolution regional WRF model with multiple nesting grids is used
to provide the first guess and ensemble forecasts. An ensemble
assimilation algorithm based on Maximum Likelihood Ensemble Filter
(MLEF) is used to perform analysis. Precipitation-affected radiances are
assimilated along with the observations from the NCEP regional data
stream. Prognostic hydrometeors and dynamical variables are
simultaneously updated by the analysis every 3 hours.  The experiments
using the current available satellite precipitation data (AMSR-E and
TRMM-TMI radiances) will be presented to discuss some of the challenging
issues, such as model-predicted hydrometeor control variables and
associated background error covariance, quality control and bias
estimation in radiance space overland.