32nd Conference on Broadcast Meteorology/31st Conference on Radar Meteorology/Fifth Conference on Coastal Atmospheric and Oceanic Prediction and Processes

Friday, 8 August 2003: 5:00 PM
Use of polarimetric radar observations in the evaluation of a TRMM combined radar-radiometer algorithm for estimation of precipitation profiles
Mircea Grecu, University of Maryland, Baltimore County and NASA/GSFC, Greenbelt, MD; and W. S. Olson
Poster PDF (305.0 kB)
In this study, the retrieval of precipitation profiles using a combined radar-radiometer approach is investigated based on polarimetric radar data. The data originate in Tropical Rainfall Measuring Mission (TRMM) field experiments, such as the Texas Florida Underflights Fields Experiments (TEFLUN) and Kwajalein Experiment (KWAJEX). Disdrometer data are also considered for the development and validation of the algorithm used for precipitation estimation from polarimetric radar observations. The polarimetric radars provide observations that can be effectively used to characterize two parameters drop-size distributions (DSD). The two parameters are the intercept and the mean size in a normalized gamma formulation, and they are estimated based on the horizontal and vertical reflectivity factors, and the differential phase. The TRMM combined algorithm investigated in this study also provides estimates of the two parameters in the normalized gamma DSD. This is because the existence of complementary information in the radar and radiometer observations makes possible the use of a two-parameter DSD formulation. The mean size is determined uniquely from the DSD intercept and the TRMM Precipitation Radar (PR) observations, and the DSD intercept is iteratively determined based on radiometer observations. The DSD estimates from the combined radar-radiometer algorithm are compared against the polarimetric radar retrievals. Based on the comparison, various components of the combined approach, i.e. the parameterization of the cloud profile and the transition from mixed to liquid phase, are refined. Also, the uncertainty associated with retrievals from combined algorithm is assessed.

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