Vector Radiative Transfer Model: Application to Rainfall Retrieval with Microwave Radiometric Data.
A new vector radiative transfer model is developed in this dissertation. The physical processes included are thermal emission, scattering, absorption and bidirectional reflection and emission at the lower boundary. The medium may be forced at the top boundary by polarized parallel or diffuse radiation and by polarized internal and boundary thermal sources as well. The model is unconditionally stable for an arbitrarily large number of streams and arbitrarily large optical depths. Brightness temperature structures of mesoscale precipitation systems (MPSs) from radiative transfer modeling are presented and analysed. The analysis reveals following primary results: (1) Polarization brightness temperatures at 85.50 GHz well reflect structures of convective and stratiform precipitation in the MPSs. Distinct contrasts between PCTs at 85.50 GHz in the convective and stratiform regions in the MPSs exist. (2) Horizontally polarized brightness temperatures at 19.35 and 37.00 GHz are more sensitive to the light rain over ocean than those at other frequencies and polarization states. (3) The PCTs at 37.00 and 85.50 GHz well correlate the precipitation ice water path in the MPSs and the PCT at 19.35 GHz correlates the precipitation liquid water path. Inversion relations between PCTs and rain rates are derived from radiative transfer calculations in terms of a new precipitation model. This model includes precipitation -sized ice hydrometeors, raindrops and cloud-sized hydrometeors. Error sensitivity study shows that variations of cloud water content are major causes responsible for errors of retrieved rain rates and that light rain rates retrieved from low frequency inversion relations include larger uncertainty than those from high frequency inversion relations. A microwave multi-channel algorithm is developed for retrieving monthly precipitation over global land and ocean. The probability density function of rain rates is employed in the algorithm. Retrieved monthly precipitation exhibits consistency with presently existing precipitation data in terms of large scale features and discrepancy in terms of detailed structures.
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- Physics: Atmospheric Science; Physics: Radiation; Physics: Optics