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Using a cloud resolving model to generate the beam-filling correction for microwave retrieval of oceanic rainfall
Estimating rain rate from microwave emission is hampered by several difficulties. One of these difficulties is known as the beam-filling error. This error stems from the fact that the relationship between microwave brightness temperature and rain rate is nonlinear, coupled with the fact that the field of view is large or comparable to important scales of variability of rain field. In the previous studies, the beam-filling correction factor was derived by using two dimensional or three dimensional rainfall intensity fields estimated from radar observations as the basis for simulation studies. Meanwhile, vertical structure and the structure along a sloping radiometer view path had also been considered, but it is very costly to gain radar data through field campaigns and it is hard to cover many locations. Cloud Resolving Models (CRM) have made progress. To generate beam-filling corrections with CRMs is very promising; however, the quality of the results is questionable. The present study derives the beam-filling corrections for different channels of TRMM based on data output of a CRM and compares them with the those derived from radar data (ARMAR). In addition, the comparison between Monte Carlo (MC) Radiative Model and Plane-parallel Radiative Transfer Model (RTM) was examined. The physical cloud information that the CRM provides are input into the MC model and the RTM model to compare results for different channels or frequencies. In addition, a simulation study based on the rain rate from the CRM along a sloping radiometer view path is conducted to calculate the beam-filling corrections. The best resolution of the CRM we can get is 3km and the beam-filling corrections based on radar data come from another member of our group, Roy Chen. The final results reveal that the difference between the Monte Carlo Model and the Radiation Transfer Model is very small at low and medium frequencies, but there is a significant difference at high frequency because of scattering. Also, the results reveal that two assumptions of the plane-parallel model contribute to the difference. The first is that the plane parallel model does not allow energy to leak out of raining areas into surrounding areas. The second is that the plane parallel model cannot accommodate physical boundaries in the horizontal dimension for off-nadir viewing angles. Furthermore, the beam-filling correction factors (BCF) derived from the CRM are much larger that those derived from radar data, and the limited width of radar data do not introduce much difference in the BCFs.
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Includes bibliographical references (leaves 66-67).
Issued also on microfiche from Lange Micrographics.
Feng, Kai (2003). Using a cloud resolving model to generate the beam-filling correction for microwave retrieval of oceanic rainfall. Master's thesis, Texas A&M University. Available electronically from
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