STOCHASTIC FILTERING OF RAIN PROFILES USING RADAR, SURFACE-REFERENCEDRADAR, OR COMBINED RADAR-RADIOMETER MEASUREMENTS

This paper describes a computationally efficient nearly optimal Bayesi an algorithm to estimate rain (and drop size distribution) profiles, g iven a radar reflectivity profile at a single attenuating wavelength. In addition to estimating the averages of all the mutually ambiguous c ombinations of rain parameters that can produce the data observed, the approach also calculates the rms uncertainty in its estimates (this u ncertainty thus quantifies the ''amount of ambiguity'' in the ''soluti on''). The paper also describes a more general approach that can make estimates based on a radar reflectivity profile together with an appro ximate measurement of the path-integrated attenuation, or a radar refl ectivity profile and a set of passive microwave brightness temperature s. This more general ''combined'' algorithm is currently being adapted for the Tropical Rainfall Measuring Mission.