Stochastic Filtering of Rain Profiles using Radar, Surface-Referenced Radar, or Combined Radar/Radiometer Measurements

This paper describes a computationally efficient nearly-optimal Bayesian algorithm to estimate rain (and drop-size-distribution) profiles, given a radar reflectivity profile at a single attenuating wavelength. In addition to estimating the averages of all the mutually ambiguous combinations of rain parameters that can produce the data observed, the approach also calculates the r.m.s. uncertainty in its estimates (this uncertainty thus quantifies the "amount of ambiguity" in the "solution"). The paper also describes a more general approach that can make estimates based on a radar reflectivity profile together with an approximate measurement of the path-integrated attenuation, or a radar reflectivity profile and a set of passive microwave brightness temperatures. This more general "combined" algorithm is currently being adapted for the Tropical Rainfall Measuring Mission. 1 Introduction It is well-documented (Hitschfeld and Bordan 1954, Meneghini 1978, Haddad et al 1993) that there ar..