Feasibility of Raindrop Size Distribution Parameter Estimation with TRMM Precipitation Radar

Abstract

This paper studies the feasibility of estimating raindrop size distribution (DSD) parameters from Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) measurements. A methodology is described for DSD estimation with PR, in which parameter “e” or “a” in the Z-R relation Z=aRb is used as a DSD parameter. The e parameter is an adjustment factor for α in the relation between the attenuation coefficient κ and the effective radar reflectivity factor Ze (κ = αZeβ) that makes the attenuation correction stable by using the path-integrated attenuation estimated from the surface echo as a reference. e is also recognized as a path-averaged DSD parameter. Large (small) e corresponds to small (large) a, i.e., to small (large) median volume diameters (D0s) with the assumption of the gamma DSD model. e exhibits a clear diurnal variation over land suggesting that afternoon convection causes DSDs with large D0s. In contrast, there is no significant diurnal variation over the ocean. e also exhibits a clear negative correlations with the storm-top height deduced from the PR and with the lightning flash rate, both of which again suggest that deep convections over land produce large D0s. There are several error sources that may produce bias errors in the DSD estimates: non-uniform beam filling (NUBF) within the PR antenna beam, non-liquid hydrometeors aloft (such as hail), and variation in the Normalized Radar Cross Section (NRCS) under rain as compared with no-rain conditions. Preliminary evaluations are performed on these error sources, which generally cause negative errors in e (i.e., overestimation of raindrop size). Nevertheless, comparisons of PR- and disdrometer-estimated a (in Z=aRb) generally are in agreement at various locations over both land and oceanic sites. This result suggests the feasibility of PR estimation of DSD. It is concluded that, at the present stage, PR estimates of global DSD distribution should be considered to be “qualitative.” Nevertheless, it would be useful to study the tuning of spaceborne radar algorithms and climatological studies of cloud microphysics.