A Study of Air/Space-borne Dual-Wavelength Radar for Estimation of Rain Profiles

In this study, a framework is given by which air/space-borne dual-wavelength radar data can beused to estimate the characteristic parameters of hydrometeors. The focus of the study is on the GlobalPrecipitation Measurement (GPM) precipitation radar, a dual-wavelength radar that will operate in theKu (13.6 GHz) and Ka (35 GHz) bands. A key aspect of the retrievals is the relationship between thedifferential frequency ratio (DFR) and the median volume diameter, Do, and its dependence on the phasestate of the hydrometeors. It is shown that parametric plots of Do and particle concentration in the plane ofthe DFR and the radar reflectivity factor in the Ku band can be used to reduce the ambiguities in derivingDo from DFR. A self-consistent iterative algorithm, which does not require the use of an independent path-attenuation constraint, is examined by applying it to the apparent radar reflectivity profiles simulated froma drop size distribution (DSD) model. For light to moderate rain, the self-consistent rain profiling approachconverges to the correct solution only if the same shape factor of the Gamma distributions is used both togenerate and retrieve the rain profiles. On the other hand, if the shape factors differ, the iteration generallyconverges but not to the correct solution. To further examine the dual-wavelength techniques, the self-consistent iterative algorithm, along with forward and backward rain profiling algorithms, are appliedto measurements taken from the 2nd generation Precipitation Radar (PR-2) built by the Jet PropulsionLaboratory. Consistent with the model results, it is found that the estimated rain profiles are sensitive tothe shape factor of the size distribution when the iterative, self-consistent approach is used but relativelyinsensitive to this parameter when the forward- and backward-constrained approaches are used.