Validation of precipitation measurements and estimates from satellite active and passive sensors is essential for the success of the TRMM and GPM missions. One of the critical steps of validation is to accurately resample data from space-borne and ground-based instruments to a common grid. Because of differences in the scattering geometries of space-borne and ground-based observations, accurate registration of data is a challenging problem. This problem is further complicated if there are offsets in time among the measurements. As a result, one or more of the data sets may require translation, rotation, or scaling to ensure reliable comparisons among them. In our proposed study, we will establish data coordinate transformation system (DCTS) that would be used to accurately register the data acquired by multiple sensors from space- and ground-based platforms followed by instantaneous and statistical comparisons of the satellite products such as rain rate and radar reflectivity factor derived from TRMM TMI and PR (or GPM GMI and DPR) to the same products obtained from the ground-based observations. Comparisons of PR and DPR to ground radars (such as WSR-88D) provide a means to examine the radar calibrations and attenuation correction procedures adopted in the satellite radar algorithms. The microphysical properties of hydrometeors derived from the DPR can also be verified through the results obtained from the polarimetric ground-based radar systems. A strategy for an assessment of multiple scattering effects at the DPR Ka-band is also described. In addition, because the spatial (sample) resolution of the ground-based weather surveillance radar varies as a function of radar range (while the satellite radar yields nearly uniformly spatial sampling), uniform gridding over the overlap area of satellite and ground radar observations might lead to biases or ambiguities particularly because of variability of the precipitation in space. These uncertainties will be estimated by means of radar simulations using cloud resolving models (CRM), TRMM PR data sets and ground-based radar measurements. To improve the degree of agreement between the PR and ground-based radar, non-uniform gridding, where the grid spacing at a particular location depends on the inherent resolutions of the radars, will be considered.
