An Examination of Version-5 Rainfall Estimates from the TRMM Microwave Imager, Precipitation Radar, and Rain Gauges on Global, Regional, and Storm Scales

Stephen W. Nesbitt and Edward J. Zipser

Department of Meteorology, University of Utah, Salt Lake City, Utah

Christian D. Kummerow

Department of Atmospheric Science, Colorado State University, Fort Collins, Colorado

ABSTRACT

An evaluation of the version-5 precipitation radar (PR; algorithm 2A25) and Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI; algorithm 2A12) rainfall products is performed across the Tropics in two ways: 1) by comparing long-term TRMM rainfall products with Global Precipitation Climatology Centre (GPCC) global rain gauge analyses and 2) by comparing the rainfall estimates from the PR and TMI on a rainfall feature-by-feature basis within the narrow swath of the PR using a 1-yr database of classified precipitation features (PFs). The former is done to evaluate the overall biases of the TMI and PR relative to “ground truth” to examine regional differences in the estimates; the latter allows a direct comparison of the estimates with the same sampling area, also identifying relative biases as a function of storm type. This study finds that the TMI overestimates rainfall in most of the deep Tropics and midlatitude warm seasons over land with respect to both the GPCC gauge analysis and the PR (which agrees well with the GPCC gauges in the deep Tropics globally), in agreement with past results. The PR is generally higher than the TMI in midlatitude cold seasons over land areas with gauges. The analysis by feature type reveals that the TMI overestimates relative to the PR are due to overestimates in mesoscale convective systems and in most features with 85-GHz polarization-corrected temperature of less than 250 K (i.e., with a significant optical depth of precipitation ice). The PR tended to be higher in PFs without an ice-scattering signature of less than 250 K. Normalized for a subset of features with a large rain volume (exceeding 104 mm h−1 km2) independent of the PF classification, features with TMI > PR in the Tropics tended to have a higher fraction of stratiform rainfall, higher IR cloud tops, more intense radar profiles and 85-GHz ice-scattering signatures, and larger rain areas, whereas the converse is generally true for features with PR > TMI. Subtropical-area PF bias characteristics tended not to have such a clear relationship (especially over the ocean), a result that is hypothesized to be due to the influence of more variable storm environments and the presence of frontal rain. Melting-layer effects in stratiform rain and a bias in the ice-scattering–rain relationship were linked to the TMI producing more rainfall than the PR. However, noting the distinct characteristic biases Tropics-wide by feature type, this study reveals that accounting for regime-dependent biases caused by the differing horizontal and vertical morphologies of precipitating systems may lead to a reduction in systematic relative biases in a microwave precipitation algorithm.