The TRMM Multi-satellite Precipitation Analysis (TMPA) provides three-hourly, 0.25°x0.25° gridded precipitation estimates based on intercalibrated passive microwave estimates, microwave-calibrated infrared estimates, and monthly raingauge analyses for 1998-present over the latitude band 50°N-50°S. The uniform, fine-scale coverage is appealing to a wide range of users, but we continue to work to summarize the dataset in useful ways and compare these results to surface-based data to validate the dataset as possible.

Estimates of “high-impact” or “extreme” events require particular attention because the tails of the precipitation event distribution may display features that are not necessarily reflected in bulk statistical measures. Here, we focus on metrics developed by the joint CCl/CLIVAR/JCOMM Expert Team (ET) on Climate Change Detection and Indices (ETCCDI). These include annual precipitation, annual precipitation for days exceeding the 95th percentile threshold, and runs of consecutive dry days. The ETCCDI provides index values computed with station data drawn from around the globe, but clearly they can be computed quasi-globally using the TMPA, although its period of record is too short to yield truly climatological values. Particularly in light of the point-to-area conversion problem for precipitation, it is important to compare the TMPA index values against existing station data to determine how faithfully the TMPA-based results reflect the station-based results. This is done both by pooling all years for all stations and by looking at the interannual variation at individual stations. The comparison is done for all ETCCDI stations in the latitude belt 40°N-40°S that have data for each of the years 1998-2003. The metric that tends to compare the best between the two data sets, with >95th percentile rain next. Consecutive dry days, on the other hand, is more sensitive to the occurrence of isolated rain events and shows less of a relationship between the two data sets is annual precipitation, followed by >95th percentile accumulation, then runs of consecutive dry days. In the analysis, we see general consistency among the various indices, but the shifts in relationships give insight into the regimes that dominate various regions.