Studying Rain Rate from Space and Ground Observations

摘要

The distribution of rain rates (R) is of great interest in many fields. For example, hydrological applications such as flood forecasting depend on an accurate representation of the excess rainfall—driven by R—that does not infiltrate the soil. It is also of great concern to radio wave propagation—the theme of this symposium. Probability distribution functions (pdf) of R can now be obtained from spaceborne radar observations. Effort to evaluate these pdfs using ground observations is presented.The evaluation of instantaneous rainfall products and rain rate estimates from space is quite a challenge. Scatter plots of pixel-by-pixel comparisons of space-based R estimates with ground-based radar R estimates are extremely noisy because of sample volume discrepancies, timing and navigation mismatches, and uncertainties in the observed-radar reflectivity rain-rate Ze-R relations. Furthermore, comparisons of rainfall over daily, weekly or even monthly time scales suffer from the temporal sampling errors of the satellite where the revisit time is on the order of hours or days (e.g., the Tropical Rainfall Measuring Mission [TRMM] satellite, the future Global Precipitation Measurement [GPM] mission satellite). Consequently, an alternative approach of comparing space-based radar pdfs with pdfs derived from co-located ground-based radar observations is attractive for evaluating satellite-based precipitation products, such as those from TRMM precipitation radar (PR).We will present comparisons of R estimates from the TRMM PR and co-located data from gauge-adjusted ground-based radar (WSR-88D) estimates obtained during nine years of observations. These results provide an overview of how well the satellite retrieved estimates—based on the new NASA TRMM radar rainfall products—compare to the ground-based estimates. These comparisons are part of a new framework for global verification of space-borne radar estimates of precipitation based on comparing pdfs of R. The framework demonstrates how a hydrologic approach that uses statistical properties of precipitation to estimate the uncertainties can be combined with a meteorological approach that uses physical properties of rainfall. The presentation provides insights into the uncertainties in space-based and ground-based radar estimates of rain rate distributions, and a discussion of opportunities and challenges to determine and reduce these uncertainties. This presentation combines results which are summarized in [1], [2], and [3].Examples of comparison are provided in the following figures.