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Rainfall intensities during extreme events over the continental U.S. are compared for several advanced radar products. These products include: 1) TRMM spaceborne radar (PR) near surface estimates; 2) NOAA Next-Generation Quantitative Precipitation Estimation (QPE) very high-resolution (1 km) radar-only national mosaics (Q2); 3) very high-resolution instantaneous gauge adjusted radar national mosaics, which we have developed by applying gauge correction on the Q2 instantaneous radar-only products; and 4) several independent C-band dual-polarimetric radar-estimated rainfall samples collected with the ARMOR radar in northern Alabama. Though accumulated rainfall amounts are often similar, we find the satellite and the ground radar rain rate pdfs to be quite different. PR pdfs are shifted towards lower rain rates, implying a much larger stratiform/convective rain ratio than do ground radar products. The shift becomes more evident during strong continental convective storms and much less during tropical storms. Resolving the continental/maritime regime behavior and other large discrepancies between the products presents an important challenge. A challenge to improve our understanding of the source of the discrepancies, to determine the uncertainties of the estimates, and to improve remote-sensing estimates of precipitation in general.

The Tropical Rainfall Measuring Mission (TRMM) satellite was successfully launched in November, 1997. The main purpose of TRMM is to sample tropical rainfall using the first active spaceborne precipitation radar. To validate TRMM satellite observations, a comprehensive Ground Validation (GV) Program has been implemented. The primary goal of TRMM GV is to provide basic validation of satellite-derived precipitation measurements over monthly climatologies for the following primary sites: Melbourne, FL; Houston, TX; Darwin, Australia; and Kwajalein Atoll, RMI. As part of the TRMM GV effort, research analysts at NASA Goddard Space Flight Center (GSFC) generate standardized TRMM GV products using quality-controlled ground-based radar data from the four primary GV sites as input. This presentation will provide an overview of the TRMM GV climatological processing system. A description of the data flow between the primary GV sites, NASA GSFC, and the TRMM Science and Data Information System (TSDIS) will be presented. The radar quality control algorithm, which features eight adjustable height and reflectivity parameters, and its effect on monthly rainfall maps will be described. The methodology used to create monthly, gauge-adjusted rainfall products for each primary site will also be summarized. The standardized monthly rainfall products are developed in discrete, modular steps with distinct intermediate products. These developmental steps include: (1) extracting radar data over the locations of rain gauges, (2) merging rain gauge and radar data in time and space with user-defined options, (3) automated quality control of radar and gauge merged data by tracking accumulations from each instrument, and (4) deriving Z-R relationships from the quality-controlled merged data over monthly time scales. A summary of recently reprocessed official GV rainfall products available for TRMM science users will be presented. Updated basic standardized product results and trends involving monthly accumulation, Z-R relationship, and gauge statistics for each primary GV site will be also displayed.

The TRMM Global Validation Program is giving us a unique opportunity to compare radar datasets from different sites since they are analyzed in a relatively uniform procedure. Monthly Ze-R relations for four different sites (i.e, Melbourne Florida, Houston Texas, Darwin Australia and Kwajalein Atoll) were derived. The relations were obtained using the Window Probability Matching Method (WPMM). This version of the PMM relies on matching unconditional probabilities of rain rates, R, and radar reflectivity, Ze, using rain gauge and radar data, respectively. This procedure was done separately for convective and stratiform rain type using the Steiner classification procedure. The radar and gauge data from all sites were quality controlled using the same algorithms, which include also an automatic procedure to filter unreliable rain gauge data upon comparison to radar data. An adjusted power law Z-R for each rain type was also derived by comparing the radar-gauge coincident pairs in order to adjust the total monthly rainfall to match the gauges. The obtained PMM based Ze-R relations are found to be curved lines in log-log space rather than any straight line power law. While the PMM based Ze-R curves were always distinctly different between the convective and stratiform rain, the power law based Z-R, in few cases, was found to be the same for both types. In general, a given reflectivity was matched to a much lower rain intensity in the convective rainfall as compared to that in stratiform rainfall. These findings are inherently contradictory to previous findings based on disdrometer data and suggest some precaution for using the latter Z-R relations on radar data when the partition of stratiform and convective rainfall amount is in concern. The inverse trends in the relations might be caused by effects such as partial beam fillings, the use of different classification schemes, as well as having a distinct difference in the Z-R relations between the initial convective and the trailing transition regions as suggested by recent findings.

The Primary goal of the Tropical Rainfall Measuring Mission (TRMM) Ground Validation (GV) effort is to provide basic validation of satellite-derived precipitation measurements over monthly climatologies. To this end, the Joint Center for Earth Systems Technology (JCET) at the University of Maryland, Baltimore County produces monthly rainfall accumulation reference products for each of the four primary TRMM GV sites. These products, standard methodology for deriving monthly, gauge-adjusted rainfall products, are utilized for each primary site. The monthly rainfall GV reference products are developed in discrete, modular steps with distinct intermediate products. These developmental steps, which will be fully discussed, include: (1) extracting radar data over locations of rain gauges, (2) merging rain gauge and radar data in time and space with user-defined options, (3) quality control of radar and gauge merged data by tracking accumulations from each instrument, and (4) deriving Z_R relationship from quality-controlled merged data over monthly time scales. A summary of all gauge statistics and GV rainfall reference products available for TRMM science users will be presented. Basic reference product results and trends involving monthly accumulation, Z-R relationship, and gauge statistics for primary GV site will be discussed. Finally, the sample impact on monthly rainfall reference products, through varying the time interval between intermediate rainfall accumulations, will be analyzed and presented.

The Tropcial RAinfall Measuring Mission-Large Scale Biosphere-Atmosphere experiment in Amazonia (TRMM-LBA) was conducted near Ji Parana, Rondonia, Brazil during the 1999 Amazonian wet season (Jan-Feb). TRMM-LBA provided detailed observations of precipitating systems from surface and aircraft instrumentation which may be compared to measurements from the TRMM satellite. The surface-based platforms included two scanning Doppler radars (the NASA TOGA C-band radar and the NCAR SPOL S-band dual polarization radar) which collected continuous dual-Doppler measurements of precipitating convection.This paper focuses on data from the TOGA radar to provide a preliminary overview of general properties of convective organization observed during TRMM-LBA. These include squall line evolution and morphology, diurnal variation of precipitation, and the vertical intensity of convection. Mesoscale squall lines were most commonly observed in the afternoon, with associated regions of stratiform precipitation persisting into the evening. Nocturnal widespread stratiform rain often formed before sunrise, with no apparent source region of deep convection and very weak radar bright band. Reflectivity values in deep convective cells typically decreased rapidly above the melting level, reminiscent of tropical oceanic convection, and consistent with the relative scarcity of lightning (with respect to other tropical continental regions). Vertically developed electrified convection, though infrequent, did occur regularly.

Application of the window probability matching method to radar and rain gauge data that have been objectively classified into different rain types resulted in distinctly different Z(sub e)-R relationships for the various classifications. These classification parameters, in addition to the range from the radar, are (a) the horizontal radial reflectivity gradients (dB/km); (b) the cloud depth, as scaled by the effective efficiency; (c) the brightband fraction within the radar field window; and (d) the height of the freezing level. Combining physical parameters to identify the type of precipitation and statistical relations most appropriate to the precipitation types results in considerable improvement of both point and areal rainfall measurements. A limiting factor in the assessment of the improved accuracy is the inherent variance between the true rain intensity at the radar measured volume and the rain intensity at the mouth of the rain guage. Therefore, a very dense rain gauge network is required to validate most of the suggested realized improvement. A rather small sample size is required to achieve a stable Z(sub e)-R relationship (standard deviation of 15% of R for a given Z(sub e)) -- about 200 mm of rainfall accumulated in all guages combined for each classification.