products (e.g., reflectivity volumes, brightness temperatures, hydrometeor contents etc.) on convective scales, and the creation of VHF-optical lightning proxies for use in testing and improving GOES-R Geostationary Lightning Mapper algorithms.2.1.5 Ground validation data processingA key component of the TRMM project is the Ground Validation (GV) effort (http://trmm- fc.gsfc.nasa.gov/trmm_gv). The GV effort is primarily a data collection and product generation program. Ground-based radar, rain gauge and disdrometer data are collected and quality-controlled, and validation products are produced for comparison with TRMM satellite products. Detailed information and product analysis is available on the TRMM GV web site. The four primary GV sites are Darwin, Australia; Houston, Texas; Kwajalein, Republic of the Marshall Islands; and, Melbourne, Florida (Wolff et al 2005). There is also a significant effort being supported at NASA Wallops Flight Facility (WFF) to provide high quality, long-term measurements of rain rates (via a network of rain gauges collocated with National Weather Service gauges), as well as drop size distributions (DSD) using a variety of instruments, including impact-type Joss Waldvogel, laser-optical Parsivel, as well as two- dimensional video disdrometers. DSD measurements are also being collected at Melbourne and Kwajalein using Joss-Waldvogel disdrometers. The list of GV products is given in Appendix A.The largest part of the validation effort involves the routine, careful collection, processing and product generation of ground-based radar, rain gauge and disdrometer data in order to produce standard validation products. Products are produced using techniques developed to carefully quality control ground radar data sets and estimate surface rainfall rates, adjusted by quality-controlled rain gauge data. The procedures for performing these tasks are optimized to take advantage of each site’s strengths. The primary radar data quality control (QC) algorithm masks non-precipitation echoes by use of adjustable echo-height and reflectivity thresholds. Additional QC algorithms make use of signal quality and semi-permanent ground clutter sources (Silberstein et al. 2008). Rain gauge data QC is performed on several automated levels, one of which is a procedure to filter unreliable rain gauge data upon comparison to radar data (Amitai 2000). To ensure GV data products are of the highest possible quality, dependent and independent rain gauge data (when available) are compared with radar estimates via scatter- plot analysis. Further analyses include time series comparisons of gauge and radar rain rates and detailed study of QC results. These efforts have resulted in standard validation data sets, at both instantaneous and monthly time scales, with which to compare TRMM- based rain estimates, and have helped to establish the accuracy of the various TRMM products. In addition, other specific gauge data sets are used to produce additional validation products.
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