179 Radar Deployments and Field Sampling for GPM Ground Validation Field Campaigns

Monday, 16 September 2013
Breckenridge Ballroom (Peak 14-17, 1st Floor) / Event Tent (Outside) (Beaver Run Resort and Conference Center)
Walter A. Petersen, NASA, Wallops, VA; and V. Bringi, L. D. Carey, V. Chandrasekar, S. Rutledge, A. Tokay, and D. B. Wolff Sr.

Handout (5.8 MB)

To test and improve physical assumptions made in Global Precipitation Measurement (GPM) mission satellite-based precipitation retrieval algorithm physics and to characterize uncertainties in precipitation products over a wide range of time/space scales and precipitation environments, the GPM Ground Validation (GV) program has focused on network deployments of dual-polarimetric multi-frequency radars and supporting networks of disdrometers and rain gauges. GV research radars and dense disdrometer/gauge networks are operated as a means to bridge scales between point-measurements (e.g., a single rain gauge), satellite instrument footprints (5-10 km or more), satellite remote sensing retrieval algorithms, and physical processes occurring in the atmospheric column. The design approach to radar data collections is often targeted to minimizing temporal sampling error in multi-parameter retrievals of rain rate, hydrometeor type, particle size distributions, and microphysical processes occurring in the column. In turn, networks of disdrometers provide a means to develop robust polarimetric estimators for DSD retrieval, thus facilitating more detailed studies of DSD evolution and variability.

For example, spatial decorrelation studies of precipitation can be conducted via implementation of sub 1-minute low-level PPI rain scanning, or similar vertical column sampling using rapid back-to-back RHI or narrow sector-volume scanning. In particular, the vertical sampling strategy, especially when conducted at multiple frequencies (e.g., Ka, Ku and S) couples remote sensing measurements made from space to rainfall observed at the surface as a function of the physical processes producing precipitation in the column. Collectively, data detailing DSD variability in all three dimensions is important for constraining GPM DPR and combined algorithm rain rate retrievals, providing datasets for beam filling studies, assessing point-to-area representativeness errors in validating ground or space-based estimates using rain gauges, and to coupling observed horizontal variability to column microphysics.

The aforementioned radar operations and ground network strategies have been successfully used in several previous and ongoing field campaigns including the GCPEX, LPVEX, MC3E, and IFloodS, and also in more extended data collections conducted in Huntsville, AL, and at the NASA Wallops Flight Facility in coastal Virginia. This study will present results from several field data collections.

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