Browsing Rangeland Ecology & Management, Volume 61, Number 3 (May 2008) by Authors
Evaluation of NEXRAD Radar Precipitation Products for Natural Resource ApplicationsHardegree, Staurt P.; Van Vactor, Steven S.; Levinson, David H.; Winstral, Adam H. (Society for Range Management, 2008-05-01)Timing and amount of precipitation are principal drivers of most rangeland processes, but the availability of rainfall-gauge data over extensive rangelands, particularly in the western United States, is limited. The National Weather Service (NWS), Department of Defense, and Federal Aviation Administration operate a network of Doppler radar stations that produce hourly rainfall estimates, at approximately 16-km2 resolution, with nominal coverage of 96% of the conterminous United States. Internal utilization of these data by the three agencies is primarily for the detection and modeling of extreme weather events. The usefulness of these data for external hydrologic and natural resource applications is limited by a lack of tools for decoding and georeferencing digital precipitation data products. We modified NWS source code to produce decoding and georeferencing tools and used them to evaluate radar precipitation data for the Boise (CBX) radar relative to gauges in the Snake River Plain of southwestern Idaho for the period January 1998 to May 2004. The relationship between radar and gauge precipitation estimates changed after a revision of radar-processing protocols in 2002 and 2003. Cumulative radar precipitation estimates made prior to November 2002 underestimated gauge readings by 50%-60%. Subsequent radar data overestimated cumulative gauge precipitation by 20%-40%. The radar, however, detected precipitation during significantly fewer hours than were detected by the gauge network both before and after programming changes. Additional modification of NWS precipitation- processing procedures might improve accessibility and utility of these data for rangeland management and natural resource modeling applications. Currently available data can still be very useful for estimating high-intensity events that greatly affect processes such as soil erosion and flooding.