NOAA's National Severe Storms Laboratory (NSSL) Q2 System (www. nmq.nssl.noaa.gov) produces Vertical Profiles of Reflectivity (VPR) every five minutes for each continental United States (CONUS) NEXRAD site. These VPRs are used in the production of five-minute multi-sensor Quantitative Precipitation Estimates (QPE) to provide constantly updated relationships between radar reflectivity factor, Z, and rain rate, R (Z-R). VPRs were archived for June 3 and 4 for AKQ, RDU, and MHX. The VPRs were analyzed to quantify radar reflectivity trends over the course of the storm event. These trends were then correlated with rainfall rates, atmospheric sounding data, and surface observations, to investigate the characteristics of the VPRs associated with the highest rainfall rates. Results of this analysis indicate VPRs associated with the highest hourly rainfall rates observed with the storm system occurred as VPRs lost a concentrated area of high reflectivities around the atmospheric freezing level. Additionally, the gradient of radar reflectivities above and below this dissipating high reflectivity area diminished. Atmospheric soundings and surface map analysis indicated the air mass characteristics were acquiring tropical characteristics as surface dew points and atmospheric water content were increasing, wind directions transitioned from westerly to an easterly fetch off the Atlantic Ocean, and the atmospheric freezing level was rising. As the storm system moved away from the Carolinas, VPRs began to regain a concentrated area of high reflectivities around the atmospheric freezing level and the gradient of radar reflectivities began to increase once again above and below the area of higher reflectivities.
To quantify the implications of these VPR characteristics on the accuracy of the Q2 system's five-minute multi-sensor Quantitative Precipitation Estimates (QPE), the Q2 statistical verification tools were used to evaluate the performance of the system during the periods of the most intense rainfall. The Q2 system has recently implemented a tropical rain Z-R when VPRs and atmospheric sounding data meet criteria which have been identified by NSSL scientists as common factors in intense rainfall events. The VPRs observed through this June, 2007 storm event, were consistent with their findings. Results of this assessment show the Q2 tropical Z-R relationship produced highly accurate precipitation estimates which are available at a 1 km grid mesh resolution every five minutes. Additionally, the dynamic VPR system captured the air mass changes which occurred during the event. This feature provides improved information on a storm's environment to determine appropriate radar Z-R adjustments. This case demonstrates the ability to increase the accuracy of precipitation estimates especially in ungauged locations which can improve NOAA and our nation's flash flood monitoring and prediction programs.
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