377
Analysis of National Mosaic and Multi-sensor Quantitative Precipitation Estimates during warm season rainfall events in Oklahoma

- Indicates paper has been withdrawn from meeting
- Indicates an Award Winner
Wednesday, 26 January 2011
Analysis of National Mosaic and Multi-sensor Quantitative Precipitation Estimates during warm season rainfall events in Oklahoma
Washington State Convention Center
Anthony L. Brown, CIMMS/Univ. of Oklahoma, Norman, OK; and S. Van Cooten, K. Howard, K. M. Willingham, J. Zhang, and C. Langston

Poster PDF (1.3 MB)

Accurate estimates of areal rainfall are critical for water management. Inaccuracies in quantitative precipitation estimates (QPE) can lead to inaccurate stream flow simulations, which provide erroneous information to forecasters responsible for flood and flash flood warning products. The National Mosaic and Multi-sensor QPE (NMQ), developed by the National Severe Storms Laboratory, is a tool used to increase the accuracy of rainfall estimates. The NMQ integrates raw radar, rain gauge, and RUC model data to produce gridded precipitation estimates.

May is Oklahoma's climatological rainiest month and presents interesting challenges for water resource monitoring and management. Thus, heavy rainfall events in Oklahoma during May are examined using vertical profiles of reflectivity (VPR) created through the NMQ system, in conjunction with upper-air, RUC model, and surface rain gauge data. Particular attention is paid to the environmental conditions necessary to produce excessive rainfall rates estimated by the NMQ.