Journal
WEATHER AND FORECASTING
Volume 29, Issue 5, Pages 1106-1119Publisher
AMER METEOROLOGICAL SOC
DOI: 10.1175/WAF-D-13-00072.1
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Funding
- National Oceanic and Atmospheric Administration (NOAA)
- Federal Aviation Administration's Aviation Weather Research Program
- NOAA/Office of Oceanic and Atmospheric Research under NOAA-University of Oklahoma Co-operative Agreement [NA11OAR4320072]
- U.S. Department of Commerce
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Polarimetric radar observations provide information regarding the shape and size of scatterers in the atmosphere, which help users to differentiate between precipitation and nonprecipitation radar echoes. Identifying and removing nonprecipitation echoes in radar reflectivity fields is one critical step in radar-based quantitative precipitation estimation. An automated algorithm based on reflectivity, correlation coefficient, and temperature data is developed to perform reflectivity data quality control through a set of physically based rules. The algorithm was tested with a large number of real data cases across different geographical regions and seasons and showed a high accuracy (Heidke skill score of 0.83) in segregating precipitation and nonprecipitation echoes. The algorithm was compared with two other operational and experimental reflectivity quality control methodologies and showed a more effective removal of nonprecipitation echoes and a higher computational efficiency. The current methodology also demonstrated a satisfactory performance in a real-time national multiradar and multisensor system.
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