4.5 Article

MRMS QPE Performance East of the Rockies during the 2014 Warm Season

Journal

JOURNAL OF HYDROMETEOROLOGY
Volume 18, Issue 3, Pages 761-775

Publisher

AMER METEOROLOGICAL SOC
DOI: 10.1175/JHM-D-16-0179.1

Keywords

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Funding

  1. NOAA/Office of Oceanic and Atmospheric Research under NOAA-University of Oklahoma [NA11OAR4320072]
  2. U.S. Department of Commerce
  3. Radar Operations Center technical transfer memorandum of agreement

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Multi-Radar Multi-Sensor (MRMS) quantitative precipitation estimation (QPE) radar only (Q3RAD), Q3RAD local gauge corrected (Q3gc), dual polarization (Dual Pol), legacy Precipitation Processing System (PPS), and National Centers for Environmental Prediction (NCEP) stage IV product performance were evaluated for data collected east of the Rockies during the 2014 warm season. For over 22 000 radar QPE-gauge data pairs, Q3RAD had a higher correlation coefficient (0.85) and a lower mean absolute error (9.4 mm) than the Dual Pol (0.83 and 10.5 mm, respectively) and PPS (0.79 and 10.8 mm, respectively). Q3RAD performed best when the radar beam sampled precipitation within or above the melting layer because of its use of a reflectivity mosaic corrected for brightband contamination. Both NCEP stage IV and Q3gc showed improvement over the radar-only QPEs; while stage IV exhibited the lower errors, the performance of Q3gc was remarkable considering the estimates were automatically generated in near-real time. Regional analysis indicated Q3RAD outperformed Dual Pol and PPS over the southern plains, Southeast/mid-Atlantic, and Northeast. Over the northern United States, Q3RAD had a higher wet bias below the melting layer than both Dual Pol and PPS; within and above the melting layer, Q3RAD exhibited the lowest errors. The Q3RAD wet bias was likely due to MRMS's overestimation of tropical rain areas in continental regions and applying a high yield reflectivity-rain-rate relationship. An adjustment based on precipitation climatology reduced the wet bias errors by similar to 22% and will be implemented in the operational MRMS in the fall of 2016.

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