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Evaluation of Spatial Errors of Precipitation Rates and Types from TRMM Spaceborne Radar over the Southern CONUS

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  • 1 * School of Civil Engineering and Environmental Science, University of Oklahoma, and Advanced Radar Research Center, National Weather Center, Norman, Oklahoma
  • | 2 School of Civil Engineering and Environmental Science, University of Oklahoma, and Advanced Radar Research Center, National Weather Center, and NOAA/National Severe Storms Laboratory, Norman, Oklahoma
  • | 3 NOAA/National Severe Storms Laboratory, Norman, Oklahoma
  • | 4 Earth System Science Interdisciplinary Center, University of Maryland, College Park, College Park, and Hydrological Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, Maryland
  • | 5 NOAA/National Severe Storms Laboratory, and Cooperative Institute for Mesoscale Meteorological Studies, University of Oklahoma, Norman, Oklahoma
  • | 6 ** School of Computer Science, University of Oklahoma, Norman, Oklahoma
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Abstract

In this paper, the authors estimate the uncertainty of the rainfall products from NASA and Japan Aerospace Exploration Agency's (JAXA) Tropical Rainfall Measurement Mission (TRMM) Precipitation Radar (PR) so that they may be used in a quantitative manner for applications like hydrologic modeling or merging with other rainfall products. The spatial error structure of TRMM PR surface rain rates and types was systematically studied by comparing them with NOAA/National Severe Storms Laboratory's (NSSL) next generation, high-resolution (1 km/5 min) National Mosaic and Multi-Sensor Quantitative Precipitation Estimation (QPE; NMQ/Q2) over the TRMM-covered continental United States (CONUS). Data pairs are first matched at the PR footprint scale (5 km/instantaneous) and then grouped into 0.25° grid cells to yield spatially distributed error maps and statistics using data from December 2009 through November 2010. Careful quality control steps (including bias correction with rain gauges and quality filtering) are applied to the ground radar measurements prior to considering them as reference data. The results show that PR captures well the spatial pattern of total rainfall amounts with a high correlation coefficient (CC; 0.91) with Q2, but this decreases to 0.56 for instantaneous rain rates. In terms of precipitation types, Q2 and PR convective echoes are spatially correlated with a CC of 0.63. Despite this correlation, PR's total annual precipitation from convection is 48.82% less than that by Q2, which points to potential issues in the PR algorithm's attenuation correction, nonuniform beam filling, and/or reflectivity-to-rainfall relation. Finally, the spatial analysis identifies regime-dependent errors, in particular in the mountainous west. It is likely that the surface reference technique is triggered over complex terrain, resulting in high-amplitude biases.

Corresponding author address: Dr. Yang Hong, National Weather Center, Advanced Radar Research Center, Suite 4610, 120 David L. Boren Blvd., Norman, OK 73072-7303. E-mail: yanghong@ou.edu

Abstract

In this paper, the authors estimate the uncertainty of the rainfall products from NASA and Japan Aerospace Exploration Agency's (JAXA) Tropical Rainfall Measurement Mission (TRMM) Precipitation Radar (PR) so that they may be used in a quantitative manner for applications like hydrologic modeling or merging with other rainfall products. The spatial error structure of TRMM PR surface rain rates and types was systematically studied by comparing them with NOAA/National Severe Storms Laboratory's (NSSL) next generation, high-resolution (1 km/5 min) National Mosaic and Multi-Sensor Quantitative Precipitation Estimation (QPE; NMQ/Q2) over the TRMM-covered continental United States (CONUS). Data pairs are first matched at the PR footprint scale (5 km/instantaneous) and then grouped into 0.25° grid cells to yield spatially distributed error maps and statistics using data from December 2009 through November 2010. Careful quality control steps (including bias correction with rain gauges and quality filtering) are applied to the ground radar measurements prior to considering them as reference data. The results show that PR captures well the spatial pattern of total rainfall amounts with a high correlation coefficient (CC; 0.91) with Q2, but this decreases to 0.56 for instantaneous rain rates. In terms of precipitation types, Q2 and PR convective echoes are spatially correlated with a CC of 0.63. Despite this correlation, PR's total annual precipitation from convection is 48.82% less than that by Q2, which points to potential issues in the PR algorithm's attenuation correction, nonuniform beam filling, and/or reflectivity-to-rainfall relation. Finally, the spatial analysis identifies regime-dependent errors, in particular in the mountainous west. It is likely that the surface reference technique is triggered over complex terrain, resulting in high-amplitude biases.

Corresponding author address: Dr. Yang Hong, National Weather Center, Advanced Radar Research Center, Suite 4610, 120 David L. Boren Blvd., Norman, OK 73072-7303. E-mail: yanghong@ou.edu
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