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Correction of Radar QPE Errors for Nonuniform VPRs in Mesoscale Convective Systems Using TRMM Observations

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  • 1 Cooperative Institute for Mesoscale Meteorological Studies, University of Oklahoma, and NOAA/OAR/National Severe Storms Laboratory, Norman, Oklahoma and Nanjing University of Information Science and Technology, Nanjing, China
  • 2 NOAA/OAR/National Severe Storms Laboratory, Norman, Oklahoma
  • 3 Advanced Radar Research Center, and Hydrometeorology and Remote Sensing Laboratory, University of Oklahoma, Norman, Oklahoma
  • 4 Advanced Radar Research Center, and Hydrometeorology and Remote Sensing Laboratory, and School of Civil Engineering and Environmental Sciences, University of Oklahoma, Norman, Oklahoma
  • 5 Center for Analysis and Prediction of Storms, University of Oklahoma, Norman, Oklahoma
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Abstract

Mesoscale convective systems (MCSs) contain both regions of convective and stratiform precipitation, and a bright band (BB) is often found in the stratiform region. Inflated reflectivity intensities in the BB often cause positive biases in radar quantitative precipitation estimation (QPE). A vertical profile of reflectivity (VPR) correction is necessary to reduce such biases. However, existing VPR correction methods for ground-based radars often perform poorly for MCSs owing to their coarse resolution and poor coverage in the vertical direction, especially at far ranges. Spaceborne radars such as the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR), on the other hand, can provide high resolution VPRs. The current study explores a new approach of incorporating the TRMM VPRs into the VPR correction for the Weather Surveillance Radar-1988 Doppler (WSR-88D) radar QPE. High-resolution VPRs derived from the Ku-band TRMM PR data are converted into equivalent S-band VPRs using an empirical technique. The equivalent S-band TRMM VPRs are resampled according to the WSR-88D beam resolution, and the resampled (apparent) VPRs are then used to correct for BB effects in the WSR-88D QPE when the ground radar VPR cannot accurately capture the BB bottom. The new scheme was tested on six MCSs from different regions in the United States and it was shown to provide effective mitigation of the radar QPE errors due to BB contamination.

Corresponding author address: Youcun Qi, Cooperative Institute for Mesoscale Meteorological Studies, University of Oklahoma, and NOAA/OAR National Severe Storms Laboratory, 120 David L Boren Blvd., Norman, OK 73072. E-mail: youcun.qi@noaa.gov; youcun.qi@gmail.com

Abstract

Mesoscale convective systems (MCSs) contain both regions of convective and stratiform precipitation, and a bright band (BB) is often found in the stratiform region. Inflated reflectivity intensities in the BB often cause positive biases in radar quantitative precipitation estimation (QPE). A vertical profile of reflectivity (VPR) correction is necessary to reduce such biases. However, existing VPR correction methods for ground-based radars often perform poorly for MCSs owing to their coarse resolution and poor coverage in the vertical direction, especially at far ranges. Spaceborne radars such as the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR), on the other hand, can provide high resolution VPRs. The current study explores a new approach of incorporating the TRMM VPRs into the VPR correction for the Weather Surveillance Radar-1988 Doppler (WSR-88D) radar QPE. High-resolution VPRs derived from the Ku-band TRMM PR data are converted into equivalent S-band VPRs using an empirical technique. The equivalent S-band TRMM VPRs are resampled according to the WSR-88D beam resolution, and the resampled (apparent) VPRs are then used to correct for BB effects in the WSR-88D QPE when the ground radar VPR cannot accurately capture the BB bottom. The new scheme was tested on six MCSs from different regions in the United States and it was shown to provide effective mitigation of the radar QPE errors due to BB contamination.

Corresponding author address: Youcun Qi, Cooperative Institute for Mesoscale Meteorological Studies, University of Oklahoma, and NOAA/OAR National Severe Storms Laboratory, 120 David L Boren Blvd., Norman, OK 73072. E-mail: youcun.qi@noaa.gov; youcun.qi@gmail.com
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