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A Real-Time Algorithm to Identify Convective Precipitation Adjacent to or within the Bright Band in the Radar Scan Domain

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  • 1 Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
  • | 2 University of Chinese Academy of Sciences, Beijing, China
  • | 3 Institute of Urban Meteorology, China Meteorological Administration, Beijing, China
  • | 4 Shaanxi Meteorological Bureau, Xi’an, Shaanxi, China
  • | 5 National Meteorological Centre, Beijing, China
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Abstract

Hydrological hazards usually occur after heavy precipitation, especially during strong convection. Therefore, accurately identifying convective precipitation is very helpful for hydrological warning and forecasting. However, separating the convective, bright band (BB), and stratiform precipitation is found to be challenging when the convection is adjacent to or within the BB region. A new convection/BB/stratiform precipitation segregation algorithm is proposed in this study to resolve this challenging issue. This algorithm is applicable for a single radar volume scan data in native (polar) coordinates and consists of four processes: 1) check the freezing (0°C) level to roughly assess whether convection is occurring or not; 2) identify the convective cores through analyzing composite reflectivity (maximum reflectivity for a given range gate among all the sweeps), vertically integrated liquid water (VIL), VIL horizontal gradient, and reflectivity at the levels of 0°, −10°, and above −10°C; 3) delineate the whole convective region through the seeded region growing method by taking account of the microphysical differences between the BB and convective regions; and 4) delineate BB features in the stratiform region. The proposed algorithm utilizes the physical characteristics of different precipitation types for precisely segregating the convective, BB, and stratiform precipitation. This algorithm has been tested with radar data of different precipitation events and evaluated with three months of rain gauge data. The results show that the proposed algorithm performs consistently well for challenging precipitation events with the convection adjacent to or within a strong BB. Furthermore, the proposed algorithm could be used to improve the vertical profile of reflectivity (VPR) correction and reduce the overestimation of rainfall in the BB precipitation region.

© 2021 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Youcun Qi, youcun.qi@igsnrr.ac.cn

Abstract

Hydrological hazards usually occur after heavy precipitation, especially during strong convection. Therefore, accurately identifying convective precipitation is very helpful for hydrological warning and forecasting. However, separating the convective, bright band (BB), and stratiform precipitation is found to be challenging when the convection is adjacent to or within the BB region. A new convection/BB/stratiform precipitation segregation algorithm is proposed in this study to resolve this challenging issue. This algorithm is applicable for a single radar volume scan data in native (polar) coordinates and consists of four processes: 1) check the freezing (0°C) level to roughly assess whether convection is occurring or not; 2) identify the convective cores through analyzing composite reflectivity (maximum reflectivity for a given range gate among all the sweeps), vertically integrated liquid water (VIL), VIL horizontal gradient, and reflectivity at the levels of 0°, −10°, and above −10°C; 3) delineate the whole convective region through the seeded region growing method by taking account of the microphysical differences between the BB and convective regions; and 4) delineate BB features in the stratiform region. The proposed algorithm utilizes the physical characteristics of different precipitation types for precisely segregating the convective, BB, and stratiform precipitation. This algorithm has been tested with radar data of different precipitation events and evaluated with three months of rain gauge data. The results show that the proposed algorithm performs consistently well for challenging precipitation events with the convection adjacent to or within a strong BB. Furthermore, the proposed algorithm could be used to improve the vertical profile of reflectivity (VPR) correction and reduce the overestimation of rainfall in the BB precipitation region.

© 2021 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Youcun Qi, youcun.qi@igsnrr.ac.cn
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