An Improved Bright Band Identification Algorithm Based on GPM-DPR Ku-Band Reflectivity Profiles

Abstract

Bright band (BB) is a layer of enhanced radar reflectivity due to hydrometeor melting and coalescence. BB identification is of high importance on radar quantitative precipitation estimation (QPE) and other applications. The Dual-frequency Precipitation Radar onboard the core satellite of the Global Precipitation Measurement mission (GPM-DPR) enables new investigations of BB characteristics at a global scale. However, the GPM-DPR operational BB identification algorithm based on the vertical profile of reflectivity (VPR) from single-frequency (SF; Ku band) or dual-frequency (DF; Ku and Ka band) observations still has the room for improvement. In the current study, an improved GPM-DPR SF BB identification algorithm is presented based on the detection of inflection points within a given range in a VPR. The improved GPM-DPR SF BB identification algorithm decreases the overestimation (underestimation) error of the BB bottom (top) height identified by the GPM-DPR SF algorithm, from 322 m (-345 m) to 182 m (-211 m), compared against the identifications by the GPM-DPR DF algorithm. The GPM-DPR SF will mis-estimate the depth of the melting layer, and the reflectivity difference between BB bottom (top) and BB peak to about 1.5 (3.5) dB, which will lead to mis-understand the vertical physical variation of the precipitation particles. The validation through ρ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">HV</sub> derived from WSR-88D observations in the CONUS demonstrates that the GPM-DPR DF algorithm is of higher accuracy, and the improved GPM-DPR SF algorithm performs better than the GPM-DPR SF algorithm. The new algorithm will contribute to hydrometeor phase classification and the studies on BB characteristics.