The enigma of spurious echoes: Enhancing phase transition height detection in shallow convective precipitation with GPM DPR

The Global Precipitation Measurement (GPM) core satellite’s Dual-frequency Precipitation Radar (DPR) provides new insights into detecting solid-to-liquid phase transition heights of precipitation particles. However, significant anomalies can be found in the “binMixedPhaseTop” parameter within its official Level 2 data products during shallow convective precipitation events. Statistical analysis of the Yangtze and Huai River Basins from 2014 to 2023 reveals that the anomaly rate for shallow convective precipitation is 64.94%, far exceeding those for convective (0.61%) and stratiform (0.48%) precipitation. Further investigation demonstrates that the warm-rain process characteristic of shallow convective systems lacks a distinct solid-to-liquid phase transition layer, leading to algorithmic misinterpretations. An improved identification algorithm for “binMixedPhaseTop” is proposed to address this problem. It incorporates additional checks to ensure that the phase-transition height is only identified when a melting layer is present, thereby preventing misjudgments and redundant computations. The enhanced version is validated against 10-year observations from South China (2014–2023), demonstrating 91% anomaly suppression through extreme deviation truncation. This study highlights the need for algorithm refinement to accurately detect phase-change heights in different precipitation types, thereby enhancing the reliability of the “binMixedPhaseTop” product for convective precipitation detection. 星载双频降水测量雷达GPM DPR能够探测降水相变层顶高度.然而, 其Level 2数据 (V07A) 中的“binMixedPhaseTop”物理量在浅对流降水中表现异常.在2014年—2023年夏季GPM DPR探测江淮流域降水数据中, "binMixedPhaseTop"在浅对流降水中的异常率高达64.94%, 显著高于其在对流降水 (0.61%) 和层状降水 (0.48%) 中的异常率.本文认为浅对流降水的暖雨过程缺乏固态到液态的清晰相变层, 导致GPM DPR现有算法出现误判.为此, 本文提出一种改进的“binMixedPhaseTop”识别算法, 即通过增加相变层存在性验证, 有效避免了无相变层时的误判及冗余计算.验证结果表明改进算法有效降低了GPM DPR探测浅对流降水相变高度的识别异常率.