遥感
动能
雷达
能量(信号处理)
环境科学
地质学
气象学
计算机科学
物理
电信
量子力学
作者
Jingxuan Zhu,Qiang Dai,Yuanyuan Xiao,Jun Zhang,Lu Zhuo,Dawei Han
标识
DOI:10.1109/tgrs.2025.3542493
摘要
As rainfall undergoes a series of complex microphysical processes in the atmosphere, studying its vertical profiles is crucial for understanding the mechanisms of rainfall evolution. While previous research has focused on vertical profiles of rainfall intensity and drop size distribution (DSD) parameters, there remains a gap in the study of rainfall energy. This study uses the dual-frequency precipitation radar (DPR) in global precipitation measurement (GPM) to analyze the vertical profile characteristics of rainfall energy (KEt) for the first time. Using DPR data collected from 2015 to 2022 across the U.K., rainfall energy calculations reveal a strong correlation (over 0.99) between the rainfall energy of adjacent 125-m-height bins, with stratiform rain showing higher correlation than convective rain. Specifically, below 1500 m, the correlation coefficient for KEt in stratiform rain is 0.9973, while for convective rain, it is 0.9957, showing higher KEt variability in convective rain. The study also introduces the change ratio (R) to characterize the degree of change from the lower to upper height bins, finding that rainfall energy variability has a larger standard deviation compared to DSD parameters, with standard deviations for R mean values of KEt reaching up to 28.37% for convective rain and 12.08% for stratiform rain within 1500 m. In addition, the profiles of rainfall energy exhibit significant seasonal variations, with these variations increasing with height. KEt is consistently highest in summer and lowest in winter at all same altitudes. This study enhances the understanding of the vertical pattern of rainfall evolution, contributes to providing more accurate surface rainfall energy estimates, analyzing influencing factors and the uncertainty of vertical rainfall variability.
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