Radar remote sensing retrieval of vertical profile of rainfall kinetic energy in the U.K

Zhu, Jingxuan, Dai, Qiang, Xiao, Yuanyuan, Zhang, Jun, Zhuo, Lu and Han, Dawei 2025. Radar remote sensing retrieval of vertical profile of rainfall kinetic energy in the U.K. IEEE Transactions on Geoscience and Remote Sensing 63 10.1109/TGRS.2025.3542493

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Abstract

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.

Item Type:	Article
Date Type:	Published Online
Status:	In Press
Schools:	Schools > Earth and Environmental Sciences
Publisher:	Institute of Electrical and Electronics Engineers
ISSN:	0196-2892
Date of First Compliant Deposit:	7 March 2025
Date of Acceptance:	25 January 2025
Last Modified:	10 Mar 2025 11:45
URI:	https://orca.cardiff.ac.uk/id/eprint/176719

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