Vertical Structures and Microphysical Mechanisms of Meiyu Precipiation Using Wind Profile Radar

K. Krishna Reddy and V. Adinarayana
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K. Krishna Reddy: Professor, Department of Physics, Yogi Vemana University, Kadapa
V. Adinarayana: Lecturer, Department of Physics, Govt. College for Men(A), Kadapa

International Journal of Research and Scientific Innovation, 2025, vol. 12, issue 5, 1104-1116

Abstract: This study investigates the vertical structure and temporal evolution of Meiyu precipitating cloud systems over Dongshan, China, utilizing data from an L-band Wind Profiler Radar (WPR) collected during the Intensive Observation Periods (IOPs) of 2001 and 2002. The WPR provides crucial insights into hydrometeor characteristics and vertical air motion by measuring reflectivity, reflectivity-weighted fall speed, and variance of hydrometeor fall speeds. Observations from June 2001 revealed the complex interaction between a Meiyu front and Typhoon Chebi (0102), illustrating how their movements influenced precipitation patterns. Detailed WPR data showed varied vertical rainfall structures, with horizontal mixing of rain mass in the lowest 2 km and a distinct bright band near 4.5 km indicating stratiform precipitation. Doppler vertical velocity measurements largely indicated stratiform structures with downward velocities, though weak updrafts were observed within the Meiyu frontal system. An X-band Doppler Radar comparison showed less precipitation in IOP-2001 compared to IOP-2002, with notable diurnal variations in the latter. A key aspect of this research involved classifying Meiyu precipitating clouds into convective, transition, and stratiform types using a WPR-based algorithm that assesses the presence of a melting layer and turbulence/hydrometeors. Convective regions exhibited strong updrafts and high reflectivity, while stratiform areas showed weaker vertical velocities and a clear bright band. Analysis of occurrence percentages revealed that IOP-2001 was dominated by mixed and stratiform clouds, whereas IOP-2002 had a more balanced distribution of convective and stratiform types. These differences were attributed to variations in atmospheric moisture content (relative humidity, precipitable water) and local environmental conditions (CAPE, CIN). This research highlights the effectiveness of WPR data in understanding Meiyu rainfall mechanisms and their potential for improving cloud-scale and mesoscale numerical models, ultimately aiding in better predictions and flood disaster mitigation efforts in East Asia.

Date: 2025
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