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深圳“9·7”极端特大暴雨过程雨滴谱特征分析

Analysis of raindrop size distribution characteristics during the extreme rainstorm on September 7, 2023 in Shenzhen

  • 摘要: 本文基于深圳福田站雨滴谱观测数据,对2023年9月7—8日深圳极端特大暴雨过程(以下简称“9·7”特大暴雨),分析了不同降水类型雨滴谱关键参数的分布特征,并从时间演变角度评估了不同雨滴粒径对降水率的贡献。结果表明:“9·7”特大暴雨的对流性降水更接近于海洋性降水特征,相比其他暴雨个例具有雨滴粒径小、数浓度高的特征;层状云降水的归一化截距参数(Nw)相较于国内其他地区偏高,雨滴质量加权平均直径(Dm)则与广东省内其他地区相当。不同降水类型的降水率增强机制存在差异,对流性降水主要依赖于雨滴数浓度(Nt)的增多,层状云降水则由NtDm共同作用。在雨滴粒径贡献方面,中雨滴对降水率的贡献占比最高,强降水集中时段内(9月7日14:00—22:30)占比约为50%~95%,但降水率的变化与大雨滴贡献呈紧密正相关,两者相关系数达0.820。当降水率增强时,大雨滴对降水率的贡献迅速升高,且大雨滴数浓度增多是降水率增强的关键,即R的增加伴随着雨滴向更大粒径增长。进一步分析表明,不同降水强度下雨滴粒径的贡献率表现出规律性变化:随着降水率增强,大雨滴贡献占比逐渐升高、小雨滴贡献占比逐渐下降、中雨滴贡献占比出现先升后降的特征。

     

    Abstract: This study investigates the raindrop size distribution (DSD) characteristics of the extreme rainstorm that occurred on September 7-8, 2023, in Shenzhen (hereinafter referred to as the “9·7” rainstorm), based on DSD observation data from Shenzhen FuTian station. The characteristics of key DSD parameters for different precipitation types were analyzed, and the contribution of different raindrop size levels to the rain rate was evaluated from the aspect of temporal evolution. The results show that the convective precipitation during the “9·7” rainstorm is well consistent with the characteristics of “maritime” types. Compared with rainstorm cases from other regions, the DSD in this rainstorm is characterized by smaller raindrop particle sizes and higher number concentrations. The normalized intercept parameter (Nw) of stratiform precipitation is higher than that recorded in other regions of China, while the mass-weighted mean raindrop particle size is equivalent to that observed in other regions of Guangdong Province. The mechanisms of precipitation rate enhancement differ between precipitation types: convective precipitation is primarily due to an increase in raindrop number concentration(Nt), while stratiform precipitation is driven by both Nt and Dm. Regarding the contribution of raindrop sizes, medium-sized raindrops dominate the precipitation rate, accounting for approximately 50%~95% during the peak rainfall period (from 14:00 to 22:30 UTC on September 7). While variations in precipitation rate are closely related to the contribution of large raindrops, with a correlation coefficient of 0.820. When precipitation rate increases, the fractional contribution from large raindrops rises rapidly, with the increase in number concentration playing a critical role. Namely, the increase in R is accompanied by the growth of raindrops toward larger particle sizes. Further analysis reveals a systematic pattern in the fractional contribution of different raindrop sizes with varying precipitation intensity: as precipitation rate increases, the contribution of large raindrops rises steadily, that of small raindrops declines, while the contribution of medium-sized raindrops first increases and then decreases.

     

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