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Characterization of raindrop size distributions and its response to cloud microphysical properties
Atmospheric Research ( IF 5.5 ) Pub Date : 2021-02-01 , DOI: 10.1016/j.atmosres.2020.105292
Abin Thomas , Vijay P. Kanawade , Kaustav Chakravarty , Atul K. Srivastava

Abstract Cloud feedbacks continue to alter with climate change, which remains the largest source of uncertainty in global climate. Raindrop size distribution (DSD) is a fundamental characteristic of cloud microphysical and dynamical processes. This study characterizes the DSD and its response to cloud microphysical properties during the Indian Summer Monsoon season (June-October 2013–2015). The derived rain rate varied from 0.50 to 395.4 mm/h, which was segregated into stratiform rain (mean and standard deviation of 2.12 ± 1.24 mm/h) and convective rain (13.10 ± 14.45 mm/h). We found that as the convective DSD mode diameter gradually shifts to a larger drop size with increasing rain rate, the number concentration of small-sized rain drops decreased by about three orders of magnitude. While the mass-weighted mean diameter and normalized DSD scaling parameter were significantly higher for convective rain than stratiform rain, the normalized DSD scaling parameter was lowest for both convective and stratiform rain compared to previous studies over this region. The stratiform DSD was more skewed towards large raindrop size at a high cloud effective radius compared to a low cloud effective radius. However, the opposite response of the DSD for convective rain suggests the predominance of small-sized cloud/ice hydrometeors. This finding was further corroborated by the presence of narrower DSD at high cloud droplet number concentration compared to a low cloud droplet number concentration for the convective rain. The low wind shear and high convective available potential energy for convective rain further substantiated the persistent convective cores during monsoon accompanied by the formation of large size raindrops in the convective systems. Such a distinct response of DSD to different rain regimes could help in the short-term prediction of extreme rainfall events.

中文翻译:

雨滴大小分布特征及其对云微物理特性的响应

摘要 云反馈随着气候变化而不断变化,气候变化仍然是全球气候不确定性的最大来源。雨滴大小分布 (DSD) 是云微物理和动力过程的基本特征。本研究描述了印度夏季风季节(2013 年 6 月至 2015 年 10 月)期间 DSD 及其对云微物理特性的响应。得出的降雨率从 0.50 到 395.4 毫米/小时不等,分为层状雨(平均值和标准偏差为 2.12 ± 1.24 毫米/小时)和对流雨(13.10 ± 14.45 毫米/小时)。我们发现,随着对流 DSD 模式直径随着降雨率的增加逐渐转移到更大的雨滴尺寸,小尺寸雨滴的数量浓度下降了大约三个数量级。虽然对流雨的质量加权平均直径和归一化 DSD 标度参数明显高于层状雨,但与该地区之前的研究相比,对流雨和层状雨的归一化 DSD 标度参数最低。与低云有效半径相比,层状 DSD 在高云有效半径下更倾向于大雨滴尺寸。然而,DSD 对对流雨的相反响应表明小型云/冰水凝物占主导地位。与对流雨的低云滴数浓度相比,在高云滴数浓度下存在更窄的 DSD 进一步证实了这一发现。对流雨的低风切变和高对流可用势能进一步证实了季风期间持续的对流核心伴随着对流系统中大尺寸雨滴的形成。DSD 对不同降雨情况的这种明显反应有助于短期预测极端降雨事件。
更新日期:2021-02-01
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