Climatology of extreme precipitation spells induced by cloudburst-like events during the Indian Summer Monsoon

IF 3.1 Q2 GEOSCIENCES, MULTIDISCIPLINARY
Akash Singh Raghuvanshi , Ricardo M. Trigo , Ankit Agarwal
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引用次数: 0

Abstract

This study enhances existing understanding of extreme precipitation spells induced by cloudburst-like (EPS-CBL) events in India, emphasizing climatology and geographical distribution often overlooked by traditional observations. EPS-CBL is defined as continuous rainfall exceeding 200 mm/day and intermittent extreme rates above 30 mm/hour or the 99.9th percentile threshold, differing from definitions proposed by the IMD and other studies. Our findings reveal significant biases in various precipitation products compared to IMD data. CMORPH consistently outperforms other datasets by capturing more extreme events and showing significant rising trends in regions influenced by orographic effects, such as the Himalayan foothills and the Western Ghats. Although IMERG aligns well with IMD overall, it exhibits variability in extreme events, while IMDAA tends to underestimate these extremes, especially in complex terrains. Analysis of EPS-CBL trends from 2000 to 2022 highlights regional differences across datasets. Both CMORPH and IMERG show an increase in EPS-CBL events in the hilly region, while IMDAA indicates a decline. Understanding EPS-CBL climatology provides valuable insights for modeling studies exploring the underlying mechanisms of these events.

Abstract Image

印度夏季风期间由类似云暴事件引起的极端降水的气候学
这项研究加强了对印度由类云暴(EPS-CBL)事件引起的极端降水的现有认识,强调了传统观测经常忽略的气候和地理分布。EPS-CBL被定义为连续降雨量超过200毫米/天,间歇性极端率超过30毫米/小时或99.9百分位阈值,与IMD和其他研究提出的定义不同。我们的研究结果表明,与IMD数据相比,各种降水产品存在显著偏差。CMORPH通过捕获更多极端事件,并在受地形影响的地区(如喜马拉雅山麓和西高止山脉)显示出显著的上升趋势,始终优于其他数据集。尽管IMERG总体上与IMD保持一致,但它在极端事件中表现出可变性,而IMDAA往往低估了这些极端事件,特别是在复杂地形中。对2000年至2022年EPS-CBL趋势的分析突出了各数据集之间的区域差异。CMORPH和IMERG均显示丘陵地区EPS-CBL事件增加,而IMDAA显示EPS-CBL事件减少。了解EPS-CBL气候学为探索这些事件的潜在机制的建模研究提供了有价值的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Hydrology X
Journal of Hydrology X Environmental Science-Water Science and Technology
CiteScore
7.00
自引率
2.50%
发文量
20
审稿时长
25 weeks
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