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Influence of boreal summer intraseasonal oscillation on rainfall extremes in southern China

机译:夏季夏季北方季节内振荡对中国南方极端降水的影响

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摘要

How boreal summer intraseasonal oscillation (BSISO) modulates the probability and spatial distributions of extreme rainfall occurrence over populous southern China was examined, using the newly proposed BSISO indices and two high-resolution rain-gauge-based rainfall datasets in China. The probability density function of May-August rainfall in southern China is skewed towards large values in phases 2-4 of the first component and in phases 5-7 of the second component of BSISO life cycle, during which the probability of extreme rainfall events at the 75th (90th) percentile increases by 30-50% (over 60%) relative to the non-BSISO period. The devastating floods with prolonged extreme rainfall in southern China over the three past decades occurred coincidently with these BSISO phases. The first component of BSISO, associated with 30-60-day eastwardortheastward-propagating ISO, is more favourable for the rainfall extreme over in-land China. In contrast, the second component of BSISO, related to the 10-30-day northwestward propagating ISO, tends to link with the rainfall extreme along the southeast coast of South China. Moisture budget indicates that the favourable environment for rainfall extreme is associated with southwesterly moisture convergence over southern China, while the moisture advection contributes insignificantly. This study suggests a potential for monitoring and probabilistic prediction of extreme rainfall events in southern China based on the real-time BSISO indices.
机译:使用新提出的BSISO指数和中国的两个高分辨率雨量计降雨数据集,研究了夏季北方季节内振荡(BSISO)如何调节中国南部人口极端降雨发生的概率和空间分布。在BSISO生命周期的第一部分2-4阶段和第二部分5-7阶段,中国南方5-8月降雨的概率密度函数偏向较大的值,在此期间,极端降雨事件的概率为相对于非BSISO时期,第75(第90)个百分位数增加了30-50%(超过60%)。在过去的三个十年中,中国南部地区持续的极端降雨造成的毁灭性洪水与这些BSISO阶段同时发生。 BSISO的第一部分与向东/向北传播30-60天的ISO相关,对中国内陆地区的极端降雨更为有利。相比之下,BSISO的第二个组成部分与向西北传播10-30天的ISO有关,它往往与华南东南沿海的极端降雨有关。水分预算表明,降雨极端的有利环境与中国南部西南部的水分汇聚有关,而水分对流的贡献则微不足道。这项研究表明,基于实时BSISO指数,中国南方极端降雨事件的监测和概率预测潜力。

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