收稿日期: 2022-10-09
修回日期: 2022-12-29
网络出版日期: 2023-08-03
基金资助
新疆区域协同创新专项项目(2022E01014)
Change characteristics of extreme precipitation events in Central Asia in recent 60 years based on RClimDex model
Received date: 2022-10-09
Revised date: 2022-12-29
Online published: 2023-08-03
选取1960—2020年中亚126个气象站点逐日降水数据，基于RClimDex模型计算中亚8种极端降水指数，利用线性回归分析、Mann-Kendall法分析、相关性分析、小波变换和重标极差（R/S）分析，探究中亚极端降水事件特征。结果表明：（1）近60 a中亚极端降水事件频率和强度均明显增加，表征降水强度（SDII）变化倾向率为0.02 mm·d-1·(10a)-1。极端降水量指数中，强降水量（R95p）、单日最大降水量（Rx1day）、连续5 d最大降水量（Rx5day）、年总降水量（PRCPTOT）的变化倾向率分别为1.93 mm·(10a)-1、0.24 mm·(10a)-1、0.66 mm·(10a)-1和0.73 mm·(10a)-1。在极端降水日指数中，中雨日数（R10）、持续干燥日数（CDD）、持续湿润日数（CWD）变化倾向率分别为0.02 d·(10a)-1、-0.65 d·(10a)-1和0.08 d·(10a)-1。极端降水存在明显的空间差异性和高海拔依赖性，高原和山区附近极端降水事件频发。中亚极端降水周期特征为多峰谱型，具有准5 a短周期振荡、6~9 a中周期振荡和10~15 a长周期振荡。（2）极端降水指数与年总降水量具有良好的相关性，CWD对年总降水的贡献最大；太平洋年代际振荡（PDO）和北大西洋年代际振荡（AMO）对极端降水事件具有明显正相关性。R/S分析表明该地区极端降水特征未来持续可能性较大。研究结果可为中亚极端气候预测、自然环境保护、防灾减灾工作等提供科学依据。
黄鑫 , 焦黎 , 马晓飞 , 王勇辉 , 阿尔曼·阿布拉 . 基于RClimDex模型的近60 a中亚极端降水事件变化特征[J]. 干旱区地理, 2023 , 46(7) : 1039 -1051 . DOI: 10.12118/j.issn.1000-6060.2022.511
In this study, based on the RClimDex model, we considered daily precipitation data from 126 meteorological stations in Central Asia from 1960 to 2020 to calculate eight extreme precipitation indices in Central Asia. We performed linear regression, Mann-Kendall, correlation, wavelet, and rescaled range analyses to investigate the characteristics of extreme precipitation events in Central Asia. The results revealed that: (1) The frequency and intensity of extreme precipitation events in Central Asia have increased considerably in the last 60 years. The climate trend of the simple precipitation intensity index (SDII) increased at an average of 0.02 mm·d−1·(10a)−1. The change tendency rates of extreme precipitation index heavy precipitation (R95p), maximum daily precipitation (Rx1day), maximum precipitation for five consecutive days (Rx5day), total annual precipitation (PRCPTOT)] were 1.93 mm·(10a)−1, 0.24 mm·(10a)−1, 0.66 mm·(10a)−1, and 0.73 mm·(10a)−1, respectively. The extreme precipitation days index [middle precipitation days (R10), continuous dry days (CDD), continuous wet days (CWD)] also exhibited a slight increase, with the exception of the number of CDD, which exhibited a decreasing trend. The change tendency rates were 0.02 d·(10a)−1, −0.65 d·(10a)−1, and 0.08 d·(10a)−1, respectively. Extreme precipitation exhibit obvious spatial variability and high altitude dependence and occur frequently near highlands and mountains. The extreme precipitation cycle in Central Asia is characterized by a multipeaked spectrum with short-period oscillations of approximately 5 years, medium-period oscillations of 6-9 years, and long-period oscillations of 10-15 years. (2) The extreme precipitation index exhibits an excellent correlation with the total annual precipitation, and CWD contributes most to the total annual precipitation. The Pacific interdecadal oscillation (PDO) and the North Atlantic interdecadal oscillation (AMO) exhibit significant positive correlation with extreme precipitation events. Both PDO and AMO are the primary climate system internal variability modes that affect abrupt changes in extreme precipitation in Central Asia. The results of the R/S analysis indicates that in the future, the indices of PRCPTOT R95p, Rx1day, Rx5day, SDII, and CWD are likely to continue to increase in the future with high persistence, whereas CDD is likely to continue to exhibit a decreasing trend with average persistence. This study can provide a scientific basis for the extreme climate prediction, natural environment protection, disaster prevention, and mitigation in Central Asia.
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