Climate change is one of the major reasons for the increased intensity and frequency of precipitation extremes in tropical regions. This will have a significant impact on underdeveloped countries in South Asia and Southeast Asia. Therefore, this study analyzes changes in spatiotemporal patterns and the joint behavior of precipitation extremes across South Asian and Southeast Asian countries for the historical period (1975 to 2014) and future periods (2021–2060 (F1) and 2061–2100 (F2)). This study develops bias-corrected precipitation data and ranks General Circulation Models (GCMs) using the Empirical Quantile Mapping method and TOPSIS method, respectively. A multi-model ensemble of precipitation extremes is created using the top five GCMs. The Mann Kendall test is used to analyze trends in precipitation extremes. Joint probabilistic analysis is also conducted for different combinations of ETCCDI precipitation-based indices using Archimedes and Elliptical copulas. The results of the trend analysis indicate significant positive trends for R20mm (19.26%), R95pTOT (18.40%), Rx5Day (11.53%), and CWD (10.46%), while CDD (5.07%) shows a significant negative trend across the study area during historical period (1975–2014). The results of R20mm, R95pTOT, and Rx5Day under SSP585 shows almost 19 to 39% of area comes under significant positive trend during the F1 period. This becomes more evident in F2, with trends under SSP585 rising between 32% and 61%. The high-emissions scenario SSP585 reveals an increase in these positive trends compared to SSP126 in both the future periods (F1 and F2). These results indicating a noticeable rise in extreme precipitation events. The analysis of changes in the joint return period of precipitation extremes indicates that the South Peninsular India, North East India, West Central India and Central Northeast India, as well as most parts of Southeast Asian countries, will experience very heavy intensify precipitations in the future. In addition, persistent co-occurrence of dry and wet conditions will be observed in Pakistan, North West India, and Central Northeast India. This study provides useful information on the distribution of precipitation extremes in different regions of the study area.

中文翻译：

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南亚和东南亚地区过去和未来极端降水的联合重现期


气候变化是热带地区极端降水强度和频率增加的主要原因之一。这将对南亚、东南亚等欠发达国家产生重大影响。因此，本研究分析了南亚和东南亚国家历史时期（1975年至2014年）和未来时期（2021年至2060年（F1）和2061年至2100年（F2））的时空格局变化和极端降水的联合行为。 。本研究开发了偏差校正的降水数据，并分别使用经验分位数映射方法和 TOPSIS 方法对大气环流模型 (GCM) 进行排名。使用前五个 GCM 创建极端降水的多模型集合。曼肯德尔检验用于分析极端降水的趋势。还使用阿基米德和椭圆联结函数对基于 ETCCDI 降水的指数的不同组合进行联合概率分析。趋势分析结果表明，R20mm (19.26%)、R95pTOT (18.40%)、Rx5Day (11.53%) 和 CWD (10.46%) 具有显着的正向趋势，而 CDD (5.07%) 在整个研究中显示出显着的负向趋势历史时期（1975-2014）的面积。 SSP585 下的 R20mm、R95pTOT 和 Rx5Day 结果显示，在 F1 期间，几乎 19% 至 39% 的面积处于显着的正趋势。这在 F2 中变得更加明显，SSP585 下的趋势上升了 32% 至 61%。与 SSP126 相比，高排放情景 SSP585 在未来两个时期（F1 和 F2）中显示出这些积极趋势的增加。这些结果表明极端降水事件显着增加。 极端降水联合重现期变化分析表明，印度半岛南部、印度东北部、印度中西部和东北部中部以及东南亚国家大部分地区未来将出现特大强降水天气。 。此外，巴基斯坦、印度西北部和印度东北部中部将持续出现干燥和潮湿的天气。这项研究提供了有关研究区域不同地区极端降水分布的有用信息。