Extreme Rainfall Characteristics Analysis Using Climate Models in the Mount Merapi Area

E. G. A. Sapan, J. Sujono, K. Karlina
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Abstract

Extreme rainfall is one of the trigger factors for debris floods in stratovolcanos. It caused by volcanic materials will be easily eroded in large quantity with surface water flow as the result of extreme rainfall. Extreme rainfall is avnatural phenomenon which is often related with climate change. In the future, changes in extreme rainfall characteristics may occur. Therefore, it’s necessary to conduct extreme rainfall analysis for historical and future periods. In this study, the characteristics of rainfall analyzed were the variability of extreme rain as shown by trend analysis of extreme rain indices namely RTOT. Hourly rainfall data at eight rain stations used as input. Future rainfall data was projected using the global climate model CanESM2 (RCP4.5 and RCP8.5 and downscaling process using Statistical Downscaling Model (SDSM). Comparison of the projection rainfall with historical rainfall shows a different trend at each station. Increasing trend occurred at four stations including Plosokerep, Pucanganom, Sopalan, and Talun stations, with the highest increasing trend occurring at Sopalan stations. In addition, there was also a decreasing trend that occurred at Ngandong station for both scenarios and at Sorasan station in the RCP8.5 scenario. The Jrakah and Randugunting stations show a steady trend.
应用气候模型分析默拉皮山地区的极端降雨特征
极端降雨是平流层火山碎屑洪水的触发因素之一。由火山物质引起的它很容易在极端降雨的情况下随着地表水的流动而被大量侵蚀。极端降雨是一种自然现象,通常与气候变化有关。未来,极端降雨特征可能会发生变化。因此,有必要对历史和未来时期的极端降雨量进行分析。在本研究中,分析的降雨特征是极端降雨指数(RTOT)的趋势分析所显示的极端降雨的可变性。八个雨量站的小时降雨量数据用作输入。使用全球气候模型CanESM2(RCP4.5和RCP8.5)预测未来的降雨量数据,并使用统计降尺度模型(SDSM)进行降尺度过程。预测降雨量与历史降雨量的比较显示,每个站点的趋势不同。Plosokerep、Pucanganom、Sopalan和Talun四个车站出现了增长趋势,其中Sopalan车站的增长趋势最高。此外,在两种情况下,Ngandong站和RCP8.5情况下的Sorasan站也出现了下降趋势。Jrakah和Randugunting车站呈现出稳定的趋势。
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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