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Evaluating the effects of climate change on precipitation and temperature for Iran using RCP scenarios
Journal of Water & Climate Change ( IF 2.7 ) Pub Date : 2021-02-01 , DOI: 10.2166/wcc.2020.114
Shahab Doulabian 1 , Saeed Golian 1, 2 , Amirhossein Shadmehri Toosi 3 , Conor Murphy 2
Affiliation  

Climate change has caused many changes in hydrologic processes and climatic conditions globally, while extreme events are likely to occur more frequently at a global scale with continued warming. Given the importance of general circulation models (GCMs) as an essential tool for climate studies at global/regional scales, together with the wide range of GCMs available, selecting appropriate models is of great importance. In this study, six synoptic weather stations were selected as representative of different climatic zones over Iran. Utilizing monthly data for 20 years (1981–2000), the outputs of 25 GCMs for surface air temperature (SAT) and precipitation were evaluated for the historical period. The root-mean-square error and skill score were chosen to evaluate the performance of GCMs in capturing observed seasonal climate. Finally, the outputs of selected GCMs for the three Representative Concentration Pathways emission scenarios (RCPs), namely RCP2.6, RCP4.5, and RCP8.5, were downscaled using the change factor method for each station for the period 2046–2065. Results indicate that SAT in all months is likely to increase for each region, while for precipitation, large uncertainties emerge, despite the selection of climate models that best capture the observed seasonal cycle. These results highlight the importance of selecting a representative ensemble of GCMs for assessing future hydro-climatic changes for Iran.



中文翻译:

使用RCP情景评估气候变化对伊朗降水和温度的影响

气候变化在全球范围内引起了许多水文过程和气候条件的变化,而随着全球变暖,极端事件在全球范围内可能更频繁地发生。鉴于普通循环模型(GCM)作为全球/区域范围气候研究的基本工具的重要性,以及广泛的可用GCM,选择合适的模型非常重要。在这项研究中,选择了六个天气气象站来代表伊朗不同的气候区。利用20年(1981-2000年)的月度数据,对历史时期的25个GCM的地表气温(SAT)和降水量进行了评估。选择均方根误差和技能得分来评估GCM在捕获观测到的季节性气候中的性能。最后,在2046年至2065年期间,使用变化因子方法对每个站的三个代表性浓度路径排放情景(RCP),RCP2.6,RCP4.5和RCP8.5选定的GCM的输出进行了缩减。结果表明,尽管选择了最能反映观测到的季节性周期的气候模型,但每个地区的SAT可能会在每个区域增加,而对于降水,仍会出现较大的不确定性。这些结果突显了选择一个具有代表性的GCM集合体来评估伊朗未来水文气候变化的重要性。结果表明,尽管选择了最能反映观测到的季节性周期的气候模型,但每个地区的SAT可能会在每个区域增加,而对于降水,仍会出现较大的不确定性。这些结果突显了选择一个具有代表性的GCM集合体来评估伊朗未来水文气候变化的重要性。结果表明,尽管选择了最能反映观测到的季节性周期的气候模型,但每个地区的SAT可能会在每个区域增加,而对于降水,仍会出现较大的不确定性。这些结果突显了选择一个具有代表性的GCM集合体来评估伊朗未来水文气候变化的重要性。

更新日期:2021-02-23
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