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Spatial and Temporal Variability of Temperature in Iran for the Twenty-First Century Foreseen by the CMIP5 GCM Models

机译:CMIP5 GCM型号预见二十一世纪伊朗温度的空间和时间变异性

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The changes and fluctuations in climate variables, especially temperature, that subsequently affect human activities and natural environments are one of the critical topics in scientific societies. Therefore, time variability analysis of average temperature is an important concept in climate studies, particularly in environmental planning and management at various levels. The main purpose of the present study is to detect the temporal and spatial variability of average monthly temperature in Iran during the period 2015-2060 based on the RCP4.5 and RCP 8.5 scenarios simulated by the CMIP5 atmospheric general circulation models. For this purpose, the monthly average temperature data relative to four CMIP5 models, including CMCC-CM, CESMI-BGC, CCSM4, and MRI-CGCM3 models, for the period 1987-2060, and the observed monthly average temperature for the period 1987-2014 measured at 88 synoptic stations distributed all over Iran were used. The accuracy of the CMIP5 models in simulating the historical data for the period 1987-2005 was evaluated against the observed data at the synoptic stations using R, R2, RMSE, bias, EF, NARMSE, slope, and IA statistics. To study the temporal and spatial variation of temperature relative to the historical and future periods across Iran, the statistical spatial variance model was applied. The result showed that the historical temperatures estimated by all CMIP5 models are highly correlated with the observed temperatures all over Iran, but the accuracy of the MRI-CGCM3 model was found slightly higher than the other three models in most areas of Iran. In general, the results showed that the temperature estimated by the selected models and scenarios have a very high correlation with the observed data in most parts of Iran, especially in the mountainous areas of the western country. In the coastal areas of southern and northern Iran, the accuracies of the models somehow decreased which can be attributed to the complex topographical structure of these areas and/or the other effective local features that have not been incorporated in the models. The results showed that the highest temporal variability of temperature has occurred in winter months and partly in the autumn, and the spatial variability of temperature has been observed primarily in the mountainous areas of Iran. The investigation of the temperature variability in the future decades (2015-2059) was found in parallel with the temporal variations of temperature in the present period, considering that the highest temperature variability will occur in winter and somehow in the autumn, mostly in the mountainous areas of Iran. Generally, in most parts of the country, the air temperature in future decades will have an increasing tendency in all four seasons of the year.
机译:随后影响人类活动和自然环境的气候变量,尤其是温度的变化和波动,是科学社会的关键话题之一。因此,平均温度的时变分析是气候研究中的一个重要概念,尤其是在各级环境规划和管理中。本研究的主要目的是基于RCP4,检测2015-2060年间伊朗月平均气温的时空变化。5和RCP 8.5情景,由CMIP5大气环流模式模拟。为此,使用了1987-2060年期间与四个CMIP5模型(包括CMCC-CM、CESMI-BGC、CCSM4和MRI-CGCM3模型)相关的月平均温度数据,以及分布在伊朗各地的88个气象站在1987-2014年期间测得的观测月平均温度。利用R、R2、RMSE、bias、EF、NARMSE、slope和IA统计数据,对照天气观测站的观测数据,评估了CMIP5模型模拟1987-2005年历史数据的准确性。为了研究伊朗历史和未来时期气温的时空变化,采用了统计空间方差模型。结果表明,所有CMIP5模型估计的历史温度与伊朗各地的观测温度高度相关,但在伊朗大部分地区,MRI-CGCM3模型的精度略高于其他三个模型。总的来说,结果表明,所选模型和情景估计的温度与伊朗大部分地区的观测数据具有非常高的相关性,尤其是在该国西部的山区。在伊朗南部和北部沿海地区,模型的精度有所下降,这可归因于这些地区复杂的地形结构和/或模型中未包含的其他有效局部特征。结果表明,温度的时间变异性最高发生在冬季,部分发生在秋季,温度的空间变异性主要出现在伊朗山区。对未来几十年(2015-2059年)温度变化的调查与当前时期温度的时间变化是平行的,考虑到最高的温度变化将出现在冬季和秋季,主要是在伊朗的山区。一般来说,在全国大部分地区,未来几十年的气温在一年中的所有四季都将有上升的趋势。

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