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Climate conditions and drought assessment with the Palmer Drought Severity Index in Iran: evaluation of CORDEX South Asia climate projections (2070-2099)

机译:伊朗的气候条件和干旱评估与帕尔默干旱严重指数:CORDEX南亚气候预测的评估(2070-2099)

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Climate change projections were evaluated over both the whole Iran and six zones having different precipitation regimes considering the CORDEX South Asia dataset, for assessing space-time distribution of drought occurrences in the future period 2070-2099 under RCP4.5 scenario. Initially, the performances of eight available CORDEX South Asia Regional Climate Models (RCMs) were assessed for the baseline period 1970-2005 through the GPCC v.7 precipitation dataset and the CFSR temperature dataset, which were previously selected as the most reliable within a set of five global datasets compared to 41 available synoptic stations. Though the CCLM RCM driven by the MPI-ESM-LR General Circulation Model is in general the most suitable for temperature and, together with the REMO 2009 RCM also driven by MPI-ESM-LR, for precipitation, their performances do not overwhelm other models for every season and zone in which Iranian territory was divided according to a principal component analysis approach. Hence, a weighting approach was tested and adopted to take into account useful information from every RCM in each of the six zones. The models resulting more reliable compared to current climate show a strong precipitation decrease. Weighted average predicts an overall yearly precipitation decrease of about 20%. Temperature projections provide a mean annual increase of 2.4 degrees C. Future drought scenarios were depicted by means of the self-calibrating version of the Palmer drought severity index (SC-PDSI) model. Weighted average predicts a sharp drying that can be configured as a real shift in mean climate conditions, drastically affecting water resources of the country.
机译:考虑到CORDEX南亚数据集,对整个伊朗和具有不同降水方式的六个地区的气候变化预测进行了评估,以评估RCP4.5情景下2070-2099年未来干旱发生的时空分布。最初,通过GPCC v.7降水数据集和CFSR温度数据集评估了八种可用的CORDEX南亚区域气候模型(RCM)在1970-2005年基准期间的性能,这些数据先前被选为一组中最可靠的的五个全球数据集与41个可用的天气观测站进行比较。尽管通常由MPI-ESM-LR通用循环模型驱动的CCLM RCM最适合温度,并且与同样由MPI-ESM-LR驱动的REMO 2009 RCM一起用于降水,但它们的性能不会压倒其他模型根据主要成分分析方法,将伊朗领土划分为每个季节和地区。因此,测试并采用了一种加权方法,以考虑到来自六个区域中每个区域的每个RCM的有用信息。与当前气候相比,结果更加可靠的模型显示降水量下降幅度很大。加权平均值预测全年降水量减少约20%。气温预测提供的年平均增长率为2.4摄氏度。借助Palmer干旱严重性指数(SC-PDSI)模型的自校准版本,描绘了未来的干旱情况。加权平均预测会出现急剧干燥,这可以配置为平均气候条件的实际变化,从而严重影响该国的水资源。

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