The objective of this analysis is to provide an up-to-date observation-based assessment of the evolution of temperature extremes in the Middle East–North Africa (MENA) region and evaluate the performance of global climate model simulations of the past four decades. A list of indices of temperature extremes, based on absolute level, threshold, percentile and duration is used, as defined by the Expert Team on Climate Change Detection and Indices (ETCCDI). We use daily near-surface air temperature (Tmax and Tmin) to derive the indices of extremes for the period 1980–2018 from: (i) re-analyses (ERA-Interim, MERRA-2) and gridded observational data (Berkeley Earth) and (ii) 18 CMIP5 model results combining historical (1950–2005) and scenario runs (2006–2018 under RCP 2.6, RCP 4.5 and RCP 8.5). The CMIP5 results show domain-wide strong, statistically significant warming, while the observation based ones are more spatially variable. The CMIP5 models capture the climatology of the hottest areas in the western parts of northern Africa and the Gulf region with the thewarmest day (TXx) > 46 ${}^{\circ }$C and warmest night (TNx) > 33 ${}^{\circ }$C. For these indices, the observed trends are about 0.3–0.4 ${}^{\circ }$C/decade while they are 0.1–0.2 ${}^{\circ }$C/decade stronger in the CMIP5 results. Overall, the modeled climate warming up to 2018, as reflected in the indices of temperature extremes is confirmed by re-analysis and observational data.

中文翻译：

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从观测和CMIP5数据更新的中东-北非（MENA）地区极端温度评估

该分析的目的是对中东-北非（MENA）地区极端温度的演变提供基于观测的最新评估，并评估过去40年中全球气候模型模拟的性能。根据气候变化检测和指数专家组（ETCCDI）的定义，使用了基于绝对水平，阈值，百分位数和持续时间的极端温度指标列表。我们使用每日近地表气温（Tmax和Tmin）从以下各项得出1980-2018年期间的极端指数：（i）重新分析（ERA-临时，MERRA-2）和网格化观测数据（伯克利地球） （ii）结合历史（1950–2005）和情景运行（在RCP 2.6，RCP 4.5和RCP 8.5下的2006–2018）的18个CMIP5模型结果。CMIP5的结果表明，具有统计学意义的变暖，而基于观测的变暖在空间上却更多。CMIP5模型以最暖的一天（TXx）> 46捕获北部非洲西部和海湾地区最热地区的气候${}^{\circ }$C和最温暖的夜晚（TNx）> 33 ${}^{\circ }$C.对于这些指数，观察到的趋势约为0.3-0.4 ${}^{\circ }$C /十进位，而它们是0.1-0.2 ${}^{\circ }$C / decade在CMIP5结果中更强。总体而言，通过重新分析和观测数据证实了至2018年的模拟气候变暖，反映在极端温度指数中。