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Detection and prediction of mean and extreme European summer temperatures with a multimodel ensemble

机译:利用多模型集合检测和预测欧洲夏季平均气温和极端气温

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We analyze observed mean to extreme summer temperature indices across Europe in order to determine whether there is evidence for a detectable climate change signal and whether these indices show evidence for predictability. Observations from 1960 to 2011, taken from E-OBS an observational dataset created for the European Commission funded project (ENSEMBLES), are compared with the model simulations from the global coupled climate models CanCM4, HadCM3, MIROC5, and MPI-ESM-LR, as published on the CMIP5 archive. Indices are examined that span a moderate to extreme range of the summer temperature distribution by including the summer average, the hottest 5day average, and the hottest daily maximum and daily minimum temperatures during summer. The region of interest is Europe; however, a number of subregions are also studied, which include Western Europe, the British Isles, the Mediterranean, and Central Europe. The observed changes in the analyzed indices are well represented by the multimodel mean and are within the range of the multimodel ensemble for most regions, with the exception of 1 and 5day average daily maximum temperature extremes across the UK. Observed changes are detectable against estimates of internal climate variability for both moderate and extreme temperature indices across all regions in almost all cases. Exceptions are the hottest 5day average daily maximum temperature in the UK and Central Europe, for which results are not conclusive. An analysis of the skill in decadal hindcasts of these indices shows that there is significant prediction skill across these indices for three of the four models for some regions and some models. This skill exceeds the skill of forecasts based on observed climatology and random noise and is largely due to external forcing. However, there is some evidence that there is additional skill originating from the assimilation of observations into the initialization in some cases. Key Points Observed changes detectable in extreme temperature indices across EuropeSkill in CMIP5 decadal predictions of European Summer extreme temperaturesPrediction skill due to initialisation in European Summer temperature extremes
机译:我们分析了整个欧洲观测到的夏季至极端夏季温度指数,以确定是否有可检测到的气候变化信号的证据,以及这些指数是否显示可预测的证据。从E-OBS获得的1960年至2011年的观测数据,该数据是为欧盟委员会资助的项目(ENSEMBLES)创建的,与全球耦合气候模型CanCM4,HadCM3,MIROC5和MPI-ESM-LR的模型模拟进行了比较,如发布在CMIP5存档中。通过包括夏季平均值,最热的5天平均值以及夏季最热的每日最高和每日最低温度,对跨越夏季温度分布的中度到极端范围的指标进行了检查。感兴趣的地区是欧洲;但是,也对许多次区域进行了研究,其中包括西欧,不列颠群岛,地中海和中欧。除英国全境1天和5天的每日平均最高气温极端值外,大多数地区的多指标均值很好地代表了所观察到的分析指标变化,并且在多模总体范围内。在几乎所有情况下,根据所有区域的中,极端温度指数的内部气候变异性估计值,可以观察到观测到的变化。英国和中欧最热的5天平均每日最高温度是个例外,其结果尚无定论。对这些指标的年代际后验技术的分析表明,对于某些区域和某些模型,这四个模型中的三个模型在这些指标上具有显着的预测技能。该技能超出了根据观测到的气候和随机噪声进行预测的技能,并且很大程度上是由于外部强迫。但是,有证据表明,在某些情况下,将观察值同化会导致其他技能。要点观察到的整个欧洲极端温度指数中可检测到的变化CMIP5对欧洲夏季极端温度的十年预报的技能由于在欧洲夏季极端温度中的初始化而产生的预测技能

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