Detection and prediction of mean and extreme European summer temperatures with a multimodel ensemble
Detection and prediction of mean and extreme European summer temperatures with a multimodel ensemble
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使用多模型集合检测和预测欧洲夏季平均和极端气温
DOI：
10.1002/jgrd.50703
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发表时间：
2013
期刊：
影响因子：
--
通讯作者：
Hanlon H
中科院分区：
文献类型：
--
作者：
Hanlon H
我们分析了整个欧洲观测到的平均到极端夏季温度指数，以确定是否有证据表明存在可检测的气候变化信号，以及这些指数是否显示出可预测性。从1960年到2011年的观测，从欧洲委员会资助的项目（ENSEMBLES）创建的观测数据集E-OBS，与全球耦合气候模式CanCM4，HadCM3，MIROC5和MPI-ESM-LR的模式模拟进行了比较，如CMIP5档案中所公布的。指数检查，包括夏季平均值，最热的5天平均值，最热的日最高和日最低温度在夏季温度分布的一个温和的极端范围。感兴趣的地区是欧洲;然而，也研究了一些次区域，包括西欧，不列颠群岛，地中海和中欧。所观察到的变化，分析的指数是很好的代表了多模式的平均值和范围内的多模式合奏的大部分地区，除了1日和5日平均日最高温度极端在英国。在几乎所有情况下，所有区域的中等和极端温度指数的内部气候变率估计值都可以检测到观测到的变化。这是英国和中欧最热的5天平均日最高气温，结果并不确定。对这些指数的十年后报技巧的分析表明，对于某些地区和某些模型，四个模型中的三个模型在这些指数中具有显着的预测技巧。这种能力超过了基于观测到的气候学和随机噪声的预测能力，主要是由于外部强迫。然而，有一些证据表明，在某些情况下，将观测同化到初始化过程中还产生了额外的技能。
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.
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影响因子：
4.6
作者：
Goddard, L.;Kumar, A.;Delworth, T.
通讯作者：
Delworth, T.
DOI：
--
发表时间：
2011
期刊：
影响因子：
--
作者：
Lisa Goddard;Paula Gonzalez;Simon Mason;Arthur Greene
通讯作者：
Arthur Greene
英格兰中部气温的人为变暖
影响因子：
3
作者：
D. Karoly;P. Stott
通讯作者：
P. Stott
DOI：
--
发表时间：
--
期刊：
影响因子：
--
作者：
G. Hegerl;W. Zwiers
通讯作者：
W. Zwiers
影响因子：
3.2
作者：
Pascal, M;Laaidi, K;Empereur-Bissonnet, P
通讯作者：
Empereur-Bissonnet, P