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Climate change scenarios of precipitation extremes in Central Europe from ENSEMBLES regional climate models

机译:从ENSEMBLES区域气候模型看中欧极端降水的气候变化情景

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The study examines future scenarios of precipitation extremes over Central Europe in an ensemble of 12 regional climate model (RCM) simulations with the 25-km resolution, carried out within the European project ENSEMBLES. We apply the region-of-influence method as a pooling scheme when estimating distributions of extremes, which consists in incorporating data from a 'region' (set of gridboxes) when fitting an extreme value distribution in any single gridbox. The method reduces random variations in the estimates of parameters of the extreme value distribution that result from large spatial variability of heavy precipitation. Although spatial patterns differ among the models, most RCMs simulate increases in high quantiles of precipitation amounts when averaged over the area for the late-twenty-first century (2070-2099) climate in both winter and summer. The sign as well as the magnitude of the projected change vary only little for individual parts of the distribution of daily precipitation in winter. In summer, on the other hand, the projected changes increase with the quantile of the distribution in all RCMs, and they are negative (positive) for parts of the distribution below (above) the 98% quantile if averaged over the RCMs. The increases in precipitation extremes in summer are projected in spite of a pronounced drying in most RCMs. Although a rather general qualitative agreement of the models concerning the projected changes of precipitation extremes is found in both winter and summer, the uncertainties in climate change scenarios remain large and would likely further increase considerably if a more complete ensemble of RCM simulations driven by a larger suite of global models and with a range of possible scenarios of the radiative forcing is available.
机译:这项研究在欧洲项目ENSEMBLES中对12个区域气候模型(RCM)进行了模拟,以25 km的分辨率对中欧地区极端降雨的未来情况进行了研究。在估计极值分布时,我们将影响区域方法用作汇总方案,其中包括在将极值分布拟合到任何单个网格盒中时,合并来自“区域”(网格盒集)的数据。该方法减少了由于强降水的较大空间变化而导致的极值分布参数估计中的随机变化。尽管模型之间的空间格局不同,但大多数RCM都模拟了冬季和夏季在二十一世纪末(2070-2099)气候区域内平均降水量的增加。对于冬季每日降水分布的各个部分,符号和预计变化的幅度变化很小。另一方面,在夏季,所有RCM中分位数的预计变化都随着分布的分位数而增加,如果在RCM上进行平均,则低于(高于)98%分位数的部分分布区域将为负(正)。尽管大多数RCM干旱明显,但预计夏季极端降水将增加。尽管在冬季和夏季都发现了与预计的极端降水变化有关的模型的定性比较普遍,但气候变化情景的不确定性仍然很大,如果更大范围内的RCM模拟更完整,则可能会大大增加提供了一系列全球模型以及一系列可能的辐射强迫方案。

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  • 来源
    《Theoretical and applied climatology 》 |2011年第4期| p.529-542| 共14页
  • 作者单位

    Institute of Atmospheric Physics AS CR,Bocni II 1401,141 31 Prague, Czech Republic;

    Institute of Atmospheric Physics AS CR,Bocni II 1401,141 31 Prague, Czech Republic;

    Slovak University of Technology,Bratislava, Slovakia;

    Faculty of Mathematics and Physics, Charles University,Prague, Czech Republic;

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