首页> 外文期刊>Journal of Glaciology >Statistical modelling of the surface mass-balance variability of the Morteratsch glacier, Switzerland: strong control of early melting season meteorological conditions
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Statistical modelling of the surface mass-balance variability of the Morteratsch glacier, Switzerland: strong control of early melting season meteorological conditions

机译:瑞士马腾腾冰川表面大幅平衡变异性的统计建模:强烈控制早期熔化季节气象条件

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摘要

In this study we analyse a 15-year long time series of surface mass-balance (SMB) measurements performed between 2001 and 2016 in the ablation zone of the Morteratsch glacier complex (Engadine, Switzerland). For a better understanding of the SMB variability and its causes, multiple linear regressions analyses are performed with temperature and precipitation series from nearby meteorological stations. Up to 85% of the observed SMB variance can be explained by the mean May-June-July temperature and the total precipitation from October to March. A new method is presented where the contribution of each month's individual temperature and precipitation to the SMB can be examined in a total sample of 2(24) (16.8 million) combinations. More than 90% of the observed SMB can be explained with particular combinations, in which the May-June-July temperature is the most recurrent, followed by October temperature. The role of precipitation is less pronounced, but autumn, winter and spring precipitation are always more important than summer precipitation. Our results indicate that the length of the ice ablation season is of larger importance than its intensity to explain year-to-year variations. The widely used June-July-August temperature index may not always be the best option to describe SMB variability through statistical correlation.
机译:在这项研究中,我们分析了在Morteratch Glacier Complex(Engadine,Switzerland)的消融区之间进行的15年长时间的表面质量平衡(SMB)测量。为了更好地了解SMB变异性及其原因,使用附近气象站的温度和降水系列进行多元线性回归分析。最高可观察到的SMB方差的85%可以通过平均5月至7月温度和10月至3月的总降水来解释。介绍了一种新方法,其中每个月单个温度和降水对SMB的贡献可以在2(24)(1680万)组合的总样本中进行检查。观察到的SMB的90%以上可以用特定组合来解释,其中5月至7月温度是最重复的,其次是10月温度。降水的作用不太明显,但秋季,冬季和春季降水总比夏季降水更重要。我们的研究结果表明,冰冻消融季节的长度比其向年度变化的强度更重要。广泛使用的6月至7月 - 8月温度指数可能并不总是通过统计相关描述SMB变异性的最佳选择。

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