首页> 外文期刊>Journal of Geographic Information System >Mapping Glacier Variations at Regional Scale through Equilibrium Line Altitude Interpolation: GIS andStatistical Application in Massif des écrins (French Alps)
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Mapping Glacier Variations at Regional Scale through Equilibrium Line Altitude Interpolation: GIS andStatistical Application in Massif des écrins (French Alps)

机译:通过平衡线高度插值在区域尺度上绘制冰川变化:地理信息系统和统计在法国阿尔卑斯山的应用

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Glacier variation is one of the best indicators of climate change in mountainous environment. In French Alps, many temporal data are acquired by glaciologists at glaciers scale: geometrical parameters (surface area, thickness, length and front altitude) are surveyed since the end of the 19th century. Those parameters are necessary to estimate the mass-balance of glaciers and, then, an accurate temporal signal of glacier variation. However, the time-response of the glaciers can be highly variable because of the topoclimate, and more generally the local settings of the glaciers. Moreover, climatologists and hydrologists are requiring estimation of glacier variations at regional scale and not only at local scale. In this paper, we highlight that the Equilibrium Line Altitude (ELA) is a parameter prone to spatio-temporal reconstructions at regional scale. ELA can indeed be interpolated at a region scale from local data: for instance, many geographers have reconstructed spatial trends during 1980s. Here, we try to interpolate ELA from multi-dimensionnal regression analysis: ELA is explained by many local parameters (Incoming solar radiation, topographic indexes, snow-redistribution by wind, etc.). Regression model was adjusted from a spatio-temporal database of 50 glaciers, located in the Massif des écrins. ELA was estimated for each glacier thanks to the Accumulation Area Ratio (ratio = 0.65) at two stages: LIA maximum and at present. Results first show that the multiple regression analysis is efficient to interpolate ELA through space: the adjusted r2 is about 0.49 for the reconstruction during the LIA, and 0.47 at present. Moreover, the RMSE error is about 50 meters for the LIA period, 55 meters at present. Finally, a high spatial variability (standard deviation of about 150 meters) is highlighted: incoming solar radiation and snow redistribution by wind mostly explain the observed differences. We can also assess a rise of the ELA of about 250 meters during the 20th century.
机译:冰川变化是山区环境气候变化的最好指标之一。在法国阿尔卑斯山,冰川学家以冰川规模获取了许多时间数据:自19世纪末以来,已对几何参数(表面积,厚度,长度和前高度)进行了调查。这些参数对于估算冰川的质量平衡是必需的,然后才能估算出冰川变化的准确时间信号。但是,由于地形气候的影响,冰川的时间响应变化很大,更普遍的原因是冰川的局部环境。此外,气候学家和水文学家要求在区域范围而不是仅在局部范围内估计冰川变化。在本文中,我们强调了平衡线高度(ELA)是易于在区域范围内进行时空重建的参数。确实可以从本地数据在区域范围内插值ELA:例如,许多地理学家在1980年代重构了空间趋势。在这里,我们尝试通过多维回归分析对ELA进行插值:ELA由许多局部参数(入射太阳辐射,地形指数,风雪分布等)解释。回归模型是根据位于Massif desécrins的50个冰川的时空数据库进行调整的。由于在两个阶段:LIA最大和当前两个阶段的累积面积比(比率= 0.65),估计了每个冰川的ELA。结果首先表明,多元回归分析可有效地在空间中插值ELA:对于LIA期间的重建,调整后的r2约为0.49,而目前为0.47。此外,LIA期间的RMSE误差约为50米,目前为55米。最后,强调了高的空间变异性(标准偏差约为150米):传入的太阳辐射和风的积雪重新解释了观察到的差异。我们还可以估计20世纪ELA上升约250米。

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