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Improving a terrain-based parameter for the assessment of snow depths with TLS data in the Col du Lac Blanc area

机译:在Col du Lac Blanc地区使用TLS数据改进用于评估雪深的基于地形的参数

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Wind and the associated snow drift are dominating factors determining the snow distribution and accumulation in alpine areas, resulting in a high spatial variability of snow depth that is difficult to evaluate and quantify. The terrain-based parameter Sx characterizes the degree of shelter or exposure of a grid point provided by the upwind terrain without the computational complexity of numerical wind field models. The parameter has shown to qualitatively predict snow redistribution with good reproduction of spatial patterns, but has failed to quantitatively describe the snow redistribution. By comparing the parameter with high-resolution snow surface data obtained through terrestrial laser scanning (TLS), we are able a) to identify areas of poor correlations between predicted and measured snow distribution and changes in snow depths, and b) to increase its ability to predict changes in snow depths by modifying the parameter, based on the TLS data and the terrain and wind conditions specific to our research site, the Col du Lac Blanc in the French Alps. We show how results improve if a snow surface model is used for calculating the parameter instead of a digital elevation model, and demonstrate the effects of changing the parameter's maximum search distance and of raster smoothing. Our analyses and results are important steps in the improvements of the parameter's ability to predict changes in snow depths. (C) 2015 Elsevier B.V. All rights reserved.
机译:风和相关的积雪漂移是决定高山地区积雪分布和积聚的主要因素,导致积雪深度的高度空间变异性,难以评估和量化。基于地形的参数Sx表征了上风地形提供的栅格点的遮挡或暴露程度,而没有数值风场模型的计算复杂性。该参数已显示出定性预测降雪的重新分布以及空间模式的良好再现,但未能定量描述降雪的重新分布。通过将该参数与通过地面激光扫描(TLS)获得的高分辨率雪面数据进行比较,我们能够a)识别预测和实测雪分布与雪深变化之间相关性较差的区域,b)增强其能力根据TLS数据以及我们研究站点法国阿尔卑斯山的Col du Lac Blanc特定的地形和风况,通过修改参数来预测雪深的变化。我们将展示如果使用雪面模型而不是数字高程模型来计算参数时如何改善结果,并演示更改参数的最大搜索距离和栅格平滑化的效果。我们的分析和结果是提高参数预测雪深变化能力的重要步骤。 (C)2015 Elsevier B.V.保留所有权利。

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