Spatio-temporal variability of the winter surface mass balance is a major uncertainty in the modelling of annual surface mass balance. Moreover, its measurement at high spatio-temporal resolution (sub-200 m) is very useful to force, calibrate or validate models. This study presents the results of year-round field campaigns to study the evolution of the surface mass balance in a ~2 km2 portion of the accumulation zone of the Mer de Glace (France). It is based on repeated LiDAR acquisitions, submergence-velocity measurements and meteorological records. The two methods used to quantify submergence velocities show good agreement. They present a linear temporal evolution without significant seasonal changes but display significant spatial variability. We conclude that a dense network of submergence velocity measurements is required to reduce the uncertainties when computing winter and annual surface mass balance from digital elevation model differencing. Finally, a hight spatio-temporal variability of the winter surface mass balance is highlighted (e.g., a std dev. of 0.92 m in April) even though the topography is homogeneous (std dev. of 25 m). Attempts to relate this variability to different morpho-topographic variables and wind-related indexes show the need for studies conducted at the snowfall event scale to obtain a better understanding of the variability in mass balance at the glacier scale.

中文翻译：

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法国阿尔卑斯山 Mer de Glace 堆积区地表质量平衡的时空变化，来自多时相陆地 LiDAR 测量

冬季地表质量平衡的时空变化是年地表质量平衡建模的主要不确定性。此外，它在高时空分辨率（低于 200 m）下的测量对于强制、校准或验证模型非常有用。本研究展示了全年野外活动的结果，以研究约 2 公里范围内表面质量平衡的演变2Mer de Glace（法国）堆积带的一部分。它基于重复的 LiDAR 采集、淹没速度测量和气象记录。用于量化淹没速度的两种方法显示出良好的一致性。它们呈现线性时间演化，没有显着的季节性变化，但表现出显着的空间变异性。我们得出结论，当从数字高程模型差异计算冬季和年表面质量平衡时，需要一个密集的淹没速度测量网络来减少不确定性。最后，即使地形是均匀的（标准偏差为 25 m），冬季表面质量平衡的高度时空变化也被突出显示（例如，四月份的标准偏差为 0.92 m）。