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Interannual snow accumulation variability on glaciers derived from repeat, spatially extensive ground-penetrating radar surveys

机译:重复,空间广泛的地面渗透雷达调查中冰川的际雪积累可变性

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There is significant uncertainty regarding the spatiotemporal distribution of seasonal snow on glaciers, despite being a fundamental component of glacier mass balance. To address this knowledge gap, we collected repeat, spatially extensive high-frequency ground-penetrating radar (GPR) observations on two glaciers in Alaska during the spring of 5?consecutive years. GPR measurements showed steep snow water equivalent (SWE) elevation gradients at both sites; continental Gulkana Glacier's SWE gradient averaged 115?mm 100?m ?1 and maritime Wolverine Glacier's gradient averaged 440?mm 100?m ?1 (over ?1000?m). We extrapolated GPR point observations across the glacier surface using terrain parameters derived from digital elevation models as predictor variables in two statistical models (stepwise multivariable linear regression and regression trees). Elevation and proxies for wind redistribution had the greatest explanatory power, and exhibited relatively time-constant coefficients over the study period. Both statistical models yielded comparable estimates of glacier-wide average SWE (1?% average difference at Gulkana, 4?% average difference at Wolverine), although the spatial distributions produced by the models diverged in unsampled regions of the glacier, particularly at Wolverine. In total, six different methods for estimating the glacier-wide winter balance average agreed within ±11 ?%. We assessed interannual variability in the spatial pattern of snow accumulation predicted by the statistical models using two quantitative metrics. Both glaciers exhibited a high degree of temporal stability, with ~85 ?% of the glacier area experiencing less than 25?% normalized absolute variability over this 5-year interval. We found SWE at a sparse network (3 stakes per glacier) of long-term glaciological stake sites to be highly correlated with the GPR-derived glacier-wide average. We estimate that interannual variability in the spatial pattern of winter SWE accumulation is only a small component (4?%–10?% of glacier-wide average) of the total mass balance uncertainty and thus, our findings support the concept that sparse stake networks effectively measure interannual variability in winter balance on glaciers, rather than some temporally varying spatial pattern of snow accumulation.
机译:尽管是冰川大规模平衡的基本组成部分,但冰川上季节性雪的时空分布存在显着的不确定性。为了解决这一知识差距,我们在5年的春天期间收集了阿拉斯加的两种冰川上的重复,空间广泛的高频地面穿透雷达(GPR)观察。 GPR测量显示陡峭的雪水等同(SWE)升高梯度在两个地点;大陆Gulkana冰川的SWE梯度平均为115?mm 100?m?1和海上狼犬冰川的梯度平均440?mm 100?m?1(超过&?1000?m)。我们使用从数字高程模型导出的地形参数作为两个统计模型中的预测变量(逐步多变量线性回归和回归树),推断GPR点观察。风力再分配的高度和代理具有最大的解释能力,并在研究期间表现出相对时常数的系数。统计模型均产生了冰川宽的平均SWE的可比估计(Gulkana的1倍平均差异,狼獾的平均差异为4?%),尽管模型产生的空间分布在冰川的未夹杂地区分散,特别是在狼獾处。总共估计冰川宽的冬季余额平均值的六种不同的方法在±11±11℃。我们评估了使用两种定量度量预测的统计模型预测的雪积累空间模式的续变性。两个冰川都表现出高度的时间稳定性,〜85?%的冰川地区经历较小的25倍的常规绝对变异性。我们在长期冰川杆菌桩位点的稀疏网络(每冰川3个赌场)中找到了SWE,以与GPR衍生的冰川宽的平均水平高度相关。我们估计冬季SWE积累空间模式的续集变异只是总质量平衡的不确定性的小组分(冰川宽的范围内的4倍),因此,我们的研究结果支持稀疏股权网络的概念有效地衡量冰川上冬季平衡的持续变化,而不是一些时间变化的积雪空间模式。

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