Results from the Ice Thickness Models Intercomparison eXperiment Phase 2 (ITMIX2)
Results from the Ice Thickness Models Intercomparison eXperiment Phase 2 (ITMIX2)
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DOI：
10.3389/feart.2020.571923
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发表时间：
2021-01-21
影响因子：
2.9
通讯作者：
Andreassen, Liss M.
中科院分区：
文献类型：
--
作者：
Farinotti, Daniel;Brinkerhoff, Douglas J.;Andreassen, Liss M.
了解冰川的冰厚分布对于从冰川学实地考察的规划到未来海平面变化的评估等一系列应用具有根本重要性。然而，在空间尺度上，这种知识受到可用厚度观测的缺乏和离散特性的限制。为了获得冰川冰厚度的空间连贯分布，必须使用插值或数值模型。虽然冰厚度模型相互比较实验（ITMIX）的第一阶段侧重于仅从冰川表面特征估计此类空间信息的方法，但ITMIX 2寻求对模型从有限数量的厚度观测中提取信息的能力的见解。这些分析是围绕23个测试案例设计的，包括真实世界和合成冰川，每个测试案例包括一组16个不同的实验，模拟数据可用性的可能场景。共有13名模特参加了实验。结果表明，在计算的局部厚度的模型间的变化是高的，对于未测量的位置，平均冰川厚度的16%的偏差是典型的（中位数估计，四分之三的偏差在37%的平均冰川厚度）。尽管如此，有限的冰厚度观测集被证明是有效的，在限制平均冰川厚度，甚至部分调查的价值。虽然结果是只有微弱的影响，空间分布的观测，调查，优先采样的最低冰川海拔被发现在几个模型中造成系统的厚度低估。相反，最厚的冰川部分的优先采样证明有效地减少偏差。对冰厚观测可用性的反应是每种方法的特征，并因模型而异。平均而言，模型和观测厚度之间的偏差增加了8.5%的平均冰厚度时，距离最近的观察增加了10倍。分析中没有出现单一的最佳模型，这证实了使用模型集合的附加值。
Knowing the ice thickness distribution of a glacier is of fundamental importance for a number of applications, ranging from the planning of glaciological fieldwork to the assessments of future sea-level change. Across spatial scales, however, this knowledge is limited by the paucity and discrete character of available thickness observations. To obtain a spatially coherent distribution of the glacier ice thickness, interpolation or numerical models have to be used. Whilst the first phase of the Ice Thickness Models Intercomparison eXperiment (ITMIX) focused on approaches that estimate such spatial information from characteristics of the glacier surface alone, ITMIX2 sought insights for the capability of the models to extract information from a limited number of thickness observations. The analyses were designed around 23 test cases comprising both real-world and synthetic glaciers, with each test case comprising a set of 16 different experiments mimicking possible scenarios of data availability. A total of 13 models participated in the experiments. The results show that the inter-model variability in the calculated local thickness is high, and that for unmeasured locations, deviations of 16% of the mean glacier thickness are typical (median estimate, three-quarters of the deviations within 37% of the mean glacier thickness). This notwithstanding, limited sets of ice thickness observations are shown to be effective in constraining the mean glacier thickness, demonstrating the value of even partial surveys. Whilst the results are only weakly affected by the spatial distribution of the observations, surveys that preferentially sample the lowest glacier elevations are found to cause a systematic underestimation of the thickness in several models. Conversely, a preferential sampling of the thickest glacier parts proves effective in reducing the deviations. The response to the availability of ice thickness observations is characteristic to each approach and varies across models. On average across models, the deviation between modeled and observed thickness increase by 8.5% of the mean ice thickness every time the distance to the closest observation increases by a factor of 10. No single best model emerges from the analyses, confirming the added value of using model ensembles.