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Topoclimatic forcing and non-linear dynamics in the climate change adaption of glaciers in High Asia (TopoCliF)

高亚洲冰川适应气候变化的地形气候强迫和非线性动力学（TopoCliF）

基本信息

批准号：
356944332
负责人：
Dr. David Loibl
金额：
--
依托单位：
依托单位国家：
德国
项目类别：
Research Grants
财政年份：
2017
资助国家：
德国
起止时间：
2016-12-31 至 2021-12-31
项目状态：
已结题

来源：
https://gepris.dfg.de/gepris/projekt/356944332?language=en
关键词：
Topoclimatic forcing non linear dynamics

项目摘要

Glaciers in High Asia, a substantial resource of water supply for more than a billion people, are known to react highly heterogeneous to climate change. However, spatial patterns, forcing mechanisms, and sensitivities underlying this heterogeneity are still poorly understood. Recent studies highlight the role of topoclimatic effects at the scale of individual valleys and ridges, implying substantial potential for non-linear melt dynamics. To date, adequate tools to analyze such big data-prone mesoscale phenomena are lacking, resulting in a data gap between large-scale remote sensing studies and field-based investigations at individual glaciers. The equilibrium line altitude (ELA) of a glacier is an integrating phenomenon, reflecting a cross total of all topographic and climatic factors affecting the mass balance (MB); ELAs are thus eminently suited indicators for topoclimatic effects. The proposed project will apply a novel remote sensing approach, specifically designed to retrieve datasets of ELA and multitemporale ELA change calculations for whole orogens and with unprecedented level of detail. An artificial neural network will be applied to investigate how climatic drivers, such as global radiation, temperature, precipitation, and wind (data provided by the High Asia Refined analysis; HAR), and topographic factors, such as aspect, slope angle, and summit altitude (derived from digital elevation models; DEM) control ELAs in High Asia. For each mountain range in High Asia at least one benchmark settings will be selected basing on good data availability. Here, processes will be investigated at the scale of individual glaciers by applying a numerical model to obtain detailed surface energy and MB data. Resulting MBs will subsequently be used to model the sensitivity of the investigated glaciers to monthly anomalies in temperature and precipitation (from HAR data). Preliminary surveys showed that near-planar surfaces in accumulation areas of Himalayan glaciers entail great potential for non-linear melt dynamics if ELA rise continues. Surface areas and topographic configurations of such high-elevation surfaces will be quantified by DEM-based GIS analyses for glaciers throughout High Asia. Tipping points, at which ELA reaches the altitude of particular surfaces, will be identified by measuring remaining altitudinal buffers between the surfaces and modern ELAs. Temperature and precipitation offsets correlating to the altitudinal buffers may subsequently be assessed using the sensitivity data processed before. Ultimately, time remaining until ELAs exceed the tipping point elevation thresholds at individual glaciers will be estimated based on climate change projections under different emission scenarios. In summary, the results of the proposed interdisciplinary and poly-methodological approach will contribute substantially to disentangling the topoclimatic forcing of High Asia's glaciers and to quantify their potential for non-linear melt dynamics.

高亚洲的冰川是10亿多人的重要供水资源，众所周知，冰川对气候变化的反应非常不均匀。然而，这种异质性的空间格局，强迫机制和敏感性仍然知之甚少。最近的研究突出了地形气候效应在个别山谷和山脊规模的作用，这意味着非线性熔体动力学的巨大潜力。到目前为止，缺乏足够的工具来分析这种大数据倾向的中尺度现象，导致大规模遥感研究和个别冰川的实地调查之间存在数据差距。冰川平衡线高度（ELA）是一个综合现象，反映了影响物质平衡（MB）的所有地形和气候因素的交叉总和;因此ELA是非常适合的地形气候效应指标。拟议的项目将采用一种新的遥感方法，专门设计用于检索整个造山带的ELA和多时相ELA变化计算数据集，并具有前所未有的详细程度。人工神经网络将被应用于调查气候驱动因素，如全球辐射，温度，降水和风（由高亚洲精细分析提供的数据; HAR），地形因素，如方面，坡度角和山顶海拔（来自数字高程模型; DEM）控制ELAs在高亚洲。对于高亚洲的每一山脉，将根据良好的数据可用性至少选择一个基准设定。在这里，将通过应用数值模型以获得详细的表面能和甲基溴数据，在单个冰川的尺度上对这些过程进行调查。由此产生的MB随后将被用来模拟调查的冰川每月的温度和降水异常（从HAR数据）的敏感性。初步调查表明，近平面的喜马拉雅冰川积累区的表面带来了巨大的潜力，非线性融化动力学，如果ELA上升继续。这些高海拔表面的表面积和地形配置将通过基于数字高程模型的地理信息系统对整个高亚洲冰川的分析加以量化。将通过测量地表和现代ELA之间的剩余高度缓冲区来确定ELA到达特定地表高度的临界点。随后可以使用之前处理的敏感性数据来评估与海拔缓冲区相关的温度和降水偏移。最后，将根据不同排放情景下的气候变化预测，对个别冰川的ELA超过临界点海拔阈值所剩余的时间进行估计。总之，拟议的跨学科和多方法的方法的结果将大大有助于解开高亚洲的冰川的地形气候强迫，并量化其潜在的非线性融化动力学。