SGER: Glacier sensitivity to climate change: Quantifying the influence of tributary glaciers

SGER：冰川对气候变化的敏感性：量化支流冰川的影响

• 批准号: 0913107
• 负责人: Summer Rupper
• 金额: $ 3.49万
• 依托单位: Brigham Young University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-05-01 至 2010-10-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0913107&HistoricalAwards=false
• 关键词: SGER; Glacier; sensitivity; climate; change

The Gornergletscher in Switzerland is the second largest glacier system in the Alps, and it has been retreating rapidly since the turn of the century. The rate of this retreat has varied greatly, Preliminary numerical mass-balance modeling indicate that changes in tributary glaciers that feed the main valley glacier may be the key to predicting the response of system to changes in climate. Excluding these smaller, tributary glaciers from models underestimates the magnitude and response time of the glacier terminus to changes in climate. However, the model does not yet include ice dynamics. The physical and chemical properties of ice within tributary glaciers may be drastically different than those of neighboring tributaries and the main valley glacier. It thus follows that physical properties of tributary glaciers will influence the dynamics of the glacier system as a whole, influencing both the rate and magnitude of glacier responses to changes in climate. This project will investigate the influence of tributary glaciers on ice dynamics of the Gornergletscher system, and how changes in tributary glaciers then influence the response time and sensitivity of alpine glaciers to changes in climate. This will be accomplished by analyzing the chemical and physical properties of ice in several shallow (~15 m) ice cores along a traverse through the tributary and main valley glaciers. Together with ground-penetrating radar (GPR along the same transect, the ice-core data will determine the physical and chemical ice properties within tributary glaciers on the Gornergletscher, and to quantify the influence of tributary glaciers on the internal ice dynamics of the main valley glacier.The potential societal impacts of the near world-wide retreat of glaciers over the past century has been of the focus of much discussion in the scientific, economic, and political communities. Changes in these glaciers will greatly affect freshwater resources, hydroelectric power, tourism, local climate, and sea-level rise, among other things. Additionally, past climate reconstructions from records of past glacier extent often serve as the primary descriptor of the climate history of a region, and have proven critical for quantifying natural climate variability. Numerical glacier models are essential tools in studies of glacier sensitivity to climate change past, present, and future However, glacier retreat over the last century has been larger than was predicted by glacier models, challenging our understanding of glacier sensitivity to changes in climate. Given the current thinning and retreat rate of glaciers in many regions of the world, it is imperative that accurate reconstructions and predictions of glacier response to climate scenarios be provided. This project will greatly increase the knowledge of glacier sensitivity to climate change and improve the accuracy of numerical glacier models.

瑞士的Gornergletscher是阿尔卑斯山的第二大冰川系统，自世纪以来，它一直在迅速退缩。 初步的数值质量平衡模拟表明，为主谷冰川提供补给的支流冰川的变化可能是预测系统对气候变化响应的关键。 从模型中排除这些较小的支流冰川低估了冰川终点对气候变化的响应时间和规模。 然而，该模型尚未包括冰动力学。 支流冰川内冰的物理和化学性质可能与邻近支流和主要山谷冰川的冰有很大不同。 因此，支流冰川的物理特性将影响整个冰川系统的动态，影响冰川对气候变化的反应速度和幅度。 该项目将调查支流冰川对Gornergletscher系统冰动力学的影响，以及支流冰川的变化如何影响高山冰川对气候变化的响应时间和敏感性。 这将通过分析几个浅（~15米）冰芯中冰的化学和物理特性来完成，这些冰芯沿着支流和主要山谷冰川的横截面。 冰芯数据与同一断面的探地雷达（GPR）沿着一起，将确定Gornergletscher支流冰川内冰的物理和化学性质，并量化支流冰川对主谷冰川内部冰动力学的影响。近期世界的潜在社会影响-在过去的世纪里，冰川的大范围退缩一直是科学界、经济界和政治界讨论的焦点。 这些冰川的变化将极大地影响淡水资源、水力发电、旅游业、当地气候和海平面上升等。 此外，根据过去冰川范围的记录重建过去的气候往往是一个地区气候历史的主要描述符，并已被证明是量化自然气候变率的关键。 冰川数值模式是研究冰川对过去、现在和未来气候变化敏感性的重要工具。然而，在过去的世纪，冰川退缩比冰川模式预测的要大，这挑战了我们对冰川对气候变化敏感性的理解。 鉴于目前世界许多地区冰川的变薄和退缩速度，必须提供准确的冰川对气候情景反应的重建和预测。 该项目将大大增加关于冰川对气候变化敏感性的知识，并提高冰川数值模型的准确性。