Understanding ice loss and glacial lake expansion in the Bhutanese Himalaya

“从1990年到2010年，冰湖面积平均增长了20.8%。前冰期湖泊的发育是特别重要的物质损失加重因素；这一变量尚未包括在目前的冰损失预测中，并可能导致“危险地区”爆发洪水的危险增加。喜马拉雅山脉的前冰期湖泊可以通过崩解和海底融化导致锋面冰的迅速加速损失。在不丹，对冰川对前冰期湖泊发展的反应的观测有限，对该地区湖泊驱动的物质损失的长期影响的约束很差，并且已被证明是高度可变的。在加拿大的一个湖泊，冰裂损失占总质量损失的10 - 25%，在特殊的夏季增加49%。这项研究将利用开放全球冰川模型（OGGM），这是一个基于Python的开源冰川模型，可以模拟任何规模的冰川的历史和未来的质量平衡。该模型已被证明在喜马拉雅地区是有效的，并且还可以纳入锋面消融参数，以便了解湖泊发育和裂冰的重要性。Yang等人（2022）使用OGGM在一系列不同的历史气候情景下，从四个冰川阶段模拟不丹的历史冰川退缩，校准模型的温度敏感性和非气候参数的残余偏差，以实现模型精度，但本研究没有测试产犊参数。在本研究中必须考虑碎屑覆盖；不丹64%的冰川面积被归类为“碎片覆盖”，此外，这些冰川中的许多是低梯度的，增加了冰川退缩后形成前冰川湖的可能性。重要的是将碎片覆盖纳入我们的质量平衡模型，以进一步了解气候变化将如何影响Lunana地区和/或更广泛地区的冰川。研究还发现，量化碎片覆盖对冰的温度敏感性的影响一直是准确模拟冰川退缩的最大挑战之一；因此，这一参数应通过实地观察加以校准。碎片对产犊过程的影响也很少有研究，这可能对理解亚洲高山冰川变薄率与向浮力产犊过渡之间的关系很重要。”

"Glacial lake area grew on average by 20.8% from 1990 - 2010. Proglacial lake development is a particularly important aggravating factor in mass loss; this variable has not been included in current ice loss projections and may result in increasing outburst flood hazard in 'at risk regions'. Proglacial lakes in the Himalayas can lead to the rapid acceleration of frontal ice loss through calving and sub-marine melt. In Bhutan, observations of the glacial response to proglacial lake development have been limited, and the long-term implications for lake driven mass loss in the region are poorly constrained and have been shown to be highly variable. Calving loss was shown to account for 10 - 25% of total mass loss for a lake terminating glacier in Canada, with an increase of 49% during exceptional summers.The study will utilise the Open Global Glacier Model (OGGM), an open source glacier model based in Python that can simulate historical and future mass-balance of glaciers of any size. The model has been shown to be effective in the Himalaya and can also incorporate frontal ablation parameters to allow the significance of lake development and calving to be understood. Yang et al. (2022) used the OGGM to model historical glacier retreat in Bhutan from four glacial stages under a suite of different historical climate scenarios calibrating the models temperature sensitivity and the residual bias for non-climatic parameters to achieve model accuracy, however this study did not test calving parameters. Debris cover must be considered in this study; 64% of glacier area in Bhutan is classified as 'debris covered', furthermore, many of these glaciers are low gradient, increasing the likelihood of proglacial lake development following retreat. It is important to incorporate debris cover into our mass balance models, to further understand how climate change will affect the glaciers in the Lunana region and/or wider region. Studies have also found that quantifying the effect of debris cover on the temperature sensitivity of ice has been one of the biggest challenges for accurately modelling glacial retreat; this parameter should therefore be calibrated through field observations. The effect of debris on calving processes has also seen little research and may be important in understanding the relationship between thinning rates and the transition to buoyant calving in High Mountain Asia."