Combining glaciological field surveys, REmote sensing and regional Climate modelling to Analyze the variability of accumulation in the Pamir mountains

结合冰川实地调查、遥感和区域气候模型分析帕米尔高原堆积变化

• 批准号: 530581485
• 负责人: Dr. Christoph Mayer
• 金额: --
• 依托单位: Institut des Géosciences de l’Environnement
• 依托单位国家: 德国
• 项目类别: Research Grants
• 资助国家: 德国
• 项目状态: 未结题
• 来源: https://gepris.dfg.de/gepris/projekt/530581485?language=en
• 关键词: Combining; glaciological; field; surveys; REmote

High altitude precipitation and the related accumulation rates on the glaciers are variables with the highest uncertainties, when it comes to assessing the status of the cryosphere in High Mountain Asia (HMA). While ice melt in the lower regions can be modelled to a rather satisfying accuracy by using reanalysis data, combined with meteorological information from valley stations, the knowledge about accumulation at high elevations is still poorly constrained. We propose an integrated study, which combines novel field observations with state of the art analysis of remote sensing observations to feed into regional climate models and detailed modelling of the snow and firn conditions. The outcome will answer urgent questions at different levels on spatial and temporal scales, focussing on Fedchenko Glacier in the Pamir Mountains for the local investigations, but extending the model results to the entire Pamir region. Temporally high resolved information will be gained about the evolution of the firnlayering and the effect of surface melt on compaction, percolation and layer preservation. The regional accumulation distribution across the most significant elevation ranges will be reconstructed and used as input for mass flux estimates across the equilibrium line. These investigations will contribute to characterising the mass balance situation of the glaciers. Considering an extended scale in space and time will allow us to analyse the temporal evolution of the glacier accumulation for a larger region, also in the view of the stability of the Pamir-Karakoram anomaly, indicating more stable recent mass balance conditions across large parts of the Pamir Mountains. To do so, a regional climate model, already developed by the French counterpart of this project, will be configured to produce a centennial atmospheric reanalysis covering the period 1900-present over the whole HMA area. The model will be calibrated using both local and satellite observational data, to finally produce a reanalysis data set for the respective period. This will allow us to investigate the variability of both the climate and the cryosphere from daily to centennial timescales, a way to interpret the local observations with a regional and centennial view. Besides new insights into the processes involved in the climatic transformation across the accumulation regions, this study will also provide important information on the stability and representativeness of climate information potentially stored in the upper Fedchenko Glacier. This is of special importance, as a new project of scientific partners secured funding for the retrieval of a deep ice core from the Fedchenko Glacier accumulation region. Our results will help to improve the interpretation of the core sample analysis and integrate this information in a larger picture of the recent evolution of the high altitude precipitation history.

在评估亚洲高山（HMA）冰冻圈状况时，高海拔降水和冰川上相关的积累率是不确定性最高的变量。虽然在较低的地区的冰融化可以模拟到一个相当令人满意的精度，通过使用再分析数据，结合从山谷站的气象信息，在高海拔地区的积累的知识仍然受到很大的限制。我们提出了一个综合的研究，它结合了新的实地观察与国家的最先进的遥感观测分析，以输入到区域气候模型和详细的模拟雪和积雪条件。该结果将在空间和时间尺度上回答不同层次的紧迫问题，重点是帕米尔山脉的Fedchenko冰川的当地调查，但将模型结果扩展到整个帕米尔地区。时间上的高分辨率信息将获得有关的Firnlayering的演变和压实，渗流和层保存的表面融化的效果。将重建最重要海拔范围内的区域累积分布，并将其用作平衡线上质量通量估计的输入。这些调查将有助于描述冰川的物质平衡状况。考虑在空间和时间上的扩展尺度将使我们能够分析更大区域的冰川积累的时间演变，也可以从帕米尔-喀喇昆仑异常的稳定性的角度来分析，这表明帕米尔山脉大部分地区最近的物质平衡条件更加稳定。为此，该项目的法国同行已经开发了一个区域气候模型，该模型将被配置为生成覆盖整个HMA地区1900年至今的百年大气再分析。将利用当地和卫星观测数据对该模型进行校准，以最终生成相应时期的再分析数据集。这将使我们能够研究从每日到百年时间尺度的气候和冰冻圈的变化，这是一种用区域和百年观点解释当地观测结果的方法。除了新的见解，在整个积累区域的气候变化过程中所涉及的，这项研究还将提供重要的信息的稳定性和代表性的气候信息可能存储在上Fedchenko冰川。这一点特别重要，因为科学伙伴的一个新项目获得了从Fedchenko冰川堆积区取回深冰芯的资金。我们的研究结果将有助于提高解释的核心样品分析和整合这些信息在一个更大的图片最近的演变高海拔降水的历史。