Snow cover and glacier energy and mass balance variability (SG)

降水是将复杂的大气过程与水文循环、积雪以及冰川和冰盖的质量平衡联系在一起的最重要的气候因素之一。降水是水资源管理和预防洪涝干旱等自然灾害的关键变量。这一点尤其适用于拟议项目束PRIME的研究区域，该区域包括亚洲高地，即青藏高原及其周围的高山山脉。PRIME研究的目的是依靠新的遥感数据和先进的数值模拟方法生成和验证改进的网格化降水数据集(一)。在此基础上，我们研究了时空格局和区域边界条件、大尺度驱动因素和控制降水变率的中尺度到局地尺度过程(II)。关于降水类型和变化的更高的准确性和更好的知识使我们能够扩大对亚洲高地不同分区域冰川平衡和季节性积雪的时空变化的了解(Iii)。分项目PRIME-SG将通过三项主要研究活动为PRIME项目做出贡献。首先，PRIME的另外两个子项目新得出的降水数据集将根据MODIS卫星积雪数据和更新版本的冰雪能量与质量平衡模式(COSIMA)的更新版本进行评估。为此，COSIMA将扩大到包括冰冻的地面，而不是雪盖以下的冰。该结果将允许评估模拟(Prime-Har)和遥感(Prime-RS)降雪事件的一致性。在这一过程中，对单一事件造成的雪盖耗尽的模拟将受到MODIS卫星遥感图像的限制和评估。其次，COSIMA的高级和扩展版本和新的大气高亚洲精化分析(HAR)数据将联合用于模拟高亚洲部分冰川上的能量和质量通量，并提供可用物质平衡观测进行评估。结果将有助于分析新的COSIMA模式版本的性能和可靠性，并改进亚洲高地不同气候环境下冰川的输入数据。第三，在PRIME-SG中，我们将分析冰川物质平衡敏感性的驱动因素及其对大气强迫的空间变异性的依赖性。分析将基于灵敏度矩阵和对大气驱动因素的时间模式以及由此产生的不同区域的能量和质量通量的分析。

Precipitation is one of the most important climate elements linking complex atmospheric processes with hydrological cycles, snow cover and mass balances of glaciers and ice caps. Precipitation is a key variable for water resource management and prevention of natural disasters such as floods and droughts. This particularly holds true for the study region of the proposed project bundle prime which encompasses High Asia, i.e., the Tibetan Plateau and its surrounding high-mountain ranges. Research within prime aims at generating and validating improved gridded precipitation data sets relying on new remote sensing data and advanced numerical modelling approaches (i). Based on this we investigate spatial and temporal patterns and region-specific boundary conditions, large-scale drivers and meso- to local-scale processes controlling precipitation variability (ii). The improved accuracy and better knowledge on precipitation type and variability allow to extend our understanding of spatial and temporal variations of glacier mass balances and seasonal snow covers in different sub-regions of High Asia (iii).The sub-project prime-SG shall contribute to the project bundle prime by three major research activities. First, the newly derived precipitation datasets by the other two sub-projects of prime will be evaluated against a combination of MODIS satellite snow cover data and model runs with an updated version of the Coupled Snow and Ice Energy and Mass Balance Modell (COSIMA). For that purpose COSIMA will be extended to include frozen ground instead of ice below the snow cover. The results will allow to evaluate the consistency of modelled (prime-HAR) and remote sensing derived (prime-RS) snowfall events. The modelling of the depletion of the snow cover resulting from single events in this procedure will be constrained and evaluated by MODIS satellite remote sensing imagery. Second, an advanced and extended version of COSIMA and the new atmospheric High Asia Refined Analysis (HAR) data will jointly be used for simulations of energy and mass fluxes on selected glaciers in High Asia with available mass balance observations for evaluation. The results will allow to analyse the performance and reliability of the new COSIMA model version and improved input data for glaciers with different climatic settings in High Asia. Third, within prime-SG, we will analyse the driving factors of glacier mass balance sensitivity and their dependency on the spatial variability of atmospheric forcing. The analysis will be based on both, sensitivity matrices and the analysis of the temporal patterns in atmospheric drivers and resulting energy and mass fluxes in the different regions.