Jury Martin W, Mendlik Thomas, Tani Satyanarayana, Truhetz Heimo, Maraun Douglas, Immerzeel Walter W, Lutz Arthur F
Wegener Center for Climate and Global Change (WEGC) University of Graz Graz Austria.
Institute of Microwave and Photonic Engineering Graz University of Technology Graz Austria.
Int J Climatol. 2020 Mar 15;40(3):1738-1754. doi: 10.1002/joc.6298. Epub 2019 Dec 25.
Glaciers are of key importance to freshwater supplies in the Himalayan region. Their growth or decline is among other factors determined by an interaction of 2-m air temperature (TAS) and precipitation rate (PR) and thereof derived positive degree days (PDD) and snow and ice accumulation (SAC). To investigate determining factors in climate projections, we use a model ensemble consisting of 36 CMIP5 general circulation models (GCMs) and 13 regional climate models (RCMs) of two Asian CORDEX domains for two different representative concentration pathways (RCP4.5 and RCP8.5). First, we downsize the ensemble in respect to the models' ability to correctly reproduce dominant circulation patterns (i.e., the Indian summer monsoon [ISM] and western disturbances [WDs]) as well as elevation-dependent trend signals in winter. Within this evaluation, a newly produced data set for the Indus, Ganges and Brahmaputra catchments is used as observational data. The reanalyses WFDEI, ERA-Interim, NCEP/NCAR and JRA-55 are used to further account for observational uncertainty. In a next step, remaining TAS and PR data are bias corrected applying a new bias adjustment method, scale distribution mapping, and subsequently PDD and SAC computed. Finally, we identify and quantify projected climate change effects. Until the end of the century, the ensemble indicates a rise of PDD, especially during summer and for lower altitudes. Also TAS is rising, though the highest increases are shown for higher altitudes and between December and April (DJFMA). PRs connected to the ISM are projected to robustly increase, while signals for PR changes during DJFMA show a higher level of uncertainty and spatial heterogeneity. However, a robust decline in solid precipitation is projected over our research domain, with the exception of a small area in the high mountain Indus catchment where no clear signal emerges.
冰川对喜马拉雅地区的淡水供应至关重要。它们的增长或衰退在其他因素中,取决于2米气温(TAS)和降水率(PR)的相互作用,以及由此得出的正积温(PDD)和冰雪积累(SAC)。为了研究气候预测中的决定性因素,我们使用了一个模型集合,该集合由两个亚洲CORDEX区域的36个CMIP5通用环流模型(GCM)和13个区域气候模型(RCM)组成,用于两种不同的代表性浓度路径(RCP4.5和RCP8.5)。首先,我们根据模型正确再现主导环流模式(即印度夏季风[ISM]和西风扰动[WDs])以及冬季海拔相关趋势信号的能力,对集合进行缩减。在此评估中,一个新生成的印度河、恒河和雅鲁藏布江流域数据集被用作观测数据。再分析数据WFDEI、ERA-Interim、NCEP/NCAR和JRA-55被用于进一步考虑观测不确定性。在下一步中,应用一种新的偏差调整方法——尺度分布映射,对剩余的TAS和PR数据进行偏差校正,随后计算PDD和SAC。最后,我们识别并量化预测的气候变化影响。到本世纪末,该集合表明PDD将上升,尤其是在夏季和较低海拔地区。TAS也在上升,尽管海拔较高地区以及12月至4月(DJFMA)期间上升幅度最大。与ISM相关的PR预计将强劲增加,而DJFMA期间PR变化的信号显示出更高的不确定性和空间异质性。然而,预计我们研究区域的固态降水将大幅下降,但印度河高山流域的一个小区域除外,该区域没有明显信号出现。