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印度西喜马拉雅地区纳拉杜冰川的表面物质平衡分析。

Surface mass balance analysis at Naradu Glacier, Western Himalaya, India.

作者信息

Kumar Rajesh, Singh Shruti, Singh Atar, Kumar Ramesh, Singh Shaktiman, Randhawa Surjeet Singh

机构信息

Department of Environmental Science, School of Earth Sciences, Central University of Rajasthan (CURAJ), N.H.8, Bandar Sindri, Ajmer, Rajasthan, 305 817, India.

Department of Environmental Sciences, SBSR, Sharda University, Greater Noida, U.P., 201 306, India.

出版信息

Sci Rep. 2021 Jun 16;11(1):12710. doi: 10.1038/s41598-021-91348-3.

Abstract

In the present study, we analyze a field-based seven-year data series of surface mass-balance measurements collected during 2011/12 to 2017/18 on Naradu Glacier, western Himalaya, India. The average annual specific mass balance for the said period is  - 0.85 m w.e. with the maximum ablation of  - 1.15 m w.e. The analysis shows that the topographic features, south and southeast aspects and slopes between 7 to 24 degrees are the reasons behind the maximum ablation from a particular zone. The causes of surface mass balance variability have been analyzed through multiple linear regression analyses (MLRA) by taking temperature and precipitation as predictors. The MLRA demonstrates that 71% of the observed surface mass balance variance can be explained by temperature and precipitation. It clearly illustrates the importance of summer temperature, which alone explains 64% variance of surface mass balance. The seasonal analysis shows that most of the surface mass balance variability is described by summer temperature and winter precipitation as two predictor variables. Among monthly combinations, surface mass balance variance is best characterized by June temperature and September precipitation.

摘要

在本研究中,我们分析了2011/12年至2017/18年期间在印度西喜马拉雅地区纳拉杜冰川收集的基于实地的七年地表物质平衡测量数据系列。上述期间的年均比物质平衡为-0.85米水当量,最大消融量为-1.15米水当量。分析表明,地形特征、南坡和东南坡以及7至24度之间的坡度是特定区域最大消融的原因。通过以温度和降水为预测因子的多元线性回归分析(MLRA),分析了地表物质平衡变化的原因。MLRA表明,观测到的地表物质平衡变化的71%可由温度和降水解释。这清楚地说明了夏季温度的重要性,仅夏季温度就解释了地表物质平衡变化的64%。季节分析表明,地表物质平衡的大部分变化可由夏季温度和冬季降水这两个预测变量来描述。在月度组合中,地表物质平衡变化最好由6月温度和9月降水来表征。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a24f/8209027/cbd2ece2590a/41598_2021_91348_Fig1_HTML.jpg

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