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      Multi-decadal mass balance series of three Kyrgyz glaciers inferred from modelling constrained with repeated snow line observations

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          Abstract

          Abstract. Glacier surface mass balance observations in the Tien Shan and Pamir are relatively sparse and often discontinuous. Nevertheless, glaciers are one of the most important components of the high-mountain cryosphere in the region as they strongly influence water availability in the arid, continental and intensely populated downstream areas. This study provides reliable and continuous surface mass balance series for selected glaciers located in the Tien Shan and Pamir-Alay. By cross-validating the results of three independent methods, we reconstructed the mass balance of the three benchmark glaciers, Abramov, Golubin and Glacier no. 354 for the past 2 decades. By applying different approaches, it was possible to compensate for the limitations and shortcomings of each individual method. This study proposes the use of transient snow line observations throughout the melt season obtained from satellite optical imagery and terrestrial automatic cameras. By combining modelling with remotely acquired information on summer snow depletion, it was possible to infer glacier mass changes for unmeasured years. The model is initialized with daily temperature and precipitation data collected at automatic weather stations in the vicinity of the glacier or with adjusted data from climate reanalysis products. Multi-annual mass changes based on high-resolution digital elevation models and in situ glaciological surveys were used to validate the results for the investigated glaciers. Substantial surface mass loss was confirmed for the three studied glaciers by all three methods, ranging from −0.30 ± 0.19 to −0.41 ± 0.33 m w.e. yr−1 over the 2004–2016 period. Our results indicate that integration of snow line observations into mass balance modelling significantly narrows the uncertainty ranges of the estimates. Hence, this highlights the potential of the methodology for application to unmonitored glaciers at larger scales for which no direct measurements are available.

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          Global-scale hydrological response to future glacier mass loss

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            A spatially resolved estimate of High Mountain Asia glacier mass balances, 2000-2016

            High Mountain Asia hosts the largest glacier concentration outside the polar regions. These glaciers are important contributors to streamflow in one of the most populated areas of the world. Past studies have used methods that can only provide regionally-averaged glacier mass balances to assess the High Mountain Asia glacier contribution to rivers and sea level rise. Here we compute the mass balance for about 92 % of the glacierized area of High Mountain Asia using time series of digital elevation models derived from satellite stereo-imagery. We calculate an average region-wide mass balance of -16.3 ± 3.5 Gt yr-1 (-0.18 ± 0.04 m w.e. yr-1) between 2000 and 2016, which is less negative than most previous estimates. Region-wide mass balances vary from -4.0 ± 1.5 Gt yr-1 (-0.62 ± 0.23 m w.e. yr-1) in Nyainqentanglha to +1.4 ± 0.8 Gt yr-1 (+0.14 ± 0.08 m w.e. yr-1) in Kunlun, with large intra-regional variability of individual glacier mass balances (standard deviation within a region ˜0.20 m w.e. yr-1). Specifically, our results shed light on the Nyainqentanglha and Pamir glacier mass changes, for which contradictory estimates exist in the literature. They provide crucial information for the calibration of the models used for projections of future glacier response to climatic changes, models that presently do not capture the pattern, magnitude and intra-regional variability of glacier changes in High Mountain Asia.
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              Co-registration and bias corrections of satellite elevation data sets for quantifying glacier thickness change

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                Author and article information

                Journal
                The Cryosphere
                The Cryosphere
                Copernicus GmbH
                1994-0424
                2018
                June 06 2018
                : 12
                : 6
                : 1899-1919
                Article
                10.5194/tc-12-1899-2018
                691ce5db-c900-4e21-a2a8-14efebf4655c
                © 2018

                https://creativecommons.org/licenses/by/4.0/

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