Articles | Volume 17, issue 3
https://doi.org/10.5194/tc-17-1343-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-17-1343-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
28 Mar 2023
Research article |
| 28 Mar 2023
| 28 Mar 2023
Central Asia's spatiotemporal glacier response ambiguity due to data inconsistencies and regional simplifications
Martina Barandun
Institute of Earth Observation, Eurac Research, Bolzano, Italy
Department of Geosciences, University of Fribourg, Fribourg, Switzerland
Department of Geosciences, University of Fribourg, Fribourg, Switzerland
Related authors
Dilara Kim, Enrico Mattea, Mattia Callegari, Tomas Saks, Ruslan Kenzhebayev, Erlan Azisov, Tobias Ullmann, Martin Hoelzle, and Martina Barandun
EGUsphere, https://doi.org/10.5194/egusphere-2025-3978, https://doi.org/10.5194/egusphere-2025-3978, 2025
This preprint is open for discussion and under review for The Cryosphere (TC).
Short summary
Short summary
We investigated how the snowline changed on four glaciers in the Pamir and Tien Shan mountain ranges in Central Asia. For this we developed a new method of combining different types of satellite images. This detailed record of snowlines shows for the first time how glaciers are responding to climate change during the dry season on almost daily scale. Our results help to understand better when and how much meltwater stored in glaciers can be used for drinking water by people living downstream.
Enrico Mattea, Etienne Berthier, Amaury Dehecq, Tobias Bolch, Atanu Bhattacharya, Sajid Ghuffar, Martina Barandun, and Martin Hoelzle
The Cryosphere, 19, 219–247, https://doi.org/10.5194/tc-19-219-2025, https://doi.org/10.5194/tc-19-219-2025, 2025
Short summary
Short summary
We reconstruct the evolution of terminus position, ice thickness, and surface flow velocity of the reference Abramov glacier (Kyrgyzstan) from 1968 to present. We describe a front pulsation in the early 2000s and the multi-annual present-day buildup of a new pulsation. Such dynamic instabilities can challenge the representativity of Abramov as a reference glacier. For our work we used satellite‑based optical remote sensing from multiple platforms, including recently declassified archives.
Dilara Kim, Enrico Mattea, Mattia Callegari, Tomas Saks, Ruslan Kenzhebayev, Erlan Azisov, Tobias Ullmann, Martin Hoelzle, and Martina Barandun
EGUsphere, https://doi.org/10.5194/egusphere-2025-3978, https://doi.org/10.5194/egusphere-2025-3978, 2025
This preprint is open for discussion and under review for The Cryosphere (TC).
Short summary
Short summary
We investigated how the snowline changed on four glaciers in the Pamir and Tien Shan mountain ranges in Central Asia. For this we developed a new method of combining different types of satellite images. This detailed record of snowlines shows for the first time how glaciers are responding to climate change during the dry season on almost daily scale. Our results help to understand better when and how much meltwater stored in glaciers can be used for drinking water by people living downstream.
Enrico Mattea, Etienne Berthier, Amaury Dehecq, Tobias Bolch, Atanu Bhattacharya, Sajid Ghuffar, Martina Barandun, and Martin Hoelzle
The Cryosphere, 19, 219–247, https://doi.org/10.5194/tc-19-219-2025, https://doi.org/10.5194/tc-19-219-2025, 2025
Short summary
Short summary
We reconstruct the evolution of terminus position, ice thickness, and surface flow velocity of the reference Abramov glacier (Kyrgyzstan) from 1968 to present. We describe a front pulsation in the early 2000s and the multi-annual present-day buildup of a new pulsation. Such dynamic instabilities can challenge the representativity of Abramov as a reference glacier. For our work we used satellite‑based optical remote sensing from multiple platforms, including recently declassified archives.
Tamara Mathys, Muslim Azimshoev, Zhoodarbeshim Bektursunov, Christian Hauck, Christin Hilbich, Murataly Duishonakunov, Abdulhamid Kayumov, Nikolay Kassatkin, Vassily Kapitsa, Leo C. P. Martin, Coline Mollaret, Hofiz Navruzshoev, Eric Pohl, Tomas Saks, Intizor Silmonov, Timur Musaev, Ryskul Usubaliev, and Martin Hoelzle
EGUsphere, https://doi.org/10.5194/egusphere-2024-2795, https://doi.org/10.5194/egusphere-2024-2795, 2024
Short summary
Short summary
This study provides a comprehensive geophysical dataset on permafrost in the data-scarce Tien Shan and Pamir mountain regions of Central Asia. It also introduces a novel modeling method to quantify ground ice content across different landforms. The findings indicate that this approach is well-suited for characterizing ice-rich permafrost, which is crucial for evaluating future water availability and assessing risks associated with thawing permafrost.
Cited articles
Aizen, E. M., Aizen, V. B., Melack, J. M., Nakamura, T., and Ohta, T.:
Precipitation and atmospheric circulation patterns at mid-latitudes of Asia,
Int. J. Climatol., 21, 535–556, 2001. a
Aizen, V. B., Aizen, E. M., and Melack, J. M.: Climate, snow cover, glaciers,
and runoff in the Tien Shan, central Asia, JAWRA Journal of the American
Water Resources Association, 31, 1113–1129, 1995. a
Aizen, V. B., Mayewski, P. A., Aizen, E. M., Joswiak, D. R., Surazakov, A. B.,
Kaspari, S., Grigholm, B., Krachler, M., Handley, M., and Finaev, A.:
Stable-isotope and trace element time series from Fedchenko glacier (Pamirs)
snow/firn cores, J. Glaciol., 55, 275–291, 2009. a
Archer, D. R. and Fowler, H. J.: Spatial and temporal variations in precipitation in the Upper Indus Basin, global teleconnections and hydrological implications, Hydrol. Earth Syst. Sci., 8, 47–61, https://doi.org/10.5194/hess-8-47-2004, 2004. a
Azisov, E., Hoelzle, M., Vorogushyn, S., Saks, T., Usubaliev, R., uulu, M. E.,
and Barandun, M.: Reconstructed Centennial Mass Balance Change for Golubin
Glacier, Northern Tien Shan, Atmosphere, 13, 954, https://doi.org/10.3390/atmos13060954, 2022. a, b, c
Barandun, M. and Pohl, E.: Inconsistent mass balance relationships in Central Asia, Zenodo [data set], https://doi.org/10.5281/zenodo.6631963, 2022. a
Barandun, M., Huss, M., Usubaliev, R., Azisov, E., Berthier, E., Kääb, A., Bolch, T., and Hoelzle, M.: Multi-decadal mass balance series of three Kyrgyz glaciers inferred from modelling constrained with repeated snow line observations, The Cryosphere, 12, 1899–1919, https://doi.org/10.5194/tc-12-1899-2018, 2018. a, b, c
Barandun, M., Fiddes, J., Scherler, M., Mathys, T., Saks, T., Petrakov, D., and
Hoelzle, M.: The state and future of the cryosphere in Central Asia, Water
Security, 11, 100072, https://doi.org/10.1016/j.wasec.2020.100072,
2020. a, b
Barandun, M., Pohl, E., Naegeli, K., McNabb, R., Huss, M., Berthier, E., Saks,
T., and Hoelzle, M.: Hot spots of glacier mass balance variability in Central
Asia, Geophys. Res. Lett., 48, e2020GL092084, https://doi.org/10.1029/2020GL092084, 2021a. a, b, c, d, e, f, g, h, i, j, k, l, m, n, o, p, q, r, s, t, u, v, w, x, y, z, aa, ab, ac, ad, ae, af, ag, ah
Barandun, M., Pohl, E., Naegeli, K., McNabb, R., Huss, M., Berthier, E., Saks, T., and Hoelzle, M.: Annual mass balance time series for the Tien Shan and Pamir from 2000 to 2018, Zenodo [data set], https://doi.org/10.5281/zenodo.4782116, 2021b. a
Barry, R. G.: Mountain weather and climate, 2nd edn., Routledge, London, ISBN 9780415071130, 1992. a
Beraud, L., Cusicanqui, D., Rabatel, A., Brun, F., Vincent, C., and Six, D.:
Glacier-wide seasonal and annual geodetic mass balances from Pléiades
stereo images: application to the Glacier d'Argentière, French Alps,
J. Glaciol., 79, 1–13, https://doi.org/10.1017/jog.2022.79, 2022. a, b
Beven, K.: A manifesto for the equifinality thesis, J. Hydrol.,
320, 18–36, 2006. a
Biskop, S., Maussion, F., Krause, P., and Fink, M.: Differences in the water-balance components of four lakes in the southern-central Tibetan Plateau, Hydrol. Earth Syst. Sci., 20, 209–225, https://doi.org/10.5194/hess-20-209-2016, 2016. a, b, c
Bohner, J.: General climatic controls and topoclimatic variations in Central
and High Asia, Boreas, 35, 279–295, 2006. a
Bolch, T., Shea, J. M., Liu, S., Azam, F. M., Gao, Y., Gruber, S., Immerzeel, W. W., Kulkarni, A., Li, H., Tahir, A. A., Zhang, G., and Zhang, Y.: Status and change of the
cryosphere in the Extended Hindu Kush Himalaya Region, in: The Hindu Kush
Himalaya Assessment, edited by: Wester, P., Mishra, A., Mukherji, A., and Shrestha, A. B., Springer International Publishing, 209–255, ISBN 978-3-319-92288-1, https://doi.org/10.1007/978-3-319-92288-1_7, 2019. a, b, c, d
Boos, W. R. and Kuang, Z.: Dominant control of the South Asian monsoon by
orographic insulation versus plateau heating, Nature, 463, 218–222, 2010. a
Brun, F., Berthier, E., Wagnon, P., Kääb, A., and Treichler, D.: A
spatially resolved estimate of High Mountain Asia glacier mass balances,
2000–2016, Nat. Geosci., 10, 668, https://doi.org/10.1038/ngeo2999, 2017. a, b
Cadet, D.: Meteorology of the Indian summer monsoon, Nature, 279, 761–767,
1979. a
Copernicus Climate Change Service, Climate Data Store: ERA5 monthly averaged data on single levels from 1940 to present, Copernicus Climate Change Service (C3S) Climate Data Store (CDS) [data set], https://doi.org/10.24381/cds.f17050d7 (last access: 13 March 2023), 2023. a
Curio, J., Maussion, F., and Scherer, D.: A 12-year high-resolution climatology of atmospheric water transport over the Tibetan Plateau, Earth Syst. Dynam., 6, 109–124, https://doi.org/10.5194/esd-6-109-2015, 2015. a
Dee, D., Uppala, S., Simmons, A., Berrisford, P., Poli, P.,
Kobayashi, S., Andrae, U., Balmaseda, M., Balsamo, G., Bauer, P.,
Bechtold, P., Beljaars, A. C. M., van de Berg, L., Bidlot, J.,
Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Geer, A. J.,
Haimberger, L., Healy, S., Hersbach, H., Hólm, E., Isaksen, L.,
Kållberg, P., Köhler, M., Matricardi, M., McNally, P.,
Monge-Sanz, B., Morcrette, J., Park, B., Peubey, C., de Rosnay, P.,
Tavolato, C., Thépaut, J., and Vitart, F.: The ERA-Interim
reanalysis: configuration and performance of the data assimilation system,
Q. J. Roy. Meteor. Soc., 137, 553–597,
https://doi.org/10.1002/qj.828, 2011. a
de Kok, R. J., Kraaijenbrink, P. D. A., Tuinenburg, O. A., Bonekamp, P. N. J., and Immerzeel, W. W.: Towards understanding the pattern of glacier mass balances in High Mountain Asia using regional climatic modelling, The Cryosphere, 14, 3215–3234, https://doi.org/10.5194/tc-14-3215-2020, 2020. a, b
Farinotti, D., Immerzeel, W. W., de Kok, R. J., Quincey, D. J., and Dehecq, A.:
Manifestations and mechanisms of the Karakoram glacier Anomaly, Nat.
Geosci., 13, 8–16, 2020. a
Fiddes, J. and Gruber, S.: TopoSUB: a tool for efficient large area numerical modelling in complex topography at sub-grid scales, Geosci. Model Dev., 5, 1245–1257, https://doi.org/10.5194/gmd-5-1245-2012, 2012. a, b
Fiddes, J. and Gruber, S.: TopoSCALE v.1.0: downscaling gridded climate data in complex terrain, Geosci. Model Dev., 7, 387–405, https://doi.org/10.5194/gmd-7-387-2014, 2014. a, b
Fowler, H. and Archer, D.: Conflicting signals of climatic change in the Upper
Indus Basin, J. Climate, 19, 4276–4293, 2006. a
Fujita, K. and Nuimura, T.: Spatially heterogeneous wastage of Himalayan
glaciers, P. Natl. Acad. Sci., 108,
14011–14014, 2011. a
Gardelle, J., Berthier, E., and Arnaud, Y.: Slight mass gain of Karakoram
glaciers in the early twenty-first century, Nat. Geosci., 5, 322–325, https://doi.org/10.1038/ngeo1450, 2012. a
Gerlitz, L., Vorogushyn, S., and Gafurov, A.: Climate informed seasonal
forecast of water availability in Central Asia: State-of-the-art and decision
making context, Water Security, 10, 100061, https://doi.org/10.1016/j.wasec.2020.100061, 2020. a, b
Girod, L., Nuth, C., Kääb, A., McNabb, R., and Galland, O.: MMASTER:
Improved ASTER DEMs for Elevation Change Monitoring, Remote Sens., 9, 704, https://doi.org/10.3390/rs9070704,
2017. a
Glasser, N. F., Quincey, D. J., and King, O.: Changes in ice-surface debris,
surface elevation and mass through the active phase of selected Karakoram
glacier surges, Geomorphology, 410, 108291,
https://doi.org/10.1016/j.geomorph.2022.108291, 2022. a
Guillet, G., King, O., Lv, M., Ghuffar, S., Benn, D., Quincey, D., and Bolch, T.: A regionally resolved inventory of High Mountain Asia surge-type glaciers, derived from a multi-factor remote sensing approach (Version v1), Zenodo [data set], https://doi.org/10.5281/zenodo.5524861, 2021. a
Guillet, G., King, O., Lv, M., Ghuffar, S., Benn, D., Quincey, D., and Bolch, T.: A regionally resolved inventory of High Mountain Asia surge-type glaciers, derived from a multi-factor remote sensing approach, The Cryosphere, 16, 603–623, https://doi.org/10.5194/tc-16-603-2022, 2022. a, b, c, d, e, f
Hall, D. and Riggs, G.: MODIS/Terra Snow Cover Monthly L3 Global 0.05 Deg CMG,
Version 6, Boulder, Colorado USA. NASA National Snow
and Ice Data Center Distributed Active Archive Center, https://doi.org/10.5067/MODIS/MOD10CM.006, 2015. a, b
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., de Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J.-N.: The ERA5 global reanalysis, Q. J. Roy.
Meteor. Soc., 146, 1999–2049, 2020. a, b, c
Hoelzle, M., Barandun, M., Bolch, T., Fiddes, J., Gafurov, A., Muccione, V.,
Saks, T., and Shahgedanova, M.: The status and role of the alpine cryosphere
in Central Asia, in: The Aral Sea Basin, Taylor & Francis, https://doi.org/10.4324/9780429436475, 2019. a, b
Hugonnet, R., McNabb, R., Berthier, E., Menounos, B., Nuth, C., Girod, L., Farinotti, D., Huss, M., Dussaillant, I., Brun, F., and Kääb, A.: Accelerated
global glacier mass loss in the early twenty-first century, Nature, 592,
726–731, https://doi.org/10.1038/s41586-021-03436-z, 2021. a, b, c, d, e, f, g, h, i, j, k, l, m, n, o, p, q, r, s, t, u, v, w, x, y, z
Immerzeel, W. W., Wanders, N., Lutz, A. F., Shea, J. M., and Bierkens, M. F. P.: Reconciling high-altitude precipitation in the upper Indus basin with glacier mass balances and runoff, Hydrol. Earth Syst. Sci., 19, 4673–4687, https://doi.org/10.5194/hess-19-4673-2015, 2015. a
Jarvis, A., Reuter, H. I., Nelson, A. D., and Guevara, E.: Hole-filled SRTM
for the globe Version 4, CGIAR-CSI SRTM 90m Database, International Centre for Tropical Agriculture (CIAT),
https://srtm.csi.cgiar.org (last access: 13 March 2023), 2008. a
Kääb, A., Treichler, D., Nuth, C., and Berthier, E.: Brief Communication: Contending estimates of 2003–2008 glacier mass balance over the Pamir–Karakoram–Himalaya, The Cryosphere, 9, 557–564, https://doi.org/10.5194/tc-9-557-2015, 2015. a
Karger, D. N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza,
R. W., Zimmermann, N. E., Linder, H. P., and Kessler, M.: Climatologies at
high resolution for the earth's land surface areas, Sci. Data, 4,
170122, https://doi.org/10.1038/sdata.2017.122, 2017. a, b
Karger, D. N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza,
R. W., Zimmermann, N. E., Linder, H. P., and Kessler, M.: Climatologies at
high resolution for the earth's land surface areas, EnviDat [data set],
https://doi.org/10.16904/envidat.228.v2.1, 2021. a, b
Knoche, M., Merz, R., Lindner, M., and Weise, S. M.: Bridging Glaciological and
Hydrological Trends in the Pamir Mountains, Central Asia, Water, 9, 422–450, https://doi.org/10.3390/w9060422,
2017. a
Kotlyakov, V., Osipova, G., and Tsvetkov, D.: Monitoring surging glaciers of
the Pamirs, central Asia, from space, Ann. Glaciol., 48, 125–134,
2008. a
Kraaijenbrink, P., Bierkens, M., Lutz, A., and Immerzeel, W.: Impact of a
global temperature rise of 1.5 degrees Celsius on Asia’s glaciers, Nature,
549, 257, https://doi.org/10.1038/nature23878, 2017. a
Kronenberg, M., van Pelt, W., Machguth, H., Fiddes, J., Hoelzle, M., and Pertziger, F.: Long-term firn and mass balance modelling for Abramov Glacier in the data-scarce Pamir Alay, The Cryosphere, 16, 5001–5022, https://doi.org/10.5194/tc-16-5001-2022, 2022. a, b
Kuhn, M.: Climate and Glaciers, in: Sea level, ice and climatic change: proceedings of the Symposium held 7–8 December 1979 during the 17th General Assembly of the International Union of Geodesy and Geophysics, Canberra, edited by: Allison, I., vol. 131, International Association of Hydrological Sciences, 1980. a
Kuhn, M.: Mass budget imbalances as criterion for a climatic classification of
glaciers, Geografiska Annaler: Series A, 66, 229–238,
1984. a
Li, X., Zhang, B., Ren, R., Li, L., and Simonovic, S. P.: Spatio-Temporal
Heterogeneity of Climate Warming in the Chinese Tianshan Mountainous Region,
Water, 14, 199, https://doi.org/10.3390/w14020199, 2022. a
Liu, L., Gu, H., Xie, J., and Xu, Y.-P.: How well do the ERA-Interim, ERA-5,
GLDAS-2.1 and NCEP-R2 reanalysis datasets represent daily air temperature
over the Tibetan Plateau?, Int. J. Climatol., 41,
1484–1505, 2021. a
Maussion, F., Scherer, D., Finkelnburg, R., Richters, J., Yang, W., and Yao, T.: WRF simulation of a precipitation event over the Tibetan Plateau, China – an assessment using remote sensing and ground observations, Hydrol. Earth Syst. Sci., 15, 1795–1817, https://doi.org/10.5194/hess-15-1795-2011, 2011. a, b, c, d
Maussion, F., Scherer, D., Mölg, T., Collier, E., Curio, J., and
Finkelnburg, R.: Precipitation seasonality and variability over the Tibetan
Plateau as resolved by the High Asia Reanalysis, J. Climate, 27,
1910–1927, https://doi.org/10.1175/JCLI-D-13-00282.1, 2014 (data available at: https://data.klima.tu-berlin.de/HAR/v1/, last access: 13 March 2023). a, b, c
McCarthy, M., Miles, E., Kneib, M., Buri, P., Fugger, S., and Pellicciotti, F.:
Supraglacial debris thickness and supply rate in High-Mountain Asia, Commun. Earth Environ., 3, 269, https://doi.org/10.1038/s43247-022-00588-2, 2021. a
McNabb, R., Nuth, C., Kääb, A., and Girod, L.: Sensitivity of glacier volume change estimation to DEM void interpolation, The Cryosphere, 13, 895–910, https://doi.org/10.5194/tc-13-895-2019, 2019. a
Miles, E., McCarthy, M., Dehecq, A., Kneib, M., Fugger, S., and Pellicciotti,
F.: Health and sustainability of glaciers in High Mountain Asia, Nat.
Commun., 12, 1–10, 2021. a
Miles, E. S., Steiner, J. F., Buri, P., Immerzeel, W. W., and Pellicciotti, F.:
Controls on the relative melt rates of debris-covered glacier surfaces,
Environ. Res. Lett., 17, 064004, https://doi.org/10.1088/1748-9326/ac6966,
2022. a
Mukherjee, K., Bolch, T., Goerlich, F., Kutuzov, S., Osmonov, A., Pieczonka,
T., and Shesterova, I.: Surge-type glaciers in the Tien Shan (Central Asia),
Arct. Antarct. Alp. Res., 49, 147–171, 2017. a
Naegeli, K., Huss, M., and Hoelzle, M.: Change detection of bare-ice albedo in the Swiss Alps, The Cryosphere, 13, 397–412, https://doi.org/10.5194/tc-13-397-2019, 2019. a
National Centers for Environmental Prediction, National Weather Service,
NOAA, U. D. o. C.: NCEP FNL Operational Model Global Tropospheric Analyses,
continuing from July 1999, https://doi.org/10.5065/D6M043C6, 2000. a
Orsolini, Y., Wegmann, M., Dutra, E., Liu, B., Balsamo, G., Yang, K., de Rosnay, P., Zhu, C., Wang, W., Senan, R., and Arduini, G.: Evaluation of snow depth and snow cover over the Tibetan Plateau in global reanalyses using in situ and satellite remote sensing observations, The Cryosphere, 13, 2221–2239, https://doi.org/10.5194/tc-13-2221-2019, 2019. a, b, c
Palazzi, E., Von Hardenberg, J., and Provenzale, A.: Precipitation in the
hindu-kush karakoram himalaya: Observations and future scenarios, J.
Geophys. Res.-Atmos., 118, 85–100, https://doi.org/10.1029/2012JD018697,
2013. a, b
Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel,
O., Blondel, M., Prettenhofer, P., Weiss, R., Dubourg, V., Vanderplas, J.,
Passos, A., Cournapeau, D., Brucher, M., Perrot, M., and Duchesnay, E.:
Scikit-learn: Machine Learning in Python, J. Mach. Learn.
Res., 12, 2825–2830, 2011. a
Pohl, E., Knoche, M., Gloaguen, R., Andermann, C., and Krause, P.: Sensitivity analysis and implications for surface processes from a hydrological modelling approach in the Gunt catchment, high Pamir Mountains, Earth Surf. Dynam., 3, 333–362, https://doi.org/10.5194/esurf-3-333-2015, 2015. a, b, c, d, e, f, g, h
RGI Consortium: Randolph Glacier Inventory – A Dataset of Global Glacier Outlines, Version 6, Boulder, Colorado USA, NSIDC: National Snow and Ice Data Center [data set], https://doi.org/10.7265/4m1f-gd79, 2017b. a
Roe, G. H., Montgomery, D. R., and Hallet, B.: Orographic precipitation and the
relief of mountain ranges, J. Geophys. Res.-Sol. Earth, 108, B6, https://doi.org/10.1029/2001JB001521,
2003. a, b
Sakai, A. and Fujita, K.: Contrasting glacier responses to recent climate
change in high-mountain Asia, Sci. Rep.-UK, 7, 13717, https://doi.org/10.1038/s41598-017-14256-5, 2017. a, b, c
Scherler, D., Wulf, H., and Gorelick, N.: Global assessment of supraglacial
debris-cover extents, Geophys. Res. Lett., 45, 11–798,
https://doi.org/10.1029/2018GL080158, 2018a. a, b, c, d
Scherler, D., Wulf, H., and Gorelick, N.: Supraglacial Debris Cover. V. 1.0, GFZ Data Services [data set], https://doi.org/10.5880/GFZ.3.3.2018.005 (last access: 13 March 2023), 2018b. a
Schiemann, R., Glazirina, M. G., and Schär, C.: On the relationship between
the Indian summer monsoon and river flow in the Aral Sea basin, Geophys.
Res. Lett., 34, 5, https://doi.org/10.1029/2006GL028926, 2007. a, b
SEDOO: Accelerated global glacier mass loss in the early twenty-first century – Dataset, https://doi.org/10.6096/13, SEDOO [data set], 2023. a
Shean, D., Bhushan, S., Montesano, P., Rounce, D., Arendt, A., and Osmanoglu,
B.: A systematic, regional assessment of High Mountain Asia Glacier mass
balance. Front, Earth Sci., 7, 363, https://doi.org/10.3389/feart.2019.00363, 2020. a, b
Sicart, J. E., Hock, R., Ribstein, P., and Litt, M.: Analysis of seasonal
variations in mass balance and meltwater discharge of the tropical Zongo
Glacier by application of a distributed energy balance model, J. Geophys. Res.-Atmos., 116, 1–18,
https://doi.org/10.1029/2010JD015105, 2011. a
Skamarock, W. C. and Klemp, J. B.: A time-split nonhydrostatic atmospheric
model for weather research and forecasting applications, J.
Comput. Phys., 227, 3465–3485, https://doi.org/10.1016/j.jcp.2007.01.037,
2008. a
Sorg, A., Bolch, T., Stoffel, M., Solomina, O., and Beniston, M.: Climate
change impacts on glaciers and runoff in Tien Shan (Central Asia), Nat.
Clim. Change, 2, 725–731, https://doi.org/10.1038/nclimate1592, 2012. a
Unger-Shayesteh, K., Vorogushyn, S., Farinotti, D., Gafurov, A., Duethmann, D.,
Mandychev, A., and Merz, B.: What do we know about past changes in the water
cycle of Central Asian headwaters? A review, Global Planet. Change,
110, 4–25, https://doi.org/10.1016/j.gloplacha.2013.02.004, 2013. a, b
Vatcheva, K. P., Lee, M., McCormick, J. B., and Rahbar, M. H.:
Multicollinearity in regression analyses conducted in epidemiologic studies,
Epidemiology (Sunnyvale, Calif.), 6, 227, https://doi.org/10.4172/2161-1165.1000227, 2016. a
Wang, Q., Yi, S., Chang, L., and Sun, W.: Large-scale seasonal changes in
glacier thickness across High Mountain Asia, Geophys. Res. Lett., 44, 10–427, https://doi.org/10.1002/2017GL075300,
2017. a, b
Wang, R., Liu, S., Shangguan, D., Radić, V., and Zhang, Y.: Spatial
heterogeneity in glacier mass-balance sensitivity across High Mountain Asia,
Water, 11, 776, https://doi.org/10.3390/w11040776, 2019. a, b, c
Wei, W., Zhang, R., Wen, M., and Yang, S.: Relationship between the Asian
westerly jet stream and summer rainfall over Central Asia and North China:
Roles of the Indian monsoon and the South Asian High, J. Climate, 30,
537–552, 2017. a
Wouters, B., Gardner, A. S., and Moholdt, G.: Global glacier mass loss during
the GRACE satellite mission (2002–2016), Front. Earth Sci., 7, 96, https://doi.org/10.3389/feart.2019.00096, 2019.
a
Yang, W., Guo, X., Yao, T., Yang, K., Zhao, L., Li, S., and Zhu, M.: Summertime
surface energy budget and ablation modeling in the ablation zone of a
maritime Tibetan glacier, J. Geophys. Res.-Atmos., 116, D14, https://doi.org/10.1029/2010JD015183,
2011. a
Yao, T., Thompson, L., Yang, W., Yu, W., Gao, Y., Guo, X., Yang, X., Duan, K., Zhao, H., Xu, B., Pu, J., Lu, A., Xiang, Y., Kattel, D. B., and Joswiak, D.: Different glacier status with atmospheric
circulations in Tibetan Plateau and surroundings, Nat. Clim. Change, 2,
663, https://doi.org/10.1038/nclimate1580, 2012. a
Zandler, H., Haag, I., and Samimi, C.: Evaluation needs and temporal
performance differences of gridded precipitation products in peripheral
mountain regions, NatSR, 9, 15118, https://doi.org/10.1038/s41598-019-51666-z, 2019. a, b
Zhao, G., Tian, P., Mu, X., Jiao, J., Wang, F., and Gao, P.: Quantifying the
impact of climate variability and human activities on streamflow in the
middle reaches of the Yellow River basin, China, J. Hydrol., 519,
387–398, 2014. a
Short summary
Meteorological and glacier mass balance data scarcity introduces large uncertainties about drivers of heterogeneous glacier mass balance response in Central Asia. We investigate the consistency of interpretations derived from various datasets through a systematic correlation analysis between climatic and static drivers with mass balance estimates. Our results show in particular that even supposedly similar datasets lead to different and partly contradicting assumptions on dominant drivers.
Meteorological and glacier mass balance data scarcity introduces large uncertainties about...
