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
Enrico Mattea, Etienne Berthier, Amaury Dehecq, Tobias Bolch, Atanu Bhattacharya, Sajid Ghuffar, Martina Barandun, and Martin Hoelzle
EGUsphere, https://doi.org/10.5194/egusphere-2024-2169, https://doi.org/10.5194/egusphere-2024-2169, 2024
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 reference glacier. For our work we used satellite‑based optical remote sensing from multiple platforms, including recently declassified archives.
Martina Barandun, Matthias Huss, Ryskul Usubaliev, Erlan Azisov, Etienne Berthier, Andreas Kääb, Tobias Bolch, and Martin Hoelzle
The Cryosphere, 12, 1899–1919, https://doi.org/10.5194/tc-12-1899-2018, https://doi.org/10.5194/tc-12-1899-2018, 2018
Short summary
Short summary
In this study, we used three independent methods (in situ measurements, comparison of digital elevation models and modelling) to reconstruct the mass change from 2000 to 2016 for three glaciers in the Tien Shan and Pamir. Snow lines observed on remote sensing images were used to improve conventional modelling by constraining a mass balance model. As a result, glacier mass changes for unmeasured years and glaciers can be better assessed. Substantial mass loss was confirmed for the three glaciers.
Martin Hoelzle, Erlan Azisov, Martina Barandun, Matthias Huss, Daniel Farinotti, Abror Gafurov, Wilfried Hagg, Ruslan Kenzhebaev, Marlene Kronenberg, Horst Machguth, Alexandr Merkushkin, Bolot Moldobekov, Maxim Petrov, Tomas Saks, Nadine Salzmann, Tilo Schöne, Yuri Tarasov, Ryskul Usubaliev, Sergiy Vorogushyn, Andrey Yakovlev, and Michael Zemp
Geosci. Instrum. Method. Data Syst., 6, 397–418, https://doi.org/10.5194/gi-6-397-2017, https://doi.org/10.5194/gi-6-397-2017, 2017
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.
Enrico Mattea, Etienne Berthier, Amaury Dehecq, Tobias Bolch, Atanu Bhattacharya, Sajid Ghuffar, Martina Barandun, and Martin Hoelzle
EGUsphere, https://doi.org/10.5194/egusphere-2024-2169, https://doi.org/10.5194/egusphere-2024-2169, 2024
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 reference glacier. For our work we used satellite‑based optical remote sensing from multiple platforms, including recently declassified archives.
Eric Pohl, Christophe Grenier, Mathieu Vrac, and Masa Kageyama
Hydrol. Earth Syst. Sci., 24, 2817–2839, https://doi.org/10.5194/hess-24-2817-2020, https://doi.org/10.5194/hess-24-2817-2020, 2020
Short summary
Short summary
Existing approaches to quantify the emergence of climate change require several user choices that make these approaches less objective. We present an approach that uses a minimum number of choices and showcase its application in the extremely sensitive, permafrost-dominated region of eastern Siberia. Designed as a Python toolbox, it allows for incorporating climate model, reanalysis, and in situ data to make use of numerous existing data sources and reduce uncertainties in obtained estimates.
Martina Barandun, Matthias Huss, Ryskul Usubaliev, Erlan Azisov, Etienne Berthier, Andreas Kääb, Tobias Bolch, and Martin Hoelzle
The Cryosphere, 12, 1899–1919, https://doi.org/10.5194/tc-12-1899-2018, https://doi.org/10.5194/tc-12-1899-2018, 2018
Short summary
Short summary
In this study, we used three independent methods (in situ measurements, comparison of digital elevation models and modelling) to reconstruct the mass change from 2000 to 2016 for three glaciers in the Tien Shan and Pamir. Snow lines observed on remote sensing images were used to improve conventional modelling by constraining a mass balance model. As a result, glacier mass changes for unmeasured years and glaciers can be better assessed. Substantial mass loss was confirmed for the three glaciers.
Martin Hoelzle, Erlan Azisov, Martina Barandun, Matthias Huss, Daniel Farinotti, Abror Gafurov, Wilfried Hagg, Ruslan Kenzhebaev, Marlene Kronenberg, Horst Machguth, Alexandr Merkushkin, Bolot Moldobekov, Maxim Petrov, Tomas Saks, Nadine Salzmann, Tilo Schöne, Yuri Tarasov, Ryskul Usubaliev, Sergiy Vorogushyn, Andrey Yakovlev, and Michael Zemp
Geosci. Instrum. Method. Data Syst., 6, 397–418, https://doi.org/10.5194/gi-6-397-2017, https://doi.org/10.5194/gi-6-397-2017, 2017
M. C. Fuchs, R. Gloaguen, S. Merchel, E. Pohl, V. A. Sulaymonova, C. Andermann, and G. Rugel
Earth Surf. Dynam., 3, 423–439, https://doi.org/10.5194/esurf-3-423-2015, https://doi.org/10.5194/esurf-3-423-2015, 2015
E. Pohl, M. Knoche, R. Gloaguen, C. Andermann, and P. Krause
Earth Surf. Dynam., 3, 333–362, https://doi.org/10.5194/esurf-3-333-2015, https://doi.org/10.5194/esurf-3-333-2015, 2015
Short summary
Short summary
A semi-distributed hydrological model is used to analyse the hydrological cycle of a glaciated high-mountain catchment in the Pamirs.
We overcome data scarcity by utilising various raster data sets as meteorological input. Temperature in combination with the amount of snow provided in winter play the key role in the annual cycle.
This implies that expected Earth surface processes along precipitation and altitude gradients differ substantially.
Related subject area
Discipline: Glaciers | Subject: Mass Balance Obs
Reanalysis of the longest mass balance series in Himalaya using nonlinear model: Chhota Shigri Glacier (India)
Accumulation by avalanches as significant contributor to the mass balance of a High Arctic mountain glacier
Brief communication: The Glacier Loss Day as an indicator of a record-breaking negative glacier mass balance in 2022
European heat waves 2022: contribution to extreme glacier melt in Switzerland inferred from automated ablation readings
Recent contrasting behaviour of mountain glaciers across the European High Arctic revealed by ArcticDEM data
Characteristics of mountain glaciers in the northern Japanese Alps
Assimilating near-real-time mass balance stake readings into a model ensemble using a particle filter
Geodetic point surface mass balances: a new approach to determine point surface mass balances on glaciers from remote sensing measurements
Applying artificial snowfall to reduce the melting of the Muz Taw Glacier, Sawir Mountains
Satellite-observed monthly glacier and snow mass changes in southeast Tibet: implication for substantial meltwater contribution to the Brahmaputra
Brief communication: Ad hoc estimation of glacier contributions to sea-level rise from the latest glaciological observations
Heterogeneous spatial and temporal pattern of surface elevation change and mass balance of the Patagonian ice fields between 2000 and 2016
Long-range terrestrial laser scanning measurements of annual and intra-annual mass balances for Urumqi Glacier No. 1, eastern Tien Shan, China
Multi-year evaluation of airborne geodetic surveys to estimate seasonal mass balance, Columbia and Rocky Mountains, Canada
Interannual snow accumulation variability on glaciers derived from repeat, spatially extensive ground-penetrating radar surveys
Local topography increasingly influences the mass balance of a retreating cirque glacier
Multi-decadal mass balance series of three Kyrgyz glaciers inferred from modelling constrained with repeated snow line observations
Changing pattern of ice flow and mass balance for glaciers discharging into the Larsen A and B embayments, Antarctic Peninsula, 2011 to 2016
Mohd Farooq Azam, Christian Vincent, Smriti Srivastava, Etienne Berthier, Patrick Wagnon, Himanshu Kaushik, Arif Hussain, Manoj Kumar Munda, Arindan Mandal, and Alagappan Ramanathan
EGUsphere, https://doi.org/10.5194/egusphere-2024-644, https://doi.org/10.5194/egusphere-2024-644, 2024
Short summary
Short summary
Mass balance series on Chhota Shigri Glacier has been reanalysed by combining the traditional mass balance reanalysis framework and a nonlinear model. The nonlinear model is preferred over traditional glaciological method to compute the mass balances as the former can capture the spatiotemporal variability of point mass balances from a heterogeneous in-situ point mass balance network. The nonlinear model outperforms the traditional method and agrees better with the geodetic estimates.
Bernhard Hynek, Daniel Binder, Michele Citterio, Signe Hillerup Larsen, Jakob Abermann, Geert Verhoeven, Elke Ludewig, and Wolfgang Schöner
The Cryosphere Discuss., https://doi.org/10.5194/tc-2023-157, https://doi.org/10.5194/tc-2023-157, 2023
Revised manuscript accepted for TC
Short summary
Short summary
A strong avalanche event in winter 2018 caused thick snow deposits on Freya Glacier, a mountain glacier in Northeast Greenland. The avalanche deposits led to positive elevation changes during the study period 2013–2021 and altered the mass balance of the glacier significantly. The eight year mass balance was positive, it would have been negative without avalanches. The contribution from snow avalanches might become more important with rising temperatures in the Arctic.
Annelies Voordendag, Rainer Prinz, Lilian Schuster, and Georg Kaser
The Cryosphere, 17, 3661–3665, https://doi.org/10.5194/tc-17-3661-2023, https://doi.org/10.5194/tc-17-3661-2023, 2023
Short summary
Short summary
The Glacier Loss Day (GLD) is the day on which all mass gained from the accumulation period is lost, and the glacier loses mass irrecoverably for the rest of the mass balance year. In 2022, the GLD was already reached on 23 June at Hintereisferner (Austria), and this led to a record-breaking mass loss. We introduce the GLD as a gross yet expressive indicator of the glacier’s imbalance with a persistently warming climate.
Aaron Cremona, Matthias Huss, Johannes Marian Landmann, Joël Borner, and Daniel Farinotti
The Cryosphere, 17, 1895–1912, https://doi.org/10.5194/tc-17-1895-2023, https://doi.org/10.5194/tc-17-1895-2023, 2023
Short summary
Short summary
Summer heat waves have a substantial impact on glacier melt as emphasized by the extreme summer of 2022. This study presents a novel approach for detecting extreme glacier melt events at the regional scale based on the combination of automatically retrieved point mass balance observations and modelling approaches. The in-depth analysis of summer 2022 evidences the strong correspondence between heat waves and extreme melt events and demonstrates their significance for seasonal melt.
Jakub Małecki
The Cryosphere, 16, 2067–2082, https://doi.org/10.5194/tc-16-2067-2022, https://doi.org/10.5194/tc-16-2067-2022, 2022
Short summary
Short summary
This study presents a snapshot of the recent state of small mountain glaciers across the European High Arctic, where severe climate warming has been occurring over the past years. The analysis revealed that this class of ice mass might melt away from many study sites within the coming two to five decades even without further warming. Glacier changes were, however, very variable in space, and some glaciers have been gaining mass, but the exact drivers behind this phenomenon are unclear.
Kenshiro Arie, Chiyuki Narama, Ryohei Yamamoto, Kotaro Fukui, and Hajime Iida
The Cryosphere, 16, 1091–1106, https://doi.org/10.5194/tc-16-1091-2022, https://doi.org/10.5194/tc-16-1091-2022, 2022
Short summary
Short summary
In recent years, seven glaciers are confirmed in the northern Japanese Alps. However, their mass balance has not been clarified. In this study, we calculated the seasonal and continuous annual mass balance of these glaciers during 2015–2019 by the geodetic method using aerial images and SfM–MVS technology. Our results showed that the mass balance of these glaciers was different from other glaciers in the world. The characteristics of Japanese glaciers provide new insights for earth science.
Johannes Marian Landmann, Hans Rudolf Künsch, Matthias Huss, Christophe Ogier, Markus Kalisch, and Daniel Farinotti
The Cryosphere, 15, 5017–5040, https://doi.org/10.5194/tc-15-5017-2021, https://doi.org/10.5194/tc-15-5017-2021, 2021
Short summary
Short summary
In this study, we (1) acquire real-time information on point glacier mass balance with autonomous real-time cameras and (2) assimilate these observations into a mass balance model ensemble driven by meteorological input. For doing so, we use a customized particle filter that we designed for the specific purposes of our study. We find melt rates of up to 0.12 m water equivalent per day and show that our assimilation method has a higher performance than reference mass balance models.
Christian Vincent, Diego Cusicanqui, Bruno Jourdain, Olivier Laarman, Delphine Six, Adrien Gilbert, Andrea Walpersdorf, Antoine Rabatel, Luc Piard, Florent Gimbert, Olivier Gagliardini, Vincent Peyaud, Laurent Arnaud, Emmanuel Thibert, Fanny Brun, and Ugo Nanni
The Cryosphere, 15, 1259–1276, https://doi.org/10.5194/tc-15-1259-2021, https://doi.org/10.5194/tc-15-1259-2021, 2021
Short summary
Short summary
In situ glacier point mass balance data are crucial to assess climate change in different regions of the world. Unfortunately, these data are rare because huge efforts are required to conduct in situ measurements on glaciers. Here, we propose a new approach from remote sensing observations. The method has been tested on the Argentière and Mer de Glace glaciers (France). It should be possible to apply this method to high-spatial-resolution satellite images and on numerous glaciers in the world.
Feiteng Wang, Xiaoying Yue, Lin Wang, Huilin Li, Zhencai Du, Jing Ming, and Zhongqin Li
The Cryosphere, 14, 2597–2606, https://doi.org/10.5194/tc-14-2597-2020, https://doi.org/10.5194/tc-14-2597-2020, 2020
Short summary
Short summary
How to mitigate the melting of most mountainous glaciers is a disturbing issue for scientists and the public. We chose the Muz Taw Glacier of the Sawir Mountains as our study object. We carried out two artificial precipitation experiments on the glacier to study the role of precipitation in mitigating its melting. The average mass loss from the glacier decreased by over 14 %. We also propose a possible mechanism describing the role of precipitation in mitigating the melting of the glaciers.
Shuang Yi, Chunqiao Song, Kosuke Heki, Shichang Kang, Qiuyu Wang, and Le Chang
The Cryosphere, 14, 2267–2281, https://doi.org/10.5194/tc-14-2267-2020, https://doi.org/10.5194/tc-14-2267-2020, 2020
Short summary
Short summary
High-Asia glaciers have been observed to be retreating the fastest in the southeastern Tibeten Plateau, where vast amounts of glacier and snow feed the streamflow of the Brahmaputra. Here, we provide the first monthly glacier and snow mass balance during 2002–2017 based on satellite gravimetry. The results confirm previous long-term decreases but reveal strong seasonal variations. This work helps resolve previous divergent model estimates and underlines the importance of meltwater.
Michael Zemp, Matthias Huss, Nicolas Eckert, Emmanuel Thibert, Frank Paul, Samuel U. Nussbaumer, and Isabelle Gärtner-Roer
The Cryosphere, 14, 1043–1050, https://doi.org/10.5194/tc-14-1043-2020, https://doi.org/10.5194/tc-14-1043-2020, 2020
Short summary
Short summary
Comprehensive assessments of global glacier mass changes have been published at multi-annual intervals, typically in IPCC reports. For the years in between, we present an approach to infer timely but preliminary estimates of global-scale glacier mass changes from glaciological observations. These ad hoc estimates for 2017/18 indicate that annual glacier contributions to sea-level rise exceeded 1 mm sea-level equivalent, which corresponds to more than a quarter of the currently observed rise.
Wael Abdel Jaber, Helmut Rott, Dana Floricioiu, Jan Wuite, and Nuno Miranda
The Cryosphere, 13, 2511–2535, https://doi.org/10.5194/tc-13-2511-2019, https://doi.org/10.5194/tc-13-2511-2019, 2019
Short summary
Short summary
We use topographic maps from two radar remote-sensing missions to map surface elevation changes of the northern and southern Patagonian ice fields (NPI and SPI) for two epochs (2000–2012 and 2012–2016). We find a heterogeneous pattern of thinning within the ice fields and a varying temporal trend, which may be explained by complex interdependence between surface mass balance and effects of flow dynamics. The contribution to sea level rise amounts to 0.05 mm a−1 for both ice fields for 2000–2016.
Chunhai Xu, Zhongqin Li, Huilin Li, Feiteng Wang, and Ping Zhou
The Cryosphere, 13, 2361–2383, https://doi.org/10.5194/tc-13-2361-2019, https://doi.org/10.5194/tc-13-2361-2019, 2019
Short summary
Short summary
We take Urumqi Glacier No. 1 as an example and validate a long-range terrestrial laser scanner (TLS) as an efficient tool for monitoring annual and intra-annual mass balances, especially for inaccessible glacier areas where no glaciological measurements are available. The TLS has application potential for glacier mass-balance monitoring in China. For wide applications of the TLS, we can select some benchmark glaciers and use stable scan positions and in-situ-measured densities of snow–firn.
Ben M. Pelto, Brian Menounos, and Shawn J. Marshall
The Cryosphere, 13, 1709–1727, https://doi.org/10.5194/tc-13-1709-2019, https://doi.org/10.5194/tc-13-1709-2019, 2019
Short summary
Short summary
Changes in glacier mass are the direct response to meteorological conditions during the accumulation and melt seasons. We derived multi-year, seasonal mass balance from airborne laser scanning surveys and compared them to field measurements for six glaciers in the Columbia and Rocky Mountains, Canada. Our method can accurately measure seasonal changes in glacier mass and can be easily adapted to derive seasonal mass change for entire mountain ranges.
Daniel McGrath, Louis Sass, Shad O'Neel, Chris McNeil, Salvatore G. Candela, Emily H. Baker, and Hans-Peter Marshall
The Cryosphere, 12, 3617–3633, https://doi.org/10.5194/tc-12-3617-2018, https://doi.org/10.5194/tc-12-3617-2018, 2018
Short summary
Short summary
Measuring the amount and spatial pattern of snow on glaciers is essential for monitoring glacier mass balance and quantifying the water budget of glacierized basins. Using repeat radar surveys for 5 consecutive years, we found that the spatial pattern in snow distribution is stable over the majority of the glacier and scales with the glacier-wide average. Our findings support the use of sparse stake networks for effectively measuring interannual variability in winter balance on glaciers.
Caitlyn Florentine, Joel Harper, Daniel Fagre, Johnnie Moore, and Erich Peitzsch
The Cryosphere, 12, 2109–2122, https://doi.org/10.5194/tc-12-2109-2018, https://doi.org/10.5194/tc-12-2109-2018, 2018
Martina Barandun, Matthias Huss, Ryskul Usubaliev, Erlan Azisov, Etienne Berthier, Andreas Kääb, Tobias Bolch, and Martin Hoelzle
The Cryosphere, 12, 1899–1919, https://doi.org/10.5194/tc-12-1899-2018, https://doi.org/10.5194/tc-12-1899-2018, 2018
Short summary
Short summary
In this study, we used three independent methods (in situ measurements, comparison of digital elevation models and modelling) to reconstruct the mass change from 2000 to 2016 for three glaciers in the Tien Shan and Pamir. Snow lines observed on remote sensing images were used to improve conventional modelling by constraining a mass balance model. As a result, glacier mass changes for unmeasured years and glaciers can be better assessed. Substantial mass loss was confirmed for the three glaciers.
Helmut Rott, Wael Abdel Jaber, Jan Wuite, Stefan Scheiblauer, Dana Floricioiu, Jan Melchior van Wessem, Thomas Nagler, Nuno Miranda, and Michiel R. van den Broeke
The Cryosphere, 12, 1273–1291, https://doi.org/10.5194/tc-12-1273-2018, https://doi.org/10.5194/tc-12-1273-2018, 2018
Short summary
Short summary
We analysed volume change, mass balance and ice flow of glaciers draining into the Larsen A and Larsen B embayments on the Antarctic Peninsula for 2011 to 2013 and 2013 to 2016. The mass balance is based on elevation change measured by the radar satellite mission TanDEM-X and on the mass budget method. The glaciers show continuing losses in ice mass, which is a response to ice shelf break-up. After 2013 the downwasting of glaciers slowed down, coinciding with years of persistent sea ice cover.
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...
