EGU General Assembly 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Dynamics and drivers of High Mountain Asia’s glacier change from the mid 1980s to late 2019

David Loibl1, Georgy Ayzel2, Fiona Clubb3, Inge Grünberg4, and Jan Nitzbon1,4,5
David Loibl et al.
  • 1Climate Geography, Humbuldt-Universität zu Berlin, Berlin, Germany (
  • 2Hydrology and Climatology, Potsdam University, Potsdam, Germany (
  • 3Department of Geography, Durham University, Durham, United Kingdom (
  • 4Permafrost Research Group, AWI Potsdam, Potsdam, Germany (
  • 5Department of Geosciences, University of Oslo, Norway (

For only two out of more than 95 * 10³ glaciers in High Mountain Asia (HMA) a continuous time series of mass balance measurements covering more than 30 years (World Glacier Monitoring Service’s ‘reference glaciers’) is available to date. Considering that both glaciers are located in the Tian Shan Range, i.e. the northernmost part of HMA, and that glacier changes in HMA is known to be heterogeneous in space and time, it is clear that a substantial knowledge gap exists regarding the actual dynamics at individual glaciers and their forcing. 

Here, we present a novel data set of transient snowline altitude (TSLA) measurements covering all glaciers > 0.5 km² in HMA (n=28,501) for a time frame from the mid 1980s to late 2019 based on more than 10⁵ Landsat satellite images, allowing for investigations of the characteristics of glacier change at unprecedented spatio-temporal resolution and coverage.

Individual glacier’s total maxima of end-of-season TSLAs for the whole period of observation clearly highlight years with many (i.e. 1994, 2009, 2013, 2015) and few (i.e. 1995, 2003, 2012) maxima. Out of the glaciers that show a significant trend throughout the observation period, 90.8% have a positive trend with a median TSLA rise of 7.0 m/year. These figures increase to 95.8% and 13.8 m/year, when only observations of the last two decades are considered.

Based on ERA5 meteorological time series and fundamental physiographic glacier characteristics from the Randolph Glacier Inventory v6, we investigated drivers of the observed TSLA fluctuations. Consistent with expectations, a Random Forest analysis finds temperature to be the dominant meteorological driver of TSLA dynamics throughout all regions of HMA when whole years are considered. Conversely, meteorological forcing regimes are highly heterogeneous for different glaciers in the ablation phase, with wind, air temperature and incoming shortwave radiation being the dominant TSLA drivers for the majority of glaciers in HMA. Considering regional domains, TSLA dynamics are considerably determined by physiographic factors, such as latitude, longitude, hypsographic characteristics, slope and aspect of individual glaciers. A hierarchical clustering analysis shows distinct groups of similar forcing setups exist; Their spatial distribution, however, rather follows specific positions in the topoclimatic system than forming distinct regional clusters or aligning to large-scale gradients.

In summary, our findings indicate that spatial and temporal patterns of glacier change in HMA are considerably more complex than currently known. Multidecadal high-resolution TSLA datasets like the one presented here may inform future research to disentangle the complex topoclimatic process-response systems that control the adaptation of individual glaciers to climate change.

How to cite: Loibl, D., Ayzel, G., Clubb, F., Grünberg, I., and Nitzbon, J.: Dynamics and drivers of High Mountain Asia’s glacier change from the mid 1980s to late 2019, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-15516,, 2020


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