Past, present and future response of Russian glaciers to climate forcing


The melting of mountain glaciers and ice caps contributed around 27 ± 11 mm to global mean sea level rise between 1961 and 2016 (Zemp et al., 2019). It is therefore important to monitor and quantify global patterns of ice loss in order to accurately predict future sea levels. Changes in mountain glaciers also have important implications for surface hydrology, most notably in terms of changes in runoff from glacier catchments, and changes in glacial lakes, which pose a serious hazard in some regions. One country where these issues are particularly acute is Russia (e.g. Shahgedanova et al., 2009; Hagg et al., 2010; Petrakov et al., 2012), which hosts thousands of glaciers, covering tens of thousands of kilometres squared, and spanning a wide range of latitudes and longitudes.

Russian glaciers have, in general, retreated and thinned over the last few decades, in response to global warming (e.g. Solomina, 2000; Gurney et al., 2008; Stokes et al., 2013; Carr et al., 2014). Those in High Arctic regions (e.g. Novaya Zemyla) have been subjected to amplified warming and have experienced more negative mass balances (Moholdt et al., 2012; Zemp et al., 2019). However, several regions lack an up-to-date assessment of glacier change, especially since their most recent maximum during the Little Ice Age (Solomina, 2000). Consequently, there remain some uncertainties over the timing of the LIA maximum and subsequent glacier retreat in different regions across Russia. This limits our capacity to put observed contemporary changes into a longer-term context. It is also uncertain how long-term glacier retreat relates to climatic change and to the substantial climatic gradients present across Russia (e.g. to what extent are drier ‘continental’ glaciers more/less sensitive than those with higher precipitation?)

In addition, some recent work suggests that debris cover and glacial lakes may be increasing as Russian glaciers retreat (e.g. Stokes et al., 2007; Petrakov et al., 2012; Tielidze et al., 2020; Shugar et al., 2020; see Figure 1), although it is unclear whether this pattern is seen in all regions. The growth of proglacial lakes has been identified as an important control on ice loss and glacier response to climate. These lakes can enhance ice loss via a number of mechanisms, including calving, undercutting of the terminus and subaqueous melting. They also represent a serious hazard and several glacial lake outburst events have been documented (e.g. Petrakov et al., 2012). This is likely to be a growing issue, as climate warms and lakes grow, but the impact of proglacial lakes on the retreat of Russian glaciers has yet to be systematically investigated. The overall aim of this project is to investigate glacier retreat in a number of contrasting regions of Russia spanning climatic gradients and examine their post-LIA response to climate change. This will be achieved through the following objectives:
1. Use satellite remote sensing to map recent glacier retreat (post-1970s) from a number of different regions in Russia, including glacier area, supraglacial debris and glacial lakes.
2. Use satellite remote sensing and historical imagery/data sources to reconstruct and map the Little Ice Age limit. This objective may be supplemented by fieldwork in key areas to establish the timing of the LIA (e.g. using lichenometry: see Leigh et al., 2020).
3. Compare spatial and temporal patterns in post-LIA retreat to climate data (and ground-based measurements of mass balance, e.g. Verhaegen et al., 2020) to ascertain the key drivers of past and future change
4. Dependent on student interests and skills, it may be possible to incorporate a modelling component to examine future glacier changes (e.g. Verhaegen et al., 2020) and/or explore glacier extent at earlier times (e.g. prior to or during the Last Glacial Maximum) through mapping and dating of glacial geomorphology (Margold & Jansson, 2011).


The project is likely to use a combination of remote sensing and fieldwork, with numerical modelling an option, depending on student skills and interests.

Objective 1 will be addressed through a combination of pre-existing glacier inventories (e.g. Tielidze & Wheate, 2018) and mapping from multiple remotely sensed data sources: aerial photos/declassified satellite photographs (e.g. Corona and Hexagon) from the 1960s and 1970s; and optical satellite imagery (e.g. Landsat and Sentinel) from the 1970s onwards. Proglacial lake extent will be determined from satellite and aerial imagery, using semi-automated classifications (e.g. NDWI). To address objective 2, the Little Ice Age extent will initially be determined from remotely sensed data (e.g. moraine/vegetation ‘trimline’ mapping on high resolution satellite imagery). In some locations, results may be verified and augmented using field data, including GPS mapping of key ice limits and lichenometry to estimate age relationships (e.g. Leigh et al., 2020). Where available, results will be evaluated in relation to paleoclimate proxies and meteorological records from historical sources. Objective 3 will require the acquisition and analysis of climate data from both meterological stations and climate reanalysis data. There may also be the opportunity to use numerical modelling (e.g. Verhaegen et al. 2020) to investigate the sensitivity of Russian ice masses to climatic forcing (Objective 4) and/or use satellite imagery to map the glacial geomorphology (e.g. moraine limits) of older glacier limits (e.g. Margold and Jansson, 2011).

Project Timeline

Year 1

Training in Remote Sensing and GIS; review of relevant literature and existing glacier inventories; selection of study areas; collection and analysis of remote sensing datasets; attendance at relevant training workshops and summer schools; national conference attendance

Year 2

Mapping of recent glacier retreat and LIA limits from study areas; preparation of manuscript(s); possible fieldwork and analysis of field data; preparation of manuscript; conference attendance

Year 3

Completion of data processing and integration of field data; preparation of manuscripts on key study areas; possible fieldwork; optional numerical modelling and/or further mapping of glacial geomorphology; international conference attendance

Year 3.5

Submission of further research papers; further modelling (if required); international conference attendance; compilation and submission of thesis

& Skills

The student will receive both generic and bespoke training in Remote Sensing and GIS, including software such as QGIS and ArcGIS (where required). They will be trained in field data collection techniques, such as lichenometry and the use of a differential GPS. The student will be given training in interpreting glacier extent from geomorphological data. If required, numerical modelling skills will be provided via formal training workshops and an internationally-recognised summer school in Karthaus. Broader transferable skills (e.g. communicating science, media engagement, thesis writing, writing for publication, presentation skills) will be developed through various training events at Durham University offered by IAPETUS2. We anticipate this project will be completed as a series of publications/papers led by the student, under the guidance and supervision of the supervisors.

References & further reading

Carr, J.R., Stokes, C.R. and Vieli, A. (2014) Recent retreat of major outlet glaciers on Novaya Zemlya, Russian Arctic, influenced by fjord geometry and sea-ice conditions. Journal of Glaciology, 60 (219), 155-170.
Gurney, S.D., Popovnin, V.V., Shahgedanova, M. & Stokes, C.R. (2008) A glacier inventory for the Buordakh Massif, Cherskiy Range, Northeast Siberia, and evidence for recent glacier recession. Arctic, Antarctic and Alpine Research, 20, 81-88.
Hagg, W., Shahgedanova, M., Mayer, C, Lambrecht, A. and Popovnin, V. (2010) A sensitivity study of water availability in the Northern Caucasus based on climate projections. Global and Planetary Change, 73, 161-171.
Leigh, J.R., Stokes, C.R., Evans, D.J.A., Carr, J.R. and Andreassen, L.M. (2020) Timing of ‘Little Ice Age’ maxima and subsequent glacier retreat in northern Troms and western Finnmark, northern Norway. Arctic, Antarctic and Alpine Research, 52 (1), 281-311.
Margold, M. & Jansson, K.N. (2011) Glacial geomorphology and glacial lakes of central Transbaikalia, Siberia. Journal of Maps, 2011, 18-30.
Moholdt, G., Wouters, B. & Gardner, A.S. (2012) Recent mass changes of glaciers in the Russian High Arctic. Geophys. Res. Lett., 39, L10502.
Petrakov, D.A. et al. (2012) Monitoring of Bashkara Glacier lakes (Central Caucasus, Russia) and modelling their potential outburst. Nat. Hazards, 61, 1293-1316.
Solomina, O.N. (2000). Retreat of mountain glaciers of northern Eurasia since the Little Ice Age maximum. Ann. Glaciol., 31, 26–30.
Shahgedanova, M., Hagg, W., Hassell, D., Stokes, C.R. & Popovnin, V. (2009) Climate change, glacier retreat, and water availability in the Caucasus region. In, Jones, J.A.A., Vardanian, T.G. and Hakopian, C. (Eds) Threats to Global Water Security. NATO Science for Peace and Security Series C – Environmental Security, Springer, Netherlands, p. 131-143.
Shugar, D.H. et al. (2020) Rapid worldwide growth of glacial lakes since 1990. Nature Climate Change, 10, 939-945.
Stokes, C.R., Popovnin, V., Aleynikov, A., Gurney, S.D. & Shahgedanova, M. (2007) Recent glacier retreat in the Caucasus Mountains, Russia, and associated increase in supraglacial debris cover and supra-/proglacial lake development. Ann. Glaciol., 46, 195-203.
Stokes, C.R., Shahgedanova, M., Evans, I.S. and Popovnin, V.V. (2013) Accelerated loss of alpine glaciers in the Kodar Mountains, south-eastern Siberia. Global and Planetary Change, 101, 82-95.
Tielidze, L.G. and Wheate, R.D. (2018) The Greater Caucasus Glacier Inventory (Russia, Georgia and Azerbaijan), The Cryosphere, 12, 81–94.
Tielidze, L.G. et al. (2020) Supra-glacial debris cover changes in the Greater Caucasus from 1986 to 2014. The Cryosphere, 14, 585–598.
Verhaegen, Y., Huybrechts, P., Rybak, O., and Popovnin, V. V. (2020) Modelling the evolution of Djankuat Glacier, North Caucasus, from 1752 until 2100 CE. The Cryosphere, 14, 4039–4061

Further Information

Professor Chris R. Stokes
Durham University
Tel. 0191 334 1955

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