Glaciers in High Mountain Asia (Himalaya, Karakoram, Pamir…) represent the largest volume of ice outside the polar regions and are important components of the water resources for billions of people in the region (Pritchard et al., 2019). However, uncertainties about the glaciers contribution to the downstream flow are still large. This is partially due to the large uncertainties of high altitude precipitation, which are generally underestimated in the region (Immerzeel et al., 2015; Sakai et al. 2015). This project aims at reducing these uncertainties by estimating the flux of ice that is transported down valley by glaciers flow. Glaciers are natural reservoirs that collect the snow in altitude, which densifies into ice and flows, by gravity, to lower elevation where it melts. Following mass conservation, the flux of ice through any glacier cross-section is equal to the mass of ice accumulated (what we are looking for) and the glacier mass change above that section (Berthier & Vincent, 2012). The recent publication of remote-sensing observations of glacier mass balance (Brun et al., 2017), ice flow velocities (Dehecq et al., 2019) as well as modelled estimates of ice thickness for all glaciers in HMA (Farinotti et al., 2019) provide a unique opportunity to develop this methodology at regional scale. But uncertainties in each of these dataset are relatively large and it is necessary to test and validate the methodology.
References:
- Berthier, E. & Vincent, C. Relative contribution of surface mass-balance and ice-flux changes to the accelerated thinning of Mer de Glace, French Alps, over 1979–2008. Journal of Glaciology 58, 501–512 (2012).
- Brun, F., Berthier, E., Wagnon, P., Kääb, A. & Treichler, D. A spatially resolved estimate of High Mountain Asia glacier mass balances from 2000 to 2016. Nature Geoscience 10, 668–673 (2017).
- Dehecq, A. et al. Twenty-first century glacier slowdown driven by mass loss in High Mountain Asia. Nature Geoscience 12, 22 (2019).
- Farinotti, D. et al. A consensus estimate for the ice thickness distribution of all glaciers on Earth. Nature Geoscience (2019)
- Immerzeel, W. W., Wanders, N., Lutz, A. F., Shea, J. M. & Bierkens, M. F. P. Reconciling high-altitude precipitation in the upper Indus basin with glacier mass balances and runoff. Hydrology and Earth System Sciences; Katlenburg-Lindau 19, 4673–4687 (2015).
- Pritchard, H. D. Asia’s shrinking glaciers protect large populations from drought stress. Nature 569, 649–654 (2019).
- Sakai, A. et al. Climate regime of Asian glaciers revealed by GAMDAM glacier inventory. The Cryosphere 9, 865–880 (2015).
Glaciers in High Mountain Asia (Himalaya, Karakoram, Pamir…) represent the largest volume of ice outside the polar regions and are important components of the water resources for billions of people in the region (Pritchard et al., 2019). However, uncertainties about the glaciers contribution to the downstream flow are still large. This is partially due to the large uncertainties of high altitude precipitation, which are generally underestimated in the region (Immerzeel et al., 2015; Sakai et al. 2015). This project aims at reducing these uncertainties by estimating the flux of ice that is transported down valley by glaciers flow. Glaciers are natural reservoirs that collect the snow in altitude, which densifies into ice and flows, by gravity, to lower elevation where it melts. Following mass conservation, the flux of ice through any glacier cross-section is equal to the mass of ice accumulated (what we are looking for) and the glacier mass change above that section (Berthier & Vincent, 2012). The recent publication of remote-sensing observations of glacier mass balance (Brun et al., 2017), ice flow velocities (Dehecq et al., 2019) as well as modelled estimates of ice thickness for all glaciers in HMA (Farinotti et al., 2019) provide a unique opportunity to develop this methodology at regional scale. But uncertainties in each of these dataset are relatively large and it is necessary to test and validate the methodology.
References:
- Berthier, E. & Vincent, C. Relative contribution of surface mass-balance and ice-flux changes to the accelerated thinning of Mer de Glace, French Alps, over 1979–2008. Journal of Glaciology 58, 501–512 (2012).
- Brun, F., Berthier, E., Wagnon, P., Kääb, A. & Treichler, D. A spatially resolved estimate of High Mountain Asia glacier mass balances from 2000 to 2016. Nature Geoscience 10, 668–673 (2017).
- Dehecq, A. et al. Twenty-first century glacier slowdown driven by mass loss in High Mountain Asia. Nature Geoscience 12, 22 (2019).
- Farinotti, D. et al. A consensus estimate for the ice thickness distribution of all glaciers on Earth. Nature Geoscience (2019)
- Immerzeel, W. W., Wanders, N., Lutz, A. F., Shea, J. M. & Bierkens, M. F. P. Reconciling high-altitude precipitation in the upper Indus basin with glacier mass balances and runoff. Hydrology and Earth System Sciences; Katlenburg-Lindau 19, 4673–4687 (2015).
- Pritchard, H. D. Asia’s shrinking glaciers protect large populations from drought stress. Nature 569, 649–654 (2019).
- Sakai, A. et al. Climate regime of Asian glaciers revealed by GAMDAM glacier inventory. The Cryosphere 9, 865–880 (2015).
The project plan is in three steps:
1. Validate ice flow velocity fluctuations obtained from medium-resolution satellite data within the ITS LIVE (its-live.jpl.nasa.gov) project with high-resolution products and/or field measurements.
2. Write up a software to automatically extract glacier velocity fluctuations across cross-sections and analyse spatial correlation between these time series at the scale of 1-2 subregions of HMA.
3. Analyse the 20-year trends (1999-2018) in velocity fluctuations with regards to climate re-analysis of precipitations in HMA.
Requirements:
- Good programming skills, preferably Python in a Linux environment (Bash)
- Good physics and mathematics basics (flow mechanics, algebra…)
- Experience with Geographic Information Systems (for example QGIS) and/or remote-sensing are an advantage
The project plan is in three steps:
1. Validate ice flow velocity fluctuations obtained from medium-resolution satellite data within the ITS LIVE (its-live.jpl.nasa.gov) project with high-resolution products and/or field measurements.
2. Write up a software to automatically extract glacier velocity fluctuations across cross-sections and analyse spatial correlation between these time series at the scale of 1-2 subregions of HMA.
3. Analyse the 20-year trends (1999-2018) in velocity fluctuations with regards to climate re-analysis of precipitations in HMA.
Requirements:
- Good programming skills, preferably Python in a Linux environment (Bash)
- Good physics and mathematics basics (flow mechanics, algebra…)
- Experience with Geographic Information Systems (for example QGIS) and/or remote-sensing are an advantage
For further information please contact Dr. Amaury Dehecq (adehecq@vaw.baug.ethz.ch).
For further information please contact Dr. Amaury Dehecq (adehecq@vaw.baug.ethz.ch).