Numerical modelling of historical front variations and the 21st-century evolution of glacier AX010, Nepal Himalaya

Abstract

Due to the lack of measurements of ice velocity, mass balance, glacier geometry and other baseline data, model-based studies of glacial systems in the Nepal Himalaya are very limited. Here a numerical ice-flow model has been developed for glacier AX010 in order to study its relation to local climate and investigate the possible causes of its general retreat since the end of the Little Ice Age. First, an attempt is made to simulate the historical front variations, considering each climatic parameter separately. Good agreement between the observations and model projections can be obtained under the assumption that variations in glacier front position are a response to changes in temperature alone. The same assumption is made about future changes to explore the 21st-century evolution of the glacier. Under a no-change scenario, the glacier will retreat by another ∽600m by AD 2100, whereas it is projected to vanish completely during this century for all trends with a temperature rise larger than +2.5˚C by AD 2100 with respect to the 1980–99 mean. With constant precipitation at the 1980–99 mean, the model predicts that the glacier will cease to exist at AD 2083, 2056 or 2049 if the temperature rises linearly by 3˚C, 4.5˚C or 6˚C respectively by the end of this century. With an additional range of precipitation changes between –30% and +30%, the life expectancy of glacier AX010 varies by 18, 6 and 2 years for the respective temperature rises. Thus the role of precipitation becomes minimal for the higher trends of temperature rise.

Relative effect of slope and equilibrium line altitude on the retreat of Himalayan glaciers

“…Among them, Adhikari and Huybrechts (2009), used a simple model to simulate the variation of glacier AX010, and study scenarios for its future evolution. This simple model, based on a formulation due to Oerlemans (1988), seems to be quite effective in simulating observed data over the past fifty years.…”

Influence of high-order mechanics on simulation of glacier response to climate change: insights from Haig Glacier, Canadian Rocky Mountains

“…In this research, we test this hypothesis for a small valley glacier typical of the Canadian Rocky Mountains (Haig Glacier). Because climatic responses of many glaciers have been explored using reduced models (e.g., Oerlemans et al, 1998;De Smedt and Pattyn, 2003;Flowers et al, 2005;Adhikari and Huybrechts, 2009;Aðalgeirsdóttir et al, 2011), this study provides an idea of the glaciological uncertainties associated with such simulations.…”

“…Reasonable understanding of the dynamical response of glaciers to climate forcing requires proper coupling of, at least, a mass balance model (e.g., Jóhannesson et al, 1995;Rye et al, 2010) and an ice flow model (e.g., Hutter, 1983;Blatter, 1995;Pattyn, 2003;Zwinger et al, 2007). Such an approach of model coupling is necessary to reconstruct the past and predict the future behavior of glaciers (e.g., Oerlemans et al, 1998;Schneeberger et al, 2001;Flowers et al, 2005;Adhikari and Huybrechts, 2009). For a given geometric and climatic setting, the fidelity of such reconstructions and/or predictions of a glacier's behavior depends on how accurately the mass balance model is parameterized and to what extent the ice flow model represents actual glacier dynamics.…”

Modelling Dynamics of Valley Glaciers

“…Calov & Hutter, 1996;Huybrechts & Oerlemans, 1988), as well as valley glaciers (e.g. Adhikari & Huybrechts, 2009;Oerlemans et al, 1998). In general, ice sheet models need to thermomechanically coupled, since the polar ice sheets span a range of temperature from the melting point to ca.…”

“…Depending upon the availability of field data, this is usually accomplished through simulations of the ice surface velocities and/or historical front variations (e.g. Adhikari & Huybrechts, 2009). As we have considered synthetic glaciers, we take advantage to assume that the FS dynamics represents a real-world scenario and we constrain the reduced models accordingly.…”