Modelling Dynamics of Valley Glaciers

Adhikari, Surendra; Marshall, Shawn J.

doi:10.5772/35474

Cited by 8 publications

(14 citation statements)

References 92 publications

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“…In contrast to the Stokes model employed here, Bahr et al [1997] consider the shallow ice approximation (SIA). Because SIA mechanics generally predict thinner ice (i.e., less volume) in valley glaciers compared to Stokes models [e.g., Adhikari and Marshall , 2012], V in the latter case scales more strongly with A , giving a larger γ. From an ice dynamics point of view, we therefore argue that the match between γ = 1.375 (SIA, steady state [ Bahr et al , 1997]) and γ = 1.357 (real glaciers, transient states [ Chen and Ohmura , 1990]) is partly coincidence, a result of offsetting biases.…”

Section: V‐a Relation In Steady Statesmentioning

confidence: 99%

“…We posit that appropriate class‐specific values of V ‐ A scaling parameters can be introduced based on minimal and readily‐available information about glacier morphology. We derive these parameters through examination of V ‐ A relations with a finite‐element, Stokes model of glacier dynamics [ Adhikari and Marshall , 2012] under different physiographic conditions, including the effects of glacier disequilibrium. This study is an extension of the flowline modeling analysis of Radić et al [2007], using a high‐order 3D flow model and with a comprehensive examination of different glaciological conditions.…”

Section: Introductionmentioning

confidence: 99%

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Glacier volume‐area relation for high‐order mechanics and transient glacier states

Adhikari

Marshall

2012

Geophysical Research Letters

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[1] Glacier volume is known for less than 0.1% of the world's glaciers, but this information is needed to quantify the impacts of glacier changes on global sea level and regional water resources. Observations indicate a power-law relation between glacier area and volume, with an exponent g ≈ 1.36. Through numerical simulations of 3D, high-order glacier mechanics, we demonstrate how different topographic and climatic settings, glacier flow dynamics, and the degree of disequilibrium with climate systematically affect the volumearea relation. We recommend more accurate scaling relations through characterization of individual glacier shape, slope and size. An ensemble of 280 randomly-generated valley glaciers spanning a spectrum of plausible glaciological conditions yields a steady-state exponent g = 1.46. This declines to 1.38 for glaciers that are 100 years into a sustained retreat, which corresponds exceptionally well with the observed value for present-day glaciers.

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Section: V‐a Relation In Steady Statesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Glacier volume‐area relation for high‐order mechanics and transient glacier states

Adhikari

Marshall

2012

Geophysical Research Letters

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“…For the purpose of parameterizing the effects of lateral drag, we consider a 3-D Stokes model and a flowline model such that τ lat is the only dynamical discrepancy between them. Mathematical details of a number of different reduced models are presented by Adhikari and Marshall (2012); below we provide a brief summary of the models applied here.…”

Section: Governing Equationsmentioning

confidence: 99%

Parameterization of lateral drag in flowline models of glacier dynamics

Adhikari¹,

Marshall²

2012

J. Glaciol.

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Given the cross-sectional geometry of a valley glacier, effects of lateral drag can be parameterized in flowline models through the introduction of Nye shape factors. Lateral drag also arises due to lateral variability in bed topography and basal flow, which induce horizontal shear stress and differential ice motion. For glaciers with various geometric and basal conditions, we compare three-dimensional Stokes solutions to flowline model solutions to examine both sources of lateral drag. We calculate associated correction factors that help flowline models to capture the effects of lateraldrag. Such parameterizations provide improved simulations of the dynamics of narrow, channelized, fast-flowing glacial systems. We present an example application for Athabasca Glacier in the Canadian Rocky Mountains.

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“…5), these models provide an intuitive tool for studying the mechanics of glaciers. Below we briefly introduce them; see and Adhikari and Marshall (2012) for mathematical details.…”

Section: Diagnostic Model Classificationmentioning

confidence: 99%

“…Based on the notion that glacier movement is controlled by a balance between the gravitational driving stress and several resistances (Whillans, 1987;van der Veen, 1999), we consider a hierarchy of models for ice deformation, ranging from a simple shear-deformational model to a comprehensive Stokes flow model Adhikari and Marshall, 2012). For Haig Glacier, we couple each of these 3-D models with a mass balance model, which is constructed from observations during the period of 2001 to 2012, and simulate these in a finite element suite of Elmer/Ice software (http://elmerice.elmerfem.org; Zwinger et al, 2007;Gagliardini and Zwinger, 2008).…”

Section: Introductionmentioning

confidence: 99%

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

Adhikari

Marshall

2013

The Cryosphere

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Abstract. Evolution of glaciers in response to climate change has mostly been simulated using simplified dynamical models. Because these models do not account for the influence of high-order physics, corresponding results may exhibit some biases. For Haig Glacier in the Canadian Rocky Mountains, we test this hypothesis by comparing simulation results obtained from 3-D numerical models that deal with different assumptions concerning physics, ranging from simple shear deformation to comprehensive Stokes flow. In glacier retreat scenarios, we find a minimal role of highorder mechanics in glacier evolution, as geometric effects at our site (the presence of an overdeepened bed) result in limited horizontal movement of ice (flow speed on the order of a few meters per year). Consequently, high-order and reduced models all predict that Haig Glacier ceases to exist by ca. 2080 under ongoing climate warming. The influence of high-order mechanics is evident, however, in glacier advance scenarios, where ice speeds are greater and ice dynamical effects become more important. Although similar studies on other glaciers are essential to generalize such findings, we advise that high-order mechanics are important and therefore should be considered while modeling the evolution of active glaciers. Reduced model predictions may be adequate for other glaciologic and topographic settings, particularly where flow speeds are low and where mass balance changes dominate over ice dynamics in determining glacier geometry.

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Modelling Dynamics of Valley Glaciers

Cited by 8 publications

References 92 publications

Glacier volume‐area relation for high‐order mechanics and transient glacier states

Glacier volume‐area relation for high‐order mechanics and transient glacier states

Parameterization of lateral drag in flowline models of glacier dynamics

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

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