On the contribution of grain boundary sliding type creep to firn densification – an assessment using an optimization approach


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Angelika.Humbert [ at ] awi.de

Abstract

Simulation approaches to firn densification often rely on the assumption that grain boundary sliding is the leading process driving the first stage of densification. Alley (1987) first developed a process-based material model of firn that describes this process. However, often so-called semi-empirical models are favored over the physical description of grain boundary sliding owing to their simplicity and the uncertainties regarding model parameters. In this study, we assessed the applicability of the grain boundary sliding model of Alley (1987) to firn using a numeric firn densification model and an optimization approach, for which we formulated variants of the constitutive relation of Alley (1987). An efficient model implementation based on an updated Lagrangian numerical scheme enabled us to perform a large number of simulations to test different model parameters and identify the simulation results that best reproduced 159 firn density profiles from Greenland and Antarctica. For most of the investigated locations, the simulated and measured firn density profiles were in good agreement. This result implies that the constitutive relation of Alley (1987) characterizes the first stage of firn densification well when suitable model parameters are used. An analysis of the parameters that result in the best agreement revealed a dependence on the mean surface mass balance. This finding may indicate that the load is insufficiently described, as the lateral components of the stress tensor are usually neglected in one-dimensional models of the firn column.



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Article
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Helmholtz Cross Cutting Activity (2021-2027)
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Peer-reviewed, Web of Science / Scopus
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Published
Eprint ID
55489
DOI 10.5194/tc-16-143-2022

Cite as
Schultz, T. , Müller, R. , Gross, D. and Humbert, A. (2022): On the contribution of grain boundary sliding type creep to firn densification – an assessment using an optimization approach , The Cryosphere, 16 , pp. 143-158 . doi: 10.5194/tc-16-143-2022


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