Abstract

Abstract. Time-dependent simulations of ice sheets require two equations to be solved: the mass transport equation, derived from the conservation of mass, and the stress balance equation, derived from the conservation of momentum. The mass transport equation controls the advection of ice from the interior of the ice sheet towards its periphery, thereby changing its geometry. Because it is based on an advection equation, a stabilization scheme needs to be employed when solved using the finite-element method. Several stabilization schemes exist in the finite-element method framework, but their respective accuracy and robustness have not yet been systematically assessed for glaciological applications. Here, we compare classical schemes used in the context of the finite-element method: (i) artificial diffusion, (ii) streamline upwinding, (iii) streamline upwind Petrov–Galerkin, (iv) discontinuous Galerkin, and (v) flux-corrected transport. We also look at the stress balance equation, which is responsible for computing the ice velocity that “advects” the ice downstream. To improve the velocity computation accuracy, the ice-sheet modeling community employs several sub-element parameterizations of physical processes at the grounding line, the point where the grounded ice starts to float onto the ocean. Here, we introduce a new sub-element parameterization for the driving stress, the force that drives the ice-sheet flow. We analyze the response of each stabilization scheme by running transient simulations forced by ice-shelf basal melt. The simulations are based on an idealized ice-sheet geometry for which there is no influence of bedrock topography. We also perform transient simulations of the Amundsen Sea Embayment, West Antarctica, where real bedrock and surface elevations are employed. In both idealized and real ice-sheet experiments, stabilization schemes based on artificial diffusion lead systematically to a bias towards more mass loss in comparison to the other schemes and therefore should be avoided or employed with a sufficiently high mesh resolution in the vicinity of the grounding line. We also run diagnostic simulations to assess the accuracy of the driving stress parameterization, which, in combination with an adequate parameterization for basal stress, provides improved numerical convergence in ice speed computations and more accurate results.

Highlights

  • Numerical modeling is routinely used to understand the past and future behavior of the ice sheets in response to the evolution of the climate (e.g., Ritz et al, 2015; DeConto and Pollard, 2016; Aschwanden et al, 2019; Goelzer et al, 2020; Seroussi et al, 2020)

  • The reference model is based on a triangular structured conforming mesh with resolution of 50 m

  • Considering the entire Amundsen Sea Embayment (ASE) domain, in simulations forced by a low melt rate, the model running with artificial diffusion overestimates by 10 % the VAF loss in comparison to the one employing streamline upwind Petrov– Galerkin (SUPG) (Fig. 17)

Read more

Summary

Introduction

Numerical modeling is routinely used to understand the past and future behavior of the ice sheets in response to the evolution of the climate (e.g., Ritz et al, 2015; DeConto and Pollard, 2016; Aschwanden et al, 2019; Goelzer et al, 2020; Seroussi et al, 2020). This velocity field is used to “advect” the ice mass over time These governing equations are often solved using numerical methods such as the finite-element method (FEM), widely employed in the ice-sheet modeling community (e.g., Larour et al, 2012; Gagliardini et al, 2013; Gudmundsson, 2020). To the best of our knowledge, only studies based on finite-volume and finite-difference methods use driving stress parameterizations (Cornford et al, 2013; Feldmann et al, 2014) In this context, the present paper aims to (i) assess the response of different stabilization schemes in transient simulations subject to ice-shelf basal melt and changes in basal friction, and (ii) develop and assess a sub-element parame-.

Mass transport equation
Artificial diffusion and streamline upwinding
Streamline upwind Petrov–Galerkin
Discontinuous Galerkin
Flux-corrected transport
Time discretization of the mass transport equation
Sub-element parameterization of driving stress
MISMIP3d – numerical setup
Amundsen Sea Embayment – numerical setup
MISMIP3d – diagnostic analysis
MISMIP3d – prognostic analysis
No external forcing experiment
Basal melt experiment
Friction perturbation experiment
Amundsen Sea Embayment – prognostic analysis
Discussion
Final remarks
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call