Implementation and Initial Evaluation of the Glimmer Community Ice Sheet Model in the Community Earth System Model

Abstract

The Glimmer Community Ice Sheet Model (Glimmer-CISM) has been implemented in the Community Earth System Model (CESM). Glimmer-CISM is forced by a surface mass balance (SMB) computed in multiple elevation classes in the CESM land model and downscaled to the ice sheet grid. Ice sheet evolution is governed by the shallow-ice approximation with thermomechanical coupling and basal sliding. This paper describes and evaluates the initial model implementation for the Greenland Ice Sheet (GIS). The ice sheet model was spun up using the SMB from a coupled CESM simulation with preindustrial forcing. The model's sensitivity to three key ice sheet parameters was explored by running an ensemble of 100 GIS simulations to quasi equilibrium and ranking each simulation based on multiple diagnostics. With reasonable parameter choices, the steady-state GIS geometry is broadly consistent with observations. The simulated ice sheet is too thick and extensive, however, in some marginal regions where the SMB is anomalously positive. The topranking simulations were continued using surface forcing from CESM simulations of the twentieth century and twenty-first century (2005-2100, with RCP8.5 forcing). In these simulations the GIS loses mass, with a resulting global-mean sea level rise of 16 mm during 1850-2005 and 60 mm during 2005-2100. This mass loss is caused mainly by increased ablation near the ice sheet margin, offset by reduced ice discharge to the ocean. Projected sea level rise is sensitive to the initial geometry, showing the importance of realistic geometry in the spun-up ice sheet.

Parameterization of basal friction near grounding lines in a one-dimensional ice sheet model

“…We plan to incorporate our parameterization in the Community Ice Sheet Model (CISM), a three-dimensional model with support for a variety of higher-order stress approximations, several types of grids, and coupling to global climate models (Rutt et al, 2009;Perego et al, 2012;Lipscomb et al, 2013). A key challenge is to choose realistic values of p. One approach would be to invert for p using present-day data and obtain a map of p. From this map we could derive average values of p for specific regions or for the entire Antarctic ice sheet.…”

The initial errors that induce a significant “spring predictability barrier” for El Niño events and their implications for target observation: results from an earth system model

“…Further details on the ocean component can be found in Smith et al (2010). The CAM4 and POP2 are coupled through the version 7 coupler (CPL7) (Craig et al 2012) together with the Community Land Model version 4.0 (CLM4) (Oleson et al 2010), the Los Alamos sea ice model, referred to as the Community Ice CodE version 4.0 (CICE4) (Hunke and Lipscomb 2008), and a dynamic ice sheet model known as Glimmer-CISM (Rutt et al 2009;Lipscomb et al 2013). More details of the CESM model configuration and its simulation of the climate system are given in Hurrell et al (2013).…”

<i>Albany/FELIX</i>: a parallel, scalable and robust, finite element, first-order Stokes approximation ice sheet solver built for advanced analysis

“…Since the AR4, increased support from United States, United Kingdom, and European Union funding agencies has enabled concerted efforts towards improving the representation of ice dynamics in ice sheet models and towards their coupling to other components of Earth system models (ESMs) (Little, 2007;Lipscomb et al, 2008;van der Veen et al, 2010). Thanks to this support, there has recently been tremendous progress in the development of "next generation" community-supported ice sheet models (e.g., Bueler and Brown, 2009;Rutt et al, 2009;Gagliardini et al, 2013;Brinkerhoff and Johnson, 2013;Lipscomb et al, 2013) able to perform realistic, highresolution, continental-scale simulations. These models run on massively parallel high-performance computing (HPC)…”