The GRISLI ice sheet model (version 2.0): calibration and validation for multi-millennial changes of the Antarctic ice sheet

Quiquet, Aurélien; Dumas, Christophe; Ritz, Catherine; Peyaud, Vincent; Roche, Didier M.

doi:10.5194/gmd-2018-105

Cited by 6 publications

(8 citation statements)

References 52 publications

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“…This is likely due in large part to the use of a spatially constant value for ice-shelf basal mass balance, but also reflects the simple approach used to represent β. Nonetheless, the results are quite consistent with other models (e.g., Martin et al, 2011;Quiquet et al, 2018;Seroussi et al, 2019).…”

Section: Model Validation and Benchmarkssupporting

confidence: 91%

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Description and validation of the ice-sheet model Yelmo (version 1.0)

Robinson¹,

Álvarez-Solas²,

Montoya³

et al. 2019

Preprint

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Abstract. We describe the physics and features of the ice-sheet model Yelmo, an open-source project intended for collaborative development. Yelmo is a thermomechanical model, solving for the coupled velocity and temperature solutions of an ice sheet simultaneously. The ice dynamics are currently treated via a "hybrid" approach combining the shallow-ice and shallow-shelf/shelfy-stream approximations, which makes Yelmo an apt choice for studying a wide variety of problems. Yelmo's main innovations lie in its flexible and user-friendly infrastructure, which promotes portability and facilitates long-term development. In particular, all physics subroutines have been designed to be self-contained, so that they can be easily ported from Yelmo to other models, or easily replaced by improved or alternate methods in the future. Furthermore, hard-coded model choices are eschewed, replaced instead with convenient parameter options that allow the model to be adapted easily to different contexts. We show results for different ice-sheet benchmark tests, and we illustrate Yelmo's performance for the Antarctic ice sheet.

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Section: Model Validation and Benchmarkssupporting

confidence: 91%

“…(u b ) has units of [yr m −1 ] and the coefficient c b has units of [Pa], which helps to facilitate its physical interpretation.Most commonly, β is defined using a linear (e.g Quiquet et al, 2018),. power-law (e.g.…”

mentioning

confidence: 99%

Description and validation of the ice-sheet model Yelmo (version 1.0)

Robinson¹,

Álvarez-Solas²,

Montoya³

et al. 2019

Preprint

Self Cite

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“…consists in the superposition of the shallow-ice approximation (SIA) velocities for ice flow due to vertical shearing and the shallow-shelf approximation (SSA) velocities, used as a sliding law (Bueler and Brown, 2009). For the initMIP-Antarctica experiments, we used the GRISLI version 2.0 (Quiquet et al, 2018) which includes the analytical formulation of Schoof (2007) to compute the flux at the grounding line. Basal drag is computed with a power-law basal friction (Weertman, 1957).…”

Section: Lsce_grislimentioning

confidence: 99%

initMIP-Antarctica: An ice sheet model initialization experiment of ISMIP6

Seroussi¹,

Nowicki²,

Simon³

et al. 2019

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Abstract. Ice sheet numerical modeling is the best approach to estimate the dynamic contribution of Antarctica to sea level rise over the coming centuries. The influence of initial conditions on ice sheet model simulations, however, is still unclear. To better understand this influence, an initial state intercomparison exercise (initMIP) has been developed to compare, evaluate, and improve initialization procedures and estimate their impact on century-scale simulations. initMIP is the first set of experiments of the Ice Sheet Model Intercomparison Project for CMIP6 (ISMIP6), which is the primary Coupled Model Intercomparison Project Phase 6 (CMIP6) activity focusing on the Greenland and Antarctic Ice Sheets. Following initMIP-Greenland, initMIP-Antarctica has been designed to explore uncertainties associated with model initialization and spin-up and to evaluate the impact of changes in external forcings. Starting from the state of the Antarctic ice sheet at the end of the initialization procedure, three forward experiments are each run for 100 years: a control run, a run with a surface mass balance (SMB) anomaly, and a run with a basal melting anomaly beneath floating ice. This study presents the results of initMIP-Antarctica from 25 simulations performed by 16 international modeling groups. The submitted results use different initial conditions and initialization methods, as well as ice flow model parameters and reference external forcings. We find a good agreement among model responses to the SMB anomaly, but large variations in responses to the basal melting anomaly. These variations can be attributed to differences in the extent of ice shelves and their upstream tributaries, the numerical treatment of grounding line, as well as the initial ocean conditions applied, suggesting that ongoing efforts to better represent ice shelves in continental-scale models should continue.

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“…In the version used here, over the whole domain, the velocity field consists in the superposition of the shallow-ice approximation (SIA) velocities for ice flow due to vertical shearing and the shallow-shelf approximation (SSA) velocities, used as a sliding law (Bueler and Brown, 2009). For the LARMIP experiments, we used the GRISLI version 2.0 (Quiquet et al, 2018) which includes the analytical formulation of (Schoof, 2007) to compute the flux at the grounding line. Basal drag is computed with a power-law basal friction 30 (Weertman, 1957).…”

Section: A5 Gris-lsc: Grenoble Ice Sheet and Land Ice (Grisli)mentioning

confidence: 99%

Projecting Antarctica's contribution to future sea level rise from basal ice-shelf melt using linear response functions of 16 ice sheet models (LARMIP-2)

Levermann¹

2019

Preprint

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Abstract. The sea level contribution of the Antarctic ice sheet constitutes a large uncertainty in future sea level projections. Here we apply a linear response theory approach to 16 state-of-the-art ice sheet models to estimate the Antarctic ice sheet contribution from basal ice shelf melting within the 21st century. The purpose of this computation is to estimate the uncertainty that arises from large uncertainty in the external forcing that future warming may exert onto the ice sheet. While ice shelf melting is considered to be a major if not the largest perturbation of the ice sheet's flow into the ocean, the approach is neglecting a number of processes such as surface mass balance related contributions and mechanisms. In assuming linear response theory, we are able to capture complex temporal responses of the ice sheets, but we neglect any dampening or self-amplifying processes. This is particularly relevant in situations where an instability is dominating the ice loss. Results obtained here are thus relevant in particular wherever the ice loss is dominated by the forcing as opposed to an internal instability, for example in strong warming scenarios. In order to allow for comparison the methodology was chosen to be exactly the same as in an earlier study (Levermann et al., 2014), but with 16 instead of 5 ice sheet models. We include uncertainty in the atmospheric warming response to carbon emissions (full range of CMIP-5 climate model sensitivities), uncertainty in the oceanic transport to the Southern Ocean (obtained from the time-delayed and scaled oceanic subsurface warming in CMIP-5 models in relation to the global mean surface warming) and the observed range of responses of basal ice shelf melting to oceanic warming outside the ice shelf cavity. This uncertainty in basal ice shelf melting is then convoluted with the linear response functions of each of the 16 ice sheet models to obtain the ice flow response to the individual global warming path. The model median for the observational period from 1992 to 2017 is 9.6 mm with a likely range between 5.2 mm and 20.3 mm compared to the observed sea-level contribution from Antarctica of 7.4 mm with a standard deviation of 3.7 mm (Shepherd et al., 2018). For the so-called business-as-usual warming path, RCP-8.5, we obtain a median contribution of the Antarctic ice sheet to global mean sea-level rise within the 21st century of 17 cm with a likely range (66-percentile around the mean) between 9 cm and 36 cm and a very likely range (90-percentile around the mean) between 6 cm and 59 cm. For the RCP-2.6 warming path which will keep the global mean temperature below two degrees of global warming and is thus consistent with the Paris Climate Agreement yields a median of 13 cm of global mean sea-level contribution. The likely range for the RCP-2.6 scenario is between 7 cm and 25 cm and the very likely range is between 5 cm and 39 cm. The structural uncertainties in the method do not allow an interpretation of any higher uncertainty percentiles. We provide projections for the five Antarctic regions and for each model and each scenario, separately. The rate of sea level contribution is highest under the RCP-8.5 scenario. The maximum within the 21st century of the median value is 4 cm per decade with a likely range between 2 cm/dec and 8 cm/dec and a very likely range between 1 cm/dec and 13 cm/dec.

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The GRISLI ice sheet model (version 2.0): calibration and validation for multi-millennial changes of the Antarctic ice sheet

Cited by 6 publications

References 52 publications

Description and validation of the ice-sheet model Yelmo (version 1.0)

Description and validation of the ice-sheet model Yelmo (version 1.0)

initMIP-Antarctica: An ice sheet model initialization experiment of ISMIP6

Projecting Antarctica's contribution to future sea level rise from basal ice-shelf melt using linear response functions of 16 ice sheet models (LARMIP-2)

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