Assessment of sub-shelf melting parameterisations using the ocean–ice-sheet coupled model NEMO(v3.6)–Elmer/Ice(v8.3)

Abstract

Abstract. Oceanic melting beneath ice shelves is the main driver of the current mass loss of the Antarctic ice sheet and is mostly parameterised in stand-alone ice-sheet modelling. Parameterisations are crude representations of reality, and their response to ocean warming has not been compared to 3-D ocean–ice-sheet coupled models. Here, we assess various melting parameterisations ranging from simple scalings with far-field thermal driving to emulators of box and plume models, using a new coupling framework combining the ocean model NEMO and the ice-sheet model Elmer/Ice. We define six idealised one-century scenarios for the far-field ocean ranging from cold to warm, and representative of potential futures for typical Antarctic ice shelves. The scenarios are used to constrain an idealised geometry of the Pine Island glacier representative of a relatively small cavity. Melt rates and sea-level contributions obtained with the parameterised stand-alone ice-sheet model are compared to the coupled model results. The plume parameterisations give good results for cold scenarios but fail and underestimate sea level contribution by tens of percent for warm(ing) scenarios, which may be improved by adapting its empirical scaling. The box parameterisation with five boxes compares fairly well to the coupled results for almost all scenarios, but further work is needed to grasp the correct number of boxes. For simple scalings, the comparison to the coupled framework shows that a quadratic as opposed to linear dependency on thermal forcing is required. In addition, the quadratic dependency is improved when melting depends on both local and non-local, i.e. averaged over the ice shelf, thermal forcing. The results of both the box and the two quadratic parameterisations fall within or close to the coupled model uncertainty. All parameterisations overestimate melting for thin ice shelves while underestimating melting in deep water near the grounding line. Further work is therefore needed to assess the validity of these melting parameteriations in more realistic set-ups.

Assessing Uncertainty in the Dynamical Ice Response to Ocean Warming in the Amundsen Sea Embayment, West Antarctica

“…However, we have not investigated the impact of uncertainty in the melt rate forcing anomaly added during the extended simulations. Accounting for different ocean temperature projections is likely to add considerable spread to the distribution of future sea level contribution 10.1029/2019GL084941 (Holland et al, 2019), whereas the precise form of the ocean melt parameterization is likely to be less influential (Favier et al, 2019).…”

Ocean-forced evolution of the Amundsen Sea catchment, West Antarctica, by 2100

“…The CMIP5 ensemble consists of 50 AOGCMs and Earth system models (ESMs) from 21 modelling groups (Taylor et al, 2012), providing a valuable resource for exploring the projected future evolution of the climate under varying future emission scenarios. Biases in the representation of climatological features in the Southern Ocean have been widely investigated (Bracegirdle et al, 2013;Hosking et al, 2013;Little and Urban, 2016;Meijers et al, 2012;Sallée et al, 2013aSallée et al, , 2013b, and individual model representation of observed climate varies largely across the ensemble (Flato et al, 2013). Comparing the output of AOGCMs against climatological observations provides a means by which we can investigate biases, assess model performance (Gleckler et al, 2008) and identify models that best reproduce observed climate in the Southern Ocean.…”

ISMIP6 projections of ocean-forced Antarctic Ice Sheet evolution using the Community Ice Sheet Model

“…The ice-sheet physics is conventional in the sense that it includes well-understood retreat mechanisms such as MISI, but not hydrofracture or cliff collapse (Pollard et al, 2015;Pollard and DeConto, 2016). Some important long-term feedbacks such as solid-Earth 5 rebound and relative-sea-level changes (Gomez et al, 2010;Larour et al, 2019) are omitted, and there is no ice-ocean coupling (e.g., De Rydt and Gudmundsson, 2016;Seroussi et al, 2017;Favier et al, 2019). Thus, the timing and magnitude of simulated ice sheet retreat are imprecise, but we can identify responses that are robust across simulations, and also draw attention to the largest sources of uncertainty.…”