Design and results of the ice sheet model initialisation experiments initMIP-Greenland: an ISMIP6 intercomparison

Abstract

Abstract. Earlier large-scale Greenland ice sheet sea-level projections (e.g., those run during the ice2sea and SeaRISE initiatives) have shown that ice sheet initial conditions can have a large effect on the projections and give rise to important uncertainties. The goal of the initMIP-Greenland intercomparison exercise is to compare, evaluate and improve the initialisation techniques used in the ice sheet modelling community and to estimate the associated uncertainties. initMIP-Greenland is the first in a series of ice sheet model intercomparison activities within ISMIP6 (the Ice Sheet Model Intercomparison Project for CMIP6). Two experiments for the large-scale Greenland ice sheet have been designed to allow intercomparison between participating models of 1) the initial present-day state of the ice sheet and 2) the response in two schematic forward experiments. The forward experiments serve to evaluate the initialisation in terms of model drift (forward run without additional forcing) and in response to a large perturbation (prescribed surface mass balance anomaly), and should not be interpreted as sea-level projections. We present and discuss results that highlight the wide diversity of data sets, boundary conditions and initialisation techniques used in the community to generate initial states of the Greenland ice sheet. We find good agreement across the ensemble for the dynamic response to SMB changes in areas where the simulated ice sheets overlap, but in general differences arise due to the initial size of the ice sheet. The spread in model drift is reduced compared to earlier intercomparison exercises.

Projections of Future Sea Level Contributions from the Greenland and Antarctic Ice Sheets: Challenges Beyond Dynamical Ice Sheet Modeling

“…The opportunities offered by these new observations, however, go well beyond their simple use as model inputs. Using data assimilation methods, modelers were able to infer ice properties that cannot be directly observed, such as basal conditions that are buried under kilometers of ice, or rigidity of ice shelves (MacAyeal, 1992;Joughin et al, 2001;Goelzer et al, 2018).…”

“…Observations are also used to calibrate projections of ice sheet changes over the coming centuries in ensemble runs, such that simulations with the best agreement to the past evolution are given a higher weight in the projections (Ritz et al, 2015). However, accurately simulating the future evolution of ice sheets remains very challenging, as models' initial states (Goelzer et al, 2018) and external forcings need to be better constrained.…”

“…Two distinct methods were traditionally used for stand-alone ISMs, spin-ups and data assimilation (Nowicki et al, 2013), but we are now seeing approaches that combine these two methods (Goelzer et al, 2018). Spin-up methods that permit ISMs to be in equilibrium with climatic forcing or to retain some transient memory of previous climatic changes are currently available for the Greenland and the Antarctic Ice Sheets.…”

A confined–unconfined aquifer model for subglacial hydrology and its application to the North East Greenland Ice Stream

“…Thus far, large scale ice models have only been able to capture the distinct flow 20 pattern of NEGIS when using data assimilation techniques such as inverting for the basal friction coefficient (see e.g. horizontal velocity fields in Goelzer et al, 2017). It is assumed that most of the surface velocity can be attributed to basal sliding amplified by basal water instead of ice deformation .…”

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

“…This approach has been followed to participate in the first phase of the recent ice sheet model intercomparison project (ISMIP6, Nowicki et al, 2016) for both the Greenland (Goelzer et al, 2017) and Antarctic ice sheets. In this context, GRISLI achieves to provide sea level rise projections by the end of the century in line with the results from more complex model (Edwards et al, 2014;Goelzer et al, 2017).…”