ALBERT

Description: Glaciers and ice caps exhibit currently the largest cryospheric contributions to sea level rise. Modelling the dynamics and mass balance of the major ice sheets is therefore an important issue to investigate the current state and the future response of the cryosphere in response to changing environmental conditions, namely global warming. This requires a powerful, easy-to-use, scalable multi-physics ice dynamics model. Based on the well-known and established ice sheet model of Pattyn (2003) we develop the modular multi-physics thermomechanic ice model RIMBAY, in which we improve the original version in several aspects like a shallow-ice–shallow-shelf coupler and a full 3-D-grounding-line migration scheme based on Schoof's (2007) heuristic analytical approach. We summarise the Full–Stokes equations and several approximations implemented within this model and we describe the different numerical discretisations. The results are cross-validated against previous publications dealing with ice modelling, and some additional artificial set-ups demonstrate the robustness of the different solvers and their internal coupling. RIMBAY is designed for an easy adaption to new scientific issues. Hence, we demonstrate in very different set-ups the applicability and functionality of RIMBAY in Earth system science in general and ice modelling in particular.

Description: We present first results from a coupled model setup, consisting of a state-of-the-art ice sheet model (RIMBAY), and the community earth system model COSMOS. We show that special care has to be provided in order to ensure physical distributions of the forcings, as well as numeric stability of the involved models. We demonstrate that a statistical downscaling is crucial for ice sheet stability, especially for southern Greenland where surface temperature are close to the melting point. The simulated ice sheets are stable when forced with pre-industrial greenhouse gas parameters, with limits comparable with present day ice orography. A setup with high CO2 level is used to demonstrate the effects of dynamic ice sheets compared to the standard parameterisation; the resulting changes on ocean circulation will also be discussed.

Description: Large scale fully coupled Earth System Models (ESMs) are usually applied in climate projections like the IPCC-reports. In these models internal variability is often within the correct order of magnitude compared with the observed climate, but due to internal variability and arbitrary initial conditions they are not able to reproduce the observed timing of climate events or shifts as for instance observed in the El Niño Southern Oscillation (ENSO), the Pacific Decadal Oscillation (PDO), or the Atlantic Meridional Overturning Circulation (AMOC). Additional information about the real climate history is necessary to constrain ESMs; not only to emulate the past climate, but also to introduce a potential forecast skill into these models through a proper initialisation. We realize this by extending the fully coupled climate model Max Planck Institute Earth System Model (MPI-ESM) using a partial coupling technique (Modini-MPI-ESM). This method is implemented by adding reanalysis wind-field anomalies to the MPI-ESM's inherent climatological wind field when computing the surface wind stress that is used to drive the ocean and sea ice model. Using anomalies instead of the full wind field reduces potential model drifts, because of different mean climate states of the unconstrained MPI-ESM and the partially-coupled Modini-MPI-ESM, that could arise if total observed wind stress was used. We apply two different reanalysis wind products (National Centers for Environmental Prediction, Climate Forecast System Reanalysis (NCEPcsfr) and ERA-Interim reanalysis (ERAI)) and analyse the skill of Modini-MPI-ESM with respect to several observed oceanic, atmospheric, and sea-ice indices. We demonstrate that Modini-MPI-ESM has a significant skill over the time period 1980 to 2013 in reproducing historical climate fluctuations, indicating the potential of the method for initialising seasonal to decadal forecasts. Additionally, our comparison of the results achieved with the two reanalysis wind products NCEPcsfr and ERAI indicates that in general applying NCEPcsfr results in a better reconstruction of climate variability since 1980.