2 Model and simulation description

2.1 Model description

The sea ice-ocean component of AWI-CM is the Finite Element Sea Ice‐Ocean Model (FESOM, see Danilov et al. (2015) for the sea ice component and Wang et al. (2014) for the ocean component). It uses unstructured meshes, that allow simulations of ocean and sea ice dynamics with variable grid resolution. This also enables refinement in resolution for areas where small-scale dynamics are prevalent, (e.g. narrow straits and strongly eddying regions, Sein et al., 2016, 2017). Tools have been developed to enable users of FESOM data to perform analysis efficiently (see Appendix A1). Furthermore, selected variables are also available on regular latitude-longitude meshes.
The atmospheric component of AWI-CM is the spectral atmospheric model ECHAM6.3.04p1 from MPIM (Stevens et al., 2013) which is used here without any additional modifications or tuning. This version of ECHAM is also used in the MPIM contribution to CMIP6. Having these two setups, thus will allow future intercomparisons of the coupled systems that share the same atmosphere model but use different sea ice-ocean models.
A more detailed description of the AWI-CM components as well as an evaluation of its mean state and climate variability are provided in Sidorenko et al. (2015) and Rackow et al. (2018), respectively. AWI-CM realistically simulates many aspects of the modern climate, showing an overall performance that is generally better than the most realistic climate models participating in CMIP5.
The CMIP6 version of the code encompasses several changes compared to that described in Sidorenko et al. (2015) and Rackow et al. (2018). The major technical improvement involves the removal of the regular exchange mesh, which in earlier versions was used as an interface between FESOM and the OASIS3-MCT coupler. In the CMIP6 version, the interpolation between unstructured FESOM and structured ECHAM meshes is done by the coupler. Furthermore the coupling between ocean and atmosphere has been sped up remarkably through the use of the parallel support built in OASIS3-MCT.
Updates of physical parameterizations in the ocean sea ice component comprise the inclusion of (1) a salt plume parameterisation (Sidorenko et al. 2018) which improves the simulated sea surface salinity in the Arctic Ocean, (2) modified background diffusivities, as suggested by Wang et al. (2014) and (3) a K-Profile Parameterization (KPP) for vertical mixing (Large et al. 1994) in the ocean model which has solved shortcomings related to the North Atlantic circulation, pointed out in Sidorenko et al. (2015) and Rackow et al. (2018). Those previous publications were based on simulations on different meshes and with constant rather than transient forcing. This and the fact that these simulations were performed within the CMIP6 framework according to a common protocol calls for documentation of the CMIP6 version of the model and its results presented in this paper.

2.2 CMIP6 simulations

In this paper, the focus is on the DECK and ScenarioMIP simulations, which were defined in the CMIP6 overview paper (Eyring et al., 2016) and are summarized in Table 1. Before starting the 500-year coupled piControl-spinup simulation with constant pre-industrial forcing, a 10-year long ocean-only simulation initialized from the EN4 ocean reanalysis (Good et al., 2013) averaged over 1950–1954 has been performed. In these 10 years of ocean-only simulation the initial adjustment of the ocean state takes place. This pre-spinup helps to ensure a numerically stable adjustment phase of the coupled system. The piControl simulation is a continuation of the piControl-spinup simulation. From the piControl simulation the idealized greenhouse gas forcing simulations 1pctCO2 and abrupt-4xCO2 simulations as well as the historical forcing simulations are branched off at specific years (branch-off point(s), see Table 1). At the end of the historical forcing simulations, that is at the end of the year 2014, the scenario simulations are continued with forcing prescribed from the anthropogenic forcing scenarios. These scenarios are derived from Shared Socioeconomic Pathways (SSP) (Meinshausen et al. 2019).
The idealized and historical forcing simulations have been branched off sufficiently long before the end of the piControl simulation to ensure that every year of the sensitivity simulations (idealized, historical, and scenario simulations) has a corresponding year in the piControl simulation. The climate change signal is always computed following the delta approach (e.g. Lenderink et al., 2007), that is, as the difference between the sensitivity simulation and the corresponding year(s) of the piControl simulation, to account for possible model drift.
Table 1: DECK and ScenarioMIP simulations performed with AWI-CM. The forcing of the ScenarioMIP simulations is described in more detail in Meinshausen et al. (2019).