6 Discussion

The climate model AWI-CM-MR-1-1 presented here has proven to perform well compared to CMIP5 as well as selected CMIP6 models and therefore can be regarded as a solid contribution to the CMIP6 ensemble. Model drift in the control simulation is negligible. While some long standing model biases in AWI-CM such as a too zonal North Atlantic current, a too strong atmospheric westerly flow in the Euro-Atlantic region, a too cold subpolar North Atlantic gyre as well as a warm bias west of Africa are still present, there is a good representation of the North Atlantic ocean temperature profile, i.e. the warm bias in mid-depths is largely alleviated as discussed in Rackow et al. (2018). Furthermore, there is no pronounced Southern Ocean surface warm bias and therefore a very good representation of Antarctic sea ice and circulation compared to CMIP5 models and also compared to the Max Planck Institute for Meteorology CMIP6 model MPI-ESM (Müller et al., 2018): both mean sea level pressure and vertical profiles of zonal mean zonal wind are better represented over the Southern Ocean - except for the area west of the Antarctic peninsula where a positive mean sea level pressure bias is replaced by a negative mean sea level pressure bias.
Since the atmosphere model is the same as in MPI-ESM, it could be hypothesized that the high resolution of the ocean model in the Southern Ocean helps to reduce the long standing biases in this area that is very important for the global ocean circulation as well as heat and carbon uptake (e.g. Frölicher et al., 2015). This is subject to further investigation in the future and in collaboration with the Max Planck Institute for Meteorology. Contrary to observations, Antarctic sea ice decline has been simulated for the past decades, similar to CMIP5 and CMIP6 model results (Roach et al., 2020). .
In terms of the response to increasing greenhouse gases, our model shows very similar outcomes compared to the multi-model ensemble of CMIP5 simulations, both in patterns and in magnitude. Features such as a strong Arctic Amplification along with a weak Antarctic Amplification, Arctic wetting (Bintanja and Selten, 2014), subtropical drying, increased frequency of extreme La Niña & El Niño events (Cai et al., 2015), reduced ENSO asymmetry (Ham et al., 2017), and weakening Atlantic Meridional Overturning Circulation are very similar to the previous simulations.
However, there are potentially important differences that need further investigation: The weakening of the Atlantic Meridional Overturning Circulation is less pronounced compared to the CMIP5 ensemble mean. Since weakening of the Atlantic Meridional Overturning Circulation has been linked to the emergence of a warming hole over the North Atlantic subpolar gyre (e.g. Keil et al., 2020), it is consistent that the warming hole is only weak according to our model results.
The equilibrium climate sensitivity of our model (3.2°C) is slightly lower than the CMIP5 and CMIP6 multi-model means (3.4°C and 3.7°C, respectively, according to Meehl et al., 2020) and slightly higher than the CMIP6 version of the Max Planck Institute for Meteorology model MPI-ESM sharing the same atmosphere component (tuned to be 3.0°C). Our transient climate response is with 2.1°C slightly higher compared to the CMIP5 multi-model mean (1.9°C according to Meehl et al., 2020), slightly lower compared to the CMIP6 multi-model mean (2.2°C according to Meehl et al., 2020), and around 23% higher than in MPI-ESM (1.7°C). This might imply that the deep ocean takes up less energy in our model compared to MPI-ESM.
Furthermore, in our model, the decline of Arctic sea ice extent by the end of the 21st century is stronger than the multi-model mean over CMIP5 simulations, suggesting a higher likelihood of an ice-free Arctic in September even before 2050. According to our simulations, mitigation efforts only start to have an impact after 2050 in terms of Arctic winter sea ice. Surface albedo changes, in particular in the polar regions where sea ice declines, are projected to contribute substantially to a strong positive shortwave feedback. Note however that a recent geoengineering study based on AWI-CM indicates a small impact of the Arctic ice-albedo feedback on temperatures outside the Arctic (Zampieri and Goessling 2019).
While the Arctic sea ice extent trend is still slightly smaller in our model simulation compared to observations over the last few decades, the global mean temperature increase is slightly larger compared to observations. This could either hint at an underestimation of Arctic Amplification in our simulations or that multi-decadal internal variability is superimposed on the observed Arctic climate change. The latter hypothesis is supported by Kay et al. (2011), Ding et al. (2017), and England et al. (2019) stating that around half of the strong negative Arctic sea ice trend over the past decades is explained by internal variability and the other half by the climate change signal although there are strong seasonal and regional differences (England et al., 2019).
The AMOC decreases by around 25% until the end of the 21st century according to the AWI-CM SSP585 scenario simulation, which is less than the multi-model average value of around 40% calculated from CMIP5 models and Earth System Models of Intermediate Complexity (EMICs, Weaver et al., 2012; Cheng et al., 2013). CMIP6 models tend to show even stronger AMOC declines than CMIP5 models (Lyu et al., 2020). Previous studies suggest that the representation of western boundary currents and the Agulhas leakage in higher-resolution ocean models can influence the AMOC strength (e.g. Biastoch et al., 2009, 2018, Sein et al., 2018, Weijer et al., 2019, Hirschi et al., 2020). More dedicated studies in this regard will be carried out in our further work.