Description: We developed a new version of the Alfred Wegener Institute Climate Model (AWI-CM3), which has higher skills in representing the observed climatology and better computational efficiency than its predecessors. Its ocean component FESOM2 (Finite-volumE Sea ice-Ocean Model) has the multi-resolution functionality typical of unstructured-mesh models while still featuring a scalability and efficiency similar to regular-grid models. The atmospheric component OpenIFS (CY43R3) enables the use of the latest developments in the numerical-weather-prediction community in climate sciences. In this paper we describe the coupling of the model components and evaluate the model performance on a variable-resolution (25-125 km) ocean mesh and a 61 km atmosphere grid, which serves as a reference and starting point for other ongoing research activities with AWI-CM3. This includes the exploration of high and variable resolution and the development of a full Earth system model as well as the creation of a new sea ice prediction system. At this early development stage and with the given coarse to medium resolutions, the model already features above-CMIP6-average skills (where CMIP6 denotes Coupled Model Intercomparison Project phase 6) in representing the climatology and competitive model throughput. Finally we identify remaining biases and suggest further improvements to be made to the model.

Description: Various observational estimates indicate growing mass loss at Antarctica's margins but also heavier precipitation across the continent. In the future, heavier precipitation fallen on Antarctica will counteract any stronger iceberg discharge and increased basal melting of floating ice shelves driven by a warming ocean. Here, we use from nine CMIP5 models future projections, ranging from strong mitigation efforts to business-as-usual, to run an ensemble of ice-sheet simulations. We test, how the precipitation boundary condition determines Antarctica's sea-level contribution. The spatial and temporal varying climate forcings drive ice-sheet simulations. Hence, our ensemble inherits all spatial and temporal climate patterns, which is in contrast to a spatial mean forcing. Regardless of the applied boundary condition and forcing, some areas will lose ice in the future, such as the glaciers from the West Antarctic Ice Sheet draining into the Amundsen Sea. In general the simulated ice-sheet thickness grows in a broad marginal strip, where incoming storms deliver topographically controlled precipitation. This strip shows the largest ice thickness differences between the applied precipitation boundary conditions too. On average Antarctica's ice mass shrinks for all future scenarios if the precipitation is scaled by the spatial temperature anomalies coming from the CMIP5 models. In this approach, we use the relative precipitation increment per degree warming as invariant scaling constant. In contrast, Antarctica gains mass in our simulations if we apply the simulated precipitation anomalies of the CMIP5 models directly. Here, the scaling factors show a distinct spatial pattern across Antarctica. Furthermore, the diagnosed mean scaling across all considered climate forcings is larger than the values deduced from ice cores. In general, the scaling is higher across the East Antarctic Ice Sheet, lower across the West Antarctic Ice Sheet, and lowest around the Siple Coast. The latter is located on the east side of the Ross Ice Shelf.

Description: Understanding the influence of the Arctic troposphere on the climate at midlatitudes is critical for projecting the impacts of ongoing and anticipated Arctic changes such as Arctic amplification and rapid sea ice decline over the Northern Hemisphere. In this study, we analyze a suite of atmospheric model experiments, with and without atmospheric relaxation toward reanalysis data, to study the impacts of the Arctic troposphere on the midlatitude atmospheric circulation and climate variability. The Arctic troposphere is found to strongly impact the interannual variability of the atmospheric circulation and temperature over the midlatitude continents. The major mechanisms for the impacts of Arctic troposphere include the modulation of the large‐scale atmospheric circulation, the associated heat transport over the continents, and the impacts on synoptic variations in the North Atlantic‐European sector. The impact of the Arctic troposphere on the intensity of the Siberian High is an important factor for how the Arctic can influence temperature variability in south Siberia and East Asia. The trends in the Arctic troposphere in recent decades are closely linked to the recent winter cooling in Northern Eurasia. These recent cooling trends are not driven by the trends in sea surface temperature/sea ice, tropical atmosphere, and the stratosphere. It is argued that the temperature trend pattern of warm Arctic‐cold Eurasia is a manifestation of two possibly independent phenomena and the cooling trend is contributed to by the Arctic troposphere through impacting the large‐scale atmospheric circulation, the atmospheric blocking frequency, and the intensity of the Siberian High.

Description: We examine CMIP6 simulations of Arctic sea‐ice area and volume. We find that CMIP6 models produce a wide spread of mean Arctic sea‐ice area, capturing the observational estimate within the multi‐model ensemble spread. The CMIP6 multi‐model ensemble mean provides a more realistic estimate of the sensitivity of September Arctic sea‐ice area to a given amount of anthropogenic CO2 emissions and to a given amount of global warming, compared with earlier CMIP experiments. Still, most CMIP6 models fail to simulate at the same time a plausible evolution of sea‐ice area and of global mean surface temperature. In the vast majority of the available CMIP6 simulations, the Arctic Ocean becomes practically sea‐ice free (sea‐ice area 〈 1 million km2) in September for the first time before the year 2050 in each of the four emission scenarios SSP1‐1.9, SSP1‐2.6, SSP2‐4.5 and SSP5‐8.5 examined here.

Description: A new global climate model setup using FESOM2.0 for the sea ice‐ocean component and ECHAM6.3 for the atmosphere and land surface has been developed. Replacing FESOM1.4 by FESOM2.0 promises a higher efficiency of the new climate setup compared to its predecessor. The new setup allows for long‐term climate integrations using a locally eddy‐resolving ocean. Here it is evaluated in terms of (1) the mean state and long‐term drift under preindustrial climate conditions, (2) the fidelity in simulating the historical warming, and (3) differences between coarse and eddy‐resolving ocean configurations. The results show that the realism of the new climate setup is overall within the range of existing models. In terms of oceanic temperatures, the historical warming signal is of smaller amplitude than the model drift in case of a relatively short spin‐up. However, it is argued that the strategy of “de‐drifting” climate runs after the short spin‐up, proposed by the HighResMIP protocol, allows one to isolate the warming signal. Moreover, the eddy‐permitting/resolving ocean setup shows notable improvements regarding the simulation of oceanic surface temperatures, in particular in the Southern Ocean.

Description: The general circulation models used to simulate global climate typically feature resolution too coarse to reproduce many smaller scale processes, which are crucial to determining the regional responses to climate change. A novel approach to downscale climate change scenarios is presented which includes the interactions between the North Atlantic Ocean and the European shelves as well as their impact on the North Atlantic and European climate. The goal of this paper is to introduce the global ocean – regional atmosphere coupling concept and to show the potential benefits of this model system to simulate present day climate. A global ocean – sea ice – marine biogeochemistry model (MPIOM/HAMOCC) with regionally high horizontal resolution is coupled to an atmospheric regional model (REMO) and global terrestrial hydrology model (HD) via the OASIS coupler. Moreover, results obtained with ROM using NCEP/NCAR reanalysis and ECHAM5/MPIOM CMIP3 historical simulations as boundary conditions are presented and discussed for the North Atlantic and North European region. The validation of all the model components, i.e. ocean, atmosphere, terrestrial hydrology and ocean biogeochemistry is performed and discussed. The careful and detailed validation of ROM provides evidence that the proposed model system improves the simulation of many aspects of the regional climate, remarkably the ocean, even though some biases persist in other model components, thus leaving potential for future improvement. We conclude that ROM is a powerful tool to estimate possible impacts of climate change on the regional scale.

Description: Forecast experiments with the European Centre for Medium-Range Weather Forecasts model with and without relaxation of the Arctic troposphere toward reanalysis data are carried out in order to explore the influence that improved Arctic forecasts during wintertime would have on the skill of medium-range and extended-range prediction of 500 hPa geopotential height in the Northern Hemisphere midlatitudes. It turns out that the largest midlatitude improvements are found over eastern Europe, northern Asia, and North America; no discernible impact is found over the North Atlantic and North Pacific, where midlatitude and tropical dynamics appear to be more important. The strength of the linkage between the Arctic and the midlatitudes is found to be flow dependent, with anomalous northerly wind leading to a stronger Arctic influence. Finally, the results are discussed in the context of the possible impact of Arctic sea ice decline on midlatitude weather and climate.

Description: The transient climate response (TCR) is 20% higher in the Alfred Wegener Institute Climate Model (AWI-CM) compared to the Max Planck Institute Earth System Model (MPI-ESM) whereas the equilibrium climate sensitivity (ECS) is by up to 10% higher in AWI-CM. These results are largely independent of the two considered model resolutions for each model. The two coupled CMIP6 models share the same atmosphere-land component ECHAM6.3 developed at the Max Planck Institute for Meteorology (MPI-M). However, ECHAM6.3 is coupled to two different ocean models, namely the MPIOM sea ice-ocean model developed at MPI-M and the FESOM sea ice-ocean model developed at the Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research (AWI). A reason for the different TCR is related to ocean heat uptake in response to greenhouse gas forcing. Specifically, AWI-CM simulations show stronger surface heating than MPI-ESM simulations while the latter accumulate more heat in the deeper ocean. The vertically integrated ocean heat content is increasing slower in AWI-CM model configurations compared to MPI-ESM model configurations in the high latitudes. Weaker vertical mixing in AWI-CM model configurations compared to MPI-ESM model configurations seems to be key for these differences. The strongest difference in vertical ocean mixing occurs inside the Weddell and Ross Gyres and the northern North Atlantic. Over the North Atlantic, these differences materialize in a lack of a warming hole in AWI-CM model configurations and the presence of a warming hole in MPI-ESM model configurations. All these differences occur largely independent of the considered model resolutions.

Description: An ensemble-based data assimilation framework for a coupled ocean–atmosphere model is applied to investigate the influence of assimilating different types of ocean observations on the ocean and atmosphere simulation. The data assimilation is performed with the parallel data assimilation framework (PDAF) for the climate model AWI-CM. Observations of the ocean, namely satellite sea-surface temperature (SST) and temperature and salinity profiles, are assimilated into the ocean component. The atmospheric state is only influenced by the model dynamics. Different assimilation scenarios were carried out with different combinations of observations to investigate to what extent the assimilation into the coupled model leads to a better estimation of the state of the ocean as well as the atmosphere. The influence of the data assimilation is assessed by comparing the ocean prediction with dependent and independent ocean observations. For the atmosphere, the assimilation result is compared with the ERA-Interim atmospheric reanalysis data. The ocean temperature and salinity are improved by all the assimilation scenarios in the coupled system. The assimilation leads to a response of the atmosphere throughout the troposphere and impacts the global atmospheric circulation. Globally the temperature and wind speed are improved in the atmosphere on average.