Description: If unstructured meshes are refined to locally represent eddy dynamics in ocean circulation models, a practical question arises on how to vary the resolution and where to deploy the refinement. We propose to use the observed sea surface height variability as the refinement criterion. We explore the utility of this method (i) in a suite of idealized experiments simulating a wind-driven double gyre flow in a stratified circular basin and (ii) in simulations of global ocean circulation performed with FESOM. Two practical approaches of mesh refinement are compared. In the first approach the uniform refinement is confined within the areas where the observed variability exceeds a given threshold. In the second one the refinement varies linearly following the observed variability. The resolution is fixed in time. For the double gyre case it is shown that the variability obtained in a high-resolution reference run can be well captured on variable-resolution meshes if they are refined where the variability is high and additionally upstream the jet separation point. The second approach of mesh refinement proves to be more beneficial in terms of improvement downstream the midlatitude jet. Similarly, in global ocean simulations the mesh refinement based on the observed variability helps the model to simulate high variability at correct locations. The refinement also leads to a reduced bias in the upper-ocean temperature

Description: The ability of state‐of‐the‐art regional climate models to simulate cyclone activity in the Arctic is assessed based on an ensemble of 13 simulations from 11 models from the Arctic‐CORDEX initiative. Some models employ large‐scale spectral nudging techniques. Cyclone characteristics simulated by the ensemble are compared with the results forced by four reanalyses (ERA‐Interim, National Centers for Environmental Prediction‐Climate Forecast System Reanalysis, National Aeronautics and Space Administration‐Modern‐Era Retrospective analysis for Research and Applications Version 2, and Japan Meteorological Agency‐Japanese 55‐year reanalysis) in winter and summer for 1981–2010 period. In addition, we compare cyclone statistics between ERA‐Interim and the Arctic System Reanalysis reanalyses for 2000–2010. Biases in cyclone frequency, intensity, and size over the Arctic are also quantified. Variations in cyclone frequency across the models are partly attributed to the differences in cyclone frequency over land. The variations across the models are largest for small and shallow cyclones for both seasons. A connection between biases in the zonal wind at 200 hPa and cyclone characteristics is found for both seasons. Most models underestimate zonal wind speed in both seasons, which likely leads to underestimation of cyclone mean depth and deep cyclone frequency in the Arctic. In general, the regional climate models are able to represent the spatial distribution of cyclone characteristics in the Arctic but models that employ large‐scale spectral nudging show a better agreement with ERA‐Interim reanalysis than the rest of the models. Trends also exhibit the benefits of nudging. Models with spectral nudging are able to reproduce the cyclone trends, whereas most of the nonnudged models fail to do so. However, the cyclone characteristics and trends are sensitive to the choice of nudged variables.

Description: The Beaufort Gyre (BG) is the largest liquid freshwater reservoir of the Arctic Ocean. The liquid freshwater content (FWC) significantly increased in the BG in the 2000s during an anticyclonic wind regime and remained at a high level despite a transition to a more cyclonic state in the early 2010s. It is not well understood to what extent the rapid sea ice decline during this period has modified the trend and variability of the BG liquid FWC in the past decade. Our numerical simulations show that about 50% of the liquid freshwater accumulated in the BG in the 2000s can be explained by the sea ice decline caused by the Arctic atmospheric warming. Among this part of the FWC increase, 60% can be attributed to surface freshening associated with the reduction of the net sea ice thermodynamic growth rate, and 40% to changes in ocean circulation, which makes freshwater more accessible to the BG for storage. Thus, the rapid increase of the BG FWC in the 2000s was due to the concurrence of the anticyclonic wind regime and the high freshwater availability. We also find that if the Arctic sea ice had not declined, the liquid FWC in the BG would have shown a stronger decreasing tendency at the beginning of the 2010s owing to the cyclonic wind regime. From our results we argue that changes in sea ice conditions should be adequately taken into account when it comes to understanding and predicting variations of BG liquid FWC in a changing climate.

Description: Sea ice formation is accompanied by the rejection of salt which in nature tends to be mixed vertically by the formation of convective plumes. Here we analyze the influence of a salt plume parameterization (SPP) in an atmosphere-sea ice-ocean model. Two 330 years long simulations have been conducted with the AWI Climate Model. In the reference simulation, the rejected salt in the Arctic Ocean is added to the upper-most ocean layer. This approach is commonly used in climate modelling. In another experiment, employing SPP, the rejected salt is vertically redistributed within the mixed layer based on a power law profile that mimics the penetration of salt plumes. We discuss the effects of this redistribution on the simulated mean state and on atmosphere-ocean linkages associated with the intensity of deep water formation. We find that the salt plume parametrization leads to simultaneous increase of sea ice (volume and concentration) and decrease of sea surface salinity in the Arctic. The SPP considerably alters the interplay between the atmosphere and the ocean in the Nordic Seas. The parameterization modifies the ocean ventilation; however, resulting changes in temperature and salinity largely compensate each other in terms of density so that the overturning circulation is not significantly affected.

Description: Sea ice dynamics determine the drift and deformation of sea ice. Nonlinear physics, usually expressed in a viscous‐plastic rheology, makes the sea ice momentum equations notoriously difficult to solve. At increasing sea ice model resolution the nonlinearities become stronger as linear kinematic features (leads) appear in the solutions. Even the standard elastic‐viscous‐plastic (EVP) solver for sea ice dynamics, which was introduced for computational efficiency, becomes computationally very expensive, when accurate solutions are required, because the numerical stability requires very short, and hence more, subcycling time steps at high resolution. Simple modifications to the EVP solver have been shown to remove the influence of the number of subcycles on the numerical stability. At low resolution appropriate solutions can be obtained with only partial convergence based on a significantly reduced number of subcycles as long as the numerical procedure is kept stable. This previous result is extended to high resolution where linear kinematic features start to appear. The computational cost can be strongly reduced in Arctic Ocean simulations with a grid spacing of 4.5 km by using modified and adaptive EVP versions because fewer subcycles are required to simulate sea ice fields with the same characteristics as with the standard EVP.

Description: Coupled Model Intercomparison Project Phase 6 (CMIP6) data sets: HighResMIP HR simulations. These data include all datasets published for 'CMIP6.HighResMIP.AWI.AWI-CM-1-1-HR' according to the Data Reference Syntax defined as 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The model used in climate research named AWI-CM 1.1 HR, released in 2018, includes the components: atmos: ECHAM6.3.04p1 (T127L95 native atmosphere T127 gaussian grid; 384 x 192 longitude/latitude; 95 levels; top level 80 km), land: JSBACH 3.20, ocean: FESOM 1.4 (unstructured grid in the horizontal with 1306775 wet nodes; 46 levels; top grid cell 0-5 m), seaIce: FESOM 1.4. The model was run by the Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Am Handelshafen 12, 27570 Bremerhaven, Germany (AWI) in native nominal resolutions: atmos: 100 km, land: 100 km, ocean: 25 km, seaIce: 25 km. Project: These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions, and the results will undoubtedly be relied on by authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated at a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. - Project website: https://pcmdi.llnl.gov/CMIP6.

Description: Coupled Model Intercomparison Project Phase 6 (CMIP6) data sets: DECK (1pctCO2, abrupt-4xCO2, piControl simulations) and CMIP historical simulations. These data include all datasets published for 'CMIP6.CMIP.AWI.AWI-CM-1-1-MR' according to the Data Reference Syntax defined as 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The model used in climate research named AWI-CM 1.1 MR, released in 2018, includes the components: atmos: ECHAM6.3.04p1 (T127L95 native atmosphere T127 gaussian grid; 384 x 192 longitude/latitude; 95 levels; top level 80 km), land: JSBACH 3.20, ocean: FESOM 1.4 (unstructured grid in the horizontal with 830305 wet nodes; 46 levels; top grid cell 0-5 m), seaIce: FESOM 1.4. The model was run by the Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Am Handelshafen 12, 27570 Bremerhaven, Germany (AWI) in native nominal resolutions: atmos: 100 km, land: 100 km, ocean: 25 km, seaIce: 25 km. Project: These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions, and the results will undoubtedly be relied on by authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated at a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. - Project website: https://pcmdi.llnl.gov/CMIP6.

Description: Coupled Model Intercomparison Project Phase 6 (CMIP6) data sets: HighResMIP LR simulations. These data includes all datasets published for 'CMIP6.HighResMIP.AWI.AWI-CM-1-1-LR' according to the Data Reference Syntax defined as 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The model used in climate research named AWI-CM 1.1 LR, released in 2018, includes the components: atmos: ECHAM6.3.04p1 (T63L47 native atmosphere T63 gaussian grid; 192 x 96 longitude/latitude; 47 levels; top level 80 km), land: JSBACH 3.20, ocean: FESOM 1.4 (unstructured grid in the horizontal with 126859 wet nodes; 46 levels; top grid cell 0-5 m), seaIce: FESOM 1.4. The model was run by the Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Am Handelshafen 12, 27570 Bremerhaven, Germany (AWI) in native nominal resolutions: atmos: 250 km, land: 250 km, ocean: 50 km, seaIce: 50 km. Project: These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions, and the results will undoubtedly be relied on by authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated at a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. - Project website: https://pcmdi.llnl.gov/CMIP6.

Description: Ocean heat transport through the Barents Sea Opening (BSO) has strong impacts on the Barents Sea ice extent and the climate. In this paper we quantified the contributions from different atmospheric forcing components to the trend and interannual variability of the BSO heat transport. Ocean‐ice model simulations were conducted in which the interannual variation of atmospheric forcing was maintained only in or outside the Arctic in two different simulations. The sum of their BSO heat transport anomalies reasonably replicated the trend and variability from a hindcast simulation. The upward trend of the BSO heat transport mainly stems from the increasing ocean temperature in the subpolar North Atlantic. For the interannual variability, the local wind and upstream forcing are similarly important. The location of the Atlantic Water boundary current in the Nordic Seas, influenced by the cyclonic atmospheric circulation, is crucial in determining part of the BSO inflow variability.

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.