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The explicit representation of cryospheric components in Earth system models has become more and more important over the last years. However, there are few advanced coupled Earth system models that employ interactive icebergs, and most iceberg model studies focus on iceberg trajectories or ocean surface conditions. Here, we present multi-centennial simulations with a fully coupled Earth system model including interactive icebergs to assess the effects of heat and freshwater fluxes by iceberg melting on deep-ocean characteristics. The icebergs are modeled as Lagrangian point particles and exchange heat and freshwater fluxes with the ocean. They are seeded in the Southern Ocean, following a realistic present-day size distribution. Total calving fluxes and the locations of discharge are derived from an ice sheet model output which allows for implementation in coupled climate–ice sheet models. The simulations show a cooling of up to 0.2 K of deep-ocean water masses in all ocean basins that propagates from the southern high latitudes northward. We also find enhanced deep-water formation in the continental shelf area of the Ross Sea, a process commonly underestimated by current climate models. The vertical stratification is weakened by enhanced sea ice formation and duration due to the cooling effect of iceberg melting, leading to a 10 % reduction of the buoyancy frequency in the Ross Sea. The deep-water formation in this region is increased by up to 10 %. By assessing the effects of heat and freshwater fluxes individually, we find latent heat flux to be the main driver of these water mass changes. The altered freshwater distribution by freshwater fluxes and synergetic effects play only a minor role. Our results emphasize the importance of realistically representing both heat and freshwater fluxes in the high southern latitudes. [ABSTRACT FROM AUTHOR]

Modeled projections of climate change typically do not include a well-resolved ocean mesoscale due to the high computational cost of running high-resolution models for long time periods. This challenge is addressed using efficiency-maximizing modeling strategies applied to 3 km simulations of the Southern Ocean in past, present, and future climates. The model setup exploits reduced-resolution spin-up and transient simulations to initialize a regionally refined, high-resolution ocean model during short time periods. The results are compared with satellite altimetry data and more traditional eddy-present simulations and evaluated based on their ability to reproduce observed mesoscale activity and to reveal a response to climate change distinct from natural variability. The high-resolution simulations reproduce the observed magnitude of Southern Ocean eddy kinetic energy (EKE) well, but differences remain in local magnitudes and the distribution of EKE. The coarser, eddy-permitting ensemble simulates a similar pattern of EKE but underrepresents observed levels by 55 %. At approximately 1 ∘ C of warming, the high-resolution simulations produce no change in overall EKE, in contrast to full ensemble agreement regarding EKE rise within the eddy-permitting simulations. At approximately 4 ∘ C of warming, both datasets produce consistent levels of EKE rise in relative terms, although not absolute magnitudes, as well as an increase in EKE variability. Simulated EKE rise is concentrated where flow interacts with bathymetric features in regions already known to be eddy-rich. Regional EKE change in the high-resolution simulations is consistent with changes seen in at least four of five eddy-permitting ensemble members at 1 ∘ C of warming and all ensemble members at 4 ∘ C. However, substantial noise would make these changes difficult to distinguish from natural variability without an ensemble. [ABSTRACT FROM AUTHOR]

The explicit representation of cryospheric components in Earth System models has become more and more important over the last years. However, there are only few advanced coupled Earth System models that employ interactive icebergs, and most iceberg model studies focus on iceberg trajectories or ocean surface conditions. Here, we present multi-centennial simulations with a fully coupled Earth System model including interactive icebergs to assess the effects of heat and freshwater fluxes by iceberg melting on deep ocean characteristics. The icebergs are modeled as Lagrangian point particles and exchange heat and freshwater fluxes with the ocean. They are seeded in the Southern Ocean, following a realistic present-day size distribution. Total calving fluxes and the locations of discharge are derived from an ice sheet model output which allows for implementation in coupled climate-ice sheet models. The simulations show a cooling of deep ocean water masses in all ocean basins that propagates from the southern high latitudes northward. We also find enhanced deep water formation in the continental shelf area of the Ross Sea, a process commonly underestimated by current climate models. The vertical stratification is weakened by enhanced sea-ice formation and duration due to the cooling effect of iceberg melting. The deep water formation in this region is increased by up to 10%. By assessing the effects of heat and freshwater fluxes individually, we find latent heat flux to be the main driver of these water mass changes. The altered freshwater distribution by freshwater fluxes and synergetic effects play only a minor role. Our results emphasize the importance of realistically representing both heat and freshwater fluxes in the high southern latitudes. [ABSTRACT FROM AUTHOR]

Drifting icebergs represent a significant hazard for polar navigation and are able to impact the ocean environment around them. Freshwater flux and the associated cooling from melting icebergs can locally decrease salinity and temperature and thus affect ocean circulation, biological activity, sea ice, and –on larger spatial scales– the whole climate system. However, despite their potential impact, the large-scale operational monitoring of drifting icebergs in sea ice-covered regions is as of today typically restricted to giant icebergs, larger than 18.5 km in length. This is due to difficulties in accurately identifying and following the motion of much smaller features in the polar ocean from space. So far, tracking of smaller icebergs from satellite imagery thus has been limited to open-ocean regions not covered by sea ice. In this study, a novel automated iceberg tracking method, based on a machine learning-approach for automatic iceberg detection, is presented. To demonstrate the applicability of the method, a case study was performed for the Weddell Sea region, Antarctica, using 1213 Advanced Synthetic Aperture Radar (ASAR) satellite images acquired between 2002 and 2011. Overall, a subset of 414 icebergs (3134 re-detections in total) with surface areas between 3.4 km2 and 3612 km2 were investigated with respect to their prevalent drift patterns, size variability, and average disintegration. The majority of the tracked icebergs drifted between 1.3 km and 2679.2 km westward around the Antarctic continent, following the Antarctic Coastal Current (ACoC) and the Weddell Gyre, at an average drift speed of 3.6 ± 7.4 km day−1. The method also allowed us to estimate an average daily disintegration (i.e. iceberg area decrease) rate of ~0.13% (~37% year−1) for all icebergs. Using the sum of all detected individual surface area reductions, we estimate a total iceberg mass decrease of ~683 Gt year−1, which can be freshwater input and/or new 'child' icebergs calved from larger icebergs. The extension to an automated long-term tracking method for icebergs is challenging as the iceberg shape can vary significantly due to abrupt disintegration or calving of bergy bits. However, our machine learning approach extended by automatic shape-based tracking capabilities proved to be a reliable alternative for automatic detection and tracking of icebergs, even under the ambiguous SAR background signatures often found in the Southern Ocean. In particular, the method works in the challenging near-coastal environment where the presence of sea ice and coastal ocean dynamics such as surface waves usually pose major obstacles for other approaches. [ABSTRACT FROM AUTHOR]

This study introduces a new flow‐dependent distribution sampling (FDDS) scheme for air–sea coupling. The FDDS scheme is implemented in a climate model and used to improve the simulated mean and variability of atmospheric and oceanic surface fields and thus air–sea fluxes. Most coupled circulation models use higher resolutions in the sea ice and ocean compared to the atmospheric model component, thereby explicitly simulating the atmospheric subgrid‐scale at the interface. However, the commonly applied averaging of surface fields and air–sea fluxes tends to smooth fine‐scale structures, such as oceanic fronts. The stochastic FDDS scheme samples the resolved spatial ocean (and sea ice) subgrid distribution that is usually not visible to a coarser‐resolution atmospheric model. Randomly drawn nodal ocean values are passed to the corresponding atmospheric boxes for the calculation of surface fluxes, aiming to enhance surface flux variability. The resulting surface field perturbations of the FDDS scheme are based on resolved dynamics, displaying pronounced seasonality with realistic magnitude. The AWI Climate Model is used to test the scheme on interannual time‐scales. Our set‐up features a high ocean‐to‐atmosphere resolution ratio in the Tropics, with grid‐point ratios of about 60:1. Compared to the default deterministic averaging, changes are largest in the Tropics leading to an improved spatial distribution of precipitation with bias reductions of up to 50%. Enhanced sea‐surface temperature variability in boreal winter further improves the seasonal phase locking of temperature anomalies associated with the El Niño–Southern Oscillation. Mean 2m temperature, sea ice thickness and concentration react with a contrasting dipole pattern between hemispheres but a joint increase of monthly and interannual variability. This first approach to implement a flow‐dependent stochastic coupling scheme shows considerable benefits for simulations of global climate, and various extensions and modifications of the scheme are possible. [ABSTRACT FROM AUTHOR]

Models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) show substantial biases in the deep ocean that are larger than the level of natural variability and the response to enhanced greenhouse gas concentrations. Here, we analyze the influence of horizontal resolution in a hierarchy of five multi-resolution simulations with the AWI Climate Model (AWI-CM), the climate model used at the Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, which employs a sea ice–ocean model component formulated on unstructured meshes. The ocean grid sizes considered range from a nominal resolution of ∼1∘ (CMIP5 type) up to locally eddy resolving. We show that increasing ocean resolution locally to resolve ocean eddies leads to reductions in deep ocean biases, although these improvements are not strictly monotonic for the five different ocean grids. A detailed diagnosis of the simulations allows to identify the origins of the biases. We find that two key regions at the surface are responsible for the development of the deep bias in the Atlantic Ocean: the northeastern North Atlantic and the region adjacent to the Strait of Gibraltar. Furthermore, the Southern Ocean density structure is equally improved with locally explicitly resolved eddies compared to parameterized eddies. Part of the bias reduction can be traced back towards improved surface biases over outcropping regions, which are in contact with deeper ocean layers along isopycnal surfaces. Our prototype simulations provide guidance for the optimal choice of ocean grids for AWI-CM to be used in the final runs for phase 6 of CMIP (CMIP6) and for the related flagship simulations in the High Resolution Model Intercomparison Project (HighResMIP). Quite remarkably, retaining resolution only in areas of high eddy activity along with excellent scalability characteristics of the unstructured-mesh sea ice–ocean model enables us to perform the multi-centennial climate simulations needed in a CMIP context at (locally) eddy-resolving resolution with a throughput of 5–6 simulated years per day. [ABSTRACT FROM AUTHOR]

CMIP5 models show substantial biases in the deep ocean that are larger than the level of natural variability and the response to enhanced greenhouse gas concentrations. Here we analyse the influence of horizontal resolution in a hierarchy of five multi-resolution simulations with the AWI Climate Model (AWI-CM), which employs a sea ice-ocean model component formulated on unstructured meshes. The ocean grid sizes considered range from a nominal resolution of -1° (CMIP5-type) up to locally eddy-resolving. We show that increasing ocean resolution locally to resolve ocean eddies leads to a major reduction in deep ocean biases. A detailed diagnosis of the simulations allows to identify the origins of the biases. We find that two major sources at the surface are responsible for the deep bias in the Atlantic Ocean. Furthermore, the Southern Ocean density structure is equally improved with locally explicitly resolved eddies compared to parameterized eddies. Part of the bias reduction can be traced back towards improved surface biases over outcropping regions, which are in contact with deeper ocean layers along isopycnal surfaces. Our prototype simulations provide guidance for the optimal choice of ocean grids for AWI-CM to be used in the final runs for phase 6 of the 'Coupled Model Intercomparison Project' (CMIP6) and for the related flagship simulations in the 'High Resolution Model Intercomparison Project' (HighResMIP). Quite remarkably, retaining resolution only in areas of high eddy activity along with excellent scalability characteristics of the unstructured-mesh sea ice-ocean model enables us to perform the multi-centennial climate simulations needed in a CMIP context at (locally) eddy-resolving resolution with a throughput of 5--6 simulated years per day. [ABSTRACT FROM AUTHOR]

Abstract: It is often unclear how to optimally choose horizontal resolution for the oceanic and atmospheric components of coupled climate models, which has implications for their ability to make best use of available computational resources. Here we investigate the effect of using different combinations of horizontal resolutions in atmosphere and ocean on the simulated climate in a global coupled climate model (Alfred Wegener Institute Climate Model [AWI‐CM]). Particular attention is given to the Atlantic Meridional Overturning Circulation (AMOC). Four experiments with different combinations of relatively high and low resolutions in the ocean and atmosphere are conducted. We show that increases in atmospheric and oceanic resolution have clear impacts on the simulated AMOC, which are largely independent. Increased atmospheric resolution leads to a weaker AMOC. It also improves the simulated Gulf Stream separation; however, this is only the case if the ocean is locally eddy resolving and reacts to the improved atmosphere. We argue that our results can be explained by reduced mean winds caused by higher cyclone activity. Increased resolution of the ocean affects the AMOC in several ways, thereby locally increasing or reducing the AMOC. The finer topography (and reduced dissipation) in the vicinity of the Caribbean basin tends to locally increase the AMOC. However, there is a reduction in the AMOC around 45°N, which relates to the reduced mixed layer depth in the Labrador Sea in simulations with refined ocean and changes in the North Atlantic current pathway. Furthermore, the eddy‐induced changes in the Southern Ocean increase the strength of the deep cell. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The Alfred Wegener Institute Climate Model (AWI‐CM) participates for the first time in the Coupled Model Intercomparison Project (CMIP), CMIP6. The sea ice‐ocean component, FESOM, runs on an unstructured mesh with horizontal resolutions ranging from 8 to 80 km. FESOM is coupled to the Max Planck Institute atmospheric model ECHAM 6.3 at a horizontal resolution of about 100 km. Using objective performance indices, it is shown that AWI‐CM performs better than the average of CMIP5 models. AWI‐CM shows an equilibrium climate sensitivity of 3.2°C, which is similar to the CMIP5 average, and a transient climate response of 2.1°C which is slightly higher than the CMIP5 average. The negative trend of Arctic sea‐ice extent in September over the past 30 years is 20–30% weaker in our simulations compared to observations. With the strongest emission scenario, the AMOC decreases by 25% until the end of the century which is less than the CMIP5 average of 40%. Patterns and even magnitude of simulated temperature and precipitation changes at the end of this century compared to present‐day climate under the strong emission scenario SSP585 are similar to the multi‐model CMIP5 mean. The simulations show a 11°C warming north of the Barents Sea and around 2°C to 3°C over most parts of the ocean as well as a wetting of the Arctic, subpolar, tropical, and Southern Ocean. Furthermore, in the northern middle latitudes in boreal summer and autumn as well as in the southern middle latitudes, a more zonal atmospheric flow is projected throughout the year. Plain Language Summary: The Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research (AWI) participates for the first time with a global climate model in the Coupled Model Intercomparison Project 6 (CMIP6). The results of CMIP6 and previous model comparison projects feed into the next assessment report of the Intergovernmental Panel on Climate Change (IPCC). The IPCC assessment reports include information on past and expected climate change in the future and is written for policy‐ and decision‐makers as well as for the general public. The main characteristics of the AWI climate model are described and compared to models from previous intercomparison projects. The projected global warming in AWI‐CM is similar to the average warming predicted by climate models in the previous intercomparison project. However, the Arctic sea‐ice extent declines faster than typical previous estimates. Areas that are wet in present‐day climate become wetter, and areas that are dry in present‐day climate become drier in the future—consistent with previous climate model simulations. The ocean currents remain rather stable in the AWI climate projections, which leads to a continued warm Gulf stream and therefore an only slightly reduced warming of the North Atlantic and parts of Europe compared to other middle‐latitude regions. Key Points: The paper describes contributions of AWI‐CM, which employs a sea‐ice ocean component formulated on unstructured meshes, to CMIP6Equilibrium climate sensitivity is similar to average of CMIP5 projections; transient climate response is slightly above averageResponse patterns are similar to CMIP5 with more pronounced Arctic sea ice loss and a more stable AMOC compared to other systems [ABSTRACT FROM AUTHOR]

Two decades into the 21st century there is growing evidence for global impacts of Antarctic and Southern Ocean climate change. Reliable estimates of how the Antarctic climate system would behave under a range of scenarios of future external climate forcing are thus a high priority. Output from new model simulations coordinated as part of the Coupled Model Intercomparison Project Phase 6 (CMIP6) provides an opportunity for a comprehensive analysis of the latest generation of state‐of‐the‐art climate models following a wider range of experiment types and scenarios than previous CMIP phases. Here the main broad‐scale 21st century Antarctic projections provided by the CMIP6 models are shown across four forcing scenarios: SSP1‐2.6, SSP2‐4.5, SSP3‐7.0 and SSP5‐8.5. End‐of‐century Antarctic surface‐air temperature change across these scenarios (relative to 1995–2014) is 1.3, 2.5, 3.7 and 4.8°C. The corresponding proportional precipitation rate changes are 8, 16, 24 and 31%. In addition to these end‐of‐century changes, an assessment of scenario dependence of pathways of absolute and global‐relative 21st century projections is conducted. Potential differences in regional response are of particular relevance to coastal Antarctica, where, for example, ecosystems and ice shelves are highly sensitive to the timing of crossing of key thresholds in both atmospheric and oceanic conditions. Overall, it is found that the projected changes over coastal Antarctica do not scale linearly with global forcing. We identify two factors that appear to contribute: (a) a stronger global‐relative Southern Ocean warming in stabilisation (SSP2‐4.5) and aggressive mitigation (SSP1‐2.6) scenarios as the Southern Ocean continues to warm and (b) projected recovery of Southern Hemisphere stratospheric ozone and its effect on the mid‐latitude westerlies. The major implication is that over coastal Antarctica, the surface warming by 2100 is stronger relative to the global mean surface warming for the low forcing compared to high forcing future scenarios. [ABSTRACT FROM AUTHOR]

In September 2019, the research icebreaker Polarstern started the largest multidisciplinary Arctic expedition to date, the MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate) drift experiment. Being moored to an ice floe for a whole year, thus including the winter season, the declared goal of the expedition is to better understand and quantify relevant processes within the atmosphere–ice–ocean system that impact the sea ice mass and energy budget, ultimately leading to much improved climate models. Satellite observations, atmospheric reanalysis data, and readings from a nearby meteorological station indicate that the interplay of high ice export in late winter and exceptionally high air temperatures resulted in the longest ice-free summer period since reliable instrumental records began. We show, using a Lagrangian tracking tool and a thermodynamic sea ice model, that the MOSAiC floe carrying the Central Observatory (CO) formed in a polynya event north of the New Siberian Islands at the beginning of December 2018. The results further indicate that sea ice in the vicinity of the CO (<40 km distance) was younger and 36 % thinner than the surrounding ice with potential consequences for ice dynamics and momentum and heat transfer between ocean and atmosphere. Sea ice surveys carried out on various reference floes in autumn 2019 verify this gradient in ice thickness, and sediments discovered in ice cores (so-called dirty sea ice) around the CO confirm contact with shallow waters in an early phase of growth, consistent with the tracking analysis. Since less and less ice from the Siberian shelves survives its first summer (Krumpen et al., 2019), the MOSAiC experiment provides the unique opportunity to study the role of sea ice as a transport medium for gases, macronutrients, iron, organic matter, sediments and pollutants from shelf areas to the central Arctic Ocean and beyond. Compared to data for the past 26 years, the sea ice encountered at the end of September 2019 can already be classified as exceptionally thin, and further predicted changes towards a seasonally ice-free ocean will likely cut off the long-range transport of ice-rafted materials by the Transpolar Drift in the future. A reduced long-range transport of sea ice would have strong implications for the redistribution of biogeochemical matter in the central Arctic Ocean, with consequences for the balance of climate-relevant trace gases, primary production and biodiversity in the Arctic Ocean. [ABSTRACT FROM AUTHOR]

Fully coupled climate models have long shown a wide range of Antarctic sea ice states and evolution over the satellite era. Here, we present a high‐level evaluation of Antarctic sea ice in 40 models from the most recent phase of the Coupled Model Intercomparison Project (CMIP6). Many models capture key characteristics of the mean seasonal cycle of sea ice area (SIA), but some simulate implausible historical mean states compared to satellite observations, leading to large intermodel spread. Summer SIA is consistently biased low across the ensemble. Compared to the previous model generation (CMIP5), the intermodel spread in winter and summer SIA has reduced, and the regional distribution of sea ice concentration has improved. Over 1979–2018, many models simulate strong negative trends in SIA concurrently with stronger‐than‐observed trends in global mean surface temperature (GMST). By the end of the 21st century, models project clear differences in sea ice between forcing scenarios. Plain Language Summary: Coupled climate models are complex computer programs that simulate the interaction of the atmosphere, ocean, land surface, and cryosphere. An important feature of the Southern Ocean is its sea ice cover, which typically expands in winter to cover an area comparable to that of Russia. Climate models have shown very different amounts of Antarctic sea ice coverage and very different trajectories of sea ice change in response to expected greenhouse gas emissions. This year, new coupled climate models released under the Coupled Model Intercomparison Project (CMIP6) will form the basis of the next IPCC assessment report. Here, we compare output from those models to satellite observations of the areal coverage of sea ice. As a whole, the models successfully capture some elements of the observed seasonal cycle of sea ice but underestimate the summer minimum sea ice area. Compared to results from the previous model generation (CMIP5), the range across models has reduced, and the location of sea ice agrees better with observations. Models project sea ice loss over the 21st century in all scenarios, but confidence in the rate of loss is limited, as most models show stronger global warming trends than observed over the recent historical period. Key Points: CMIP6‐mean Antarctic sea ice area is close to observations, but intermodel spread remains substantialWe find modest improvements in the simulation of sea ice area and concentration compared to CMIP5Most CMIP6 models simulate sea ice losses and stronger‐than‐observed GMST trends over 1979–2018 [ABSTRACT FROM AUTHOR]

The article reports that the Fifth Workshop on Systematic Errors in Weather and Climate Models was organized by Environment and Climate Change Canada under the auspices of the Working Group on Numerical Experimentation. It notes that the jointly sponsored by the Commission of Atmospheric Sciences of the World Meteorological Organization. The use of explicit simulations, such as large-eddy simulations on wide geographical domains, gives rise to new opportunities to improve parameterizations.

We discuss the performance of the Finite Element Ocean Model (FESOM) on locally eddy-resolving global unstructured meshes. In particular, the utility of the mesh design approach whereby mesh horizontal resolution is varied as half the Rossby radius in most of the model domain is explored. Model simulations on such a mesh (FESOM-XR) are compared with FESOM simulations on a smaller-size mesh, where refinement depends only on the pattern of observed variability (FESOM-HR). We also compare FESOM results to a simulation of the ocean model of the Max Planck Institute for Meteorology (MPIOM) on a tripolar regular grid with refinement toward the poles, which uses a number of degrees of freedom similar to FESOM-XR. The mesh design strategy, which relies on the Rossby radius and/or the observed variability pattern, tends to coarsen the resolution in tropical and partly subtropical latitudes compared to the regular MPIOM grid. Excessive variations of mesh resolution are found to affect the performance in other nearby areas, presumably through dissipation that increases if resolution is coarsened. The largest improvement shown by FESOM-XR is a reduction of the surface temperature bias in the so-called North-West corner of the North Atlantic Ocean where horizontal resolution was increased dramatically. However, other biases in FESOM-XR remain largely unchanged compared to FESOM-HR. We conclude that resolving the Rossby radius alone (with two points per Rossby radius) is insufficient, and that careful use of a priori information on eddy dynamics is required to exploit the full potential of ocean models on unstructured meshes. [ABSTRACT FROM AUTHOR]

The ice strength parameter P* is a key parameter in dynamic/thermodynamic sea ice models that cannot be measured directly. Stochastically perturbing P* in the Finite Element Sea Ice-Ocean Model (FESOM) of the Alfred Wegener Institute aims at investigating the effect of uncertainty pertaining to this parameterization. Three different approaches using symmetric perturbations have been applied: 1) reassignment of uncorrelated noise fields to perturb P* at every grid point, 2) a Markov chain time correlation, and 3) a Markov chain time correlation with some spatial correlation between nodes. Despite symmetric perturbations, results show an increase of Arctic sea ice volume and a decrease of Arctic sea ice area for all three approaches. In particular, the introduction of spatial correlation leads to a substantial increase in sea ice volume and mean thickness. The strongest response can be seen for multiyear ice north of the Greenland coast. An ensemble of eight perturbed simulations generates a spread in the multiyear ice comparable to the interannual variability of the model. Results cannot be reproduced by a simple constant global modification of P*. [ABSTRACT FROM AUTHOR]

Existing CMIP-type climate scenario simulations are known to be vulnerable to model errors which are most noticeable in the North Atlantic. These errors are generally attributed to the imperfectness of parameterizations and the lack of ocean model resolution. However, resolving ocean mesoscales globally requires high computational resources. An alternative is to use climate models operating on unstructured meshes, allowing one to vary spatial model resolution in a way that ocean eddy dynamics is explicitly resolved only in most energetically important places. The FESOM-ECHAM climate setup offers this variable mesh functionality for the ocean. The successor version of the Finite-volumE Sea ice–Ocean circulation Model (FESOM v.2.0) has been recently released and is based on the finite volume approach with the cell centered placement of horizontal velocities (quasi-B-grid). It ensures a significant improvement in the computational performance of the ocean component (by a factor of 3 compared to the previous version). In the current work we validate the FESOM2-ECHAM climate setup using HighResMIP protocol and different ocean resolutions in the otherwise unchanged climate configurations. In particular we compare coarse and eddy-resolving ocean setups and analyze the related differences in the simulated North Atlantic climate. [ABSTRACT FROM AUTHOR]