Description: Extracted nonstationary oscillations and nonlinear trends of precipitation and sea surface temperature (SST) data reveal that rainfall variability in Mexico City is mainly composed by a long‐term positive trend, a multidecadal oscillation highly correlated with the Atlantic Multidecadal Oscillation (AMO), and year‐to‐year variability. The precipitation trend, lasting for more than a century, cannot be attributed to global warming or urbanization alone; rather, it can be thought of as part of a natural oscillation composed of alternating wet‐dry anomalies with a period of a couple of centuries, as past evidence indicates. To further test the dependence of the AMO‐related component, yearly SST time series were derived from a simplified model of the atmosphere‐ocean system forced by white noise. The simulated SST time series exhibits AMO‐like variability entirely consistent with the observed one, implying that North Atlantic SST multidecadal variability can be seen as the integrated response of surface ocean layers to external stochastic atmospheric forcing.

Description: Extreme ocean warming events, known as marine heatwaves (MHWs), have been observed to perturb significantly marine ecosystems and fisheries around the world. Here, we propose a detection method for long-lasting and large-scale summer MHWs, using a local, climatological 99th percentile threshold, based on present-climate (1976–2005) daily SST. To assess their future evolution in the Mediterranean Sea we use, for the first time, a dedicated ensemble of fully-coupled Regional Climate System Models from the Med-CORDEX initiative and a multi-scenario approach. The models appear to simulate well MHW properties during historical period, despite biases in mean and extreme SST. In response to increasing green- house gas forcing, the events become stronger and more intense under RCP4.5 and RCP8.5 than RCP2.6. By 2100 and under RCP8.5, simulations project at least one long-lasting MHW every year, up to three months longer, about 4 times more intense and 42 times more severe than present-day events. They are expected to occur from June-October and to affect at peak the entire basin. Their evolution is found to occur mainly due to an increase in the mean SST, but increased daily SST variability also plays a noticeable role. Until the mid-21st century, MHW characteristics rise independently of the choice of the emission scenario, the influence of which becomes more evident by the end of the period. Further analysis reveals e change responses in certain configurations, more likely linked to their driving global climate model rather to the individual model biases.

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: Arctic sea-ice area and volume have substantially decreased since the beginning of the satellite era. Concurrently, the pole-ward heat transport from the North Atlantic Ocean into the Arctic has increased, partly contributing to the loss of sea ice. Increasing the horizontal resolution of general circulation models (GCMs) improves their ability to represent the complex interplay of processes at high latitudes. Here, we investigate the impact of model resolution on Arctic sea ice and Atlantic Ocean heat transport (OHT) by using five different state-of-the-art coupled GCMs (12 model configurations in total) that include dynamic representations of the ocean, atmosphere and sea ice. The models participate in the High Resolution Model Intercomparison Project (HighResMIP) of the sixth phase of the Coupled Model Intercomparison Project (CMIP6). Model results over the period 1950–2014 are compared to different observational datasets. In the models studied, a finer ocean resolution drives lower Arctic sea-ice area and volume and generally enhances Atlantic OHT. The representation of ocean surface characteristics, such as sea-surface temperature (SST) and velocity, is greatly improved by using a finer ocean reso-lution. This study highlights a clear anticorrelation at interannual time scales between Arctic sea ice (area and volume) and Atlantic OHT north of 60 ◦N in the models studied. However, the strength of this relationship is not systematically impacted by model resolution. The higher the latitude to compute OHT, the stronger the relationship between sea-ice area/volume and OHT. Sea ice in the Barents/Kara and Greenland–Iceland–Norwegian (GIN) Seas is more strongly connected to Atlantic OHT than other Arctic seas.

Description: Models from phase 5 of the Coupled Model Inter-comparison 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 Al-fred Wegener Institute, Helmholtz Centre for Polar and Ma-rine Research, which employs a sea ice–ocean model com-ponent 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 im-provements 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 re-gions 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 outcrop-ping 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 per-form 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.

Description: The intensity of sediment resuspension and sedimentation in the eastern part of the Bothnian Bay near the Hanhikivi cape, where the nuclear power plant ‘Hanhikivi-1’ will be constructed, has been assessed for the first time by means of numerical modeling under the realistic external forcing that occurred in 2014. A brief description of a coupled modeling system used in the study is given. The results of local resuspension intensity and sediment accumulation rates for one-year model run are presented. It has been determined that the main areas of sediment accumulation are located along the northern coast off the Hanhikivi peninsula and in the shallow region situated to the north-east off the cape. Sedimentation rates in the navigation channel have also been estimated. Model results obtained for 2014 suggest that sedimentation in the seaward part of the channel is absent, while sediment accumulation intensity is about 10 cm/year in the middle part of the channel and 70 cm/year in the coastal part. A temporal variability of the sedimentation rates during the year has been emphasized.

Description: 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.

Description: For the first time for CORDEX-South Asia, a high-resolution regional earth system model (ROM) is adopted to assess the impact of horizontal resolution (0.22◦ and 0.11◦) in simulating the Indian summer monsoon rainfall (ISMR) and the underlying spatiotemporal variability. ROM at both resolutions bears a close resemblance to observations in simulating the mean precipitation climatology compared to other regional climate models (RCMs) participated in CORDEX- South Asia. ROM shows substantial improvement relative to the ensemble mean of the RCMs included in CORDEX-South Asia. While comparing both simulations with observations, some sys-tematic wet and dry bias over Central India (CI) and Northern Western Ghats is noticed. In general, the wet/dry bias over India is mainly associated with the overestimation/underestimation of the large-scale/convective component. Increasing horizontal resolution from 0.22◦ to 0.11◦ significantly adds value in simulating the JJAS mean precipitation by reducing the wet bias over western central India (WCI) and southern peninsular India and dry bias over eastern CI. The reduction in wet/dry bias is mainly associated with suppression/enhancement of the large scale/convective precipitation. This improvement in mean precipitation is partially due to the improved representation of the propagation of mesoscale systems such as boreal summer intraseasonal oscilla-tion (eastward and northward). Despite the above improvements, the wet precipitation bias, particularly over WCI, persists. The weaker Findlater Jet associated with weaker land-ocean thermal contrast caused by the warm sea surface temperature (SST) bias over the western Arabian Sea (AS) suggests that AS moisture transport does not contribute to the wet bias over India. The wet bias is possibly associated with favourable atmospheric conditions (atmospheric instability).

Description: Strong offshore wind events (SOWEs) occur frequently near the Antarctic coast during austral winter. These wind events are typically associated with passage of synoptic- or meso-scale cyclones, which interact with the katabatic wind field and affect sea ice and oceanic processes in coastal polynyas. Based on numerical simulations from the coupled Finite Element Sea-ice Ocean Model (FESOM) driven by the CORE-II forcing, two coastal polynyas along the East Antarctica coast––the Prydz Bay Polynya and the Shackleton Polynya are selected to examine the response of sea ice and oceanic properties to SOWEs. In these polynyas, the southern or western flanks of cyclones play a crucial role in increasing the offshore winds depending on the local topography. Case studies for both polynyas show that during SOWEs, when the wind speed is 2–3 times higher than normal values, the offshore component of sea ice velocity can increase by 3–4 times. Sea ice concentration can decrease by 20–40%, and sea ice production can increase up to two to four folds. SOWEs increase surface salinity variability and mixed layer depth, and such effects may persist for 5–10 days. Formation of high salinity shelf water (HSSW) is detected in the coastal regions from surface to 800 m after 10–15 days of the SOWEs, while the HSSW features in deep layers exhibit weak response on the synoptic time scale. HSSW formation averaged over winter is notably greater in years with longer duration of SOWEs.

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.