ALBERT

Description: Based on analysis of observational data it has been suggested that a negative feedback of ice–ocean stress coupling may limit freshwater accumulation in the Beaufort Gyre (BG). In this paper we explore how this feedback can significantly contribute to BG stabilization in an anticyclonic wind regime. We use an ice–ocean model and turn on and off the feedback in simulations to elucidate the role of the feedback. When a persistent anticyclonic wind anomaly is applied over the BG, liquid freshwater content (FWC) increases because of enhanced Ekman downwelling. As a consequence, ocean surface geostrophic currents speed up. However, the spinup of sea ice is weaker than the acceleration of surface geostrophic currents during wintertime, because of strong sea ice internal stress when ice concentration is high and ice is thick. This leads to cyclonic anomalies in the ice–ocean relative velocity and stress over the BG. The resultant seasonal Ekman upwelling anomaly reduces freshwater accumulation by about 1/4 as compared to a simulation with the negative feedback turned off in a control experiment, with a reduction range of 1/10–1/3 in all experiments conducted. We show that the feedback is more effective when the model’s mesoscale eddy diffusivity is smaller or when sea ice internal stress is stronger. Finally, we argue that the ice–ocean stress feedback may become less significant as the Arctic warms and sea ice declines.

Description: The freshwater stored in the Arctic Ocean is an important component of the global climate system. Currently the Arctic liquid freshwater content (FWC) has reached a record high since the beginning of the last century. In this study we use numerical simulations to investigate the impact of sea ice decline on the Arctic liquid FWC and its spatial distribution. The global unstructured-mesh ocean general circulation model Finite Element Sea Ice–Ocean Model (FESOM) with 4.5-km horizontal resolution in the Arctic region is applied. The simulations show that sea ice decline increases the FWC by freshening the ocean through sea ice meltwater and modifies upper ocean circulation at the same time. The two effects together significantly increase the freshwater stored in the Amerasian basin and reduce its amount in the Eurasian basin. The salinification of the upper Eurasian basin is mainly caused by the reduction in the proportion of Pacific Water and the increase in that of Atlantic Water (AW). Consequently, the sea ice decline did not significantly contribute to the observed rapid increase in the Arctic total liquid FWC. However, the changes in the Arctic freshwater spatial distribution indicate that the influence of sea ice decline on the ocean environment is remarkable. Sea ice decline increases the amount of Barents Sea branch AW in the upper Arctic Ocean, thus reducing its supply to the deeper Arctic layers. This study suggests that all the dynamical processes sensitive to sea ice decline should be taken into account when understanding and predicting Arctic changes.

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: Coupled Model Intercomparison Project Phase 6 (CMIP6) data sets: ScenarioMIP. These data include all datasets published for 'CMIP6.ScenarioMIP.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: Ocean mass variability on timescales of months to decades is still insufficiently understood. On these timescales, large-scale ocean bottom pressure (OBP) anomalies are associated both with wind induced variability as well as baroclinic processes, i.e. related to vertical shear of ocean density. The GRACE mission has been instrumental in quantifying such mass fluctuations, yet its lifetime is limited. The broader importance of non-tidal ocean mass variability for oceanography but also geodesy (i.e. for understanding the time-varying geoid, shape of the Earth's crust, centre of figure, Earth rotation) is obvious. Deep ocean processes can only be understood properly when not only sea surface height and upper ocean steric expansion are measured but deep ocean pressure anomalies are accounted for in addition. Apart from GRACE, the SWARM constellation may provide information on the lowest degrees of the time-variable gravity field of the Earth and therefore of large-scale oceanic processes. Here we introduce the project CONTIM, which is run in the framework of the German Special Priority Programme "Dynamic Earth" (SPP1788). In CONTIM we propose to combine expertise on precise satellite orbit determination, gravity field and mass modelling, and physical oceanography to retrieve, analyse and verify consistent time series of ocean mass variations from a set of low-flying Earth orbiters including GRACE, but extending the GRACE time series. This information is used to advance our understanding of oceanic movement, ocean warming and sea level rise. CONTIM will thus synergistically address three areas: (1) the methodology of precisely determining LEO orbits, applied here to the SWARM constellation. (2) a new method of retrieving large-scale time-varying gravity (TVG) and mass change associated with oceanic (and cryospheric and hydrological) processes from results of (1), based on forward modelling. (3) physical modelling of ocean mass variations, both for improved forward modelling in (2) and for integration with satellite-geodetic retrieved ocean mass, and aiding in the determination of a final consistent modelling of sea level rise, ocean warming and oceanic mass budget. In this contribution, we will give an overview of the objectives of the project and provide some first results. We will highlight the technical challenges associated with the computation of kinematic SWARM orbits. Furthermore, different scenarios for time-variable gravity field retrieval are tested and evaluated, and the CHAMP data are used to test the methods over a longer period. To better understand and parameterize the ocean mass signals, we will discuss output from a high resolution version of the ocean model FESOM forced with tides, surface winds and atmospheric pressure.

Description: 〈jats:p〉Arctic Ocean gateway fluxes play a crucial role in linking the Arctic with the global ocean and affecting climate and marine ecosystems. We reviewed past studies on Arctic–Subarctic ocean linkages and examined their changes and driving mechanisms. Our review highlights that radical changes occurred in the inflows and outflows of the Arctic Ocean during the 2010s. Specifically, the Pacific inflow temperature in the Bering Strait and Atlantic inflow temperature in the Fram Strait hit record highs, while the Pacific inflow salinity in the Bering Strait and Arctic outflow salinity in the Davis and Fram straits hit record lows. Both the ocean heat convergence from lower latitudes to the Arctic and the hydrological cycle connecting the Arctic with Subarctic seas were stronger in 2000–2020 than in 1980–2000. CMIP6 models project a continuing increase in poleward ocean heat convergence in the 21st century, mainly due to warming of inflow waters. They also predict an increase in freshwater input to the Arctic Ocean, with the largest increase in freshwater export expected to occur in the Fram Strait due to both increased ocean volume export and decreased salinity. Fram Strait sea ice volume export hit a record low in the 2010s and is projected to continue to decrease along with Arctic sea ice decline. We quantitatively attribute the variability of the volume, heat, and freshwater transports in the Arctic gateways to forcing within and outside the Arctic based on dedicated numerical simulations and emphasize the importance of both origins in driving the variability.〈/jats:p〉