Influence of fast ice on future ice shelf melting in the Totten Glacier area, East Antarctica

The Totten Glacier in East Antarctica is of major climatic interest because of the large fluctuations in its grounding line and potential vulnerability to climate change. Here, we use a series of high-resolution, regional NEMO-LIM-based (Nucleus for European Modelling of the Ocean coupled with the Louvain-la-Neuve sea ice model) experiments, which include an explicit treatment of ocean–ice shelf interactions, as well as a representation of grounded icebergs and fast ice, to investigate the changes in ocean–ice interactions in the Totten Glacier area between the recent past (1995–2014) and the end of the 21st century (2081–2100) under SSP4–4.5 climate change conditions. By the end of the 21st century, the wide areas of multiyear fast ice simulated in the recent past are replaced by small patches of first year fast ice along the coast, which decreases the total summer sea ice extent. The Antarctic Slope Current is accelerated by about 116 %, which decreases the heat exchange across the shelf and tends to reduce the ice shelf basal melt rate, but this effect is counterbalanced by the effect of the oceanic warming. As a consequence, despite the accelerated Antarctic Slope Current, the Totten ice shelf melt rate is increased by 91 % due to the intrusion of warmer water into its cavity. The representation of fast ice dampens the ice shelf melt rate increase throughout the 21st century, as the Totten ice shelf melt rate increase reaches 136 % when fast ice is not taken into account. The Moscow University ice shelf melt rate increase is even more impacted by the representation of fast ice, with a 36 % melt rate increase with fast ice, compared to a 75 % increase without a fast ice representation. This influence of the representation of fast ice in our simulations on the basal melting rate trend over the 21st century is explained by the large impact of the fast ice for present-day conditions (∼25 % difference in m yr−1), while the impact decreases significantly at the end of the 21st century (∼4 % difference in m yr−1). As a consequence, the reduction in the fast ice extent in the future induces a decrease in the fast ice effect on the ice shelf melt rate that partly compensates for the increase due to warming of the ocean. This highlights the importance of including a representation of fast ice to simulate realistic ice shelf melt rate increase in East Antarctica under warming conditions.</p

Influence of fast ice on future ice shelf melting in the Totten Glacier area, East Antarctica

The Totten Glacier in East Antarctica is of major climatic interest because of the large fluctuations in its grounding line and potential vulnerability to climate change. Here, we use a series of high-resolution, regional NEMO-LIM-based (Nucleus for European Modelling of the Ocean coupled with the Louvain-la-Neuve sea ice model) experiments, which include an explicit treatment of ocean–ice shelf interactions, as well as a representation of grounded icebergs and fast ice, to investigate the changes in ocean–ice interactions in the Totten Glacier area between the recent past (1995–2014) and the end of the 21st century (2081–2100) under SSP4–4.5 climate change conditions. By the end of the 21st century, the wide areas of multiyear fast ice simulated in the recent past are replaced by small patches of first year fast ice along the coast, which decreases the total summer sea ice extent. The Antarctic Slope Current is accelerated by about 116 %, which decreases the heat exchange across the shelf and tends to reduce the ice shelf basal melt rate, but this effect is counterbalanced by the effect of the oceanic warming. As a consequence, despite the accelerated Antarctic Slope Current, the Totten ice shelf melt rate is increased by 91 % due to the intrusion of warmer water into its cavity. The representation of fast ice dampens the ice shelf melt rate increase throughout the 21st century, as the Totten ice shelf melt rate increase reaches 136 % when fast ice is not taken into account. The Moscow University ice shelf melt rate increase is even more impacted by the representation of fast ice, with a 36 % melt rate increase with fast ice, compared to a 75 % increase without a fast ice representation. This influence of the representation of fast ice in our simulations on the basal melting rate trend over the 21st century is explained by the large impact of the fast ice for present-day conditions (∼25 % difference in m yr−1), while the impact decreases significantly at the end of the 21st century (∼4 % difference in m yr−1). As a consequence, the reduction in the fast ice extent in the future induces a decrease in the fast ice effect on the ice shelf melt rate that partly compensates for the increase due to warming of the ocean. This highlights the importance of including a representation of fast ice to simulate realistic ice shelf melt rate increase in East Antarctica under warming conditions.</p

The 1600 CE Huaynaputina eruption as a possible trigger for persistent cooling in the North Atlantic region

Paleoclimate reconstructions have identified a period of exceptional summer and winter cooling in the North Atlantic region following the eruption of the tropical volcano Huaynaputina (Peru) in 1600 CE. A previous study based on numerical climate simulations has indicated a potential mechanism for the persistent cooling in a slowdown of the North Atlantic subpolar gyre (SPG) and consequent ocean–atmosphere feedbacks. To examine whether this mechanism could have been triggered by the Huaynaputina eruption, this study compares the simulations used in the previous study both with and without volcanic forcing and this SPG shift to reconstructions from annual proxies in natural archives and historical written records as well as contemporary historical observations of relevant climate and environmental conditions. These reconstructions and observations demonstrate patterns of cooling and sea-ice expansion consistent with, but not indicative of, an eruption trigger for the proposed SPG slowdown mechanism. The results point to possible improvements in future model–data comparison studies utilizing historical written records. Moreover, we consider historical societal impacts and adaptations associated with the reconstructed climatic and environmental anomalies.This research has been supported by the Swiss National Science Foundation (grant no. P2BEP1_175214), the Swiss National Science Foundation through the SNSF Sinergia CALDERA project (grant no. CRSII5_183571), the Spanish Sci-ence and Innovation Ministry (Ministerio de Ciencia e Innovación) through the STREAM project (grant no. PID2020-114746GBI00), Fonds de la Recherche Scientifique – FNRS and the FWO under the Excellence of Science (EOS) program through the PARAMOUR project (grant no. O0100718F, EOS ID no. 30454083), and the Georgetown Environment Initiative.Peer ReviewedPostprint (published version

Impact of increased resolution on long-standing biases in HighResMIP-PRIMAVERA climate models

We examine the influence of increased resolution on four long-standing biases using five different climate models developed within the PRIMAVERA project. The biases are the warm eastern tropical oceans, the double Intertropical Convergence Zone (ITCZ), the warm Southern Ocean, and the cold North Atlantic. Atmosphere resolution increases from ∼100–200 to ∼25–50 km, and ocean resolution increases from (eddy-parametrized) to (eddy-present). For one model, ocean resolution also reaches ∘ (eddy-rich). The ensemble mean and individual fully coupled general circulation models and their atmosphere-only versions are compared with satellite observations and the ERA5 reanalysis over the period 1980–2014. The four studied biases appear in all the low-resolution coupled models to some extent, although the Southern Ocean warm bias is the least persistent across individual models. In the ensemble mean, increased resolution reduces the surface warm bias and the associated cloud cover and precipitation biases over the eastern tropical oceans, particularly over the tropical South Atlantic. Linked to this and to the improvement in the precipitation distribution over the western tropical Pacific, the double-ITCZ bias is also reduced with increased resolution. The Southern Ocean warm bias increases or remains unchanged at higher resolution, with small reductions in the regional cloud cover and net cloud radiative effect biases. The North Atlantic cold bias is also reduced at higher resolution, albeit at the expense of a new warm bias that emerges in the Labrador Sea related to excessive ocean deep mixing in the region, especially in the ORCA025 ocean model. Overall, the impact of increased resolution on the surface temperature biases is model-dependent in the coupled models. In the atmosphere-only models, increased resolution leads to very modest or no reduction in the studied biases. Thus, both the coupled and atmosphere-only models still show large biases in tropical precipitation and cloud cover, and in midlatitude zonal winds at higher resolutions, with little change in their global biases for temperature, precipitation, cloud cover, and net cloud radiative effect. Our analysis finds no clear reductions in the studied biases due to the increase in atmosphere resolution up to 25–50 km, in ocean resolution up to 0.25∘, or in both. Our study thus adds to evidence that further improved model physics, tuning, and even finer resolutions might be necessary.This research has been supported by the Horizon2020 project PRIMAVERA (H2020 GA 641727) and IS-ENES3 (H2020 GA 824084). Eduardo Moreno-Chamarro acknowledges funding from the Spanish Science and Innovation Ministry (Ministerio de Ciencia e Innovación) via the STREAM project (PID2020-114746GB-I00) and from the ESA contract CMUG-CCI3-TECHPROP. Etienne Tourigny has received funding from the European Union's Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement no. 748750 (SPFireSD project).Peer Reviewed"Article signat per 13 autors/es: Eduardo Moreno-Chamarro, Louis-Philippe Caron, Saskia Loosveldt Tomas, Javier Vegas-Regidor, Oliver Gutjahr, Marie-Pierre Moine, Dian Putrasahan, Christopher D. Roberts, Malcolm J. Roberts, Retish Senan, Laurent Terray, Etienne Tourigny, and Pier Luigi Vidale"Postprint (published version

PARASO, a circum-Antarctic fully coupled ice-sheet–ocean–sea-ice–atmosphere–land model involving f.ETISh1.7, NEMO3.6, LIM3.6, COSMO5.0 and CLM4.5

We introduce PARASO, a novel five-component fully coupled regional climate model over an Antarctic circumpolar domain covering the full Southern Ocean. The state-of-the-art models used are the fast Elementary Thermomechanical Ice Sheet model (f.ETISh) v1.7 (ice sheet), the Nucleus for European Modelling of the Ocean (NEMO) v3.6 (ocean), the Louvain-la-Neuve sea-ice model (LIM) v3.6 (sea ice), the COnsortium for Small-scale MOdeling (COSMO) model v5.0 (atmosphere) and its CLimate Mode (CLM) v4.5 (land), which are here run at a horizontal resolution close to 1/4°. One key feature of this tool resides in a novel two-way coupling interface for representing ocean–ice-sheet interactions, through explicitly resolved ice-shelf cavities. The impact of atmospheric processes on the Antarctic ice sheet is also conveyed through computed COSMO-CLM–f.ETISh surface mass exchange. In this technical paper, we briefly introduce each model's configuration and document the developments that were carried out in order to establish PARASO. The new offline-based NEMO–f.ETISh coupling interface is thoroughly described. Our developments also include a new surface tiling approach to combine open-ocean and sea-ice-covered cells within COSMO, which was required to make this model relevant in the context of coupled simulations in polar regions. We present results from a 2000–2001 coupled 2-year experiment. PARASO is numerically stable and fully operational. The 2-year simulation conducted without fine tuning of the model reproduced the main expected features, although remaining systematic biases provide perspectives for further adjustment and development.This research has been supported by the Fonds De La Recherche Scientifique – FNRS (grant no. O0100718F).Peer ReviewedArticle signat per 23 autors/es: Charles Pelletier (1), Thierry Fichefet (1), Hugues Goosse (1), Konstanze Haubner (2), Samuel Helsen (3), Pierre-Vincent Huot (1), Christoph Kittel (4), François Klein (1), Sébastien Le clec'h (5), Nicole P. M. van Lipzig (3), Sylvain Marchi (3), François Massonnet (1), Pierre Mathiot (6,7), Ehsan Moravveji (3,8), Eduardo Moreno-Chamarro (9), Pablo Ortega (9), Frank Pattyn (2), Niels Souverijns (3,10), Guillian Van Achter (1), Sam Vanden Broucke (3), Alexander Vanhulle (5), Deborah Verfaillie (1), and Lars Zipf (2) // (1) Earth and Life Institute (ELI), UCLouvain, Louvain-la-Neuve, Belgium / (2) Laboratoire de Glaciologie, Université Libre de Bruxelles, Brussels, Belgium / (3) Department of Earth and Environmental Sciences, KU Leuven, Leuven, Belgium / (4) Laboratory of Climatology, Department of Geography, SPHERES, University of Liège, Liège, Belgium / (5) Earth System Science and Departement Geografie, Vrije Universiteit Brussel, Brussels, Belgium, (6) Met Office, Exeter, United Kingdom / (7) Université Grenoble Alpes/CNRS/IRD/G-INP, IGE, Grenoble, France / (8) ICTS, KU Leuven, Leuven, Belgium / (9) Barcelona Supercomputing Center (BSC), Barcelona, Spain / (10) Environmental Modelling Unit, Flemish Institute for Technological Research (VITO), Mol, BelgiumPostprint (published version

Improving Arctic weather and seasonal climate prediction: recommendations for future forecast systems evolution from the European project APPLICATE

The Arctic environment is changing, increasing the vulnerability of local communities and ecosystems, and impacting its socio-economic landscape. In this context, weather and climate prediction systems can be powerful tools to support strategic planning and decision-making at different time horizons. This article presents several success stories from the H2020 project APPLICATE on how to advance Arctic weather and seasonal climate prediction, synthesizing the key lessons learned throughout the project and providing recommendations for future model and forecast system development.The results discussed in this article were supported by the project APPLICATE (727862), funded by the European Union's Horizon 2020 research and innovation programme. PO was additionally supported by the Spanish fellowship RYC-2017-22772.Peer ReviewedArticle signat per 29 autors/es: Pablo Ortega (1), Edward W. Blockley (2), Morten Køltzow (3), François Massonnet (4), Irina Sandu (5), Gunilla Svensson (6), Juan C. Acosta Navarro (1), Gabriele Arduini (5), Lauriane Batté (7), Eric Bazile (7), Matthieu Chevallier (8), Rubén Cruz-García (1), Jonathan J. Day (5), Thierry Fichefet (4), Daniela Flocco (9), Mukesh Gupta (4), Kerstin Hartung (6,10), Ed Hawkins (9), Claudia Hinrichs (11), Linus Magnusson (5), Eduardo Moreno-Chamarro (1), Sergio Pérez-Montero (1), Leandro Ponsoni (4), Tido Semmler (11), Doug Smith (2), Jean Sterlin (4), Michael Tjernström (6), Ilona Välisuo (7,12), and Thomas Jung (11,13) // (1) Barcelona Supercomputing Center, Barcelona, Spain | (2) Met Office, Exeter, UK | (3) Norwegian Meteorological Institute, Oslo, Norway | (4) Université catholique de Louvain, Earth and Life Institute, Georges Lemaître Centre for Earth and Climate Research, Louvain-la-Neuve, Belgium | (5) European Centre for Medium-Range Weather Forecasts, Reading, UK | (6) Department of Meteorology, Stockholm University, Stockholm, Sweden | (7) CNRM, Université de Toulouse, Météo-France, CNRS, Toulouse, France | (8) Météo-France, Toulouse, France | (9) National Centre for Atmospheric Science, Department of Meteorology, University of Reading, Reading, UK. | (10) Now at: Deutsches Zentrum für Luft- und Raumfahrt, Institut für Physik der Atmosphäre, Oberpfaffenhofen, Germany | (11) Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven, Germany | (12) Now at: Meteorology Unit, Finnish Meteorological Institute, Helsinki, Finland | (13) Department of Physics and Electrical Engineering, University of Bremen, Bremen, GermanyPostprint (published version

Atlantic circulation change still uncertain

Deep oceanic overturning circulation in the Atlantic (Atlantic Meridional Overturning Circulation, AMOC) is projected to decrease in the future in response to anthropogenic warming. Caesar et al. 1 argue that an AMOC slowdown started in the 19 th century and intensified during the mid-20th century. Although the argument and selected evidence proposed have some merits, we find that their conclusions might be different if a more complete array of data available in the North Atlantic region had been considered. We argue that the strength of AMOC over recent centuries is still poorly constrained and the expected slowdown may not have started yet.K.H.K. acknowledges funding from NOAA grant NA20OAR4310481. D.E.A. and B.L.O.-B. acknowledge support from the National Center for Atmospheric Research, which is a major facility sponsored by the National Science Foundation under cooperative agreement no. 1852977. N.M.W. acknowledges support from a NOAA Climate and Global Change Postdoctoral Fellowship. M.F.J. acknowledges support from NSF award OCE-1846821 and C.M.L. acknowledges support from NSF award OCE-1805029. This is UMCES contribution 6062.Peer ReviewedArticle signat per 17 autors/es: University of Maryland Center for Environmental Science, Chesapeake Biological Laboratory, Solomons, MD, USA: K. Halimeda Kilbourne / Department of Geological and Atmospheric Sciences, Iowa State University, Ames, IA, USA: Alan D. Wanamaker / Geography Department, Durham University, Durham, UK: Paola Moffa-Sanchez / Centre for Geography and Environmental Sciences, University of Exeter, Penryn, UK: David J. Reynolds, Paul G. Butler & James Scourse / Climate and Global Dynamics Laboratory, National Center for Atmospheric Research, Boulder, CO, USA: Daniel E. Amrhein & Bette L. Otto-Bliesner / Woods Hole Oceanographic Institution, Falmouth, MA, USA: Geoffrey Gebbie & Nina M. Whitney / Cooperative Institute for Marine and Atmospheric Studies, University of Miami, Miami, FL, USA: Marlos Goes / Atlantic Oceanographic and Meteorological Laboratory, National Oceanic and Atmospheric Administration, Miami, FL, USA: Marlos Goes / Department of the Geophysical Sciences, The University of Chicago, Chicago, IL, USA: Malte F. Jansen / Oceanography Department, Atmospheric and Environmental Research, Inc., Texas, TX, USA: Christopher M. Little / US Geological Survey, St Petersburg Coastal and Marine Science Center, St Petersburg, FL, USA: Madelyn Mette / Barcelona Supercomputing Center, Barcelona, Spain: Eduardo Moreno-Chamarro & Pablo Ortega / Graduate School of Oceanography, University of Rhode Island, Kingston, RI, USA: Thomas Rossby / University Corporation of Atmospheric Research, Boulder, CO, USA: Nina M. WhitneyPostprint (author's final draft)Matters Arising published on 17 February 2022. The Original Article was published on 25 February 2021

Connecting Paleo and Modern Oceanographic Data to Understand Atlantic Meridional Overturning Circulation Over Decades to Centuries

Modeling is an important tool for understanding AMOC on all timescales. Mechanistic studies of modern AMOC variability have been hampered by a lack of consistency between free-running models and the sensitivity of AMOC to resolution and parameterization. Recent work within the framework of the phase two Coordinated Ocean- Reference Experiments (CORE-II) addresses this issue head on, looking at model differences of AMOC mean state and interannual variability. One consistent feature across the models is that AMOC mean transport is related to mixed layer depths and Labrador Sea salt content, whereas interannual variability is primarily associated with Labrador Sea temperature anomalies. This is consistent with the hypothesized importance of salt balance for AMOC variability on geological timescales. The simulated relationships between AMOC and subsurface temperature anomalies in fully coupled climate models reveal subsurface AMOC fingerprints that could be used to reconstruct historical AMOC variations at low frequency.With the lack of long-term AMOC observations, models of ocean state that assimilate observational data have been explored as a way to reconstruct AMOC, but comparisons between models indicate they are quite variable in their AMOC representations. Karspeck et al. (2015) found that historical reconstructions of AMOC in such models are sensitive to the details of the data assimilation procedure. The ocean data assimilation community continues to address these issues through improved models and methods for estimating and representing error information.Two objectives of paleoclimate modeling are 1) to provide mechanistic information for interpretation of paleoclimate observations, and 2) to test the ability of predictive models to simulate Earth's climate under different background forcing states. In a good example of the first objective, Schmittner and Lund (2015) and Menviel et al. (2014) provided key information about the proxy signals expected under freshwater disturbance of AMOC, which were used to support the paleoclimate observations made by Henry et al. (2016). In an example of the second objective, Muglia and Schmittner (2015) analyzed Third Paleoclimate Modeling Intercomparison Project (PMIP3) models of the Last Glacial Maximum (LGM) and found consistently more intense and deeper AMOC transports relative to preindustrial simulations, counter to the paleoclimate consensus of LGM conditions, indicating that some processes are not well represented in the PMIP3 models. One challenge is to find adequate paleo observations against which to test these models. PMIP is now in phase 4 (part of CMIP6), which includes experiments covering five periods in Earth's history: the last millennium, last glacial maximum, last interglacial, and the mid-Pliocene. Newly compiled paleoclimate datasets from the PAGES2k project, more transient simulations, and participation of isotope enabled models planned for CMIP6PMIP4 will enable richer paleo data-model comparisons in the near future

The EC-Earth3 Earth system model for the Coupled Model Intercomparison Project 6

The Earth system model EC-Earth3 for contributions to CMIP6 is documented here, with its flexible coupling framework, major model configurations, a methodology for ensuring the simulations are comparable across different high-performance computing (HPC) systems, and with the physical performance of base configurations over the historical period. The variety of possible configurations and sub-models reflects the broad interests in the EC-Earth community. EC-Earth3 key performance metrics demonstrate physical behavior and biases well within the frame known from recent CMIP models. With improved physical and dynamic features, new Earth system model (ESM) components, community tools, and largely improved physical performance compared to the CMIP5 version, EC-Earth3 represents a clear step forward for the only European community ESM. We demonstrate here that EC-Earth3 is suited for a range of tasks in CMIP6 and beyond.The development of EC-Earth3 was supported by the European Union's Horizon 2020 research and innovation program under project IS-ENES3, the third phase of the distributed e-infrastructure of the European Network for Earth System Modelling (ENES) (grant agreement no. 824084, PRIMAVERA grant no. 641727, and CRESCENDO grant no. 641816). Etienne Tourigny and Raffaele Bernardello have received funding from the European Union’s Horizon 2020 research and innovation program under Marie Skłodowska-Curie grant agreement nos. 748750 (SPFireSD project) and 708063 (NeTNPPAO project). Ivana Cvijanovic was supported by Generalitat de Catalunya (Secretaria d'Universitats i Recerca del Departament d’Empresa i Coneixement) through the Beatriu de Pinós program. Yohan Ruprich-Robert was funded by the European Union's Horizon 2020 research and innovation program in the framework of Marie Skłodowska-Curie grant INADEC (grant agreement 800154). Paul A. Miller, Lars Nieradzik, David Wårlind, Roland Schrödner, and Benjamin Smith acknowledge financial support from the strategic research area “Modeling the Regional and Global Earth System” (MERGE) and the Lund University Centre for Studies of Carbon Cycle and Climate Interactions (LUCCI). Paul A. Miller, David Wårlind, and Benjamin Smith acknowledge financial support from the Swedish national strategic e-science research program eSSENCE. Paul A. Miller further acknowledges financial support from the Swedish Research Council (Vetenskapsrådet) under project no. 621-2013-5487. Shuting Yang acknowledges financial support from a Synergy Grant from the European Research Council under the European Community's Seventh Framework Programme (FP7/2007-2013)/ERC (grant agreement 610055) as part of the ice2ice project and the NordForsk-funded Nordic Centre of Excellence project (award 76654) ARCPATH. Marianne Sloth Madsen acknowledges financial support from the Danish National Center for Climate Research (NCKF). Andrea Alessandri and Peter Anthoni acknowledge funding from the Helmholtz Association in its ATMO program. Thomas Arsouze, Arthur Ramos, and Valentina Sicardi received funding from the Ministerio de Ciencia, Innovación y Universidades as part of the DeCUSO project (CGL2017-84493-R).​​​​​​​Peer Reviewed"Article signat per 61 autors/es: Ralf Döscher, Mario Acosta, Andrea Alessandri, Peter Anthoni, Thomas Arsouze, Tommi Bergman, Raffaele Bernardello, Souhail Boussetta, Louis-Philippe Caron, Glenn Carver, Miguel Castrillo, Franco Catalano, Ivana Cvijanovic, Paolo Davini, Evelien Dekker, Francisco J. Doblas-Reyes, David Docquier, Pablo Echevarria, Uwe Fladrich, Ramon Fuentes-Franco, Matthias Gröger, Jost v. Hardenberg, Jenny Hieronymus, M. Pasha Karami, Jukka-Pekka Keskinen, Torben Koenigk, Risto Makkonen, François Massonnet, Martin Ménégoz, Paul A. Miller, Eduardo Moreno-Chamarro, Lars Nieradzik, Twan van Noije, Paul Nolan, Declan O'Donnell, Pirkka Ollinaho11, Gijs van den Oord, Pablo Ortega, Oriol Tintó Prims, Arthur Ramos, Thomas Reerink, Clement Rousset, Yohan Ruprich-Robert, Philippe Le Sager, Torben Schmith, Roland Schrödner, Federico Serva, Valentina Sicardi, Marianne Sloth Madsen, Benjamin Smith, Tian Tian, Etienne Tourigny, Petteri Uotila, Martin Vancoppenolle, Shiyu Wang, David Wårlind, Ulrika Willén, Klaus Wyser, Shuting Yang, Xavier Yepes-Arbós, and Qiong Zhang"Postprint (author's final draft

Sensitivity of the Atlantic meridional overturning circulation to model resolution in CMIP6 HighResMIP simulations and implications for future changes

A multi‐model, multi‐resolution ensemble using CMIP6 HighResMIP coupled experiments is used to assess the performance of key aspects of the North Atlantic circulation. The Atlantic Meridional Overturning Circulation (AMOC), and related heat transport, tends to become stronger as ocean model resolution is enhanced, better agreeing with observations at 26.5°N. However for most models the circulation remains too shallow compared to observations, and has a smaller temperature contrast between the northward and southward limbs of the AMOC. These biases cause the northward heat transport to be systematically too low for a given overturning strength. The higher resolution models also tend to have too much deep mixing in the subpolar gyre. In the period 2015‐2050 the overturning circulation tends to decline more rapidly in the higher resolution models, which is related to both the mean state and to the subpolar gyre contribution to deep water formation. The main part of the decline comes from the Florida Current component of the circulation. Such large declines in AMOC are not seen in the models with resolutions more typically used for climate studies, suggesting an enhanced risk for Northern Hemisphere climate change. However, only a small number of different ocean models are included in the study