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1. OMIP contribution to CMIP6: Experimental and diagnostic protocol for the physical component of the Ocean Model Intercomparison Project

Author

Griffies, SM, Danabasoglu, G, Durack, PJ, Adcroft, AJ, Balaji, V, Böning, CW, Chassignet, EP, Curchitser, E, Deshayes, J, Drange, H, Fox-Kemper, B, Gleckler, PJ, Gregory, JM, Haak, H, Hallberg, RW, Heimbach, P, Hewitt, HT, Holland, DM, Ilyina, T, Jungclaus, JH, Komuro, Y, Krasting, JP, Large, WG, Marsland, SJ, Masina, S, McDougall, TJ, George Nurser, AJ, Orr, JC, Pirani, A, Qiao, F, Stouffer, RJ, Taylor, KE, Treguier, AM, Tsujino, H, Uotila, P, Valdivieso, M, Wang, Q, Winton, M, Yeager, SG, Griffies, SM, Danabasoglu, G, Durack, PJ, Adcroft, AJ, Balaji, V, Böning, CW, Chassignet, EP, Curchitser, E, Deshayes, J, Drange, H, Fox-Kemper, B, Gleckler, PJ, Gregory, JM, Haak, H, Hallberg, RW, Heimbach, P, Hewitt, HT, Holland, DM, Ilyina, T, Jungclaus, JH, Komuro, Y, Krasting, JP, Large, WG, Marsland, SJ, Masina, S, McDougall, TJ, George Nurser, AJ, Orr, JC, Pirani, A, Qiao, F, Stouffer, RJ, Taylor, KE, Treguier, AM, Tsujino, H, Uotila, P, Valdivieso, M, Wang, Q, Winton, M, and Yeager, SG

Abstract

© Author(s) 2016. The Ocean Model Intercomparison Project (OMIP) is an endorsed project in the Coupled Model Intercomparison Project Phase 6 (CMIP6). OMIP addresses CMIP6 science questions, investigating the origins and consequences of systematic model biases. It does so by providing a framework for evaluating (including assessment of systematic biases), understanding, and improving ocean, sea-ice, tracer, and biogeochemical components of climate and earth system models contributing to CMIP6. Among the WCRP Grand Challenges in climate science (GCs), OMIP primarily contributes to the regional sea level change and near-term (climate/decadal) prediction GCs. OMIP provides (a) an experimental protocol for global ocean/sea-ice models run with a prescribed atmospheric forcing; and (b) a protocol for ocean diagnostics to be saved as part of CMIP6. We focus here on the physical component of OMIP, with a companion paper (Orr et al., 2016) detailing methods for the inert chemistry and interactive biogeochemistry. The physical portion of the OMIP experimental protocol follows the interannual Coordinated Ocean-ice Reference Experiments (CORE-II). Since 2009, CORE-I (Normal Year Forcing) and CORE-II (Interannual Forcing) have become the standard methods to evaluate global ocean/sea-ice simulations and to examine mechanisms for forced ocean climate variability. The OMIP diagnostic protocol is relevant for any ocean model component of CMIP6, including the DECK (Diagnostic, Evaluation and Characterization of Klima experiments), historical simulations, FAFMIP (Flux Anomaly Forced MIP), C4MIP (Coupled Carbon Cycle Climate MIP), DAMIP (Detection and Attribution MIP), DCPP (Decadal Climate Prediction Project), ScenarioMIP, HighResMIP (High Resolution MIP), as well as the ocean/sea-ice OMIP simulations.

Published
2016

2. Wind ringing of the ocean in presence of mesoscale eddies

Author

Klein, Patrice, Lapeyre, Guillaume, Large, Wg, Klein, Patrice, Lapeyre, Guillaume, and Large, Wg

Abstract

Recent findings have highlighted the impact of high frequency (HF) winds on the inertial motions and the consequences on the large-scale oceanic circulation [Wunsch and Ferrari, 2004]. Within this context the present study focuses on the role of intermediate scales related to oceanic mesoscale eddies. Results show that a turbulent eddy field does not affect the impact of HF winds on the inertial motions. However the eddies efficiently and permanently concentrate the wind-forced inertial motions in small-scale anticyclonic structures. This leads to a spatially heterogeneous vertical mixing strongly related to the eddy field properties.

Published
2004
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3. An assessment of Southern Ocean water masses and sea ice during 1988–2007 in a suite of interannual CORE-II simulations

Author

Claus W. Böning, Simon J. Marsland, Lavinia Patara, Riccardo Farneti, Maxwell Kelley, A. M. Howard, David A. Bailey, Hiroyuki Tsujino, Jianhua Lu, Helge Drange, Matthew C. Long, Vittorio Canuto, Mats Bentsen, Nikolay Diansky, Stephen M. Griffies, Bonita L. Samuels, Anatoly Gusev, Erik Behrens, A. J. George Nurser, Qiang Wang, Dmitry Sidorenko, Alexandra Bozec, Eric P. Chassignet, Arne Biastoch, Gokhan Danabasoglu, Sergey Danilov, Paul Spence, Antonio Navarra, Simona Masina, Pier Giuseppe Fogli, Petteri Uotila, Mehmet Ilicak, Thomas Jung, Akhilesh Mishra, Daohua Bi, Stephanie M. Downes, Anthony Leboissetier, William G. Large, Stephen Yeager, Downes SM, Farneti R, Uotila P, Griffies SM, Marsland SJ, Bailey D, Behrens E, Bentsen M, Bi DH, Biastoch A, Boning C, Bozec A, Canuto VM, Chassignet E, Danabasoglu G, Danilov S, Diansky N, Drange H, Fogli PG, Gusev A, Howard A, Ilicak M, Jung T, Kelley M, Large WG, Leboissetier A, Long M, Lu JH, Masina S, Mishra A, Navarra A, Nurser AJG, Patara L, Samuels BL, Sidorenko D, Spence P, Tsujino H, Wang Q, and Yeager SG

Subjects
Atmospheric Science, geography, Ocean observations, geography.geographical_feature_category, Mixed layer, Antarctic sea ice, Geotechnical Engineering and Engineering Geology, Oceanography, Southern Ocean, CORE-II experiments, Water masses, Sea ice, Ocean dynamics, Sea ice thickness, Computer Science (miscellaneous), Sea ice, Environmental science, Thermohaline circulation, Ocean heat content
Abstract

We characterise the representation of the Southern Ocean water mass structure and sea ice within a suite of 15 global ocean-ice models run with the Coordinated Ocean-ice Reference Experiment Phase II (CORE-II) protocol. The main focus is the representation of the present (1988-2007) mode and intermediate waters, thus framing an analysis of winter and summer mixed layer depths; temperature, salinity, and potential vorticity structure; and temporal variability of sea ice distributions. We also consider the interannual variability over the same 20 year period. Comparisons are made between models as well as to observation-based analyses where available. The CORE-II models exhibit several biases relative to Southern Ocean observations, including an underestimation of the model mean mixed layer depths of mode and intermediate water masses in March (associated with greater ocean surface heat gain), and an overestimation in September (associated with greater high latitude ocean heat loss and a more northward winter sea-ice extent). In addition, the models have cold and fresh/warm and salty water column biases centred near 50 degrees S. Over the 1933-2007 period, the CORE-II models consistently simulate spatially variable trends in sea-ice concentration, surface freshwater fluxes, mixed layer depths, and 200-700 in ocean heat content. In particular, sea-ice coverage around most of the Antarctic continental shelf is reduced, leading to a cooling and freshening of the near surface waters. The shoaling of the mixed layer is associated with increased surface buoyancy gain, except in the Pacific where sea ice is also influential. The models are in disagreement, despite the common CORE-II atmospheric state, in their spatial pattern of the 20-year trends in the mixed layer depth and sea-ice. (C) 2015 Elsevier Ltd. All rights reserved

Published
2015

4. An assessment of Antarctic Circumpolar Current and Southern Ocean meridional overturning circulation during 1958–2007 in a suite of interannual CORE-II simulations

Author

Simon J. Marsland, Anthony Leboissetier, Steve G. Yeager, Antonio Navarra, Lavinia Patara, Vittorio Canuto, Simona Masina, Daohua Bi, Pier Giuseppe Fogli, Matthew C. Long, Mehmet Ilicak, Stephanie M. Downes, Eric P. Chassignet, Mats Bentsen, A. J. George Nurser, William G. Large, Riccardo Farneti, Petteri Uotila, Sergey Danilov, Anatoly Gusev, Maxwell Kelley, Akhilesh Mishra, Claus W. Böning, Robert Hallberg, Hiroyuki Tsujino, Jianhua Lu, Dmitry Sidorenko, Alexandra Bozec, Gokhan Danabasoglu, Thomas Jung, A. M. Howard, Nikolay Diansky, Stephen M. Griffies, Helge Drange, Bonita L. Samuels, Erik Behrens, Qiang Wang, Arne Biastoch, Farneti R, Downes SM, Griffies SM, Marsland SJ, Behrens E, Bentsen M, Bi DH, Biastoch A, Boning C, Bozec A, Canuto VM, Chassignet E, Danabasoglu G, Danilov S, Diansky N, Drange H, Fogli PG, Gusev A, Hallberg RW, Howard A, Ilicak M, Jung T, Kelley M, Large WG, Leboissetier A, Long M, Lu JH, Masina S, Mishra A, Navarra A, Nurser AJG, Patara L, Samuels BL, Sidorenko D, Tsujino H, Uotila P, Wang Q, and Yeager SG

Subjects
Atmospheric Science, Momentum (technical analysis), Isopycnal, Buoyancy, 010504 meteorology & atmospheric sciences, 010505 oceanography, Advection, Mode (statistics), Mesoscale meteorology, Forcing (mathematics), engineering.material, Geotechnical Engineering and Engineering Geology, Oceanography, 01 natural sciences, 13. Climate action, Climatology, Computer Science (miscellaneous), engineering, Thermohaline circulation, 14. Life underwater, Global ocean–sea ice modeling, Model comparisons, Southern Ocean meridional overturning circulation, Antarctic Circumpolar Current, Southern Ocean dynamics, Geology, 0105 earth and related environmental sciences
Abstract

In the framework of the second phase of the Coordinated Ocean-ice Reference Experiments (CORE-II), we present an analysis of the representation of the Antarctic Circumpolar Current (ACC) and Southern Ocean meridional overturning circulation (MOC) in a suite of seventeen global ocean-sea ice models. We focus on the mean, variability and trends of both the ACC and MOC over the 1958-2007 period, and discuss their relationship with the surface forcing. We aim to quantify the degree of eddy saturation and eddy compensation in the models participating in CORE-II, and compare our results with available observations, previous fineresolution numerical studies and theoretical constraints. Most models show weak ACC transport sensitivity to changes in forcing during the past five decades, and they can be considered to be in an eddy saturated regime. Larger contrasts arise when considering MOC trends, with a majority of models exhibiting significant strengthening of the MOC during the late 20th and early 21st century. Only a few models show a relatively small sensitivity to forcing changes, responding with an intensified eddy-induced circulation that provides some degree of eddy compensation, while still showing considerable decadal trends. Both ACC and MOC interannual variabilities are largely controlled by the Southern Annular Mode (SAM). Based on these results, models are clustered into two groups. Models with constant or two-dimensional (horizontal) specification of the eddy-induced advection coefficient K show larger ocean interior decadal trends, larger ACC transport decadal trends and no eddy compensation in the MOC. Eddy-permitting models or models with a threedimensional time varying K show smaller changes in isopycnal slopes and associated ACC trends, and partial eddy compensation. As previously argued, a constant in time or space lc is responsible for a poor representation of mesoscale eddy effects and cannot properly simulate the sensitivity of the ACC and MOC to changing surface forcing. Evidence is given for a larger sensitivity of the MOC as compared to the ACC transport, even when approaching eddy saturation. Future process studies designed for disentangling the role of momentum and buoyancy forcing in driving the ACC and MOC are proposed. (C) 2015 Elsevier Ltd. All rights reserved.

Published
2015

5. North Atlantic simulations in Coordinated Ocean-ice Reference Experiments phase II (CORE-II). Part II: Inter-annual to decadal variability

Author

Patrick Heimbach, Aurore Voldoire, Anatoly Gusev, Alicia Karspeck, Eric P. Chassignet, Rainer Bleck, Dmitry Sidorenko, Alexandra Bozec, David Salas y Mélia, Anastasia Romanou, Who M. Kim, Gael Forget, Daohua Bi, Vittorio Canuto, Simon J. Marsland, Gokhan Danabasoglu, Simona Masina, Hiroyuki Tsujino, Stephen M. Griffies, Sophie Valcke, Jianhua Lu, Mats Bentsen, Claus W. Böning, Pier Giuseppe Fogli, Gurvan Madec, Anthony Leboissetier, Mehmet Ilicak, Anna Pirani, Thomas Jung, Igor Yashayaev, Andrew C. Coward, Maxwell Kelley, Shan Sun, Yosuke Fujii, A. J. George Nurser, Petteri Uotila, Sergey Danilov, Elodie Fernandez, Steve G. Yeager, Christophe Cassou, Nikolay Diansky, A. M. Howard, William G. Large, Helge Drange, Anne-Marie Tréguier, Bonita L. Samuels, Erik Behrens, Qiang Wang, Arne Biastoch, Riccardo Farneti, Markus Scheinert, Antonio Navarra, National Center for Atmospheric Research [Boulder] (NCAR), Helmholtz Centre for Ocean Research [Kiel] (GEOMAR), Uni Research Climate, Uni Research Ltd, Centre for Australian Weather and Climate Research (CAWCR), NASA Goddard Institute for Space Studies (GISS), NASA Goddard Space Flight Center (GSFC), Center for Ocean-Atmospheric Prediction Studies (COAPS), Florida State University [Tallahassee] (FSU), Centre Européen de Recherche et de Formation Avancée en Calcul Scientifique (CERFACS), National Oceanography Centre (NOC), Alfred-Wegener-Institut, Helmholtz-Zentrum für Polar- und Meeresforschung (AWI), Institute of Numerical Mathematics [Moscou] (INM-RAS), Russian Academy of Sciences [Moscow] (RAS), University of Bergen (UiB), Abdus Salam International Centre for Theoretical Physics [Trieste] (ICTP), Centro Euro-Mediterraneo per i Cambiamenti Climatici [Bologna] (CMCC), Massachusetts Institute of Technology (MIT), Meteorological Research Institute [Tsukuba] (MRI), Japan Meteorological Agency (JMA), NOAA Geophysical Fluid Dynamics Laboratory (GFDL), National Oceanic and Atmospheric Administration (NOAA), Pacific Northwest National Laboratory (PNNL), Nucleus for European Modeling of the Ocean (NEMO R&D ), Laboratoire d'Océanographie et du Climat : Expérimentations et Approches Numériques (LOCEAN), Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Dipartimento di Matematica e Informatica [Perugia] (DMI), Università degli Studi di Perugia = University of Perugia (UNIPG), National Oceanography Centre [Southampton] (NOC), University of Southampton, International CLIVAR, Princeton University, Centre national de recherches météorologiques (CNRM), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS), Leibniz-Institut für Meereswissenschaften (IFM-GEOMAR), Laboratoire de physique des océans (LPO), Institut de Recherche pour le Développement (IRD)-Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS), Biomedical Research Imaging Center [North Carolina] (BRIC), University of North Carolina [Chapel Hill] (UNC), University of North Carolina System (UNC)-University of North Carolina System (UNC), Danabasoglu G, Yeager SG, Kim WM, Behrens E, Bentsen M, Bi DH, Biastoch A, Bleck R, Boning C, Bozec A, Canuto VM, Cassou C, Chassignet E, Coward AC, Danilov S, Diansky N, Drange H, Farneti R, Fernandez E, Fogli PG, Forget G, Fujii Y, Griffies SM, Gusev A, Heimbach P, Howard A, Ilicak M, Jung T, Karspeck AR, Kelley M, Large WG, Leboissetier A, Lu JH, Madec G, Marsland SJ, Masina S, Navarra A, Nurser AJG, Pirani A, Romanou A, Melia DSY, Samuels BL, Scheinert M, Sidorenko D, Sun S, Treguier AM, Tsujino H, Uotila P, Valcke S, Voldoire A, Wang Q, Yashayaev I, CERFACS [Toulouse], Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Muséum national d'Histoire naturelle (MNHN)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Muséum national d'Histoire naturelle (MNHN)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Università degli Studi di Perugia (UNIPG), Institut national des sciences de l'Univers (INSU - CNRS)-Météo France-Centre National de la Recherche Scientifique (CNRS), and CERFACS

Subjects
Atmospheric Science, 010504 meteorology & atmospheric sciences, Mixed layer, Phase (waves), [PHYS.PHYS.PHYS-GEO-PH]Physics [physics]/Physics [physics]/Geophysics [physics.geo-ph], Oceanography, 01 natural sciences, Ocean model comparisons, Computer Science (miscellaneous), 14. Life underwater, Atmospheric forcing, Variability in the North Atlantic, 0105 earth and related environmental sciences, Inter-annual to decadal variability and mechanisms, Atlantic meridional overturning circulation variability, 010505 oceanography, Global ocean - sea-ice modelling, Geotechnical Engineering and Engineering Geology, Deep water, Ocean dynamics, Marine Sciences, Sea surface temperature, 13. Climate action, North Atlantic oscillation, Climatology, Global ocean – sea-ice modelling, Ocean model comparisons, Atmospheric forcing, Hydrography, Global ocean – sea-ice modelling, Geology
Abstract

Simulated inter-annual to decadal variability and trends in the North Atlantic for the 1958-2007 period from twenty global ocean - sea-ice coupled models are presented. These simulations are performed as contributions to the second phase of the Coordinated Ocean-ice Reference Experiments (CORE-II). The study is Part II of our companion paper (Danabasoglu et al., 2014) which documented the mean states in the North Atlantic from the same models. A major focus of the present study is the representation of Atlantic meridional overturning circulation (AMOC) variability in the participating models. Relationships between AMOC variability and those of some other related variables, such as subpolar mixed layer depths, the North Atlantic Oscillation (NAO), and the Labrador Sea upper-ocean hydrographic properties, are also investigated. In general, AMOC variability shows three distinct stages. During the first stage that lasts until the mid-to late-1970s, AMOC is relatively steady, remaining lower than its long-term (1958-2007) mean. Thereafter, AMOC intensifies with maximum transports achieved in the mid-to late-1990s. This enhancement is then followed by a weakening trend until the end of our integration period. This sequence of low frequency AMOC variability is consistent with previous studies. Regarding strengthening of AMOC between about the mid-1970s and the mid-1990s, our results support a previously identified variability mechanism where AMOC intensification is connected to increased deep water formation in the subpolar North Atlantic, driven by NAO-related surface fluxes. The simulations tend to show general agreement in their temporal representations of, for example, AMOC, sea surface temperature (SST), and subpolar mixed layer depth variabilities. In particular, the observed variability of the North Atlantic SSTs is captured well by all models. These findings indicate that simulated variability and trends are primarily dictated by the atmospheric datasets which include the influence of ocean dynamics from nature superimposed onto anthropogenic effects. Despite these general agreements, there are many differences among the model solutions, particularly in the spatial structures of variability patterns. For example, the location of the maximum AMOC variability differs among the models between Northern and Southern Hemispheres. (C) 2015 Elsevier Ltd. All rights reserved.

Published
2016

6. North Atlantic simulations in Coordinated Ocean-ice Reference Experiments phase II (CORE-II). Part I: Mean states

Author

Hiroyuki Tsujino, Jianhua Lu, Anatoly Gusev, David A. Bailey, Simon J. Marsland, Yosuke Fujii, Elodie Fernandez, Nikolay Diansky, Claus W. Böning, Gael Forget, Helge Drange, Anne-Marie Tréguier, Andrew C. Coward, Gokhan Danabasoglu, Mats Bentsen, Eric P. Chassignet, William G. Large, Sergey Danilov, A. J. George Nurser, Christophe Cassou, Riccardo Farneti, Bonita L. Samuels, Patrick Heimbach, David Salas y Mélia, Erik Behrens, Stephen M. Griffies, Gurvan Madec, Qiang Wang, Anthony Leboissetier, Arne Biastoch, Maxwell Kelley, Vittorio Canuto, Markus Scheinert, Aurore Voldoire, A. M. Howard, Steve G. Yeager, Thomas Jung, Petteri Uotila, Simona Masina, Pier Giuseppe Fogli, Daohua Bi, Sophie Valcke, Dmitry Sidorenko, Alexandra Bozec, Antonio Navarra, Anna Pirani, National Center for Atmospheric Research [Boulder] (NCAR), Lawrence Berkeley National Laboratory [Berkeley] (LBNL), Uni Research Climate, Uni Research Ltd, Centre for Australian Weather and Climate Research (CAWCR), Leibniz-Institut für Meereswissenschaften (IFM-GEOMAR), Center for Ocean-Atmospheric Prediction Studies (COAPS), Florida State University [Tallahassee] (FSU), NASA Goddard Institute for Space Studies (GISS), NASA Goddard Space Flight Center (GSFC), Centre Européen de Recherche et de Formation Avancée en Calcul Scientifique (CERFACS), CERFACS, National Oceanography Centre (NOC), Massachusetts Institute of Technology (MIT), NOAA Geophysical Fluid Dynamics Laboratory (GFDL), National Oceanic and Atmospheric Administration (NOAA), Nucleus for European Modeling of the Ocean (NEMO R&D ), Laboratoire d'Océanographie et du Climat : Expérimentations et Approches Numériques (LOCEAN), Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Muséum national d'Histoire naturelle (MNHN)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Muséum national d'Histoire naturelle (MNHN)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Istituto Nazionale di Geofisica e Vulcanologia - Sezione di Bologna (INGV), Istituto Nazionale di Geofisica e Vulcanologia, International CLIVAR, Princeton University, Laboratoire de physique des océans (LPO), Institut de Recherche pour le Développement (IRD)-Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS), Groupe d'étude de l'atmosphère météorologique (CNRM-GAME), Institut national des sciences de l'Univers (INSU - CNRS)-Météo France-Centre National de la Recherche Scientifique (CNRS), Alfred-Wegener-Institut, Helmholtz-Zentrum für Polar- und Meeresforschung (AWI), Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Centre national de recherches météorologiques (CNRM), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS), Danabasoglu G, Yeager SG, Bailey D, Behrens E, Bentsen M, Bi D, Biastoch A, Boning C, Bozec A, Canuto VM, Cassou C, Chassignet E, Coward AC, Danilov S, Diansky N, Drange H, Farneti R, Fernandez E, Fogli PG, Forget G, Fujii Y, Griffies SM, Gusev A, Heimbach P, Howard A, Jung T, Kelley M, Large WG, Leboissetier A, Lu J, Madec G, Marsland SJ, Masina S, Navarra A, Nurser AJG, Pirani A, Melia DSY, Samuels BL, Scheinert M, Sidorenko D, Treguier AM, Tsujino H, Uotila P, Valcke S, Voldoire A, and Wangi Q

Subjects
Atmospheric Science, 010504 meteorology & atmospheric sciences, Mixed layer, [SDU.STU.GP]Sciences of the Universe [physics]/Earth Sciences/Geophysics [physics.geo-ph], [SDE.MCG]Environmental Sciences/Global Changes, Atlantic meridional overturning circulation, [PHYS.PHYS.PHYS-GEO-PH]Physics [physics]/Physics [physics]/Geophysics [physics.geo-ph], Oceanography, 01 natural sciences, Ocean model comparisons, Computer Science (miscellaneous), Sea ice, Potential temperature, Hindcast, 14. Life underwater, Atmospheric forcing, 0105 earth and related environmental sciences, geography, geography.geographical_feature_category, 010505 oceanography, Global ocean–sea-ice modelling, Ocean model comparisons, Atmospheric forcing, Experimental design, Atlantic meridional overturning circulation, North Atlantic simulations, Albedo, Geotechnical Engineering and Engineering Geology, Snow, Experimental design, Sea surface temperature, 13. Climate action, Meridional flow, Climatology, Environmental science, Global ocean-sea-ice modelling
Abstract

Simulation characteristics from eighteen global ocean-sea-ice coupled models are presented with a focus on the mean Atlantic meridional overturning circulation (AMOC) and other related fields in the North Atlantic. These experiments use inter-annually varying atmospheric forcing data sets for the 60-year period from 1948 to 2007 and are performed as contributions to the second phase of the Coordinated Oceanice Reference Experiments (CORE-II). The protocol for conducting such CORE-II experiments is summarized. Despite using the same atmospheric forcing, the solutions show significant differences. As most models also differ from available observations, biases in the Labrador Sea region in upper-ocean potential temperature and salinity distributions, mixed layer depths, and sea-ice cover are identified as contributors to differences in AMOC. These differences in the solutions do not suggest an obvious grouping of the models based on their ocean model lineage, their vertical coordinate representations, or surface salinity restoring strengths. Thus, the solution differences among the models are attributed primarily to use of different subgrid scale parameterizations and parameter choices as well as to differences in vertical and horizontal grid resolutions in the ocean models. Use of a wide variety of sea-ice models with diverse snow and sea-ice albedo treatments also contributes to these differences. Based on the diagnostics considered, the majority of the models appear suitable for use in studies involving the North Atlantic, but some models require dedicated development effort. (C) 2013 Elsevier Ltd. All rights reserved.

Published
2014

7. Climate Process Team on Internal Wave-Driven Ocean Mixing.

Author

MacKinnon JA, Alford MH, Ansong JK, Arbic BK, Barna A, Briegleb BP, Bryan FO, Buijsman MC, Chassignet EP, Danabasoglu G, Diggs S, Griffies SM, Hallberg RW, Jayne SR, Jochum M, Klymak JM, Kunze E, Large WG, Legg S, Mater B, Melet AV, Merchant LM, Musgrave R, Nash JD, Norton NJ, Pickering A, Pinkel R, Polzin K, Simmons HL, St Laurent LC, Sun OM, Trossman DS, Waterhouse AF, Whalen CB, and Zhao Z

Abstract

Diapycnal mixing plays a primary role in the thermodynamic balance of the ocean and, consequently, in oceanic heat and carbon uptake and storage. Though observed mixing rates are on average consistent with values required by inverse models, recent attention has focused on the dramatic spatial variability, spanning several orders of magnitude, of mixing rates in both the upper and deep ocean. Away from ocean boundaries, the spatio-temporal patterns of mixing are largely driven by the geography of generation, propagation and dissipation of internal waves, which supply much of the power for turbulent mixing. Over the last five years and under the auspices of US CLIVAR, a NSF- and NOAA-supported Climate Process Team has been engaged in developing, implementing and testing dynamics-based parameterizations for internal-wave driven turbulent mixing in global ocean models. The work has primarily focused on turbulence 1) near sites of internal tide generation, 2) in the upper ocean related to wind-generated near inertial motions, 3) due to internal lee waves generated by low-frequency mesoscale flows over topography, and 4) at ocean margins. Here we review recent progress, describe the tools developed, and discuss future directions.

Published
2017
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