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

Gokhan Danabasoglu*, Steve G. Yeager, Who M. Kim, Erik Behrens, Mats Bentsen, Daohua Bi, Arne Biastoch, Rainer Bleck, Claus Böning, Alexandra Bozec, Vittorio M. Canuto, Christophe Cassou, Eric Chassignet, Andrew C. Coward, Sergey Danilov, Nikolay Diansky, Helge Drange, Riccardo Farneti, Elodie Fernandez, Pier Giuseppe FogliGael Forget, Yosuke Fujii, Stephen M. Griffies, Anatoly Gusev, Patrick Heimbach, Armando Howard, Mehmet Ilicak, Thomas Jung, Alicia R. Karspeck, Maxwell Kelley, William G. Large, Anthony Leboissetier, Jianhua Lu, Gurvan Madec, Simon J. Marsland, Simona Masina, Antonio Navarra, A. J.George Nurser, Anna Pirani, Anastasia Romanou, Salas y.Mélia David, Bonita L. Samuels, Markus Scheinert, Dmitry Sidorenko, Shan Sun, Anne Marie Treguier, Hiroyuki Tsujino, Petteri Uotila, Sophie Valcke, Aurore Voldoire, Qiang Wang, Igor Yashayaev

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129 Atıf (Scopus)

Özet

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.

Orijinal dilİngilizce
Sayfa (başlangıç-bitiş)65-90
Sayfa sayısı26
DergiOcean Modelling
Hacim97
DOI'lar
Yayın durumuYayınlandı - 1 Oca 2016
Harici olarak yayınlandıEvet

Bibliyografik not

Publisher Copyright:
© 2015 Elsevier Ltd.

Finansman

NCAR is sponsored by the U. S. National Science Foundation (NSF) . The CESM is supported by the NSF and the U. S. Department of Energy. S. G. Yeager was supported by the NOAA Climate Program Office under Climate Variability and Predictability Program grants NA09OAR4310163 and NA13OAR4310138 and by the NSF Collaborative Research EaSM2 grant OCE-1243015 to NCAR. W. M. Kim was supported by the NOAA Climate Program Office under Climate Variability and Predictability Program grant NA13OAR4310136 to Texas A&M University. ACCESS modeling work has been undertaken as part of the Australian Climate Change Science Program, funded jointly by the Department of Climate Change and Energy Efficiency, the Bureau of Meteorology and CSIRO, and was supported by the National Computational Infrastructure facility at the Australian National University. AWI is a member of the Helmholtz Association of German Research Centers. Q. Wang and D. Sidorenko were funded by the Helmholtz Climate Initiative REKLIM (Regional Climate Change) project. The BERGEN contribution was supported by the Research Council of Norway through the EarthClim (207711/E10) and NOTUR/NorStore projects, as well as the Centre for Climate Dynamics at the Bjerknes Centre for Climate Research. The CMCC contribution received funding from the Italian Ministry of Education, University, and Research and the Italian Ministry of Environment, Land, and Sea under the GEMINA project. INMOM was sponsored by the Russian Science Foundation (project number 14-27-00126 ). The KIEL contribution acknowledges support within the Co-Operative Project RACE - Regional Atlantic Circulation and Global Change funded by the German Federal Ministry for Education and Research (BMBF) under grant number 03F0651B and computing resources from the North-German Supercomputing Alliance (HLRN). P. G. Fogli thanks W. G. Large, J. Tribbia, M. Vertenstein, G. Danabasoglu, and D. Bailey for their support and help in bringing NEMO into the CESM framework while vising NCAR. E. Fernandez was supported by the BNP-Paribas foundation via the PRECLIDE project under the CNRS research convention agreement 30023488. We thank M. Harrison and R. Hallberg of GFDL for assistance with defining the GFDL-GOLD configuration, and R. Msadek and Y. M. Ruprich-Robert of GFDL for comments on an earlier version of the manuscript. Finally, we thank both the international CLIVAR and U. S. CLIVAR projects for patiently sponsoring the Working Group on Ocean Model Development (now, Ocean Model Development Panel) over the years as COREs were developed.

FinansörlerFinansör numarası
BNP-Paribas foundation
Bureau of Meteorology
Department of Climate Change and Energy Efficiency
Helmholtz Climate Initiative REKLIM
Italian Ministry of Environment, Land
NOTUR
NorStore
National Science Foundation1243015
U.S. Department of Energy
National Oceanic and Atmospheric AdministrationOCE-1243015, NA13OAR4310138, NA13OAR4310136, NA09OAR4310163
Texas A and M University
College of Natural Resources and Sciences, Humboldt State University30023488
Natural Environment Research Councilnoc010010
Commonwealth Scientific and Industrial Research Organisation
Bundesministerium für Bildung und Forschung03F0651B
Ministero dell’Istruzione, dell’Università e della Ricerca
Norges Forskningsråd207711/E10
Russian Science Foundation14-27-00126

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