2014
DOI: 10.1016/j.ocemod.2014.03.004
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Abstract: a b s t r a c tWe provide an assessment of sea level simulated in a suite of global ocean-sea ice models using the interannual CORE atmospheric state to determine surface ocean boundary buoyancy and momentum fluxes. These CORE-II simulations are compared amongst themselves as well as to observation-based estimates. We focus on the final 15 years of the simulations (1993)(1994)(1995)(1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007), as this is a period where the CORE-II atmospheric state … Show more

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Cited by 113 publications
(151 citation statements)
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References 133 publications
(378 reference statements)
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“…In most CMIP5 models, the ocean module is based on the Boussinesq approximation and conserves volume rather than mass (Griffies and Greatbatch 2012). As a consequence, the zos output of CMIP5 models is computed from the ocean volume conservation equation rather than the mass conservation equation and does not include the effect of the global mean thermal expansion (Greatbatch 1994;Griffies and Greatbatch 2012).…”
Section: A Contribution From Dynamic Sea Levelmentioning
confidence: 99%
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“…In most CMIP5 models, the ocean module is based on the Boussinesq approximation and conserves volume rather than mass (Griffies and Greatbatch 2012). As a consequence, the zos output of CMIP5 models is computed from the ocean volume conservation equation rather than the mass conservation equation and does not include the effect of the global mean thermal expansion (Greatbatch 1994;Griffies and Greatbatch 2012).…”
Section: A Contribution From Dynamic Sea Levelmentioning
confidence: 99%
“…In most CMIP5 models, the ocean module is based on the Boussinesq approximation and conserves volume rather than mass (Griffies and Greatbatch 2012). As a consequence, the zos output of CMIP5 models is computed from the ocean volume conservation equation rather than the mass conservation equation and does not include the effect of the global mean thermal expansion (Greatbatch 1994;Griffies and Greatbatch 2012). To correct for this, we estimate the global averaged thermosteric sea level from the monthly 3D temperature fields (''thetao'' output) of the CMIP5 models (we do not use the ''zostoga'' field, which is inconsistent between models in particular because of the use of different global masks in different climate model simulations; see Part I) and we add it to the zos fields.…”
Section: A Contribution From Dynamic Sea Levelmentioning
confidence: 99%
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“…The dominant feature of observed RSL change in the altimeter period is the contrast of rising sea level in the west and falling in the east in the Pacific, due to changes in wind stress forcing [149,150]. It has been argued that unforced variability associated with the Pacific Decadal Oscillation (PDO) [151][152][153][154] contributes to this pattern, although Frankcombe et al [155] found that the relationship between the sea level pattern and the PDO is not statistically robust in short observational records.…”
Section: Regional Projections and Emergence Time Of The Forced Signalmentioning
confidence: 99%
“…For example, papers of the CORE-II virtual special issue of the Ocean Modelling Journal, such as Danabasoglu et al (2014Danabasoglu et al ( , 2016; Downes et al (2015); Farneti et al (2015); Griffies et al (2014); Wang et al (2016a, b), and of the ORA-IP special issue of the Climate Dynamics Journal, such as Chevallier et al (2015), are particularly relevant for this study. As the majority of CORE-II and ORA-IP ocean model configurations, our grid configuration (ORCA1) does not resolve ocean eddies.…”
Section: Introductionmentioning
confidence: 99%