a b s t r a c tSimulation 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.

pnas.0509057102), the numerical scales corresponding to the color bars in Figs. 2, 4, and 5 appeared incorrectly, due to a printer's error. The corrected figures and their legends appear below.

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[1] The IPCC AR4 global warming climate simulations reveal a pronounced seasonality of polar warming amplification with maximum warming amplification in winter and minimum in summer. In this paper, we study the relative importance of surface albedo feedback (SAF), changes in cloud radiative forcing (CRF), changes in surface sensible and latent heat fluxes, changes in heat storage, and changes in the clear-sky downward infrared radiation in causing the strong seasonality of polar warming amplification by calculating partial temperature changes due to each of these processes using the surface energy budget equation. The main thermodynamic factor for a small polar warming amplification in summer is that the positive SAF is largely cancelled out by the negative surface CRF feedback in summer. The positive SAF is relatively much weaker in winter compared to its amplitude in summer, therefore does not contribute to the pronounced polar warming amplification in winter. The seasonal cycle of polar surface warming amplification, in terms of both spatial patterns and temporal amplitude, closely follows the seasonal cycle of the warming due to changes in clear-sky downward longwave radiation alone, indicating the importance of the atmospheric processes, such as water vapor feedback and dynamical feedbacks associated with the enhancement of poleward moist static energy transport, in causing the pronounced seasonality of polar warming amplification.

International audienceSimulated 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

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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 is well sampled, and it allows us to compare sea level related fields to both satellite and in situ analyses. The ensemble mean of the CORE-II simulations broadly agree with various global and regional observation-based analyses during this period, though with the global mean thermosteric sea level rise biased low relative to observation-based analyses. The simulations reveal a positive trend in dynamic sea level in the west Pacific and negative trend in the east, with this trend arising from wind shifts and regional changes in upper 700 m ocean heat content. The models also exhibit a thermosteric sea level rise in the subpolar North Atlantic associated with a transition around 1995/1996 of the Atlantic Oscillation to its negative phase, and the advection of warm subtropical waters into the subpolar gyre. Sea level trends are predominantly associated with steric trends, with thermosteric effects generally far larger than halosteric effects, except in the Arctic and North Atlantic. There is a general anticorrelation between thermosteric and halosteric effects for much of the World Ocean, associated with density compensated changes.Published by Elsevier Ltd.

The Arctic Ocean simulated in fourteen global ocean-sea ice models in the framework of the Coordinated Ocean-ice Reference Experiments, phase II (CORE II) is analyzed in this study. The focus is on the Arctic liquid freshwater (FW) sources and freshwater content (FWC). The models agree on the interannual variability of liquid FW transport at the gateways where the ocean volume transport determines the FW transport variability. The variation of liquid FWC is induced by both the surface FW flux(associated with sea ice production) and lateral liquid FW transport, which are in phase when averaged on decadal time scales. The liquid FWC shows an increase starting from the mid-1990s, caused by the reduction of both sea ice formation and liquid FW export, with the former being more significant in most of the models. The mean state of the FW budget is less consistently simulated than the temporal variability. The model ensemble means of liquid FW transport through the Arctic gateways compare well with observations. On average, the models have too high mean FWC, weaker upward trends of FWC in the recent decade than the observation, and low consistency in the temporal variation of FWC spatial distribution, which needs to be further explored for the purpose of model development.Dear editor, The paper has been revised according to the reviewers' comments. The reply letters are enclosed separately.Thank you for your help during the review process. Yours sincerely the authors Cover LetterDear reviewer, Thank you for your helpful comments. The replies to your comments are given below.Minor comments: 1.Page 3, line 36: I would add "upper mixed layer" before "sea ice." reply: added (line 36) 2.Page 9, the top paragraph: I would skip it entirely. Reply: we decide to keep this short paragraph, because it is important information about the models.3.Page 9, second paragraph: I would skip "It is obvious that." reply: Now it writes as "The information in Table 2 Reply: SSH appears earlier in the text. Now we introduce this abbreviation when it appears the first time.12. Figure 11: The authors may modify figure increasing its readability: a) for all panels but very bottom labels for months and caption "Month" can be removed; b) geographical names may be moved inside the panels. (a) and (b) will release a lot of space which can be used to decrease overall size of figure. "Freshwater transports" and "Volume transports" may be placed at the center of the columns. *Revision NotesReply: We now only leave x-label and caption "Month" at the very bottom of the figure, and put "Freshwater transports" and "Volume transports" to the center of the columns. We keep the panel names at the top of each panel for readability.13. Figure