Description: 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 per- iod from 1948 to 2007 and are performed as contributions to the second phase of the Coordinated Ocean- ice Reference Experiments (CORE-II). The protocol for conducting such CORE-II experiments is summa- rized. 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 contribu- tors 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 vertica 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 con- sidered, the majority of the models appear suitable for use in studies involving the North Atlantic, but some models require dedicated development effort.

Description: Author Posting. © The Author(s), 2010. This is the author's version of the work. It is posted here by permission of Elsevier B.V. for personal use, not for redistribution. The definitive version was published in Ocean Modelling 34 (2010): 70-91, doi:10.1016/j.ocemod.2010.04.006.

Description: We have found a new way to express the solutions of the RSM (Reynolds Stress Model) equations that allows us to present the turbulent diffusivities for heat, salt and momentum in a way that is considerably simpler and thus easier to implement than in previous work. The RSM provides the dimensionless mixing efficiencies Γα (α stands for heat, salt and momentum). However, to compute the diffusivities, one needs additional information, specifically, the dissipation ε. Since a dynamic equation for the latter that includes the physical processes relevant to the ocean is still not available, one must resort to different sources of information outside the RSM to obtain a complete Mixing Scheme usable in OGCMs. As for the RSM results, we show that the Γα’s are functions of both Ri and Rρ (Richardson number and density ratio representing double diffusion, DD); the Γα are different for heat, salt and momentum; in the case of heat, the traditional value Γh = 0.2 is valid only in the presence of strong shear (when DD is inoperative) while when shear subsides, NATRE data show that Γh can be three times as large, a result that we reproduce. The salt Γs is given in terms of Γh. The momentum Γm has thus far been guessed with different prescriptions while the RSM provides a well defined expression for Γm (Ri, Rρ). Having tested Γh, we then test the momentum Γm by showing that the turbulent Prandtl number Γm/Γh vs. Ri reproduces the available data quite well. As for the dissipation ε, we use different representations, one for the mixed layer (ML), one for the thermocline and one for the ocean’s bottom. For the ML, we adopt a procedure analogous to the one successfully used in PB (planetary boundary layer) studies; for the thermocline, we employ an expression for the variable εN-2 from studies of the internal gravity waves spectra which includes a latitude dependence; for the ocean bottom, we adopt the enhanced bottom diffusivity expression used by previous authors but with a state of the art internal tidal energy formulation and replace the fixed Γα = 0.2 with the RSM result that brings into the problem the Ri,Rρ dependence of the Γα; the unresolved bottom drag, which has thus far been either ignored or modeled with heuristic relations, is modeled using a formalism we previously developed and tested in PBL studies. We carried out several tests without an OGCM. Prandtl and flux Richardson numbers vs. Ri. The RSM model reproduces both types of data satisfactorily. DD and Mixing efficiency Γh (Ri, Rρ). The RSM model reproduces well the NATRE data. Bimodal ε-distribution. NATRE data show that ε (Ri〈1) ≈10ε(Ri〉1), which our model reproduces. Heat to salt flux ratio. In the Ri〉〉1 regime, the RSM predictions reproduce the data satisfactorily. NATRE mass diffusivity. The z-profile of the mass diffusivity reproduces well the measurements at NATRE. The local form of the mixing scheme is algebraic with one cubic equation to solve.