Search Results
quick overview of the results. Table 1. Different dispersion regimes, conditions under which they are applicable, corresponding relative diffusivities [Eqs. (3) and (5) , section 5 , appendix C ], PDF solutions to the Fokker–Plank equation [Eq. (4) , section 4 , appendix B ], the corresponding moments ( section 4 ), and the FSLE scalings [Eq. (6) , section 6 ] ( Graff et al. 2015 ; Foussard et al. 2017 ). The square brackets note the equations and sections where the different metrics are
quick overview of the results. Table 1. Different dispersion regimes, conditions under which they are applicable, corresponding relative diffusivities [Eqs. (3) and (5) , section 5 , appendix C ], PDF solutions to the Fokker–Plank equation [Eq. (4) , section 4 , appendix B ], the corresponding moments ( section 4 ), and the FSLE scalings [Eq. (6) , section 6 ] ( Graff et al. 2015 ; Foussard et al. 2017 ). The square brackets note the equations and sections where the different metrics are
topography and on the connection to the ocean basins to the north. Over the last 20 years, it has become clear that geostrophic eddies are an additional crucial aspect of ACC dynamics ( Marshall and Speer 2012 ), but we are still far from having a theory of the ACC transport as complete as Sverdrup’s theory for the transport of the western boundary currents along continental margins ( Pedlosky 1996 ). The emerging consensus is that the ACC vertically integrated zonal transport is set by a balance of
topography and on the connection to the ocean basins to the north. Over the last 20 years, it has become clear that geostrophic eddies are an additional crucial aspect of ACC dynamics ( Marshall and Speer 2012 ), but we are still far from having a theory of the ACC transport as complete as Sverdrup’s theory for the transport of the western boundary currents along continental margins ( Pedlosky 1996 ). The emerging consensus is that the ACC vertically integrated zonal transport is set by a balance of
density (buoyancy) surfaces. Marshall and Radko (2003) used Eqs. (1) – (4) to construct a model of the overturning circulation of the SO. Their model offers useful insights into the dynamics of unblocked zonal flows. Questions remain, however, whether this and similar models are quantitatively accurate because the solution is determined by the boundary conditions at the surface, where the quasigeostrophic approximations used to derive the planetary geostrophic equations for the residual circulation
density (buoyancy) surfaces. Marshall and Radko (2003) used Eqs. (1) – (4) to construct a model of the overturning circulation of the SO. Their model offers useful insights into the dynamics of unblocked zonal flows. Questions remain, however, whether this and similar models are quantitatively accurate because the solution is determined by the boundary conditions at the surface, where the quasigeostrophic approximations used to derive the planetary geostrophic equations for the residual circulation
span the top 1900 m, are all less than 35 m thick. 1 The Interim European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-Interim; Simmons et al. 2006 ) 6-h winds and buoyancy fluxes force the model’s surface, and the Ocean Comprehensive Atlas (OCCA; Forget 2010 ) provides monthly transports, heat and salt fluxes, as well as sea ice area and thickness at the lateral boundaries. Initial model conditions are an interpolation of the 1° × 1° resolution OCCA state on 1 January 2005
span the top 1900 m, are all less than 35 m thick. 1 The Interim European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-Interim; Simmons et al. 2006 ) 6-h winds and buoyancy fluxes force the model’s surface, and the Ocean Comprehensive Atlas (OCCA; Forget 2010 ) provides monthly transports, heat and salt fluxes, as well as sea ice area and thickness at the lateral boundaries. Initial model conditions are an interpolation of the 1° × 1° resolution OCCA state on 1 January 2005
dbar, respectively. The target surface lay near the boundary between Upper and Lower Circumpolar Deep Water, about 100 m below the oxygen minimum. Hydrographic characteristics near the injection site, including front locations, were very similar to those seen in World Ocean Circulation Experiment Section P18 ( McTaggart et al. 1996 ; Talley 2007 ), which passed near this site. The initial diapycnal distribution of the tracer was measured with conventional CTD rosette casts and with a towed array
dbar, respectively. The target surface lay near the boundary between Upper and Lower Circumpolar Deep Water, about 100 m below the oxygen minimum. Hydrographic characteristics near the injection site, including front locations, were very similar to those seen in World Ocean Circulation Experiment Section P18 ( McTaggart et al. 1996 ; Talley 2007 ), which passed near this site. The initial diapycnal distribution of the tracer was measured with conventional CTD rosette casts and with a towed array
). If the diffusivity is held constant, the integral constraint yields statements about conditions on the boundary. When the diffusivity is allowed to vary in space, as in White (1977) and Marshall (1981) , the constraint can be used to yield information about the vertical structure of the eddy diffusivity. The eddy potential vorticity flux can be expressed as the sum of the eddy relative vorticity flux and the vertical divergence of eddy buoyancy fluxes (e.g., Marshall 1981 ; Vallis 2006
). If the diffusivity is held constant, the integral constraint yields statements about conditions on the boundary. When the diffusivity is allowed to vary in space, as in White (1977) and Marshall (1981) , the constraint can be used to yield information about the vertical structure of the eddy diffusivity. The eddy potential vorticity flux can be expressed as the sum of the eddy relative vorticity flux and the vertical divergence of eddy buoyancy fluxes (e.g., Marshall 1981 ; Vallis 2006
length scales thought to be responsible for diapycnal mixing in the ocean (e.g., Toole et al. 1994 ; Polzin et al. 1995 ; St. Laurent et al. 2012 ). However, the availability of these measurements is limited because of cost, the need for trained personnel, and the difficulty of deploying the instruments in rough weather conditions. As a result, a number of alternative methods of estimating κ from finescale measurements have been developed, including methods based on detecting static
length scales thought to be responsible for diapycnal mixing in the ocean (e.g., Toole et al. 1994 ; Polzin et al. 1995 ; St. Laurent et al. 2012 ). However, the availability of these measurements is limited because of cost, the need for trained personnel, and the difficulty of deploying the instruments in rough weather conditions. As a result, a number of alternative methods of estimating κ from finescale measurements have been developed, including methods based on detecting static
observations, the optimization adjusts the atmospheric variables (air temperature, specific humidity, shortwave radiation, wind velocity, and precipitation) and ocean initial conditions as well as open boundary conditions at 24.7°S. Cerovečki et al. (2011) found the air–sea heat and freshwater flux estimates obtained using adjusted atmospheric variables to be consistent with other recent estimates (e.g., Large and Yeager 2009 ). Determining the model solution by optimizing model inputs does not require
observations, the optimization adjusts the atmospheric variables (air temperature, specific humidity, shortwave radiation, wind velocity, and precipitation) and ocean initial conditions as well as open boundary conditions at 24.7°S. Cerovečki et al. (2011) found the air–sea heat and freshwater flux estimates obtained using adjusted atmospheric variables to be consistent with other recent estimates (e.g., Large and Yeager 2009 ). Determining the model solution by optimizing model inputs does not require
of the 33% simulation becomes further from the observations with time. The differences between the simulations and measurements is also expected to increase with time because of the limitations of the simulations—imperfect knowledge of initial conditions and the velocity field, static boundary conditions, and so on—compounding over time. Figure 7 shows the same observations as Fig. 6 but with simulations with diffusivities K d = 0.2, 2, and 20 m 2 s −1 as labeled and a horizontal
of the 33% simulation becomes further from the observations with time. The differences between the simulations and measurements is also expected to increase with time because of the limitations of the simulations—imperfect knowledge of initial conditions and the velocity field, static boundary conditions, and so on—compounding over time. Figure 7 shows the same observations as Fig. 6 but with simulations with diffusivities K d = 0.2, 2, and 20 m 2 s −1 as labeled and a horizontal
; Lumpkin and Pazos 2007 ; Sallée et al. 2008 ). These analyses suggest large regional variations. In the boundary currents (in the Agulhas and Brazil Currents and near the Kerguelen and Campbell Plateaus), diffusivities can reach values of 10 4 m 2 s −1 . In more quiescent regions, the diffusivities can be two orders of magnitude smaller. The DIMES floats were deployed in one such region (although they later entered the Drake Passage where they experienced much more rapid spreading). The dispersion
; Lumpkin and Pazos 2007 ; Sallée et al. 2008 ). These analyses suggest large regional variations. In the boundary currents (in the Agulhas and Brazil Currents and near the Kerguelen and Campbell Plateaus), diffusivities can reach values of 10 4 m 2 s −1 . In more quiescent regions, the diffusivities can be two orders of magnitude smaller. The DIMES floats were deployed in one such region (although they later entered the Drake Passage where they experienced much more rapid spreading). The dispersion
