Search Results
(compared to the channel width), the flow is still approximately steady and thus a poor stirrer. The three methods employed to study transport and stirring give results that are both consistent and complementary. It was found that the geometry of the stable manifold at time t = 0 is associated with the regime of behavior. It also divides the flow field into areas of short, long, and infinite residence times. FSLE maps indicate where stirring is maximum: a comparison between the average FSLE values
(compared to the channel width), the flow is still approximately steady and thus a poor stirrer. The three methods employed to study transport and stirring give results that are both consistent and complementary. It was found that the geometry of the stable manifold at time t = 0 is associated with the regime of behavior. It also divides the flow field into areas of short, long, and infinite residence times. FSLE maps indicate where stirring is maximum: a comparison between the average FSLE values
, however, Nof et al. (2011) present a synthesis of the paleosouthern wind data suggesting that their approximately linear relationship holds on longer time scales as well. (Specifically, they examined the variations in the strength of the Agulhas retroflection during glacial periods.) Fig . 1. A global map showing the location of two cores used in the study. They provide proxies for the following: 1) Southern Winds (Palmer Deep core; Domack et al. 2001 ), and 2) flow through the BS (core HLY0501-JPC
, however, Nof et al. (2011) present a synthesis of the paleosouthern wind data suggesting that their approximately linear relationship holds on longer time scales as well. (Specifically, they examined the variations in the strength of the Agulhas retroflection during glacial periods.) Fig . 1. A global map showing the location of two cores used in the study. They provide proxies for the following: 1) Southern Winds (Palmer Deep core; Domack et al. 2001 ), and 2) flow through the BS (core HLY0501-JPC
Reynolds stresses, Eulerian shears, and Stokes drift shears in Eqs. (6) and (7) in cases LT45 and LT90 to algebraically compute ν t s and ν t (top panels, Fig. 6 ). For both cases LT45 and LT90, ν t s and ν t are different throughout most depths except near the surface. In addition, the ratio of ν t s to ν t differs for the two cases, illustrating its sea-state dependency (blue solid lines, bottom panels, Fig. 6 ). For comparison, we utilize the ARSM developed by Harcourt (2015
Reynolds stresses, Eulerian shears, and Stokes drift shears in Eqs. (6) and (7) in cases LT45 and LT90 to algebraically compute ν t s and ν t (top panels, Fig. 6 ). For both cases LT45 and LT90, ν t s and ν t are different throughout most depths except near the surface. In addition, the ratio of ν t s to ν t differs for the two cases, illustrating its sea-state dependency (blue solid lines, bottom panels, Fig. 6 ). For comparison, we utilize the ARSM developed by Harcourt (2015
any geographic location and any instant of time, without relying on assumptions of homogeneity or isotropy. It can be used to analyze nonlinear processes, detect and measure energy transfer rates between oceanic structures, and map out energy pathways from ocean altimetry and model data. This paper presents an implementation of coarse-graining analysis for the quantification of oceanic energy flow across spatial scales. Our results indicate that the consequences of the assumption of statistical
any geographic location and any instant of time, without relying on assumptions of homogeneity or isotropy. It can be used to analyze nonlinear processes, detect and measure energy transfer rates between oceanic structures, and map out energy pathways from ocean altimetry and model data. This paper presents an implementation of coarse-graining analysis for the quantification of oceanic energy flow across spatial scales. Our results indicate that the consequences of the assumption of statistical
finding the actual positions of the surfaces in the model domain. Even in the case of the prognostic level models, validation of these models can only be made by comparison with data from the real ocean. It must be borne in mind that the strong lateral mixing of these prognostic models occurs along neutral surfaces. As such, maps of properties along neutral surfaces and the heights of neutral surfaces are the most relevant variables from the real ocean to be compared with the model output
finding the actual positions of the surfaces in the model domain. Even in the case of the prognostic level models, validation of these models can only be made by comparison with data from the real ocean. It must be borne in mind that the strong lateral mixing of these prognostic models occurs along neutral surfaces. As such, maps of properties along neutral surfaces and the heights of neutral surfaces are the most relevant variables from the real ocean to be compared with the model output
several FZs along an irregular grid ( Fig. 1 ), some regions of the inverse domain correspond to regions that were sparsely sampled. There is no survey data in the northeast and southeast corners of the 19°–25°S, 14°–22°W inverse domain, so the mapped properties in these regions are poorly constrained. The inverse estimates in these sparsely sampled regions will receive minimal attention. d. Linear algebraic equations The fitted hydrographic fields and the dissipation data were used to assemble a
several FZs along an irregular grid ( Fig. 1 ), some regions of the inverse domain correspond to regions that were sparsely sampled. There is no survey data in the northeast and southeast corners of the 19°–25°S, 14°–22°W inverse domain, so the mapped properties in these regions are poorly constrained. The inverse estimates in these sparsely sampled regions will receive minimal attention. d. Linear algebraic equations The fitted hydrographic fields and the dissipation data were used to assemble a
, the vector c = ( c x , c y ) indicates the tangential direction of the trajectory and therefore, is parallel to the absolute velocity vector, V = γ ( x, y, ρ ) c , (11) where the absolute value of γ is the speed, | γ | = | V |. c. Determination of the proportionality γ Applying the thermal wind relation (4) to any two different isopycnal levels ρ k and ρ m , a set of algebraic equations for determining the parameter r is obtained: which are two linear algebraic equations for γ ( k
, the vector c = ( c x , c y ) indicates the tangential direction of the trajectory and therefore, is parallel to the absolute velocity vector, V = γ ( x, y, ρ ) c , (11) where the absolute value of γ is the speed, | γ | = | V |. c. Determination of the proportionality γ Applying the thermal wind relation (4) to any two different isopycnal levels ρ k and ρ m , a set of algebraic equations for determining the parameter r is obtained: which are two linear algebraic equations for γ ( k
cross-shelf coordinate. Results are presented for a range ofvalues of the region d/mension and the fr/ct/on coeffident. Comparisons are made between the analytical modeland recent observagons of the wind-driven ~ow in the northern Great Barrier Reef.1. Introduction The generation of coastal-trapped waves by windstress has been extensively studied over the last twentyyears, both observationally and theoretically (see, forinstance, the reviews by Allen, 1980); Mysak, 1980;and Csanady, 1982). Most
cross-shelf coordinate. Results are presented for a range ofvalues of the region d/mension and the fr/ct/on coeffident. Comparisons are made between the analytical modeland recent observagons of the wind-driven ~ow in the northern Great Barrier Reef.1. Introduction The generation of coastal-trapped waves by windstress has been extensively studied over the last twentyyears, both observationally and theoretically (see, forinstance, the reviews by Allen, 1980); Mysak, 1980;and Csanady, 1982). Most
b and the residual overturning circulation ψ † within the channel. For the typical circulation in the Southern Ocean driven by the westerly winds, surface buoyancy distribution across the channel, set in the mixed layer, is mapped through interior of the channel to its northern edge. To complete the problem, boundary conditions at the base of the mixed layer and at the northern edge of the channel need to be specified. At the base of the mixed layer, at z = 0, we assume that buoyancy
b and the residual overturning circulation ψ † within the channel. For the typical circulation in the Southern Ocean driven by the westerly winds, surface buoyancy distribution across the channel, set in the mixed layer, is mapped through interior of the channel to its northern edge. To complete the problem, boundary conditions at the base of the mixed layer and at the northern edge of the channel need to be specified. At the base of the mixed layer, at z = 0, we assume that buoyancy
through averages on quasi-homogeneous subdataset, we propose here a data processing technique to separate the whole dataset in classes of trajectories morphologically homogeneous and characterized by different regimes of dispersion and by different qualitative behavior of the velocity correlation function. The statistical properties computed averaging on such subdatasets are then used, first, to investigate kinematics relations in the different regimes and, second, to map in the geographical space the
through averages on quasi-homogeneous subdataset, we propose here a data processing technique to separate the whole dataset in classes of trajectories morphologically homogeneous and characterized by different regimes of dispersion and by different qualitative behavior of the velocity correlation function. The statistical properties computed averaging on such subdatasets are then used, first, to investigate kinematics relations in the different regimes and, second, to map in the geographical space the
