1. Introduction
The motivation for the present work dates back to the paper of McDougall (1984) in which the conservation equations of heat and salt were combined in a form that did not include the dianeutral advection, leaving a balance between lateral advection along a density surface and a specific combination of the effects of mixing of both heat and salt. This motivation will be described in this introduction for the advective form of the conservation equations. To make this approach workable as an inverse method in the ocean we need to implement this combination of conservation equations in the divergence form, and this is tackled in section 2.
2. A careful linear combination of conservation equations
Equation (20) corresponds to (4) in the advective approach, and notice that, like (4), (20) does not contain dianeutral advection and that diapycnal mixing enters proportionally to the curvature of the S–Θ diagram of the vertical water columns, averaged over the area A [since (Suz − Slz) and ΔΘ correspond to Szz and Θz, respectively]. Vertical heave contributes considerable noise when evaluating Szz and Θzz but, through cancellation, does not contribute significantly to the combination of terms (ΘzSzz − SzΘzz), especially when the atlas data has been isopycnally averaged [as is the case with the atlas data of Gouretski and Koltermann (2004), which we use].
3. Diffusivities from hydrographic atlas data
Hydrographic data from the region of the North Atlantic near the Strait of Gibraltar have been taken from the atlas of Gouretski and Koltermann (2004). We have used the atlas at a horizontal resolution of ½° of longitude and latitude. Eight layers were chosen, bounded by nine neutral density surfaces, and in each of these layers we consider five areas from the Strait of Gibraltar to different salinity contours. In Fig. 1 we show S–Θ curves from the three locations (38°N, 350°E), (38°N, 345°E), and (38°N, 340°E). The easternmost cast has a salinity maximum close to a neutral density of γn = 27.70 kg m−3, but the salinity maximum rises to less dense surfaces as one moves along the tongue to the west. As explained by McDougall and Giles (1987), such a diapycnal migration of a salinity maximum should not automatically be interpreted as implying asymmetric vertical mixing processes since salinity itself is an asymmetric variable. Another way of looking at this issue is to form a salinity anomaly variable that represents the presence of Mediterranean Water with respect to a background North Atlantic water mass field that exists in the rest of the North Atlantic. This variable has isolines that rise about 15°C for every unit increase in salinity, and the maximum of this anomaly variable does not so obviously move across isopycnals.
Based on the curvature of the casts at (38°N, 350°E) and (38°N, 345°E) we see that the peak salinity occurs at a density of approximately γn = 27.65 kg m−3 and take this to be the central neutral density of the Mediterranean outflow. We will henceforth consider the hydrography between neutral densities of 27.50 and 27.80 kg m−3 in order to capture the majority of the outflow, consistent with the work of Baringer and Price (1997).
Looking closely at the S–Θ cast at (38°N, 350°E) we notice a “dented” section between the neutral densities 27.6 and 27.7. This dent represents a discontinuity in the curvature and is consistent with the observation that the Mediterranean Water does tend to have a strong signature on two distinct density surfaces (sometimes called two “cores”) close to the outflow region [as reviewed by Baringer and Price (1997)]. To minimize the influence of this vertical variation of S–Θ curvature we choose S0 contours well away from the Gulf of Cadiz; that is, we choose contours that extend west of 340°E.
On the density surface γn = 27.70 kg m−3 we show (Fig. 2) the five S0 contours that are used as bounds for five overlapping areas on this density surface. For the other density interfaces used in this study we chose S0 contours at the locations of the arrow tips in Fig. 2, thus forming regions of roughly equivalent areas on each density surface. In this way we have chosen S0 contours passing through longitudes 332°, 336.5°, 338°, 340°, and 341.5°E, each at 35.5°N, on neutral density surfaces of 27.5, 27.55, 27.6, 27.65, 27.7, 27.725, 27.75, 27.775, and 27.8. Thus we have five sets of areas on each of eight density layers, giving 40 equations of the form (20). Note that the density intervals were chosen to give approximately equal vertical spacing (dbar) between layers. We have limited the area of our calculations to being west of 351°E in order to exclude the region of complicated geometry and complex mixing processes close to the Strait of Gibraltar and north of the Iberian Peninsula. Factoring in these areas would marginally increase the surface area and contour length, but we would expect it to produce a negligible change in our results. Table 1 gives the areas and lengths along the S0 and Θ0 contours corresponding to the largest area on Fig. 2. The salinity and conservative temperature of the Mediterranean Water entering each layer, SM and ΘM, are taken to be the maximum values close to (36°N, 352°E), which is close to the easternmost point of our dataset and the position of maximum salinity and conservative temperature.
Baringer and Price (1997) describe the Mediterranean outflow as it descends from the Strait of Gibraltar. After the bulk of the mixing and entrainment has occurred, the volume flux of “Mediterranean Water” into the North Atlantic is estimated as 1.52 Sv (Sv ≡ 106 m3 s−1). Based on this paper we take this as the transport of the outflow once it has stopped actively entraining and that this outflow was distributed vertically over a range of neutral densities of 0.75 kg m−3 centered at approximately γn = 27.65 kg m−3. Plots of salinity and temperature on our surfaces affirm this range of densities. Hence we approximate the distribution of the flow as a sine wave with zeros at neutral densities of 27.65 ± 0.375 kg m−3 and an integral between this region equalling 1.52 Sv. Figure 3 shows the volume flux that is assumed to flow into each density bin of width 0.05 kg m−3. We use only the central half of the density range shown in Fig. 3, and the actual volume flux into our densest three layers is half that shown, simply because those layers have a density “width” of only 0.025 kg m−3. Baringer and Price’s estimate has been gathered from mooring data, and, although it is indeed not exact, we take it as a known for the purposes of this study. The sensitivity of changes in Q of ±10% is explored later in this section, and it is emphasized that the solutions for K and D are proportional to the magnitude of Q.
In Table 2 we present the three relevant coefficients that appear in (20) for each of the 40 areas considered (5 contours times 8 layers). The upper set of 40 numbers are of ∫S0h(ΔS∇γΘ − ΔΘ∇γS) · n dl, which multiplies K in (20); the middle set are of A〈(Θuz − Θlz)ΔS − (Suz − Slz)ΔΘ〉, which multiplies D in (20); and the third set of coefficients are of Q(ΔΘ[SM − S0] − ΔS[ΘM − Θ0]), which multiplies F in (20).
We argue in the appendix that F lies in the range 0.85 < F < 1.0, or F = 0.925 ± 0.075, and in what follows actually take F to be unity because the uncertainty in estimating Q is considered to be larger than that associated with estimating F. Hence we will consider the left-hand side of (20) to be known for each of our 40 equations. As a first step, one might assume that the diffusivities K and D do not vary in space, either laterally or vertically. Then we have 40 equations in just two unknowns and find that the overdetermined least squares solution is K = 481 ± 114 m2 s−1 and D = 2.2 × 10−5 ± 7.5 × 10−5 m2 s−1. The estimate of the standard error of K was found by substituting D = 2.2 × 10−5 m2 s−1 into each of the 40 equations, and, similarly, the estimate for the standard error of D was found by substituting K = 481 m2 s−1 into each of the 40 equations. The spatially constant diapycnal diffusivity, at D = 2.2 × 10−5 ± 7.5 × 10−5 m2 s−1 while being relatively small, is also rather poorly known in that even its sign is in doubt.
The rather uncertain value found for the spatially invariant diapycnal diffusivity raises the question of whether this is simply indicative of resolving power of the method and the hydrography or whether this result was indicative of a real variation of diffusivity in space. Noting that each of our 40 equations are simply linear relations between K and D, we plotted these 40 linear relations on the D–K diagram and noticed that the straight lines for the five contours from each density layer tended to intersect, while these points of (near) intersection are different from one layer to the next. This is illustrated in Fig. 4, which shows 10 such straight lines, 5 from each of two different layers. There is a strong tendency for the lines from an individual layer to nearly cross at a point: This strongly suggested that the method has sufficient resolving power to be able to estimate both D and K and that these diffusivities were not constant in the vertical.
Hence, we performed least squares fits, assuming that the diffusivities K and D were constant along each layer. In this way we performed eight such fits with five equations in each fit, and the resulting values of the diffusivities for the eight layers are shown in Fig. 5 and Table 3. The errors bars σD and σK for these diffusivities are obtained by taking the constant value of the other diffusivity (either K or D) in each layer and the five equations, (20), then give five values of the diffusivity in question (either D or K) from which the standard deviation is calculated.
The first thing to notice in Fig. 5 is that the diffusivities are all positive and they vary quite smoothly from one layer to the next rather than varying randomly in the vertical. The standard error of these diffusivities is quite small, especially for the dianeutral diffusivity D. The error bars here do not reflect any uncertainty in the estimate of the effective transport FQ but rather the resolving power of the signature of the tracer patterns in the averaged hydrography to be able to distinguish between dianeutral and epineutral diffusion for a given FQ. We find the rather small standard errors of these diffusivities remarkable and surprising.
The vertical structure of the diapycnal diffusivity in Fig. 5 exhibits a rather strong vertical variation from the core of the Mediterranean Water at γn ≈ 27.65 kg m−3 where we find D ≈ 2 × 10−4 m2 s−1 toward deeper layers where the diapycnal diffusivities are seen to be about 0.5 × 10−4 m2 s−1. The epineutral diffusivities in this region of about 200 m2 s−1 are much less than values nearer the sea surface but may be appropriate for this depth and region of the ocean. The orderly progression of both D and K with density is probably due to our use of the rather smooth hydrographic atlas data. Nevertheless, the small error bars on these diffusivities give us some hope that the idea of carefully choosing the reference temperatures and salinities and the ratios ΔS/ΔΘ in order to achieve the three properties described in section 2 may add skill to the determination of diffusivities in a more general inverse problem. There have been few observational studies of diffusivity in this region. In the North Atlantic Tracer Release Experiment (NATRE) region (25°N, 332°E), which is farther to the south and west of the area that we are considering, Ferrari and Polzin (2005) found D ≈ 10−5 m2 s−1 and K ≈ 300 m2 s−1. Our diapycnal diffusivity is a factor of about 10 greater than this and our epineutral diffusivity is about a factor of 2 smaller.
The relative importance of vertical and epineutral diffusion in explaining the effective lateral advection of Mediterranean Water through this part of the North Atlantic is indicated in Fig. 6. For each density layer we have used the least-squares-determined values of D and K to evaluate the fraction of the right-hand sides of the five equations, (20), that are due to vertical and epineutral diffusion. The regular progression of the lines in this figure is probably indicative of the smoothed nature of the hydrographic atlas data and the fact that the areas that we consider are cumulative so that the properties of the area might be expected to vary slowly. The dashed curve with the smallest fractional influence is the curve for the largest horizontal area (the westernmost contour), and the successive dashed lines are the contours proceeding to the east in a monotonic fashion. The opposite occurs for the full lines where the curve for the smallest fractional influence is the easternmost contour with the smallest horizontal area. Perhaps this regular progression indicates that there may be more information that can be extracted using this technique, such as trying to determine a spatial variation of the diffusivities inside each isopycnal layer. We have not attempted to do so in this exploratory study but note that, if we took the diapycnal diffusivity to decrease and the lateral diffusivity to increase away from the Gulf of Cadiz, this would be consistent with the differences in D and K between the NATRE site and our study region, as well as tending to have the five solid lines and five dashed lines in Fig. 6 collapsing onto single full and dashed lines.
We have checked the robustness of the technique presented in this paper by varying the values of the vertical difference in salinity and conservative temperature, ΔS and ΔΘ, separately by ±10% and then redoing the analysis. These four separate changes typically resulted in changes to the diffusivities of less that 1%, confirming that the terms (22) and (23) that we neglected in arriving at our conservation equation (20) are indeed small. Another assumption built into our results is the vertical structure of the volume flux of Mediterranean Water entering the North Atlantic. Since we examined only the central range of densities between neutral densities of 27.50 and 27.80, we effectively chose the volume flux per unit density interval to be nearly constant (see Fig. 3). Nevertheless, this is an assumption. and our results in each density layer are directly proportional to the volume flume entering the layer.
Another key assumption that we have made is to use the same diapycnal turbulent diffusivity for heat as for salt. This is equivalent to assuming that the diapycnal mixing is caused by isotropic turbulent mixing. Another assumption would be to take the ratio of the diapycnal fluxes of heat and salt to be that in salt fingers, but we have not attempted this here.
4. Diffusivities from Hallberg Isopycnal Model data
Model output from the same region of the North Atlantic as in section 3 has been gained from the Hallberg Isopycnal Model (HIM; Hallberg 2000). There are three main advantages of using HIM as a means of testing the accuracy of the method already applied to the atlas data: First, HIM is one of the few global circulation models to impose a volume transport through the Strait of Gibraltar. If only temperature and salinity fluxes are allowed through the strait the overall dynamics of the region are changed (Griffies et al 2005). Second, by utilizing a density coordinate system HIM avoids the unwanted mixing effects caused by the Veronis effect in z-coordinate GCMs (Veronis 1975). Third, as HIM is already on density surfaces, we avoid any error implicit in interpolating to density surfaces from a Cartesian grid of Θ, S, and p values. The HIM output used is the time average of the final 20 years of a 100-yr coupled experiment The model uses a σ2-coordinate system with a total of 49 layers in the vertical and a horizontal resolution of 1° of longitude and latitude. The model is not eddy resolving, has an isopycnal diffusivity (Kmodel) of 600 m2 s−1, and employs a Richardson number (Ri) dependent vertical diffusion scheme that results in high vertical diffusivities [Dmodel O(10−4)] in regions of high Ri and relaxes to a background profile [depth-dependent O(10−5)] in the deep ocean. For the region explored by this study, Dmodel is close to 1.8 × 10−5 (i.e., within 10%).
The model stores velocity, advective flux, and diffusive fluxes of heat and salt in the meridional, zonal, and vertical directions. From the advective fluxes close to the Strait of Gibraltar we are able to assign a specific Q value to each layer in the vertical. Layers 36.0, 36.1, 36.2, and 36.3 are chosen as they represent the majority of the volume of the salt tongue and are bounded by five surfaces equally spaced in density coordinates. Contours are chosen such that they pass through latitude 35.5°N and longitudes 336°, 338°, 340°, 342°, and 344°E. One downside of using model output is the unsmoothed nature of the data close to the continents. Along both the Portuguese and Moroccan coasts the pressures on density surfaces are quite variable, and this data is removed by defining an eastern boundary to the region that is 1°–2° from the coast. The inflow Q may now be approximated as the volume flux through that boundary rather than simply the flux out of the Gulf of Cadiz. The region in question is shown in Fig. 7 along with the position of all five contours on the 36.2 σ2 layer.
Once again we have five sets of areas, now on each of four density layers, giving 20 equations of the form (20). Our initial overdetermined least squares solution is K = 586 ± 131 m2 s−1 and D = 3.42 × 10−5 ± 1.79 × 10−5 m2 s−1. It was found in the previous section that, when K and D were solved for each layer, much greater precision resulted, and it is thus pertinent to look to the intersection of lines in K–D space formed by each equation. A comparison between the lines formed by areas on both the 36.2 σ2 and 36.3 σ2 layers is shown in Fig. 8. While the lines formed by the 36.2 σ2 layer compare well to those of the hydrographic atlas, each having varied slopes and intersecting within a small range, the lines formed on the 36.3 σ2 layer are close to parallel. Clearly the ratio of coefficients in front of K and D in Eq. (20) varies little within each extra area on the 29.0 σ2 layer, and thus not enough information is present to solve for K and D within that layer individually. Possible explanations for this may lie in the averaging problem mentioned earlier and the fact that there may be something implicit in HIM that maintains a constant ratio between the K and D coefficients in (20), which is not observed in the real Mediterranean outflow.
We chose to solve for K and D for each set of equivalently sized areas in the vertical, making the assumption that K and D are constant on each set. The values obtained along with the average values used in HIM for these regions are displayed in Table 4 and Figs. 9a and 9b (for F = 1), and these results show that the diagnosed K and D values vary little throughout this region. The model values also vary little in space but differ from those diagnosed by around a factor of 2 in the D case and 20%–50% in the K case.
In the above calculations the assumption that FQ = Q has been made, as was the case in section 3, where an estimate for Q was all that was known. Since time-averaged volume fluxes are known at every point in space of the HIM data, we examine whether the inclusion of a better approximation for F will improve our ability to estimate K and D. In section 2, it was shown that FQ can be thought of as the average of the flow into the layer from the Mediterranean and the flow out through the contour that bounds it. Making this modification to the left-hand side of (20), the overall least squares estimates become K = 625 ± 109 m2 s−1 and D = 2.52 × 10−5 ± 1.87 × 10−5 m2 s−1, and K and D for each set of areas in the vertical are shown in Figs. 9a and 9b. Here K adjusts slightly upward, while D is reduced by 30%–50%, bringing the model D value well within the standard deviation of that diagnosed by this inverse technique. With F = 1, the gain or loss of volume within each layer is not accounted for. In the above case, diapycnal fluxes create a reduction in the outflow volume of each layer, and constructing an inverse model without taking this into account gives an overestimate of the vertical diffusivities. When advective fluxes are incorporated into the inverse model through the variable F, a better estimate for D results, with little change to our estimate for the lateral diffusivity K.
5. Summary
By taking a carefully chosen linear combination of the conservation statements of volume, salinity, and conservative temperature, we have arrived at (20), which is effectively a conservation equation for the variable ΔS(Θ − Θ1) − ΔΘ(S − S1) where the offset values Θ1 and S1 are chosen to be the volume-averaged conservative temperature and salinity of the control volume, and the vertical differences ΔS and ΔΘ are the area-averaged differences between the values at the upper and lower interfaces bounding a density layer. Because of its careful construction, the vertical gradient of this variable is on average zero, and hence dianeutral advection makes a negligible contribution to (20), as does the vertical gradient of the dianeutral diffusivity. Rather, the process of dianeutral mixing enters (20) only as the average of the dianeutral diffusivity at the upper and lower interfaces. In addition, this dianeutral diffusion term is proportional to the vertical curvature of the S–Θ diagram, which is much less subject to numerical noise than is traditionally the case when estimating second derivatives such as Szz and Θzz. These advantages were the motivation for forming this rather careful linear combination of the conservation equations.
Needler and Heath (1975) analyzed the Mediterranean Water signature in the North Atlantic using a salinity anomaly measured at fixed values of potential temperature with respect to a linear S–θ relation. Diapycnal advection of this salinity anomaly was ignored in their study. This can be justified at the central density of the Mediterranean Water because there this type of salinity anomaly shares the same important property as our (21), namely that its vertical gradient is zero, so the effect of diapycnal advection can be neglected. Above and below the central density, the vertical gradient of the salinity anomaly is nonzero, and our technique, which has a different ratio ΔΘ/ΔS for each density layer, is preferred.
Before using this technique in a more general inverse model of ocean hydrography we have applied it to the hydrography in the eastern North Atlantic, which has two very important advantages for our purposes. First, the volume flux entering the North Atlantic from the Mediterranean Sea can be taken as known and regarded as steady and, second, the hydrographic data has a very obvious Mediterranean Water signature. The extra terms (A1)–(A3) due to dianeutral advection and the vertical variation of the dianeutral diffusivity that should appear in (20) have been shown to have a negligible influence on the results of our study.
The method seems able to distinguish between the effects of epineutral and dianeutral diffusion on the dilution of the Mediterranean Water signature in the eastern North Atlantic. Also, the overdetermined least squares “inversion” gives dianeutral and epineutral diffusivities that vary smoothly in the vertical. The data examined here is from an ocean atlas (Gouretski and Koltermann 2004), and it remains to be seen how the method performs on unaveraged ocean hydrography. In this region of the ocean meddies are known to transport a significant amount of heat and salt laterally (Armi and Zenk 1984), and it is clear that this mechanism will not be well parameterized as diffusion. The analysis of the HIM data provided a further test of the ideas. It is not clear why the coefficients of the two diffusivities were so closely proportional along one of the model layers but, in any case, the technique recognized this and attached large uncertainties to the diffusion coefficients. We are encouraged by the results of this technique in this rather special region and plan to apply it as a more general inverse technique in the ocean, where one does not have an a priori estimate of the volume flux entering one side of the box.
Acknowledgments
We thank Drs. Susan Wijffels and Nathan Bindoff for insightful and helpful comments on a draft of this paper. This work contributes to the CSIRO Climate Change Research Program and has been partially supported by the CSIRO Wealth from Oceans Flagship.
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APPENDIX
The Three Extra Terms in Eq. (20)
Notice that the choice of the constant salinity S1 appears in the conservation equation (20) only through its influence on F and in one of the additional terms, namely term (A1). Since we will ignore this term, it is important to ensure that it is small, and a suitable choice of S1 will ensure that this term is zero. While we are unsure of this value of S1, we believe that it lies in a range that implies that F is between 0.85 and 1.0. Hence we conclude that the price of ignoring the contribution of (A1) to (20) is merely to suffer this relatively small uncertainty in the magnitude of the product FQ.
In summary, we believe that the errors involved in ignoring the contributions of the three terms (A1)–(A3) to (20) can be made to be small and will not materially affect the results. Ignoring (A1) causes us to suffer some uncertainty in F and hence in the effective lateral advection FQ along the layer, while the effect of ignoring the terms in (A2) and (A3) will be shown to be small by empirically varying the ratio ΔS/ΔΘ that we use in (20) away from the value set by (19).
Table of contour values S0 and Θ0; the values of salinity (psu) and temperature (°C) coming into each layer from the Mediterranean Sea, SM and ΘM; and the length, L, along these contours of the largest area of Fig. 2.
Based on the hydrography and the volume flux of Mediterranean Water (from Baringer and Price 1997), the coefficients of K and D in (20) (the first two parts of the table) and the left-hand side of (20) (the third part of the table) for the 40 different control volumes we consider in this paper. The first two parts of the table have units: m psu K; the third has units: m3 s−1 psu K.
The diffusivities and their standard errors, with both D and K being treated as constant along each density layer. The eight layers are treated independently, and in each layer D and K are determined as the only two unknowns in an overdetermined set of five equations corresponding to the five different S0 contours.
The diffusivities determined from HIM output and their standard errors, with both D and K being treated as constant for a set of areas in the vertical. The five contour locations are treated independently, and in each contour D and K are determined as the only two unknowns in an overdetermined set of four equations corresponding to the four different layers.