Pathways of eddies in the South Atlantic Ocean revealed from satellite altimeter observations

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1 GEOPHYSICAL RESEARCH LETTERS, VOL. 33,, doi: /2006gl026245, 2006 Pathways of eddies in the South Atlantic Ocean revealed from satellite altimeter observations Lee-Lueng Fu 1 Received 8 March 2006; revised 6 June 2006; accepted 9 June 2006; published 22 July [1] The majority of the kinetic energy of ocean currents is contained in the mesoscale eddies. The pathways of ocean eddies, which are the weather of ocean circulation, are mapped from space using a decade-long record of sea surface height measured by two simultaneously flying satellite radar altimeters. The speed and direction of the propagation of eddies in the South Atlantic Ocean are presented in the paper. The patterns of the eddy propagation velocity reveal the effects of the interaction between mean flow and eddies with strong influence of bottom topography. The information describes a unique property of the ocean general circulation and serves as a basis for testing ocean models. Citation: Fu, L.-L. (2006), Pathways of eddies in the South Atlantic Ocean revealed from satellite altimeter observations, Geophys. Res. Lett., 33,, doi: /2006gl Introduction [2] The variability of ocean currents is dominated by the mesoscale eddies, characterized by a time scale on the order of 100 days and a spatial scale on the order of 100 km [Robinson, 1983]. The generic term eddies is used here to represent the various forms of ocean current variability at the mesoscale: vortices, fronts, planetary waves, and current meanders. Eddies are the oceanic analog of weather in the atmosphere. They contain most of the kinetic energy of the circulation of the ocean and play important roles in determining the water properties of the ocean: temperature, salinity, dissolved gases, and nutrients. The distribution of eddy energy in the ocean has been well mapped from space using satellite altimeter observations [Cheney et al., 1983; Zlotnicki et al., 1989; Stammer, 1997; Ducet et al., 2000]. However, the patterns of the movement of eddies and their propagation velocity, or the pathways of ocean eddies, are more difficult to study due to the lack of long and global observations with sufficient spatial and temporal resolutions. Jacobs et al. [2001] provided a smoothed estimate of the eddy propagation velocity of the global ocean using a method of binned covariance. The same method was applied to the North Atlantic Ocean by Brachet et al. [2004]. In the present study, the combined data from the TOPEX/Poseidon (T/P hereafter) and ERS altimeters are used to construct a high-resolution map of the pathways of ocean eddies in the South Atlantic Ocean, showing the details of the interaction between mean flow and eddies with strong influence of bottom topography. The information describes a unique property of the ocean general circulation and serves as a basis for testing ocean models as well as for constraints in data assimilation and empirical prediction of eddy movement. The approach can be readily applied to the global oceans. 2. Data and Methods [3] The combined data from the T/P and ERS altimeters are the first decade-long record that is useful for tracking the movement of ocean eddies in two dimensions. Although the spatial resolution of a radar altimeter is typically 6 7 km along the satellite s ground tracks, the wide separation between the ground tracks, typically km for a single altimeter, limits the resolution of eddy variability in the satellite s cross-track direction. When the data from the two satellites are combined with the use of an objective mapping technique, the resulting spatial resolution is approximately 150 km in wavelength [Ducet et al., 2000], covering a substantial portion of the mesoscale spectrum (also see Chelton and Schlax [2003] for the estimate of a lower spatial resolution). This data set, available form the French AVISO data center ( com/html/mod_actu/public/welcome_uk.php3, 2006), allows the tracking of large ocean eddies for studying their propagation velocity and pathways. [4] The propagation velocity of eddies is computed using a space-time lagged correlation analysis similar to the maximum cross correlation method [Emery et al., 1986]. At a given location, the sea surface height (SSH) anomalies were computed as the residuals after a time mean was removed from the SSH time series. The correlations of the SSH anomalies with all the neighboring SSH anomalies at various time lags were computed. Such space-time lagged correlation analysis was performed to estimate the speed and direction of the maximum correlations as they move in space and time. [5] The AVISO altimetry data are available on 1/3 degree Mercator grids, with the meridional grid spacing kept the same as the zonal grid spacing of 1/3 degree longitude, varying from 37 km at the equator to 24 km at 50 latitude. At each grid node location (x, y), the cross-correlations (C x,y ) of the SSH time series (h) with others in a square box were computed for time lags DT in multiples of 7 days (the time step of the data) as C x;y ðdx; Dy; DT Þ ¼ hx; ð y; t Þhxþ ð Dx; y þ Dy; t þ DTÞ 1 Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, USA. Copyright 2006 by the American Geophysical Union /06/2006GL where Dx and Dy are the spatial lags and the over bar denotes time averaging. At each time lag, the location of the maximum correlation was identified and a velocity was estimated from the time lag and the distance of the location 1of5

2 FU: EDDIES IN THE SOUTH ATLANTIC OCEAN Figure 1. The color shading displays the standard deviation of sea surface height in cm. The arrows show the vectors of eddy propagation velocity. A sample vector of 10 km/day is shown at the lower right corner. The two colors of the arrows are for easy viewing. South latitudes and west longitudes are shown in negative numbers and east longitudes in positive numbers. from the origin. An average velocity vector (u, v) weighted by the correlation coefficients was then computed from the estimates at various time lags as X ðu; vþ ¼ i ðdxi =DTi ; Dyi =DTi ÞCi X C i i correlation analysis. Since the space and time lags of the correlation analysis are chosen for the mesoscales, the estimated velocities represent the speed and direction of the propagation of ocean eddy variability. 3. Results where Ci is the maximum correlation at DTi, and Dxi, Dyi represent the location of the maximum correlation. The average velocity was then assigned to the eddy propagation velocity at the given grid node. The size of the box for computing the correlations was determined by the estimated speed and the time lag. To focus on the mesoscale, the time lags were limited to less than 70 days and the dimension of the box was generally less than 400 km. The resulting velocities are associated with the variabilities that dominate the variance of the SSH time series at the scales of the [6] Displayed in color shades in Figure 1 is the standard deviation of SSH measured by the satellite altimeters, showing the intensity of eddy variability. Superimposed on the eddy variability are the velocity vectors estimated from tracking the movement of eddies in the time series of SSH using the method described in Section 2. The velocity vectors represent the speed and direction of the horizontal propagation of ocean eddy variability. Most previous studies of the movement of ocean eddies were based on visual tracking of identifiable features in time sequence of SSH maps. For example, studies of the migration of eddies shed 2 of 5

3 FU: EDDIES IN THE SOUTH ATLANTIC OCEAN Figure 2. A close-up of the eddy propagation velocity in the Argentine Basin. The color shading displays the depths of the ocean bottom. into the South Atlantic from the Agulhas Current and its retroflection off the southern tip of South Africa [Gordon and Haxby, 1990; Byrne et al., 1995] show that these eddies were often traceable for almost two years on their journey toward the east coast of South America. Morrow et al. [2004] applied an objective method to tracking the movement of individual eddies over large distance. Instead of a Lagrangian description of the movement of individual eddies as reported in the previous studies, the space-time correlation analysis used in the present study provides an Eulerian description of the eddy propagation velocity. As shown in Figure 1, the technique has mapped the northwestward propagation velocities of the eddies originated from the Agulhas Current region, showing a typical speed of 3 4 km/day. After leaving the energetic source region, the eddies essentially propagate westward in a vast region of westward propagation velocity north of 35 S. The region is located at the northern part of the subtropical gyre with northwestward mean flow, which may have contributed to the westward motion of the eddies to be discussed later. [7] Along the west coast of Africa, one can see the influence of the northward flowing Benguela Current on the northward component of eddy propagation velocity. Although the eddy signals are quite weak here, their horizontal propagation is highly organized, especially in the region of strong upwelling near S. This is also the region where the cold Benguela current meets the warm coastal waters from the north, a region of frequent eddy shedding into the open ocean [Cole and Villacastin, 2000]. Near 20 S along the east coast of South America is a region of divergence of eddy propagation velocity. Eddies move northward in the region north of 20 S and southward in the region south of 20 S. This is in the vicinity where the Atlantic South Equatorial Current diverges into northward and southward flows. [8] The influence of the Brazil Current is clearly seen between 20 S and 35 S, creating an organized band of southwestward eddy propagation velocity. South of 40 S and west of 40 W, clear indications are shown of the effects of the Antarctic Circumpolar Current (ACC) and the Malvinas Current. The eddy propagation velocities are highly correlated with the paths of the two currents. In the region of maximum eddy variability associated with the confluence of the Brazil Current and the Malvinas Current, the eddy propagation velocities are surprisingly low. On the other hand, a highly organized pattern of anticlockwise eddy propagation velocity is situated in an area of relatively low eddy variability centered at 45 S and 45 W, surrounded by high eddy variability. This region of low eddy variability is filled with barotropic circulation (uniform current velocity from the ocean s top to bottom) called the Zapiola Anticyclone [Saunders and King, 1995; de Miranda et al., 1999]. Apparently, the anticlockwise mean flow has a significant effect on the propagation of eddies in the region. To the east of the Zapiola Anticyclone, the patterns of the eddy propagation velocity reveal the swiftest part of the ACC in the region. The two meandering streams of generally eastward velocity vectors between 10 W and10 E reflect the paths of the Subantarctic and Polar Fronts of the ACC [Orsi et al., 1995]. [9] The complex patterns of eddy propagation velocity in the southwestern part of the South Atlantic, called the Argentine Basin, are superimposed on a map of the ocean s bathymetry in Figure 2. The steering effects of the bathymetry are clearly illustrated. To a large extent, the eddy propagation velocity is in alignment with the direction of the mean flow which is affected by the bathymetry. The generation of eddies is also affected by the bathymetry. The eddies are carried by the mean currents over the depths of the eddies vertical extent. The eddies also have their own intrinsic propagation velocity in the absence of any mean flow [Flierl, 1977; McWilliams and Flierl, 1979]. The net propagation velocity is caused by a combination of the intrinsic eddy propagation and the advection of mean flow. In general, the eddy propagation velocity is several fold less than the surface velocity of the mean flow. However, the patterns of the eddy propagation velocity reveal many details of the mean flow in the region: the meander of the ACC just east of the Drake Passage, the northward velocities in the path of the Malvinas Current over the continental slope, the anticyclonic velocities around the submarine bank at 50 S and 42 W as well as the South Georgia Island (55 S, 37 W). [10] The most striking pattern of the eddy propagation velocity is associated with the anti-clockwise Zapiola Anticyclone surrounding the Zapiola Rise in the middle of an abyssal plane. The details of the velocity vectors even reveal the shape of the Zapiola Rise, especially the wavy patterns along 47 S between 45 W and 38 W. As noted earlier, the mean flow of the region extends from surface to bottom as a tight anticyclonic recirculation gyre. This gyre is believed to be driven by the strong eddy field of the Argentine Basin [de Miranda et al., 1999]. It is interesting to note that the eddies themselves propagate along the path of the mean current, at a speed comparable to that of the mean current. [11] There is firm evidence in Figures 1 and 2 for the effects of mean flow on the eddy propagation velocity. To further illustrate the effects, displayed in Figure 3 is the speed of eddy propagation superimposed by the contours of the dynamic topography of the ocean [Niiler et al., 2003]. 3of5

4 FU: EDDIES IN THE SOUTH ATLANTIC OCEAN the ACC and the Malvinas Current also have strong deep currents to carry eddies in the direction of the mean flow with significant speeds. Figure 3. The color shading displays the speed of eddy propagation in km/day. The contours represent the surface dynamic topography. The contour intervals are 10 cm. The highest values are in the center of the subtropical gyre enclosed by the 20 cm contour. The dashed line is a schematic representation of the ridge of the subtropical gyre with northwestward mean flow in the north and eastward mean flow in the south as indicated by the arrows. There is a sharp demarcation between the high speeds of 4 6 km/day north of 30 S and the low speeds of 0 2 km/day south of 30 S. This transition occurs along a ridge of the dynamic topography, which divides the subtropical gyre of the South Atlantic into two regions. The general direction of the surface flow is eastward in the south and northwestward in the north. Since the intrinsic propagation velocity of an eddy has a westward component [Flierl, 1977; McWilliams and Flierl, 1979], this component is reinforced by the mean flow in the north and compensated by the mean flow in the south. When the mean flow has strong eastward velocity as in the ACC, it is able to reverse eddy propagation from its intrinsic westward direction into eastward direction with substantial speeds as shown in the region of 50 W 70 W, 50 S 60 S as well as 20 W 10 E, 45 S 55 S (also see Figure 1). [12] The high speed in the region west of 35 W and south of 35 S is interesting. The surface flow in the region is generally toward the east as indicated by the dynamic topography and should therefore reduce the eddy propagation speed. However, the dynamic topography at 3000 m depth indicates that the anticyclonic deep circulation in the Zapiola region has a branch extending northward to 35 S [Niiler et al., 2003]. Therefore the deep currents in the region are to the west in opposition to the surface currents. The eddy propagation velocities are apparently affected by the deep currents instead of the surface currents. The largest eddy propagation velocities occur in the region where the westward barotropic currents are known to be the strongest just north of the Zapiola Rise along 45 S. South of the Zapiola Rise, the eastward deep currents are strong enough to carry the eddies eastward with substantial speeds. Both 4. Conclusions [13] The new information on the propagation velocity of ocean eddies obtained from the study represents a unique asset of long-term measurement of global sea surface height from multiple satellites. The decade-long record length provides a large degree of freedom in the velocity estimates, leading to a reliable description of this property of the ocean general circulation. It is a property reflecting the interplay between ocean eddies and mean flow, a subject of great importance in our pursuit of understanding and modeling ocean circulation and its effects on climate and ecosystem. The information on eddy propagation velocity thus provides a basis for testing the performance of ocean general circulation models. [14] Acknowledgments. The author would like to acknowledge stimulating discussions with Dudley Chelton of Oregon State University. This work was in part inspired by his interesting animation of eddy motions from altimetry observations. The research presented in the paper was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautic and Space Administration. Support from the TOPEX/Poseidon and Jason Projects is acknowledged. References Brachet, S., P. Y. Le Traon, and C. 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5 FU: EDDIES IN THE SOUTH ATLANTIC OCEAN Saunders, P. M., and B. A. King (1995), Bottom currents derived from a shipborne ADCP on the WOCE Cruise A11 in the South Atlantic, J. Phys. Oceanogr., 25, Stammer, D. (1997), Global characteristics of ocean variability estimated from regional TOPEX/POSEIDON altimeter measurements, J. Phys. Oceanogr., 27, Zlotnicki, V., L.-L. Fu, and W. Patzert (1989), Seasonal variability in global sea level observed with GEOSAT altimetry, J. Geophys. Res., 94, 17,959 17,969. L.-L. Fu, Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USA. (llf@pacific.jpl.nasa.gov) 5of5