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The seasonal variability of the circulation in the South Indian Ocean: Model and observations
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Journal of Marine Systems 74 (2008) 315 – 328 www.elsevier.com/locate/jmarsys
The seasonal variability of the circulation in the South Indian Ocean: Model and observations R.P. Matano a,⁎, E.J. Beier b , P.T. Strub a a
College of Oceanic and Atmos. Sciences, Oregon State University, Corvallis, OR, 97331-5503, United States b CICESE Unidad La Paz, La Paz, B.C.S. Mexico Received 20 November 2006; received in revised form 12 January 2008; accepted 16 January 2008 Available online 14 February 2008
Abstract This article compares the seasonal variability patterns of the South Indian Ocean circulation derived from a global, eddypermitting, numerical model and altimeter observations. The seasonal variability of the Indian Ocean circulation is driven by the inflow from the Indonesian Passages and by the local wind forcing. Our analysis indicates that the influence of the Indonesian throughflow is confined to the easternmost portion of the basin, while the influence of the wind stress forcing is important everywhere. Model and observations indicate that, between ~ 105°E and 75°E, the seasonal variability is characterized by the southwestward propagation of an annual wave over a period of ~ 4 months. Preliminary calculations using Pathfinder data also indicate that, in the western region, there are seasonal perturbations that originate in the tropics and propagate poleward through the Mozambique Channel. Our calculations, however, did not find the connections between the tropical and the Agulhas Current variability suggested by earlier modeling studies. © 2008 Elsevier B.V. All rights reserved. Keywords: Western boundary; Seasonal variability; Modeling; South Indian Ocean; Model and observation
1. Introduction The South Indian Ocean circulation includes a tropical cyclonic gyre, which extends from the equator to approximately 17°S, and a subtropical anticyclonic gyre that extends from approximately 17°S to 47°S (see Lutjeharms, 2007 and references therein) (Fig. 1). These gyres are the conduit through which Pacific waters entrained by the Indonesian throughflow are discharged onto the eastern Atlantic by the Agulhas retroflection (Gordon, 1985; Gordon et al., 1999; Lutjeharms, 1996).
⁎ Corresponding author. E-mail address: [email protected] (R.P. Matano). 0924-7963/$ - see front matter © 2008 Elsevier B.V. All rights reserved. doi:10.1016/j.jmarsys.2008.01.007
Since the entrainment from the Pacific occurs in the tropics, and the detrainment onto the Atlantic in the subtropics, the Indian Ocean circulation has to transfer mass and energy between its gyres. These transfers are largely accomplished by eddies and narrow currents within the Mozambique Channel and east of Madagascar (De Ruijter et al., 2002, 2004; Schouten et al., 2002; Ridderinkhof and de Ruijter, 2003; Quartly and Srokosz, 2004; Lutjeharms, 2007). The variability of these eddies and currents are linked to the large-scale circulation and are therefore modulated by its low-frequency variability (e.g., Schouten et al., 2002; Palastanga et al., 2006). Thus, our ability to understand the dynamical mechanisms that participate in the global interocean exchanges is tied to our ability to understand the process that controls the
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Fig. 1. Bottom topography of the Tropical and the South Indian Ocean. Grey arrows mark the mean geostrophic circulation according to Stramma and Lutjeharms (1997). The boxes in the stippled rectangles mark the approximate domains of the three modes of annual variability defined by Matano et al. (2002).
variability of the Indian Ocean gyres. In this article we investigate one of the most distinctive modes of lowfrequency variability of the Indian Ocean circulation, the seasonal cycle. Previously we investigated the seasonal variability of the South Indian Ocean using the results of a global, eddy-permitting, numerical simulation (Matano et al., 2002; henceforth M2002). This analysis showed that at seasonal time scales, the large-scale circulation in the South Indian Ocean is modulated by the oscillation of barotropic modes forced directly by the wind. The pulsation of these modes generates a seasonal variation of the transport of the Agulhas Current, with a peak at the transition between the austral winter and the austral spring, and a trough at the transition between the austral summer and the austral autumn. The modes described by M2002 appear to be a robust characteristic of other numerical simulations of the South Indian Ocean circulation (e.g., Matano et al., 1998; Biastoch et al., 1999; Fetter et al., submitted for publication). The existence of these modes, however, has not been confirmed by observations, i.e., most of what we know about the seasonal variations of the South Indian Ocean circulation has been inferred from model results without a direct verification from real data. It seems, therefore, of broad interest to determine whether the variability structure predicted by numerical models are corresponded by observations. As a step in that direction in this article we compare the results of the numerical simulation described by M2002 with altimeter data. We show that the structure of the seasonal variability deduced from models is similar to that obtained from observations. This finding indicates that regional processes, i.e., pro-
cesses occurring within sub-basins determined by the bottom topography, control the seasonal variability of the South Indian Ocean circulation. 2. Data and methods 2.1. Model The model results were produced by the Parallel Ocean Circulation Model (POCM) experiment (Tokmakian and Challenor, 1999). The model configuration and numerical results have been described in M2002 therefore only a brief discussion will be included here. The model solves the primitive equation in a Mercator grid with an average horizontal grid spacing of 1/4° and 20 vertical levels. Our analysis is focused on the experiment 4C, which was run for a 19-year period. From 1979 to 1994 the model was forced with atmospheric fluxes derived from the reanalysis of the European Center for Medium-Range Weather Forecast, after that the forcing fluxes were replaced with data from operational forecast experiments. 2.2. Altimeter data T/P and ERS data, reprocessed by the NASA/GSFC Pathfinder Ocean Altimeter group, are the basis for the gridded fields of sea surface height. To determine the 0spatial structure of the large-scale variability we use T/P data which was interpolated using a loess smoother filter with 8° in longitude, 2° in latitude and 25 days in time with estimates at 3 days intervals on a one degree grid. A detailed discussion of the data processing can be
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found in Chelton et al. (1990). To reduce the steric effect associated with the annual variation of the solar radiation we subtracted the zonal average of the SSHAs from the original fields. Since the interpolation procedures used by Chelton et al. eliminates most of the data in the Mozambique Channel and surrounding area we did some ancillary calculations using higher resolution data from the Pathfinder mission.
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To characterize the variability from the model and the observations we calculated the standard deviations, annual harmonics, Hovmöller diagrams, and EOF modes of the sea surface heights anomalies (SSHAs). To facilitate the comparison we used only data of the period during which both data sets overlap i.e., from 1993 through 1998. Our study will focus in the Indian Ocean region between 5°N and 30°S.
Fig. 2. Standard deviation [cm] from T/P data (panel a) and POCM_4C (panel b). The values were calculated from time series from the beginning of 1993 to the end of 1997. The shadow areas represent regions where the values are bigger than 3 cm. Panel c shows the time evolution of the basin averaged sea level elevation from both time series.
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3. Results The M2002 analysis indicates that the seasonal variabilities of the tropical and subtropical Indian Ocean are connected by three barotropic modes. The first is located in the eastern portion of the basin and reaches its maximum amplitude in the Indonesian Passages. The second mode is centered in the middle of the basin and it is limited, in the zonal direction, by the bottom topography. The third mode is restricted to the western portion of the basin and encompasses two distinctive regions. To the south it extends into the Mozambique
Channel and reaches up to the Agulhas Current. To the north it extends up to the equator and encompasses the South Equatorial Current. M2002 concluded that while the first mode is largely driven by the seasonal variations of the Indonesian throughflow, the other two are forced by the wind stress forcing. These conclusions were in general agreement with the earlier modeling results of Biastoch et al. (1999) who also noted that seasonal anomalies in the tropical circulation propagate poleward through the Mozambique Channel and influence the mass transport of the Agulhas Current. The seasonal variations described from these models,
Fig. 3. Amplitudes (background color) and phases (white contours) of the annual harmonic from altimeter observations (upper panel) and the POCM4C experiment (bottom panel). The units of the amplitudes are in cm and the phases are in months. A color version of this figure could be found in the online version of this article.
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however, have not yet been verified by observations. As a step in that direction in what follows we compare the results of POCM with altimeter observations. 3.1. Standard deviations To characterize the overall variability of both data sets we computed the standard deviations of the SSHAs (Fig. 2). There is a reasonable agreement between model and observations although the former shows small-scale structures that are absent in the coarsely sampled altimeter data (Fig. 2a and b). The largest differences are observed near coastal regions (e.g., the Mozambique
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Channel, the eastern Madagascar coast), which are outside of the resolution of the altimeter data. The region between 4° and 18° S shows the largest variability in SSHAs, with peaks of 14 cm near Indonesia and 11 cm near 80°E 10°S. Most of the variance in both data sets is contained in the annual and inter-annual periods (Fig. 2c). The annual cycle explains 32% of the variance of the T/P data and 37% of POCM. The amplitude of the annual fit of the basin averaged T/P data is 1.3 +/− 0.15 cm with a maximum during the middle of December and a minimum during July. The amplitude of the model data is 1.1 +/− 0.13 cm. The phase difference between both data sets is 10 days.
Fig. 4. (a) Hovmöller diagrams of the SSHA from model (top panel) and the altimeter data (middle panel) at 8°S. The bottom panel shows the bottom topography of the model at the same latitudinal strip. The units of SSHA are in cm. (b): Hovmöller diagrams of the SSHA from model (top panel) and the altimeter data (middle panel) at 12°S. The bottom panel shows the bottom topography of the model at the same latitudinal strip. The units of SSHA are in cm.
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Fig. 4 (continued ).
3.2. Harmonic analysis The amplitudes and phases of the annual harmonics from both data sets are very similar (Fig. 3). The amount of variance explained by the annual harmonic is generally high, with a maximum of ~ 60% over the central region and ~ 40% near the eastern and western boundaries (not shown). Both data sets show amplitude maxima (background color) in the northeastern and northwestern portions of the basin, although the spatial structures of the model show more mesoscale structure due to their higher spatial resolution. The model, for example, shows two relative maximum in the northeastern region: one centered at ~ 90°E and the other over the Indonesian Passages, while the altimeter data shows a single maximum that extends from ~ 80°E to 120°E. The model maxima have been also reported in previous observational studies, which argue that they are driven
by different dynamical processes: the maximum near 90°W is driven by the local winds, while the one centered in the Indonesian Passages is driven by the inflow from the Pacific Ocean (Woodberry et al., 1989; Inoue and Welsh, 1993, Morrow and Birol, 1998; Gordon et al., 1999). Model and observations also show high amplitudes in the northwestern portion of the basin (Fig. 3). The observations show an absolute maximum near the northeastern tip of Madagascar and a secondary maximum centered near 5°S 48°E. This maximum is displaced to the northwest in the model and it is driven by the seasonal variations of the South Equatorial Countercurrent. The distribution of phases (white contours), indicate that the eastern and western regions are not connected by annually propagating waves but are separated by a region of vanishing amplitudes (in both data sets), and an amphidromic line (Fig. 3). The most robust propagating
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Fig. 5. Amplitudes (upper panel) and phases (lower panel) of the annual harmonic of the zonally averaged sea surface elevation from the altimeter (grey dashed contours) and the model (black solid line). The bars indicate the error of the fit.
signal of both data sets is observed in the northeastern portion of the basin. There, there is a southwestward propagating signal that moves between 105° and 75°E in a period of ~4 months. This signal was previ-
ously reported, and extensively described, by Perigaud and Delecluse (1992) and Morrow and Birol (1998). The model results indicate the existence of westward propagation in the western portion of the domain (west of
Fig. 6. Amplitude of the annual harmonic derived from the model (upper panel) and from the Pathfinder altimeter data (bottom). The amplitudes are given in cm. The stars in the left panel mark the location of the data (both model and altimeter) that we used to calculate Fig. 6.
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~75°E), but this signal is not obvious in the observations. The region that separates the eastern and western amplitude maxima follows the approximate course of the Mid-Indian Ridge and the Ninety East Ridge (Fig. 1). M2002 observed that these topographic features interrupt the westward progression of the annual signal in POCM. These signals appear to be particularly sensitive to the presence of the Mid-Indian Ridge, the Chagos Archipelago, and the Mascarene Plateau. M2002 argued that the topographic effects enhance the contribution of the local forcing (in detriment to remote forcing), and that the seasonal adjustment of the South Indian Ocean is therefore better described in terms of standing modes rather than in terms of propagating waves. According to this argument the transport of the Agulhas Current, for example, is largely unaffected by the seasonal changes of the winds in the eastern portion of the Indian basin (east of ~75°E), or the seasonal variations of the Indonesian Throughflow. These arguments are in agreement with the earlier modeling results of Kindle (1991) who reported
that the predominantly barotropic, seasonal signal that is generated in the eastern portion of the Indian basin is reflected at the Mascarene Plateau. The M2002 arguments were entirely based on the POCM results. Therefore it is of interest to compare the characteristics of the westward propagating signals derived from POCM with those from the altimeter (Fig. 4a and b). There is a general agreement between POCM and observations although the amplitudes predicted by the model are smaller than those calculated from the altimeter. The phase speeds derived from POCM, however, are close to those found in T/P and for this range of latitudes and to the values predicted by theory (Chelton and Schlax, 1996). The topographic effects discussed in M2002 are also observed in the altimeter data. At 8°S, the Ninety East Ridge limits the westward progression of the signals generated near the eastern boundary (Fig. 4a). New waves appear to be generated along the eastern flank of the ridge (Fig. 4a). These waves appear to be affected, farther west, by the Mascarene Plateau.
Fig. 7. Amplitudes and phases of the annual harmonic computed along the coastal points in Fig. 5. The black line correspond to the mode and the grey line to the observations.
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There are some noticeable differences between the model and observations in the region between 60°E and 80°E. The model shows a standing mode with a maximum near the western limit while the existence of such a mode is not obvious in the observations. Both data sets show similar amplitudes (~ 3 cm) to the west of the Mascarene Plateau and the existence of a regional mode between 60˚E and the African coast. The same general characteristics are also observed at 12°S (Fig. 4b). In both cases the main discrepancies between the annual fits to the model and the observations are located in the central region. The modeled amplitudes of the annual fit are also smaller in both cases. To further quantify the fitness between observations and model we calculated the annual harmonic of the zonally averaged SSH for the model and the T/P ob-
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servations (Fig. 5). As expected from the above discussion the amplitudes of both data sets show similar latitudinal distributions (Fig. 5, upper panel). The largest differences are observed in region between the equator and 8°S but even there the fitting error bars indicate that these differences are not statistically significant. Model and observations, however, show significant discrepancies of their phases, with a maximum of 4 months, in the latitudinal strip between the equator and 5°S (Fig. 5, lower panel). In that region however, the amplitudes are relatively small. Farther south the sea level reaches a maximum (in both model and observations) between February and March and a minimum between August and September. In the overall balance this calculation shows that there is a high correlation between model and observations outside from the tropics, the correlation
Fig. 8. (a)Amplitudes of the first EOF from the observations (top panel) and the model (middle panel). The bottom panel shows their corresponding time series. The units of amplitudes are in cm. A color version of this figure could be found in the online version of this article.
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Fig 8b. (b): Amplitudes of the second EOF from the observations (top panel) and the model (middle panel). The bottom panel shows their corresponding time series. The units of amplitudes are in cm. A color version of this figure could be found in the online version of this article.
coefficient of annual harmonics of the SSHs from model and observations is approximately 0.8. The above analysis indicates that the seasonal variability of the South Indian Ocean circulation can be explained in terms of basin modes that draw their energy from the local winds and that are delimited by the bottom topography. Those conclusions are in agreement with the earlier findings of M2002 whom, in addition, showed that the tropical variations of the westernmost mode propagates poleward into the Mozambique Channel and, from there, into the Agulhas Current. It is not possible to corroborate these model predictions from the coarsely gridded T/P data used in this analysis (e.g., Fig. 3). To address these matters however, we recalculated the annual harmonic of the western region using a data set with higher spatial resolution (Pathfinder) (Fig. 6). The new calculation indicates that the
spatial structures derived from the altimeter are qualitatively similar to those from the model although the amplitudes are smaller and there is no evidence of the intense western intensification that characterize the western boundary region. To investigate the existence of poleward propagating signals in the Mozambique we computed the amplitudes and phases of the annual harmonics at the nearshore locations marked in Fig. 6 (Fig. 7). The altimeter data used for this calculation correspond to the first ocean grid point along the descending tracks (~ 50 km from the coast), while the location from the model data corresponds to the grid point closest to the observations. There is a close correspondence between model and observations. The largest discrepancies are observed in the equatorial region where the model appears to overestimate the amplitude of the seasonal cycle. South of ~ 5°S, however, there is a
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Fig. 8c. (c): Amplitudes of the third EOF from the observations (top panel) and the model (middle panel). The bottom panel shows their corresponding time series. The units of amplitudes are in cm. A color version of this figure could be found in the online version of this article.
remarkable agreement between the phases and amplitudes from both data sets. The distribution of phases indicates the possible existence of propagation between 10° and ~ 20°S. This signal, however, is lost near 20°S, perhaps due to the existence of a sharp bending of the coastline that diverts the flow farther offshore (e.g., M2002). 3.3. EOF analysis To further evaluate the realism of the numerical simulation we calculated the Empirical Orthogonal Functions (EOFs) of the SSHA anomalies of both data sets (Fig. 8). The first three modes account for 49% of the total variance of the observations and 46% of the model. The first mode, which accounts for 23% and
24% of the variances of the observations and model, reflects more the large-scale structure of the equatorial circulation than the mesoscale structures associated with the subtropical gyre (Fig. 8a). The amplitudes and time series associated with both data sets are qualitatively similar although the model amplitudes are slightly smaller than those of the observations. The largest SSHA gradients of both EOFs are located in the northeastern portion of the basin. The time series associated with this mode seems to reflect more inter-annual variations than seasonal changes. Note, for example, that both data sets capture the 1995 and 1998 El Niños. In fact, the annual fit to the time series indicates that annual cycle accounts for only 36% of the variance in the T/P mode and 25% in the POCM mode. As a side calculation we extracted the annual signal from both
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Fig. 9. (a) Amplitudes of the first EOF mode [dyne/cm⁎⁎3 10⁎⁎9] of the wind stress curl (upper panel) and the corresponding time series (lower panel). Shadow areas correspond to values bigger than 10 (solid) and − 10 (stippled). (b): Amplitudes of the second EOF mode [dyne/cm⁎⁎3 10⁎⁎9] of the wind stress curl (upper panel) and the corresponding time series (lower panel). Shadow areas correspond to values bigger than 5 (solid) and − 5 (stippled).
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data sets and re-calculated the corresponding EOFs. The results (not shown) are similar to those shown herein except that the westernmost maximum disappears and there is only one maximum at 73°E–8°S. In this calculation the spatial structures of model and observed EOFs at the Indonesian Passages are more similar to each other than those shown in Fig. 8a. The second EOFs represent 15% and 14% of the variances of the observations and the model (Fig. 8b). The annual fits to these modes explain 72% and 84% of their respective variances, which indicates that this particular mode contains most of the seasonal signal. Both EOFs show similar spatial and temporal structures, although the amplitudes of the model are smaller than those of the observations. North of 20°S, both data sets show two regional maximum centered near 90°E and 65°E. The corresponding maxima in the observations are displaced to the northwest of those in the model, although they both are within the region of maximum SSHA variation found in the harmonic analysis (Fig. 3). There are relatively minor differences in the spatial structures of the model and observations over the eastern equatorial region. The model, for example, shows a maximum at 83°E 5°S that is absent in the observations. Both data sets, however, show the well-defined structure of the South Equatorial Current near 5°S. The third EOF mode explains 11% and 9% of the observations and models variance (Fig. 8c). This mode also represents the seasonal variability with annual fittings that explain 86% and 68% of the variance of the observations and model. The largest differences between model and observations are in the eastern side of the basin. There, the SSHA maxima that extends towards the northwest in the altimeter is absent in the model. This discrepancy seems to be related to the dominance of the seasonal variability in this region. In fact, the similarity between the EOFs is greatly improved when the annual signal is extracted from the respective time series of both data sets. For the sake of completeness we also calculated the EOFs of the curl of the ECMWF wind stress, which is used to force POCM (Fig. 9a and b). The spatial structure of the first mode is largely uniform with no major regional differentiation (except for a local maximum at the tip of Madagascar), and therefore can be thought as representations of the large-scale (hemispheric) circulation (Fig. 9a). Most of the information on the basin scale circulation is captured by the second EOF (Fig. 9b), which explains 11% of the total variance (the annual fit to this mode explains 54% of its own variance). One of the most interesting characteristics of this mode is the relative maximum in the eastern side of the basin
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(~ 90°E 11°S), which closely corresponds with the amplitude maxima observed in the EOF and annual harmonic of the SSHAs (Figs. 7 and 3 respectively). It seems, therefore, reasonable to conclude that the wind stress forcing locally drives the seasonal variability of this region. 4. Summary and discussion The seasonal variability of the Indian Ocean circulation is driven by the inflow from the Indonesian Passages and by the local wind forcing. The influence of the Indonesian throughflow, however, appears to be confined to the easternmost portion of the basin, while the influence of the wind stress forcing is important everywhere. Our analysis indicates that seasonal variations of tropical origin propagate to the subtropics in the central portion of the basin and in the western region. In the central region, there is strong evidence of an annual wave that propagates southwestward between ~ 105°E and 75°E in a period of ~ 4 months. The connection between the tropics and subtropics in the western region is less robust. Preliminary calculations using Pathfinder data, however, appears to confirm the propagation of seasonal variations of tropical origin through the Mozambique Channel. These calculations, however, did not show the connections between the tropical and the Agulhas Current variability suggested by earlier modeling studies (e.g., Biastoch et al., 2001, M2002; Reason et al., 2003). This result is, perhaps, not surprising since the region south of the Mozambique Channel is characterized by high eddy variability and strong recirculation cells that obscure the location of the mean flow (e.g., De Ruijter et al., 2002; Riderinkhof and de Ruijter et al., 2003). The problem is compounded by the fact that the annual signal in the model appears to be trapped close to the coast where it is difficult to compare model with observations (e.g., Ffield et al., 1997). The recent analysis of Palastanga et al. (2006), however, has shown evidence on the dynamical connections between the mesoscale variability around Madagascar and the large-scale variability of the Indian Ocean. Thus, our analysis confirms the model-based hypothesis that regional barotropic processes control the seasonal variability of the South Indian Ocean circulation. The importance of this finding lies in the fact that very little is known about the low-frequency variability of this region. To the best of our understanding, for example, there are only three studies that tried to address these matters with observations: Quartly and Srokosz (1993); Ffield et al. (1997), and Matano et al. (1998).
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These articles, however, were largely focused on the Agulhas retroflection region and not in the basin scale circulation. Most of our understanding of the seasonal variability of the South Indian Ocean has been surmised from modeling studies. These studies have a limited academic value until validated by observations. In this article, however, we show that the structure of the seasonal variability deduced from model simulations is very similar to that obtained from satellite observations. The reasonable good correspondence between model and observations is partially attributed to the fact that seasonal variations are controlled by barotropic motions which, due to their relatively large scale, are well resolved by eddy-permitting simulations, and are largely insensitive to the details of the model stratification or the particulars of the parameterization of sub-grid processes (e.g., bottom friction, horizontal and vertical diffusion, etc), which are the Achilles tendon of most numerical simulations. Acknowledgments This article benefited from the criticism of two reviewers. The good sense of humor of one of them is particularly appreciated. This work was supported by NSF grant OCE-0726994, NASA grant NAG512378 and JPL contract 1206714. References Biastoch, A., Reason, C.J.C., Lutjeharms, J.R.E., Boebel, O., 1999. The importance of flow in the Mozambique Channel to seasonality in the greater Agulhas Current System. Geophys. Res. Lett. 26, 3321–3324. Chelton, D.B., Schlax, M.G., 1996. Global observations of oceanic Rossby waves. Science 272, 234–238. Chelton, D.B., Schlax, M.G., Witter, D.L., Richman, J.G., 1990. Geo altimeter observations of the surface circulation of the Southern Ocean. J. Geophys. Res. 101, 14131–14145. De Ruijter, W.P.M., Ridderinkhof, H., Lutjeharms, J.R.E., Schouten, M.W., Veth, C., 2002. Observations of the flow in the Mozambique Channel. Geophys. Res. Lett. 29 (10), 1502. doi:10.1029/ 2001GL013714. De Ruijter, W.P.M., van Aken, H.M., Beier, E.J., Lutjeharms, J.R.E., Matano, R.P., Schouten, M.W., 2004. Eddies and dipoles around South Madagascar: formation, pathways and large-scale impact. Deep-Sea Res., Part 1 51, 383–400. Fetter, A.J., Lutjeharms, J.R.E., Matano, R.P., 2007. Atmospheric driving forces for the Agulhas Current in the subtropics. Geophys. Res. Lett. 4, L15605. doi:10.1029/2007GL030200.
Ffield, A., Toole, J., Wilson, D., 1997. Seasonal circulation in the South Indian Ocean. Geophys. Res. Lett. 24, 2773–2776. Gordon, A.L., 1985. Indian-Atlantic transfer of thermocline water at the Agulhas retroflection. Science 227 (4690), 1030–1033. Gordon, A.L., Susanto, R.D., Ffield, A., 1999. Throughflow within Makasaar Strait. Geophys. Res. Lett. 26 (21), 3325–3328. Inoue, M., Welsh, S.E., 1993. Modeling seasonal variability in the wind-driven upper-layer circulation of the Indo-Pacific region. J. Phys. Oceanogr. 23, 1411–1436. Kindle, J.C., 1991. Topography effects on the seasonal circulation of the South Indian Ocean. J. Phys. Oceanogr. 96, 16827–16837. Lutjeharms, J.R.E., 1996. The exchange of water between the South Indian and the South Atlantic. In: Wefer, G., Berger, W.H., Siedler, G., Webb, D. (Eds.), The South Atlantic: Present and Past Circulation. Springer-Verlag, Berlin, pp. 152–162. Lutjeharms, J.R.E., 2007. The Agulhas Current. Springer-Verlag. (330 pp). Matano, R.P., Simionato, C.G., de Ruijter, W.P., van Leeuween, P.J., Chelton, D.B., Schlax, M.G., 1998. Seasonal variability in the Agulhas retroflection region. Geophys. Res. Lett. 25, 4361–4364. Matano, R.P., Beier, E.J., Strub, P.T., Tokmakian, R., 2002. Largescale forcing of the Agulhas variability: the seasonal cycle. J. Phys. Oceanogr. 32, 1228–1241. Morrow, R., Birol, F., 1998. Variability in the South Indian Ocean from altimeter. Forcing mechanisms for the Leeuwin Current. J. Geophys. Res. 99, 26565–26583. Palastanga, V., van Leeuwen, P.J., de Ruijter, W.P.M., 2006. A link between low-frequency mesoscale eddy variability around Madagascar and the large-scale Indian Ocean variability. J. Geophys. Res. 111, C09029. doi:10.1029/2005JC003081. Perigaud, C., Delecluse, P., 1992. Annual sea level variations in the southern Indian Ocean from Geosat and shallow-water simulation. J. Geophys. Res. 97, 20169–20178. Quartly, G.D., Srokosz, M.A., 1993. Seasonal variations in the region of the Agulhas Retroflection: studies with Geosat and Fram. J. Phys. Oceanogr. 23, 2107–2124. Quartly, G.D., Srokosz, M.A., 2004. Eddies in the Southern Mozambique Channel. Deep-Sea Res., Part 2 51, 69–83. Reason, C.J.C., Lutjeharms, J.R.E., Hermes, J., Biastoch, A., 2003. Inter-ocean fluxes south of Africa in an eddy permitting model. Deep-Sea Res., Part 2 50, 281–298. Ridderinkhof, H., de Ruijter, W.P.M., 2003. Moored current observations in the Mozambique Channel. Deep Sea Res., Part 2 50, 1933–1955. Schouten, M.W., de Ruijter, W.P.M., van Leeuwen, P.J., 2002. Upstream control of the Agulhas Ring shedding. J. Geophys. Res. 107 (C8), 3109. doi:10.1029/2001JC00804. Stramma, L., Lutjeharms, J.R.E., 1997. The flow field of the subtropical gyre of the South Indian Ocean. J. Geophys. Res. 102 (C3), 5513–5530. Tokmakian, R., Challenor, P.G., 1999. On the joint estimation of model and satellite sea surface height anomaly errors. Ocean Model. 1, 39–52. Woodberry, K.E., Luther, M.E., O'Brien, J.J., 1989. The wind-driven seasonal circulation in the southern tropical Indian Ocean. J. Geophys. Res. 94, 17985–18002.
Journal of Marine Systems 74 (2008) 315 – 328 www.elsevier.com/locate/jmarsys
The seasonal variability of the circulation in the South Indian Ocean: Model and observations R.P. Matano a,⁎, E.J. Beier b , P.T. Strub a a
College of Oceanic and Atmos. Sciences, Oregon State University, Corvallis, OR, 97331-5503, United States b CICESE Unidad La Paz, La Paz, B.C.S. Mexico Received 20 November 2006; received in revised form 12 January 2008; accepted 16 January 2008 Available online 14 February 2008
Abstract This article compares the seasonal variability patterns of the South Indian Ocean circulation derived from a global, eddypermitting, numerical model and altimeter observations. The seasonal variability of the Indian Ocean circulation is driven by the inflow from the Indonesian Passages and by the local wind forcing. Our analysis indicates that the influence of the Indonesian throughflow is confined to the easternmost portion of the basin, while the influence of the wind stress forcing is important everywhere. Model and observations indicate that, between ~ 105°E and 75°E, the seasonal variability is characterized by the southwestward propagation of an annual wave over a period of ~ 4 months. Preliminary calculations using Pathfinder data also indicate that, in the western region, there are seasonal perturbations that originate in the tropics and propagate poleward through the Mozambique Channel. Our calculations, however, did not find the connections between the tropical and the Agulhas Current variability suggested by earlier modeling studies. © 2008 Elsevier B.V. All rights reserved. Keywords: Western boundary; Seasonal variability; Modeling; South Indian Ocean; Model and observation
1. Introduction The South Indian Ocean circulation includes a tropical cyclonic gyre, which extends from the equator to approximately 17°S, and a subtropical anticyclonic gyre that extends from approximately 17°S to 47°S (see Lutjeharms, 2007 and references therein) (Fig. 1). These gyres are the conduit through which Pacific waters entrained by the Indonesian throughflow are discharged onto the eastern Atlantic by the Agulhas retroflection (Gordon, 1985; Gordon et al., 1999; Lutjeharms, 1996).
⁎ Corresponding author. E-mail address: [email protected] (R.P. Matano). 0924-7963/$ - see front matter © 2008 Elsevier B.V. All rights reserved. doi:10.1016/j.jmarsys.2008.01.007
Since the entrainment from the Pacific occurs in the tropics, and the detrainment onto the Atlantic in the subtropics, the Indian Ocean circulation has to transfer mass and energy between its gyres. These transfers are largely accomplished by eddies and narrow currents within the Mozambique Channel and east of Madagascar (De Ruijter et al., 2002, 2004; Schouten et al., 2002; Ridderinkhof and de Ruijter, 2003; Quartly and Srokosz, 2004; Lutjeharms, 2007). The variability of these eddies and currents are linked to the large-scale circulation and are therefore modulated by its low-frequency variability (e.g., Schouten et al., 2002; Palastanga et al., 2006). Thus, our ability to understand the dynamical mechanisms that participate in the global interocean exchanges is tied to our ability to understand the process that controls the
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Fig. 1. Bottom topography of the Tropical and the South Indian Ocean. Grey arrows mark the mean geostrophic circulation according to Stramma and Lutjeharms (1997). The boxes in the stippled rectangles mark the approximate domains of the three modes of annual variability defined by Matano et al. (2002).
variability of the Indian Ocean gyres. In this article we investigate one of the most distinctive modes of lowfrequency variability of the Indian Ocean circulation, the seasonal cycle. Previously we investigated the seasonal variability of the South Indian Ocean using the results of a global, eddy-permitting, numerical simulation (Matano et al., 2002; henceforth M2002). This analysis showed that at seasonal time scales, the large-scale circulation in the South Indian Ocean is modulated by the oscillation of barotropic modes forced directly by the wind. The pulsation of these modes generates a seasonal variation of the transport of the Agulhas Current, with a peak at the transition between the austral winter and the austral spring, and a trough at the transition between the austral summer and the austral autumn. The modes described by M2002 appear to be a robust characteristic of other numerical simulations of the South Indian Ocean circulation (e.g., Matano et al., 1998; Biastoch et al., 1999; Fetter et al., submitted for publication). The existence of these modes, however, has not been confirmed by observations, i.e., most of what we know about the seasonal variations of the South Indian Ocean circulation has been inferred from model results without a direct verification from real data. It seems, therefore, of broad interest to determine whether the variability structure predicted by numerical models are corresponded by observations. As a step in that direction in this article we compare the results of the numerical simulation described by M2002 with altimeter data. We show that the structure of the seasonal variability deduced from models is similar to that obtained from observations. This finding indicates that regional processes, i.e., pro-
cesses occurring within sub-basins determined by the bottom topography, control the seasonal variability of the South Indian Ocean circulation. 2. Data and methods 2.1. Model The model results were produced by the Parallel Ocean Circulation Model (POCM) experiment (Tokmakian and Challenor, 1999). The model configuration and numerical results have been described in M2002 therefore only a brief discussion will be included here. The model solves the primitive equation in a Mercator grid with an average horizontal grid spacing of 1/4° and 20 vertical levels. Our analysis is focused on the experiment 4C, which was run for a 19-year period. From 1979 to 1994 the model was forced with atmospheric fluxes derived from the reanalysis of the European Center for Medium-Range Weather Forecast, after that the forcing fluxes were replaced with data from operational forecast experiments. 2.2. Altimeter data T/P and ERS data, reprocessed by the NASA/GSFC Pathfinder Ocean Altimeter group, are the basis for the gridded fields of sea surface height. To determine the 0spatial structure of the large-scale variability we use T/P data which was interpolated using a loess smoother filter with 8° in longitude, 2° in latitude and 25 days in time with estimates at 3 days intervals on a one degree grid. A detailed discussion of the data processing can be
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found in Chelton et al. (1990). To reduce the steric effect associated with the annual variation of the solar radiation we subtracted the zonal average of the SSHAs from the original fields. Since the interpolation procedures used by Chelton et al. eliminates most of the data in the Mozambique Channel and surrounding area we did some ancillary calculations using higher resolution data from the Pathfinder mission.
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To characterize the variability from the model and the observations we calculated the standard deviations, annual harmonics, Hovmöller diagrams, and EOF modes of the sea surface heights anomalies (SSHAs). To facilitate the comparison we used only data of the period during which both data sets overlap i.e., from 1993 through 1998. Our study will focus in the Indian Ocean region between 5°N and 30°S.
Fig. 2. Standard deviation [cm] from T/P data (panel a) and POCM_4C (panel b). The values were calculated from time series from the beginning of 1993 to the end of 1997. The shadow areas represent regions where the values are bigger than 3 cm. Panel c shows the time evolution of the basin averaged sea level elevation from both time series.
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3. Results The M2002 analysis indicates that the seasonal variabilities of the tropical and subtropical Indian Ocean are connected by three barotropic modes. The first is located in the eastern portion of the basin and reaches its maximum amplitude in the Indonesian Passages. The second mode is centered in the middle of the basin and it is limited, in the zonal direction, by the bottom topography. The third mode is restricted to the western portion of the basin and encompasses two distinctive regions. To the south it extends into the Mozambique
Channel and reaches up to the Agulhas Current. To the north it extends up to the equator and encompasses the South Equatorial Current. M2002 concluded that while the first mode is largely driven by the seasonal variations of the Indonesian throughflow, the other two are forced by the wind stress forcing. These conclusions were in general agreement with the earlier modeling results of Biastoch et al. (1999) who also noted that seasonal anomalies in the tropical circulation propagate poleward through the Mozambique Channel and influence the mass transport of the Agulhas Current. The seasonal variations described from these models,
Fig. 3. Amplitudes (background color) and phases (white contours) of the annual harmonic from altimeter observations (upper panel) and the POCM4C experiment (bottom panel). The units of the amplitudes are in cm and the phases are in months. A color version of this figure could be found in the online version of this article.
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however, have not yet been verified by observations. As a step in that direction in what follows we compare the results of POCM with altimeter observations. 3.1. Standard deviations To characterize the overall variability of both data sets we computed the standard deviations of the SSHAs (Fig. 2). There is a reasonable agreement between model and observations although the former shows small-scale structures that are absent in the coarsely sampled altimeter data (Fig. 2a and b). The largest differences are observed near coastal regions (e.g., the Mozambique
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Channel, the eastern Madagascar coast), which are outside of the resolution of the altimeter data. The region between 4° and 18° S shows the largest variability in SSHAs, with peaks of 14 cm near Indonesia and 11 cm near 80°E 10°S. Most of the variance in both data sets is contained in the annual and inter-annual periods (Fig. 2c). The annual cycle explains 32% of the variance of the T/P data and 37% of POCM. The amplitude of the annual fit of the basin averaged T/P data is 1.3 +/− 0.15 cm with a maximum during the middle of December and a minimum during July. The amplitude of the model data is 1.1 +/− 0.13 cm. The phase difference between both data sets is 10 days.
Fig. 4. (a) Hovmöller diagrams of the SSHA from model (top panel) and the altimeter data (middle panel) at 8°S. The bottom panel shows the bottom topography of the model at the same latitudinal strip. The units of SSHA are in cm. (b): Hovmöller diagrams of the SSHA from model (top panel) and the altimeter data (middle panel) at 12°S. The bottom panel shows the bottom topography of the model at the same latitudinal strip. The units of SSHA are in cm.
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Fig. 4 (continued ).
3.2. Harmonic analysis The amplitudes and phases of the annual harmonics from both data sets are very similar (Fig. 3). The amount of variance explained by the annual harmonic is generally high, with a maximum of ~ 60% over the central region and ~ 40% near the eastern and western boundaries (not shown). Both data sets show amplitude maxima (background color) in the northeastern and northwestern portions of the basin, although the spatial structures of the model show more mesoscale structure due to their higher spatial resolution. The model, for example, shows two relative maximum in the northeastern region: one centered at ~ 90°E and the other over the Indonesian Passages, while the altimeter data shows a single maximum that extends from ~ 80°E to 120°E. The model maxima have been also reported in previous observational studies, which argue that they are driven
by different dynamical processes: the maximum near 90°W is driven by the local winds, while the one centered in the Indonesian Passages is driven by the inflow from the Pacific Ocean (Woodberry et al., 1989; Inoue and Welsh, 1993, Morrow and Birol, 1998; Gordon et al., 1999). Model and observations also show high amplitudes in the northwestern portion of the basin (Fig. 3). The observations show an absolute maximum near the northeastern tip of Madagascar and a secondary maximum centered near 5°S 48°E. This maximum is displaced to the northwest in the model and it is driven by the seasonal variations of the South Equatorial Countercurrent. The distribution of phases (white contours), indicate that the eastern and western regions are not connected by annually propagating waves but are separated by a region of vanishing amplitudes (in both data sets), and an amphidromic line (Fig. 3). The most robust propagating
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Fig. 5. Amplitudes (upper panel) and phases (lower panel) of the annual harmonic of the zonally averaged sea surface elevation from the altimeter (grey dashed contours) and the model (black solid line). The bars indicate the error of the fit.
signal of both data sets is observed in the northeastern portion of the basin. There, there is a southwestward propagating signal that moves between 105° and 75°E in a period of ~4 months. This signal was previ-
ously reported, and extensively described, by Perigaud and Delecluse (1992) and Morrow and Birol (1998). The model results indicate the existence of westward propagation in the western portion of the domain (west of
Fig. 6. Amplitude of the annual harmonic derived from the model (upper panel) and from the Pathfinder altimeter data (bottom). The amplitudes are given in cm. The stars in the left panel mark the location of the data (both model and altimeter) that we used to calculate Fig. 6.
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~75°E), but this signal is not obvious in the observations. The region that separates the eastern and western amplitude maxima follows the approximate course of the Mid-Indian Ridge and the Ninety East Ridge (Fig. 1). M2002 observed that these topographic features interrupt the westward progression of the annual signal in POCM. These signals appear to be particularly sensitive to the presence of the Mid-Indian Ridge, the Chagos Archipelago, and the Mascarene Plateau. M2002 argued that the topographic effects enhance the contribution of the local forcing (in detriment to remote forcing), and that the seasonal adjustment of the South Indian Ocean is therefore better described in terms of standing modes rather than in terms of propagating waves. According to this argument the transport of the Agulhas Current, for example, is largely unaffected by the seasonal changes of the winds in the eastern portion of the Indian basin (east of ~75°E), or the seasonal variations of the Indonesian Throughflow. These arguments are in agreement with the earlier modeling results of Kindle (1991) who reported
that the predominantly barotropic, seasonal signal that is generated in the eastern portion of the Indian basin is reflected at the Mascarene Plateau. The M2002 arguments were entirely based on the POCM results. Therefore it is of interest to compare the characteristics of the westward propagating signals derived from POCM with those from the altimeter (Fig. 4a and b). There is a general agreement between POCM and observations although the amplitudes predicted by the model are smaller than those calculated from the altimeter. The phase speeds derived from POCM, however, are close to those found in T/P and for this range of latitudes and to the values predicted by theory (Chelton and Schlax, 1996). The topographic effects discussed in M2002 are also observed in the altimeter data. At 8°S, the Ninety East Ridge limits the westward progression of the signals generated near the eastern boundary (Fig. 4a). New waves appear to be generated along the eastern flank of the ridge (Fig. 4a). These waves appear to be affected, farther west, by the Mascarene Plateau.
Fig. 7. Amplitudes and phases of the annual harmonic computed along the coastal points in Fig. 5. The black line correspond to the mode and the grey line to the observations.
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There are some noticeable differences between the model and observations in the region between 60°E and 80°E. The model shows a standing mode with a maximum near the western limit while the existence of such a mode is not obvious in the observations. Both data sets show similar amplitudes (~ 3 cm) to the west of the Mascarene Plateau and the existence of a regional mode between 60˚E and the African coast. The same general characteristics are also observed at 12°S (Fig. 4b). In both cases the main discrepancies between the annual fits to the model and the observations are located in the central region. The modeled amplitudes of the annual fit are also smaller in both cases. To further quantify the fitness between observations and model we calculated the annual harmonic of the zonally averaged SSH for the model and the T/P ob-
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servations (Fig. 5). As expected from the above discussion the amplitudes of both data sets show similar latitudinal distributions (Fig. 5, upper panel). The largest differences are observed in region between the equator and 8°S but even there the fitting error bars indicate that these differences are not statistically significant. Model and observations, however, show significant discrepancies of their phases, with a maximum of 4 months, in the latitudinal strip between the equator and 5°S (Fig. 5, lower panel). In that region however, the amplitudes are relatively small. Farther south the sea level reaches a maximum (in both model and observations) between February and March and a minimum between August and September. In the overall balance this calculation shows that there is a high correlation between model and observations outside from the tropics, the correlation
Fig. 8. (a)Amplitudes of the first EOF from the observations (top panel) and the model (middle panel). The bottom panel shows their corresponding time series. The units of amplitudes are in cm. A color version of this figure could be found in the online version of this article.
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Fig 8b. (b): Amplitudes of the second EOF from the observations (top panel) and the model (middle panel). The bottom panel shows their corresponding time series. The units of amplitudes are in cm. A color version of this figure could be found in the online version of this article.
coefficient of annual harmonics of the SSHs from model and observations is approximately 0.8. The above analysis indicates that the seasonal variability of the South Indian Ocean circulation can be explained in terms of basin modes that draw their energy from the local winds and that are delimited by the bottom topography. Those conclusions are in agreement with the earlier findings of M2002 whom, in addition, showed that the tropical variations of the westernmost mode propagates poleward into the Mozambique Channel and, from there, into the Agulhas Current. It is not possible to corroborate these model predictions from the coarsely gridded T/P data used in this analysis (e.g., Fig. 3). To address these matters however, we recalculated the annual harmonic of the western region using a data set with higher spatial resolution (Pathfinder) (Fig. 6). The new calculation indicates that the
spatial structures derived from the altimeter are qualitatively similar to those from the model although the amplitudes are smaller and there is no evidence of the intense western intensification that characterize the western boundary region. To investigate the existence of poleward propagating signals in the Mozambique we computed the amplitudes and phases of the annual harmonics at the nearshore locations marked in Fig. 6 (Fig. 7). The altimeter data used for this calculation correspond to the first ocean grid point along the descending tracks (~ 50 km from the coast), while the location from the model data corresponds to the grid point closest to the observations. There is a close correspondence between model and observations. The largest discrepancies are observed in the equatorial region where the model appears to overestimate the amplitude of the seasonal cycle. South of ~ 5°S, however, there is a
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Fig. 8c. (c): Amplitudes of the third EOF from the observations (top panel) and the model (middle panel). The bottom panel shows their corresponding time series. The units of amplitudes are in cm. A color version of this figure could be found in the online version of this article.
remarkable agreement between the phases and amplitudes from both data sets. The distribution of phases indicates the possible existence of propagation between 10° and ~ 20°S. This signal, however, is lost near 20°S, perhaps due to the existence of a sharp bending of the coastline that diverts the flow farther offshore (e.g., M2002). 3.3. EOF analysis To further evaluate the realism of the numerical simulation we calculated the Empirical Orthogonal Functions (EOFs) of the SSHA anomalies of both data sets (Fig. 8). The first three modes account for 49% of the total variance of the observations and 46% of the model. The first mode, which accounts for 23% and
24% of the variances of the observations and model, reflects more the large-scale structure of the equatorial circulation than the mesoscale structures associated with the subtropical gyre (Fig. 8a). The amplitudes and time series associated with both data sets are qualitatively similar although the model amplitudes are slightly smaller than those of the observations. The largest SSHA gradients of both EOFs are located in the northeastern portion of the basin. The time series associated with this mode seems to reflect more inter-annual variations than seasonal changes. Note, for example, that both data sets capture the 1995 and 1998 El Niños. In fact, the annual fit to the time series indicates that annual cycle accounts for only 36% of the variance in the T/P mode and 25% in the POCM mode. As a side calculation we extracted the annual signal from both
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Fig. 9. (a) Amplitudes of the first EOF mode [dyne/cm⁎⁎3 10⁎⁎9] of the wind stress curl (upper panel) and the corresponding time series (lower panel). Shadow areas correspond to values bigger than 10 (solid) and − 10 (stippled). (b): Amplitudes of the second EOF mode [dyne/cm⁎⁎3 10⁎⁎9] of the wind stress curl (upper panel) and the corresponding time series (lower panel). Shadow areas correspond to values bigger than 5 (solid) and − 5 (stippled).
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data sets and re-calculated the corresponding EOFs. The results (not shown) are similar to those shown herein except that the westernmost maximum disappears and there is only one maximum at 73°E–8°S. In this calculation the spatial structures of model and observed EOFs at the Indonesian Passages are more similar to each other than those shown in Fig. 8a. The second EOFs represent 15% and 14% of the variances of the observations and the model (Fig. 8b). The annual fits to these modes explain 72% and 84% of their respective variances, which indicates that this particular mode contains most of the seasonal signal. Both EOFs show similar spatial and temporal structures, although the amplitudes of the model are smaller than those of the observations. North of 20°S, both data sets show two regional maximum centered near 90°E and 65°E. The corresponding maxima in the observations are displaced to the northwest of those in the model, although they both are within the region of maximum SSHA variation found in the harmonic analysis (Fig. 3). There are relatively minor differences in the spatial structures of the model and observations over the eastern equatorial region. The model, for example, shows a maximum at 83°E 5°S that is absent in the observations. Both data sets, however, show the well-defined structure of the South Equatorial Current near 5°S. The third EOF mode explains 11% and 9% of the observations and models variance (Fig. 8c). This mode also represents the seasonal variability with annual fittings that explain 86% and 68% of the variance of the observations and model. The largest differences between model and observations are in the eastern side of the basin. There, the SSHA maxima that extends towards the northwest in the altimeter is absent in the model. This discrepancy seems to be related to the dominance of the seasonal variability in this region. In fact, the similarity between the EOFs is greatly improved when the annual signal is extracted from the respective time series of both data sets. For the sake of completeness we also calculated the EOFs of the curl of the ECMWF wind stress, which is used to force POCM (Fig. 9a and b). The spatial structure of the first mode is largely uniform with no major regional differentiation (except for a local maximum at the tip of Madagascar), and therefore can be thought as representations of the large-scale (hemispheric) circulation (Fig. 9a). Most of the information on the basin scale circulation is captured by the second EOF (Fig. 9b), which explains 11% of the total variance (the annual fit to this mode explains 54% of its own variance). One of the most interesting characteristics of this mode is the relative maximum in the eastern side of the basin
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(~ 90°E 11°S), which closely corresponds with the amplitude maxima observed in the EOF and annual harmonic of the SSHAs (Figs. 7 and 3 respectively). It seems, therefore, reasonable to conclude that the wind stress forcing locally drives the seasonal variability of this region. 4. Summary and discussion The seasonal variability of the Indian Ocean circulation is driven by the inflow from the Indonesian Passages and by the local wind forcing. The influence of the Indonesian throughflow, however, appears to be confined to the easternmost portion of the basin, while the influence of the wind stress forcing is important everywhere. Our analysis indicates that seasonal variations of tropical origin propagate to the subtropics in the central portion of the basin and in the western region. In the central region, there is strong evidence of an annual wave that propagates southwestward between ~ 105°E and 75°E in a period of ~ 4 months. The connection between the tropics and subtropics in the western region is less robust. Preliminary calculations using Pathfinder data, however, appears to confirm the propagation of seasonal variations of tropical origin through the Mozambique Channel. These calculations, however, did not show the connections between the tropical and the Agulhas Current variability suggested by earlier modeling studies (e.g., Biastoch et al., 2001, M2002; Reason et al., 2003). This result is, perhaps, not surprising since the region south of the Mozambique Channel is characterized by high eddy variability and strong recirculation cells that obscure the location of the mean flow (e.g., De Ruijter et al., 2002; Riderinkhof and de Ruijter et al., 2003). The problem is compounded by the fact that the annual signal in the model appears to be trapped close to the coast where it is difficult to compare model with observations (e.g., Ffield et al., 1997). The recent analysis of Palastanga et al. (2006), however, has shown evidence on the dynamical connections between the mesoscale variability around Madagascar and the large-scale variability of the Indian Ocean. Thus, our analysis confirms the model-based hypothesis that regional barotropic processes control the seasonal variability of the South Indian Ocean circulation. The importance of this finding lies in the fact that very little is known about the low-frequency variability of this region. To the best of our understanding, for example, there are only three studies that tried to address these matters with observations: Quartly and Srokosz (1993); Ffield et al. (1997), and Matano et al. (1998).
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These articles, however, were largely focused on the Agulhas retroflection region and not in the basin scale circulation. Most of our understanding of the seasonal variability of the South Indian Ocean has been surmised from modeling studies. These studies have a limited academic value until validated by observations. In this article, however, we show that the structure of the seasonal variability deduced from model simulations is very similar to that obtained from satellite observations. The reasonable good correspondence between model and observations is partially attributed to the fact that seasonal variations are controlled by barotropic motions which, due to their relatively large scale, are well resolved by eddy-permitting simulations, and are largely insensitive to the details of the model stratification or the particulars of the parameterization of sub-grid processes (e.g., bottom friction, horizontal and vertical diffusion, etc), which are the Achilles tendon of most numerical simulations. Acknowledgments This article benefited from the criticism of two reviewers. The good sense of humor of one of them is particularly appreciated. This work was supported by NSF grant OCE-0726994, NASA grant NAG512378 and JPL contract 1206714. References Biastoch, A., Reason, C.J.C., Lutjeharms, J.R.E., Boebel, O., 1999. The importance of flow in the Mozambique Channel to seasonality in the greater Agulhas Current System. Geophys. Res. Lett. 26, 3321–3324. Chelton, D.B., Schlax, M.G., 1996. Global observations of oceanic Rossby waves. Science 272, 234–238. Chelton, D.B., Schlax, M.G., Witter, D.L., Richman, J.G., 1990. Geo altimeter observations of the surface circulation of the Southern Ocean. J. Geophys. Res. 101, 14131–14145. De Ruijter, W.P.M., Ridderinkhof, H., Lutjeharms, J.R.E., Schouten, M.W., Veth, C., 2002. Observations of the flow in the Mozambique Channel. Geophys. Res. Lett. 29 (10), 1502. doi:10.1029/ 2001GL013714. De Ruijter, W.P.M., van Aken, H.M., Beier, E.J., Lutjeharms, J.R.E., Matano, R.P., Schouten, M.W., 2004. Eddies and dipoles around South Madagascar: formation, pathways and large-scale impact. Deep-Sea Res., Part 1 51, 383–400. Fetter, A.J., Lutjeharms, J.R.E., Matano, R.P., 2007. Atmospheric driving forces for the Agulhas Current in the subtropics. Geophys. Res. Lett. 4, L15605. doi:10.1029/2007GL030200.
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