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Ocean Model Simulation of SouthernIndian Ocean Surface CurrentsAnshu Prakash Mishra a , S. Rai a & A. C. Pandey ba K. Banerjee Center of Atmospheric and Ocean Studies , Universityof Allahabad , Allahabad, Indiab Department of Physics , University of Allahabad , Allahabad, IndiaPublished online: 07 Nov 2007.

To cite this article: Anshu Prakash Mishra , S. Rai & A. C. Pandey (2007) Ocean ModelSimulation of Southern Indian Ocean Surface Currents, Marine Geodesy, 30:4, 345-354, DOI:10.1080/01490410701568467

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Marine Geodesy, 30: 345–354, 2007Copyright © Taylor & Francis Group, LLCISSN: 0149-0419 print / 1521-060X onlineDOI: 10.1080/01490410701568467

Ocean Model Simulation of Southern Indian OceanSurface Currents

ANSHU PRAKASH MISHRA,1 S. RAI,1 AND A. C. PANDEY2

1K. Banerjee Center of Atmospheric and Ocean Studies, Universityof Allahabad, Allahabad, India2Department of Physics, University of Allahabad, Allahabad, India

The dynamic importance of the Southern Indian Ocean (SIO) lies in the fact thatit connects the three major world oceans: the Pacific, Atlantic, and Indian Oceans.Modeling study has been used to understand the circulation pattern of this very importantregion. Simulation of SIO (10◦N–60◦S and 30◦E–120◦E) is performed with z-coordinateOcean General Circulation Model (OGCM) viz; MOM3.0 and the results have beencompared with observed ship drift data. It is found that except near coastal boundariesand in equatorial region, the simulated current reproduce most well known currentpattern such as Antarctic Circumpolar Current (ACC), South Equatorial Current (SEC)etc. and bears a resemblance to that of the observed data; however the magnitude ofthe surface current is weaker in model than the observed data, which may be due todeficiency in the forcing field and boundary condition and problem with observed data.The annual mean wind stress curl computed over the oceanic domain reveals aboutACC and its similar importance. The way in which the ocean responds to the windstressand vertically integrated transport using model output is fascinating and rathergood.

Keywords Southern Indian Ocean, z-coordinate Ocean General Circulation Model(OGCM), Antarctic circumpolar current, south equatorial current, wind stress curl,vertically integrated volume transport

Introduction

In the past decade, there has been significant interest in the dynamics of ocean circulationto understand its role in the climate system (Semtner and Chervin 1992). Ocean GeneralCirculation Model (OGCMs) are useful for studying the ocean circulation, interiorprocesses, and variability, but they depend on data and other atmospheric properties. Thestrongest winds in the world blow over the southern ocean. Wunsh (1998) estimated thatthe southern ocean receives 70% of the work done by the wind on the ocean. These principalwinds are responsible for driving the Antarctic Circumpolar Current (ACC). The southernocean is the only ocean whose dynamical regime resembles with that of the atmosphere, inthat a zonally unbounded current, ACC exists (Killworth and Majeed Nanneh 1994). It has

Received 6 January 2007; accepted 6 July 2007.Address correspondence to Anshu Prakash Mishra, Central Water Commission, Upper

Brahmaputra Division, J.P.Nagar, POCR Building, Dibrugarh, Assam, 786003. E-mail: anshu 786@rediffmail.com, anshu ms@yahoo.com

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also been now clear that the southern ocean is unique in that it circles the globe withoutbeing blocked by land. The strong flow of the circumpolar current from west to east aroundAntarctica connects the Pacific, Indian, and Atlantic Ocean basins and their currents, and theresulting global circulation redistributes heat and other properties. The ACC is the strongestcurrent in the world ocean, and the transport of ACC in the Drake Passage as estimatedfrom International Southern Ocean Studies (ISOS) dataset is about 130 Sv (Sv = 106 m3/s)(Nowlin and Klinck 1986). This current extends from 45◦S to 55◦S (Trenberth, Large,and Olson 1990; Orsi, Whitworth, and Nowlin 1995), and it is generally thought that thewind stress is the main source of zonal momentum for this current, although thermohalineprocesses may also be important in driving the ACC (Olbers and Wubber 1991). Therefore,a modeling study of the circulation pattern of this part of the Indian Ocean is analyticallysomewhat intractable.

Currently, the observation stations for measuring the ocean current are sparse in thesouthern ocean region, and the fields are not reliable south of 45◦S. The measurements ofoceanic current by ship drift and ocean drifter buoy are also limited and their quality is stillnot reliable. Observations collected by ship drift data in recent years enable us to quantifyand understand the ocean current pattern for the first time. In this study, we have attemptedto discuss the surface circulation pattern of SIO region performed using an ocean model andits comparison with above ship drift observation of 1◦ × 1◦ resolution (Mariano and Brown1992). The attempt is preliminary of how model output appears against the observation. Wehave used ship drift observed velocity field data in the present study in which each velocitycomponent has been estimated using the scalar objective analysis routine (Mariano andBrown 1992) after a median filter (Mariano et al. 1995) was applied to remove the grossoutliers.

Surface winds are the principal driver of the upper ocean circulation through windstress. The upper ocean circulation in each ocean basin is driven primarily by the large-scaledistribution of wind stress or, more exactly, by the curl of the wind stress. The continuinginability to adequately describe the wind field over the oceans significantly limits our abilityto simulate and model ocean circulation (Siedler, Church, and Gould 2000). Classicaltheories of wind driven circulations demonstrate that the rotational component of windstress drives ocean circulation, while the non-rotational component does not produce oceancirculations within the framework of a barotropic shallow water model but balances with thepressure gradient force due to surface displacement in the steady state (Yoshioka et al. 2002).The stress force of the wind gives the ocean an initial velocity field in the direction of thewind, but the Coriolis effect due to the earth’s rotation exerts an acceleration proportionalto velocity at 90◦ to the direction of motion. This turns the ocean velocity away fromthe direction of the wind, and the resulting Ekman transport is 90◦ to the right of winddirection in the Northern Hemisphere and 90◦ to the left of wind direction in the SouthernHemisphere. In this paper, we will present a description of wind stress curl for the southernocean and its associated importance for the ACC along with integrated volume transportbased on long-term model simulation results.

Previous studies concentrated on comparing the results between different coordinateocean model for large-scale processes (Gerdes 1993) and Gulf Stream dynmics (Willems etal. 1994), while in this study the z coordinate ocean model, that is, Modular Ocean Model(MOM3.0), has been run for sufficiently longer time (1975–1998) and its results have beencompared qualitatively/quantitatively with observed data. In the following sections 2 and3, model description and results are given, respectively. Finally, conclusions are given insection 4.

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Ocean Model Simulation of Southern Indian Ocean Surface Currents 347

2. Model Description and Data

The Ocean General Circulation Model (OGCM) used in this study is a version 3 ofthe Geophysical Fluid Dynamics Laboratory (GFDL) Modular Ocean Model 3.0 (MOM3.0) (Pacanowski, Dixon, and Rosati 1993; Huang and Schneider 1995; Schneider et al.1999). Its domain is that of the world oceans between 74.25◦S and 65◦N. The zonalresolution is 1.5◦. The meridional resolution is 0.5◦ between 10◦N and 10◦S, graduallyincreasing to 1.5◦ at 20◦N and 20◦S. There are 25 levels in the vertical. The model usesthe K Profile Parameterization (KPP) vertical mixing and diffusion parameterization. Itshorizontal viscosity is calculated from the Smagorinsky nonlinear parameterization whileits tracer diffusion is treated in isopycnal coordinate. The model is forced by the monthlyaveraged surface wind stress from the NCEP-NCAR reanalysis for the period 1958–1998.The original surface reanalysis is on an irregular grid with a zonal resolution of 1.875◦ andGaussian latitudes of grid spacing less than 2◦, which is linearly, interpolated to the OGCMgrids. The model surface salinity is relaxed to Levitus (1982) monthly climatology. Surfaceheat flux is also relaxed to Levitus (1982) climatology and relaxation time is 100 days.Initial condition is taken from annual mean temperature and salinity field without motion(Levitus 1982). Boundary condition includes restoring to monthly temperature and salinityfields. The model is initialized from an ocean at rest with climatological temperature andsalinity and then spun up for the period 24 years under NCEP-NCAR climatlogical windstress forcing. Usually spun up time scale is different for different domains such as 9 months(for Pacific Ocean) to 11 years (for midlatittudes) and extending up to 50 years for globalocean model (Kantha and Clayson 2000).

3. Results and Discussions

The long-term model mean horizontal surface circulation pattern is shown in Figure 1(a).The model is simulating almost all major current system of this region, and the currentsystems are clearly verified with the observed data shown in Figure 1(b). However, fewcurrent system around coastal areas and in equatorial region show inability to simulate thepattern.

The major uninterrupted current system, that is, ACC, is seen between 40◦S to 60◦S andits velocity is between 30 cm/s and 40 cm/s, which is somewhat consistent with observeddata and with other observational studies (Klinck and Nowlin 2001). But the strength of themodel simulated current is weaker than the observed data which could be due to problemwith boundary conditions and forcing fields (Behra, Salvekar, and Yamagata 2000) in themodel and also with quality of observed data. The limited ability of the model in reproducingthese currents is caused by the low horizontal and vertical resolution and crude formulationof mixing. Other current systems simulated by the model are Agulhas current, SouthEquatorial current (SEC), and Equatorial Counter current (ECC). The Agulhas current,which is the major western boundary current of Southern Ocean, is simulated by the modelbut the observation show this current partially. South of South Africa, the Agulhas currentretroflects, and most of the flow curves sharply southward and then eastward to join thewest wind drift; this junction is often marked by a broken and confused sea, made muchworse by westerly storms. A small part of the Agulhas current rounds the southern end ofAfrica and helps to form the Benguela current; occasionally strong eddies are formed inthe retroflection region and theses too move into southeastern Atlantic.

The South Equatorial current is simulated well by the model and is seen to combinewith ACC from the coast of Madagascar in the model and these are also compared with the

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Figure 1. (a) Long-term mean model simulated Surface Current (m/s) (b) Ship drift observed meanSurface Current (m/s) (here vector length of 0.5 cm represent speed of 0.4 m/s).

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Ocean Model Simulation of Southern Indian Ocean Surface Currents 349

observation to certain extent. It is also seen that Equatorial Counter current flowing towardeastward is simulated by the model and compared with the observation while the NorthEquatorial current (NEC) is simulated by the model only and not by the observed data.The fastest moving current in this region is SEC (Figure 1a), which has been simulatedhaving its speed in the range of 40 cm/s to 50 cm/s which is in confirmation with shipdrift observation shown in Figure 1b. Moreover the speed of the ACC simulated by themodel is 30–40 cm/s, while by the observed data it is in the range of 40–50 cm/s. For moreclarity we have also plotted difference fields between model and observed data, shown inFigure 2a. This clearly indicates the strength of the current for the model and observed data,which is in confirmation with other modeling and observational studies (Klinck and Nowlin2001).

It is to be noted that these current systems are mainly caused by the wind and tosome extent by buoyancy forces, but their effects are small and therefore all major currentsystems captured by the model are wind driven. The mechanism by which winds drive theACC have been the subject of extensive debate. Attention has focused primarily on thephysics governing the mean flow. Munk and Palmen (1951) first suggested that surfacewind stress over the ACC might be balanced by form stress due to pressure gradientsacross topographic obstructions on the ocean floor. It is also shown by John Marshall andTimour Radko (MIT, Germany 2002) in their work on ACC that westerly winds drive theACC eastward and, through associated Ekman currents, induce an Eulerian meridionalcirculation (The Deacon Cell, Doos and Webb 1994) which acts to overturn isopycnals,enhancing the strong frontal region maintained by air-sea buoyancy forcing. In order todemonstrate, ACC is wind driven circulation, a spatial plot of annual mean wind stress curl(N m−3) over the oceanic domain (74◦S–15◦N, 30◦E–120◦E) calculated from model datais shown in Figure 2b. The annual mean wind stress curl computed from the model agreesreasonably well with earlier calculations (Scientific user manual section5,www.nodc.noaa.gov/woce V2/disk14/MWF HTML/SERVICES/MWF SCI/E500ANAL.HTM). Thelargest values are located mostly in the Southern oceans as obvious in Figure 2b. The zeroline of the wind stress curl near equator and in southern ocean indicating the northwardand southward transports of subpolar and subtropical gyres, respectively. Other featuressuch as positive curls located between 25◦S and 45◦S are revealed, and a banding shapestructure between 40◦S and 50◦S (Figure 2b) is also revealed, which tells that ACC andthe curl changes in the Indian Ocean are related to the monsoon event. It is clear fromthis plot that wind stress curl is able to produce ACC as evidenced by the magnitude ofthe curl around 40–50◦S. It is to be noted that positive wind stress curls causes divergencein the Ekman Layer, and upward Ekman pumping and negative wind stress curls causesconvergence in the Ekman Layer and downward Ekman pumping. In previous researchrelated to ACC, it was shown that positive wind stress curls can drive Sverdrup circulationwithin the subtropical gyres that may indirectly force the ACC (Gille et al. 2001) as is thecase reflected in Figure 2b. Further it is to be noted that in the latitudes of Drake Passage,wind stress is coherent with ACC transport and is therefore likely to govern ACC transportfluctuations (Gille et al. 2001).

In recent years much attention has been drawn to the effect of topography (Volker 1999)and stratification on the transport of ACC, but their effects are unclear. Previous studiesbased on numerical models have suggested that in addition to wind stress and wind stresscurl, buoyancy forcing may also play a role in determining the ACC transport (Gnanadesikanand Hallberg 2000; Gent et al. 2000). Therefore an attempt has been made to evaluate howwell ocean general circulation models duplicate with the observed characteristics of ocean

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Figure 2. (a) Difference of the model and observed data (here vector length of 0.5 cm representsspeed of 0.4 m/s). (b) annual mean wind stress curl from the model data (units are in N/m3).

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Ocean Model Simulation of Southern Indian Ocean Surface Currents 351

Figure 3. Vertically integrated transport from the model data for (a) u (b) v (units are in m2/s).

response to wind. In fact, there is need to perform the model simulation with differentphysics and wind forcing and compare them with other sources of observed data to test themodel efficacy.

Since model is integrated for longer time, therefore we have also presented verticallyintegrated transport (m2/s) using simulation results shown in Figures 3a and 3b. The way inwhich the model results give integrated transport using model output is fascinating. Fromthe plot, it is clear that the eastward transport in high-latitude corresponds to westerly winds,and the westward transport in the subtropics corresponds to easterly trade winds. Thereis evidence of northward transport in mid-latitudes and southward transport in subtropics,which may corresponds to Ekman transport (The Deacon Cell, Doos and Webb 1994). In

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particular, the latitudinal variation of integrated transport near ACC region (45–55◦S) isaround 270–300 m2/s (Figure 3a), while it is 80–100 m2/s near ACC region in Figure 3b asexpected.

4. Conclusions

In this paper the circulation pattern from an ocean model has been analyzed using oceanmodel diagnostic as a tool. The present research demonstrates that the model is capable ofsimulating successfully many aspects of ocean circulation with respect to the observation.Because of the lack of observing stations in the Southern Hemisphere, considerable doubtsremain about the quality of data over Southern Ocean. We conclude that substantial progresshas been made towards realistic simulation of these features, though some challengesremain. We conclude following points:

1. The simulated long-term mean surface current pattern is in agreement withobservations. Most of the key features of the observed patterns such as ACC (alsocalled West Wind Drift), SEC, NEC, and ECC are well captured by the model.

2. The long-term mean ACC is well simulated. The mean surface current patterns suchas SEC and the Agulhas current are in agreement with observations but weaker thanobserved one. The major ACC current velocity is found between 30 cm/s and 40cm/s, which is somewhat consistent with ship drift observed data and evidenced byother observational study (Klinck and Nowlin 2001).

3. Problems include a weaker than observed surface current with too little agreementnear coastal boundaries and in equatorial region.

4. The disagreement in the strength of the currents in between simulation andobservation may be because of the deficiency in the forcing field and boundarycondition and poor quality of the observed data. Such problem may also be linkedwith relaxation to salinity climatology, as it is one of the basic problems in oceanmodel simulation because it forces the natural circulation pattern.

The spatial plot of annual mean wind stress curl (N m−3) over the oceanic domaincalculated using model data reveals that annual mean wind stress curl agrees reasonablywell with earlier calculations and ACC is seen in the banding shape along with magnitudeof wind stress curl and vertically integrated volume transport using model output data giveevidence of northward transport in mid-latitudes and southward transport in subtropics,which may corresponds to Ekman transport.

This study contribute that a general understanding of the improved circulation pattern,wind stress curl and vertically integrated transport in Southern Indian Ocean is achievedand further analysis is required to ascertain the role of model in simulating the velocityfield with other set of observed current data and also the impact of boundary condition andforcing fields.

Further, since existing OGCM still do not reproduce the observed features due toseveral flaws such as the insufficient parameterization of mixing processes (Mellor andEzer 1991), a detailed analysis of the ocean model simulation is required to verify theresults using observations and other earlier studies. This shall significantly contribute toimproving our understanding of the future numerical modeling.

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Ocean Model Simulation of Southern Indian Ocean Surface Currents 353

Acknowledgments

We gratefully acknowledge the help of the Center of Ocean Land Atmosphere Studies(COLA), Calverton, MD, USA, and Scientists Drs. Ben Kirtman and Bohua Huang inrunning the numerical model experiment and with whom we had many useful discussions.We thank Dr. P.C. Pandey, Ex-Director, NCAOR (the then D.O.D., G. O. I.), Goa, India, andDr. Renguang Wu of COLA, USA, for their valuable suggestions, and thank to NCAOR,Goa, for financial assistance. The authors would like to thank the anonymous reviewer forfruitful comments in modifying the manuscript. We would like to thank Dr. A. J. Marianoof University of Miami for providing the observed current data for the region 30◦E–120◦E,60◦S–10◦N.

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