The North Indian Ocean circulation and its variability as seen in a numerical hindcast of the years 1993–2004

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Progress in Oceanography Progress in Oceanography 76 (2008) 111–147 www.elsevier.com/locate/pocean

The North Indian Ocean circulation and its variability as seen in a numerical hindcast of the years 1993–2004 Lakshmi Kantha a

a,*

, Thaned Rojsiraphisal b, Joseph Lopez

c

Department of Aerospace Engineering Sciences, University of Colorado, UCB 431, Boulder, CO 80309-0431, United States b Department of Applied Mathematics, University of Colorado, United States c Ball Aerospace Corporation, Boulder, CO 80301, United States Received 1 October 2005; received in revised form 20 December 2006; accepted 23 May 2007

Abstract A 12-year hindcast of the physical state of the North Indian Ocean has been carried out for the period 1993–2004, using a data-assimilative, primitive equation, multi-level circulation model that assimilated altimetric sea surface height anomalies and weekly MCSST, and was driven by 6-h ECMWF winds. This period encompasses the anomalous wind events in 1994 and 1997–1998 that led to anomalous oceanic state including anomalous sea surface heights and sea surface temperatures, especially in the equatorial regions. Since the in situ database in the Indian Ocean is rather sparse, the hindcast provides an alternative means of examining the state of the ocean, including its interior, during these anomalous years, as well as normal years during this period. By comparison with observations available during this period, it is shown that the model possesses reasonable skill to be useful in the description of various events in the North Indian Ocean. In this paper, we examine the circulation and its variability over the 12 years of the hindcast. We discuss equatorial events, as well as events in the Bay of Bengal and the Arabian Sea, including the Somali Current system. The heat and mass fluxes are examined. Finally, the hindcast is repeated with QuikSCAT wind stress fields available from July 1999 onwards. Comparison of the 2000–2004 hindcasts forced by ECMWF winds and QS wind stresses shows that in the former, the currents and fluxes are underestimated by 20–30%, but the circulation patterns are roughly similar.  2007 Elsevier Ltd. All rights reserved. Keywords: North Indian Ocean; Arabian Sea; Bay of Bengal; Equatorial Indian Ocean; Ocean circulation; Numerical ocean model; Hindcast; Altimetric data assimilation; Circulation variability; QuikSCAT wind stress

1. Introduction Of all the primary ocean basins, the Indian Ocean is the least explored, despite its fascinating monsoonal circulation and its obvious importance to the welfare of the teeming billions on the Asian continent, summer monsoonal rainfall being the lifeblood of the predominantly agrarian societies in South Asia and elsewhere on

*

Corresponding author. Tel.: +1 303 492 3014; fax: +1 303 492 2825. E-mail address: [email protected] (L. Kantha).

0079-6611/$ - see front matter  2007 Elsevier Ltd. All rights reserved. doi:10.1016/j.pocean.2007.05.006

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the continent. The very first basin-wide survey took place nearly four decades ago during the 1964–1966 International Indian Ocean Expedition (IIOE), (Wyrtki, 1971) and was followed up by the Indian Ocean Experiment (INDEX) during the first GARP Global Experiment in the late 1970s. These studies were instrumental in understanding the response of the Somali Current system to monsoonal forcing (Swallow and Bruce, 1966; Swallow et al., 1983). However, while an observational program was undertaken during 1994–1996 under the Joint Global Flux Study (JGOFS) to study the response of the Arabian Sea mixed layer to monsoonal forcing (Weller et al., 1998; Lee et al., 2000), it was not until 1995–1996 that a comprehensive survey of the Indian Ocean (Ffield, 1997; Hacker et al., 1998) was undertaken under the World Ocean Circulation Experiment (WOCE). It was not until 1999 that the Indian Ocean began to capture more of the attention of oceanographers, when observational campaigns such as the Bay of Bengal Monsoon Experiment (BOBMEX), (Bhat et al., 2001) and the Joint Air-Sea Monsoon Interaction Experiment (JASMINE), (Webster et al., 2002) were undertaken to study processes in the eastern Indian Ocean. Consequently, during the anomalous year of 1994 and especially, during the extraordinarily anomalous 1997–1998 years, the Indian Ocean went mostly unobserved by in-situ sensors. Since then, the interest in the Indian Ocean has increased manyfold with plans to instrument the equatorial Indian Ocean with mooring arrays patterned after the equatorial Pacific TOGATAO arrays and designed to monitor its physical state. The catastrophic tsunami of December 26, 2004 has also spurred interest in instrumenting the basin with bottom pressure and tide gages for purposes of providing timely tsunami warning to the population around the basin. Progress in understanding the fundamental physical processes underlying the variability of the monsoonal circulation of the Indian Ocean has been hamstrung by the sparse in situ observations. Fortunately, the global ocean has been routinely monitored in recent decades by satellite-borne sensors such as AVHRR. More importantly, the NASA-CNES TOPEX/Poseidon precision altimeter and its follow-on Jason 1 have monitored sea surface height changes since late 1992. These instruments do provide some measure of the extraordinary happenings during 1994 and 1997–1998. Satellite data has also helped identify important mechanisms of variability, such as the Indian Ocean Dipole (IOD, also called Indian Ocean Oscillation, whose proper characterization should be Indian Ocean Bipole) (Saji et al., 1999; Webster et al., 1999). Meanwhile, ocean circulation models have also reached a level of maturity that makes it possible to use model simulations to comfortably fill in observational gaps (e.g. Kantha, 1999; Kantha et al., 1999; and Kantha et al., 2005) and explore the physics behind various processes (e.g. McCreary et al., 1993). The combined use of satellite data and skillful ocean circulation models in a data-assimilative mode can help in estimating the physical state of the ocean and augment sparse in situ observational database. This is precisely what we have done here by hindcasting the state of the North Indian Ocean with a data-assimilative circulation model assimilating SST and altimetric sea surface height anomaly (SSHA) data. It is our intention in this paper to describe the circulation and its variability during the 12-year hindcast covering the 1993–2004 period, which encompasses the two anomalous periods, namely the 1994 and 1997–1998 years. While no one can dare claim that a numerical model can reproduce precisely every feature of the circulation and the physical processes underlying it, it is clear that even a reasonably accurate estimate of the physical state helps immensely in obtaining a better understanding of the events and the variability in the North Indian Ocean. By comparing the model output with available in situ observations, we will show that the model in question has acceptable skill for this purpose. We will then describe the events in the North Indian Ocean as seen in the hindcast, with particular emphasis on the anomalous years, as well as regional processes, such as the Somali Current system and the equatorial currents. The July 1999–December 2004 hindcast driven by the QuikSCAT wind stresses will be compared with the hindcast driven by ECMWF winds to ascertain the degree of underestimation of currents in the latter. Finally, the meridional heat fluxes across various transects will be examined. 2. Overview of the circulation in the North Indian Ocean Before presenting the circulation and its variability in the North Indian Ocean as seen in the 12-year hindcast, it is helpful to summarize briefly our current state of knowledge resulting mainly from rather sparse observations. For greater details, the reader is referred to an excellent review by Schott and McCreary (2001). We will restrict ourselves to the region north of 10S, for two reasons: 1. Most of the interesting variability is in this region. The region south of 10S is dominated by Southeast Trade Winds present year-round,

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albeit with considerable annual variations. It harbors the westward South Equatorial Current (SEC) centered at a latitude of about 15S (see Fig. 1 reproduced from Schott and McCreary, 2001). Around the island of Madagascar, the SEC branches into the Northeast and Southeast Madagascar Currents (NEMC and SEMC). The NEMC feeds the East Africa Coastal Current (EACC), which in turn feeds the Somali Current (SC) during the summer monsoon. 2. The model extends only to 20S and because of the possible influence of the open boundary at this location, the regions immediately adjacent to the southern boundary of the model are best excluded. The North Indian Ocean is naturally divisible into three interacting regions: 1. The Equatorial Region, extending to about 5–8 on either side of the equator and dominated by wind forcing. Here equatorial processes such as the Wyrtki-Yoshida Jets (WyJ), and Kelvin and Rossby wave propagations in the waveguide prevail. 2. The Arabian Sea. Here the seasonally reversing monsoonal winds and the associated forcing dominate the physical processes. The exceptionally strong southwesterly winds blowing along the Somali and Oman coasts during the summer monsoon give rise to strong upwelling off these coasts. Due to excess of evaporation over precipitation, the Arabian Sea is comparatively saline. 3. The Bay of Bengal. The dominant aspect of this marginal sea is the large runoff from rivers draining the Indian subcontinent and the excess of precipitation over evaporation leading to comparatively fresh surface layers. The Arabian Sea and the Bay of Bengal communicate with each other through a current system that flows around the southern tip of Sri Lanka. The overwhelming determinant of the circulation in the North Indian Ocean is the seasonally reversing monsoon winds. During boreal summer, the winds are from the southwest. The Southeast Trade Winds south of the equator cross the equator and continue into the Arabian Sea in the form of a strong, southwesterly low-level jet along the Somali and Oman coasts, known as the Findlater Jet (Findlater, 1971). Strong upwelling occurs along these coasts and the SST is depressed by a few degrees. On the eastern side of the jet, wind stress curl-induced downwelling gives rise to a deep, bowl-like mixed layer in the center of the Arabian Sea. The northward flowing Somali Current exists along the Somali coast (see Fig. 1, top panel). The EACC south of the equator retroflects near the equator, giving rise to the Southern Gyre (SG) that straddles the equator. Near the tip of Somalia, an anticyclonic feature known as the Great Whirl (GW) is seen, with a smaller anticyclonic eddy, the Socotra Eddy (SE), to its north (Fischer et al., 1996). Further north, a strong jet known as the Ras al Hadd Jet forms off the northeastern tip of Arabia. Off the west coast of India, a southward coastal current, the West Indian Coastal Current (WICC), develops that feeds into the eastward Summer Monsoon Current (SMC, also known as Southwest Monsoon Current) flowing around the tip of Sri Lanka, part of which continues into the Bay of Bengal, the rest continuing to flow eastward. The winds are also southwesterly in the Bay of Bengal and the prominent feature of the circulation here is the north–northeast flowing East Indian Coastal Current (EICC). While a cyclonic feature known as the Laccadive (Lakshadweep) Low (LL) is often seen in the Arabian Sea off the southwestern tip of India, eddy features in the Bay of Bengal are mostly unknown. At the eastern end of the equatorial waveguide, the southeastward Java Current (JC) flows along the Sumatran coast as an extension of the North Equatorial Counter Current (NECC). During boreal winter, the winds are exactly in the opposite direction to summer monsoon winds, northeasterly. Both WICC and EICC reverse direction and so does the Somali Current (see Fig. 1, bottom panel). The Arabian Sea and the Bay of Bengal interact through the westward flowing Northeast Monsoon Current (NMC, also known as the Winter Monsoon Current, WMC). A cyclonic feature off the southwestern tip of India known as the Laccadive High (Bruce et al., 1998) now exists in the eastern Arabian Sea. Both the southwestward flowing Somali Current north of the equator and the northward flowing EACC south of the equator turn eastward and feed the SECC located just south of the equator. Because the winds are mostly westerlies, the sea surface height is higher at the eastern side of the equatorial waveguide in the Indian Ocean. Only when the winds are anomalous and easterly, does the equatorial Indian Ocean resemble the equatorial Pacific, where the prevailing winds are easterlies. Then the sea level is lowered at the eastern end, upwelling takes place along the equator and an eastward flowing Equatorial Undercurrent (EUC) develops at the top of the thermocline, at a depth of 100–150 m. In between the two monsoons, winds are westerlies along the equator and these drive strong eastward-flowing surface jets along the equator, known as the Wyrtki-Yoshida Jets (Wyrtki, 1973; Yoshida, 1959).

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Fig. 1. Schematic (from Schott and McCreary, 2001) of the North Indian Ocean circulation during summer (top panel) and winter (bottom panel), reproduced from ship drift data. Note that many of the features shown are transient but recurring. SEC – South Equatorial Current, SEMC (NEMC) – Southeast (Northeast) Madagascar Current, LC– Leeuwin Current, EACC – East African Coastal Current, SC – Somali Current, SG – Southern Gyre, GW – Great Whirl, SE – Socotra Eddy, RHJ – Ras al Hadd Jet, WICC (EICC) – West (East) India Coastal Current, NMC (SMC) – Northeast (Southwest) Monsoon Current, LH (LL) – Laccadive High (Low), SD – Sri Lanka Dome, JC – South Java Current. Numbers denote volume transport in Sverdrups (1 Sv = 106 m3 s1) across the transects.

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Superimposed on this ‘‘mean’’ circulation exists, strong variability at various time scales, ranging from synoptic to seasonal to interannual. The variability is moderate, generally speaking, but can, on occasion, be quite large, such as during the 1994 and 1997–1998 years, when anomalous winds in the equatorial belt gave rise to large deviations from this mean picture. So far, little is known of the variability in the circulation of the Indian Ocean, since observations have been rather sparse and sporadic. No systematic monitoring system such as the TOGA-TAO array in the Pacific exists here and appeal must often be made to satellite data, which monitor only the conditions near the sea surface. Very little can be gleamed of the variability in the interior. We hope here to remedy this situation using the 12-year hindcast from 1993 to 2004. Because of the seasonally reversing wind forcing, most of the mesoscale features in the North Indian Ocean are transient, but recurring. The year-to-year variability in their strength and location is largely unknown, since many of these features have never been sampled more than a few times at most. The 12-year hindcast has the potential for delineating their interannual variability and we will address this question later in this paper. It is worth pointing out that the 12-year hindcast has been driven by 6-hourly ECMWF winds, since satellite-measured, i.e. QuikSCAT (QS) wind stresses were not available before July 1999. This means of course that the anomalous 1994 and 1997–1998 periods cannot be hindcast when only satellite-measured winds are used. We suspect that the rather coarse resolution (about 1.1) of the ECMWF winds might lead to underestimation of the wind stresses. We can also expect QS winds to be richer in spatial structure. Consequently, we can expect currents to be underestimated by the hindcast driven by ECMWF winds with standard CD relations such as Large and Pond (1981) and Hellerman and Rosenstein (1983). This is confirmed by comparison with the July 1999–December 2004 hindcast driven by QS wind stresses. Since the region is strongly wind-driven, the results are only as accurate as the winds driving the model. Nevertheless, we believe that ECMWF winds contain prominent features of the monsoon system and compare reasonably well with other wind products such as from the NCEP reanalysis (Kalnay et al., 1996) (and QS wind stresses), and therefore, the resulting hindcast is reasonably skillful, although the currents and fluxes are underestimated by 20–30%. At the very least, we expect ECMWF winds to reproduce qualitatively, aspects of the circulation variability. While it is hard to fully assess the quantitative skill because of the inadequacy of in situ data, especially currents, comparisons with available data do suggest significant model skill and hence instill confidence in what we are setting out to do, as long as we remember the degree of underestimation of currents. 3. The hindcast The numerical model used for the hindcast is the University of Colorado version of the Princeton Ocean Model (CUPOM). It is a primitive equation model using topographically conformal coordinate in the vertical and orthogonal curvilinear coordinates in the horizontal. The sea surface height is calculated explicitly using the split-mode technique. CUPOM includes a second moment closure-based model (Kantha and Clayson, 1994) of turbulent mixing in the upper and bottom layers. More details about the basic features of CUPOM can be found in Kantha and Clayson (2000b) and Mellor (1996). The North Indian Ocean hindcast model has 1/2 resolution in the horizontal and 38 sigma levels in the vertical, with the levels closely spaced in the upper 300 m. The sigma levels are 0, 1, 2, 5, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110, 120, 130, 140, 150, 160, 170, 180, 190, 200, 210, 220, 230, 240, 250, 270, 300, 400, 700, 1000, 2000, 3000, 4000, 5000 m in a water column of 5000 m depth. The high vertical resolution in the upper 300 m is deliberately chosen to better simulate the near-surface circulation. The somewhat coarse horizontal resolution was chosen principally to render the 12-year run feasible on modern workstations, and make it possible to carry out nowcast/forecasts locally on a workstation without having to appeal to a supercomputing facility. The deliberate use of 1/2 resolution means that while the model can resolve features such as the SG and GW, smaller features such as the SE are marginally resolved. Also there is a tendency to underestimate the intensity of currents such as the EUC. The model is forced by 6-h ECMWF winds. It assimilates altimetric sea surface height anomalies and weekly composite multi-channel sea surface temperature (MCSST) using a simple optimal interpolation-based assimilation technique. The model, and the assimilation methodology based on conversion of SSH anomalies into pseudo-BT anomalies for adjusting the model temperature field via optimal interpolation, have been described by Lopez (1998) and Lopez and Kantha (2000a) and

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Lopez and Kantha (2000b), which will not be repeated here. The reader is instead referred to these references for more details. We just point out, for reasons that will be clear later, that we use Smith (1980) formulation for the drag coefficient CD to convert the ECMWF 10 m wind speed to wind stress at the surface:  0:0011; U10 < 6 m s1 CD ¼ 0:00061 þ 0:000063U10 ; U10 > 6m s1 Note that the Smith formulation is in substantial agreement with other traditionally used CD formulations (see Kantha and Clayson, 2000a) such as Large and Pond (1981). Since altimetric data is indispensable to accurate hindcasts, the hindcast could only be performed for the years when uninterrupted altimetric observations are available. Fortunately, the NASA/CNES TOPEX/Poseidon precision altimeter has been in operation since the fall of 1992. The model was therefore spun-up for a few years using climatological forcing and was then run in a data-assimilative mode starting in September 1992. Since it takes a few months for the model to ‘‘equilibrate’’ to altimetric assimilation, only the results from the beginning of the year 1993 to the end of the year 2004 will be presented, discussed and analyzed here. To better estimate the thermodynamic state of the upper layers, weekly-composite MCSST was also assimilated into the model. Since no similar salinity data are available and NASA TRMM (Tropical Rainfall Measurement Mission) to measure the tropical precipitation accurately did not take place until 1996, and since NWP (Numerical Weather Prediction) estimates of precipitation are for the most part still rather inaccurate, a decision was made to simply damp the sea surface salinity to climatological monthly mean values, instead of computing it based on the NWP estimates. Consequently, the hindcast is weakest with regard to salinity in the upper layers, as will be shown below, and we cannot address important aspects of the circulation in the Bay of Bengal such as barrier layers. We intend to remedy this deficiency in a follow-on study that will drive the hindcast model with TRMM-measured precipitation, and when it becomes available, satellite-measured sea surface salinity. We will then be able to quantify the inaccuracies resulting from the use of climatological salinity. A mean Indonesian throughflow (Godfrey, 1996) is prescribed at the eastern boundary (Lopez and Kantha, 2000a and Lopez and Kantha, 2000b), simply because of the lack of information on its interannual variability, especially during the anomalous 1994 and 1997–1998 years. We do not expect this to degrade the results north of 10S, which is the focus of this study. In the west, the model does not take into account the inflows and outflows from the Red Sea and the Persian Gulf. The same holds for the Luzon Strait on the eastern boundary; the South China Sea is not the focus of this study. It is worth pointing out that the model and the methodology used here have been proven to yield skillful results when applied to the Gulf of Mexico. The Gulf of Mexico hindcast/nowcast/forecast model has been demonstrated to reproduce the circulation and its variability rather well (Kantha et al., 1999; Schaudt et al., 2001; Kantha, 2005; Kantha et al., 2005) and the 9-year hindcast (years 1993–2001) has been analyzed extensively (Toner et al., 2001; Kuznetsov et al., 2002; Chu et al., 2002; Chu et al., 2003) and its skill quantified by comparison with observational data including drifters (Kirwan et al., 2003; Toner et al., 2003; Kantha, 2005). The real-time nowcast/forecast version of the model is now being run in the civilian sector in a routine operational mode for use by the offshore industry in petroleum exploration and production activities in the Gulf. The data-assimilative CUPOM has also been used elsewhere in regions such as the Ligurian Sea (Kantha et al., 2002; Carniel et al., 2002; Onken et al., 2005) and the Japan Sea (Bang et al., 1996). It has been run operationally at the US Naval Oceanographic Office for use by the US Navy in many regions around the world including the Mediterranean Sea (Horton et al., 1997), the Red Sea (Clifford et al., 1997), the Persian Gulf and the marginal seas of the Western Pacific for nearly a decade. The reader is referred to the above-mentioned references for a better understanding of the model skill under a variety of situations. 4. Comparison with observations and assessment of hindcast skill The hindcast 3D fields were saved daily. In addition, 3-h time series of water column properties were saved at 60 pre-selected points for detailed analysis, most of these locations coinciding with locations of earlier, existing or planned moorings. Obviously, no comparable observational database exists to assess the hindcast skill

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in its entirety. Apart from a few observational campaigns mentioned in Section 2, information about water column properties and especially the circulation is rather sparse. Nevertheless, some comparisons are feasible and we present them in this section. There exist excellent descriptions of the annual cycle of wind forcing in the Indian Ocean (e.g. Schott and McCreary, 2001). We will therefore not repeat it here. However, it is worth noting that while different wind products such as the NCEP analyses, Hellerman and Rosenstein (1983) monthly means and ECMWF products are in broad agreement as far as the annual cycle is concerned, there can be significant differences in evolutionary detail vis-a`-vis observed winds. These differences can be especially influential in the equatorial region. This should be kept in mind when comparing the equatorial circulation in the 12-year hindcast with the observed one. The best wind stress to use in a model simulation would be that measured by a satelliteborne scatterometer, but unfortunately QuikSCAT data are not available before July 1999. However, a broad idea of the deficiencies in the use of ECMWF winds can be obtained by comparison of the two roughly 5 year hindcasts (years 2000–2004) driven by ECMWF winds and QS wind stresses. This will be done in Section 8. There were no in-situ instruments during the highly anomalous period of 1997–1998; however, an array was in place along 80.5E between 045 0 S and 5N in order to study transport between the Arabian Sea and the Bay of Bengal (Reppin et al., 1999) during the 1994 anomalous period. Fig. 2 compares the zonal currents observed (taken from Schott and McCreary, 2001 – top panel) at the equator at this longitude with the currents from the hindcast (bottom panel). Zonal currents from hindcast are shown with a contour interval of 0.1 m s1; dashes indicate westward currents. The model reproduces the strong WyJ (as strong as 0.6 m s1) from October to December 1993, the weaker WyJ that occurred in April–May 1994 and again in June 1994, and the EUC that occurred from February to May 1994 and again late summer of 1994. Both the modeled WyJ and EUC occur at about the same time as observations. The WyJ in the model is deeper. The current magnitudes are somewhat underestimated, weaker than the observed model winds being the reason. Next consider the observed temperature and salinity in the Bay of Bengal at two stations TS1 and TS2 during the July–August 1999 BOBMEX campaign (Bhat et al., 2001). Station TS2 (89E, 17.5N) is in the northern Bay of Bengal and can be expected to be more influenced by the fresh water runoff from rivers draining the Indian subcontinent than Station TS1 (87E, 13N), which is in the southern part. The temperature compares fairly well at TS2 (not shown), although the hindcast lacks isotherm displacements resulting from internal wave activity, most likely due to internal tides; the model does not include tides. On the other hand, the hindcast salinity (not shown) is consistently lower by about 1 psu. The reason is that the hydrographic data for model initialization are comparatively sparse in the Bay. since most of the observations in the Indian Ocean over the past few decades have been in the Arabian Sea. The occasional depression of salinity in the mixed layer to 29 psu, presumably due to precipitation events is not obviously reproducible and hence not reproduced by the model. TRMM data could help improve the model skill in this regard. Similar conclusions hold for comparisons at the southern station TS1; the broad pattern in the water column is reproduced by the model. The thermocline is deeper at TS1 than at TS2, and this aspect is reproduced in the hindcast. Next we compare the temperature and salinity observed at a mooring deployed in the central Arabian Sea (61.5E, 15.5N) during the 1994–1995 campaign (Weller et al., 1998). Fig. 3 shows the time series of observed and hindcast temperatures in the upper 200 m of the water column (contour interval is 1 C). The temperature profiles show warm events near the surface during November–December 1994 and during March–June 1995. The model reproduces the temperature structure throughout these depths well, and not just at the surface (recall that the model assimilates weekly MCSST), even though the high frequency fluctuations (presumably tidal) are not reproduced. The observed and hindcast salinity at this location are shown in Fig. 4 (contour interval is 0.1 psu). High salinity found near surface is due to the strong evaporation within the Arabian Sea. High salinity events are found during April–June 1995 in both the observations and the hindcast, but they are shallower in the hindcast. The model does not reproduce the salinity structure in the upper water column as accurately as the temperature structure, simply because the model sea surface salinity (SSS) is damped to the climatological monthly value. The pressing need for satellite-measured SSS data to assimilate into numerical models is well known and confirmed here. Fig. 5 compares the near-surface currents from ship-borne ADCP (right panel) along the cruise tracks during the February–March 1995 WOCE campaign (Hacker et al., 1998). The hindcast (left panel), while underestimating the current magnitudes, reproduces various features of the equatorial circulation rather well.

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Fig. 2. The zonal currents (top panel) observed at 80.5E on the equator during 1993–1994 (from Fig. 25 Schott and McCreary, 2001). The strong eastward Wyrtki-Yoshida Jets (WyJ) can be seen in the fall of 1993 and weaker bursts during 1994. The EUC is strong during late summer of 1994 and early spring of 1993. The hindcast currents (bottom panel, contour interval 0.1 m s1) are in good agreement with the observed currents. The solid (dashed) contours denote eastward (westward) currents.

During this period, the westward flowing SEC is found south of about 7.5S, while the SECC flows eastward in a band between 7.5S and 2.5S. North of the SECC, the Equatorial Current (EC) and the North Equatorial Current (NEC) flow eastward. These currents are well reproduced in the hindcast; however, the modeled currents in the central Bay of Bengal are weaker.

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Fig. 3. Comparison of the observed temperature (top panel) at a mooring deployed in the Arabian Sea at 61.5E, 15.5N during 1994– 1995 with hindcast temperature (bottom panel). The agreement is excellent considering the fact that only SST is assimilated into the model and the winds are from a NWP model.

Fig. 6 compares the observed zonal and meridional currents in the upper 400 m (top two panels – adapted from Masumoto et al., 2005) at 90E on the equator with the hindcast values (bottom two panels) during 2000–2001. While there is a broad agreement in the general patterns, the currents are underestimated (note the different scales), simply because of the use of the ECMWF winds. As will be shown in Section 8, use of

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Fig. 4. Comparison of observed salinity (top panel) at a mooring deployed in the Arabian Sea at 61.5E, 15.5N during 1994–1995 with hindcast salinity (bottom panel). The agreement is not as good as that for the temperature because of the non-availability of sea surface salinity for assimilation into the model. Still, the broad pattern is reproduced by the model. Contour interval is 0.1 psu in both panels.

the observed QS wind stresses enables these currents to be more accurately reproduced. In the upper layers, at 50–100 m depth, eastward flows are present throughout the year except from January to March, and during July and August of 2001, when the EC reverses its direction. Strong WyJ occurred in November 2000, and May and October 2001. In the deeper layers, at 100–150 m depth, a band of westward jets are present most of the time except in late April until May 2001. This may be due to the abrupt change in the wind direction. Below 150 m, the eastward flows are present with a strong EUC between 150 and 250 m; the EUC is deeper in

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Fig. 5. Currents at 30 m depth from the hindcast (left panel) compared with observed ADCP velocity vectors (from Fig. 1a of Hacker et al., 1998) averaged between 25 and 75 m along the February–March 1995 WOCE Indian Ocean cruise tracks I9N (roughly along 95E) and I8N (80E). The equatorial features such as SEC, SECC, EC, NECC and NEC are clearly reproduced by the model.

the hindcast. The meridional currents show a more complex pattern with mostly southward flows resulting in a net southward transport (see Section 9). The only in situ moorings during part of the anomalous 1994 period were those deployed during WOCE along 80.5E (Reppin et al., 1999). In the comparison of the observed current time series at various depths with the hindcast currents (not shown), two aspects are noticeable. Firstly, the hindcast reproduces features except for the eastward flow at 75 m during May–June 1994. This is most likely due to the undercurrents in the hindcast being deeper, 100–150 m depths compared to 75–125 m depths in the observations (see Fig. 2). Secondly, the use of ECMWF winds causes underestimation of the current magnitudes. To our knowledge, this is the first study that makes an extensive comparison of model events with observed data. While the hindcast is by no means perfect and can certainly be improved by the use of a higher model resolution and better input data and wind forcing, it is clear that it does possess considerable skill and hence is useful for a better understanding of the evolution of the circulation in the North Indian Ocean during the 1993–2004 time period. We will describe this next. 5. Description of some notable features The hindcast 3D fields were saved daily and the resulting database is too voluminous to be presented in its entirety. Animations of the daily surface currents, SSH, SST and wind stress can be seen on http://ocean. colorado.edu/nio/index.htm. Also available are animations of 30 m currents, which tend to show the various mesoscale features with more clarity (compared to surface currents), plotted on top of SSH. Here we provide some snippets of the physical state seen in the hindcast.

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Fig. 6. Comparison of the hindcast zonal and meridional currents at 90E along the equator (bottom two panels) with the values observed by an upward-looking ADCP (top two panels adapted from Masumoto et al.).

We start with the conditions on the equator. The SSH, SST and zonal currents along the equator from 1993 to 2004 are shown in panels (a), (b), and (c) of Fig. 7, respectively. The SSH and SST are higher at the eastern end of the waveguide during normal years as seen during the rest of the hindcast. Strong WyJs are mostly found in the middle of the waveguide. The anomalous 1994 and even more anomalous 1997–1998 years can be clearly seen, with SSH and SST anomalously depressed at the eastern end during the fall. The WyJ normally seen during the transition seasons disappeared in 1997 and the equatorial Indian Ocean behaved more like the equatorial Pacific with strong westward zonal currents in the waveguide (panel c). Compara-

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Fig. 7. Longitude–time plots of SSH (panel a), SST (panel b) and zonal currents (panel c) along the equator over the 12 years of the hindcast run. Note the signature of the highly anomalous 1997–1998 years, when SSH and SST were anomalously low at the eastern end of the waveguide and the zonal current westward. Relatively weaker 1994 anomaly is also evident.

tively speaking, overall, the years 1995, 1996 and 1999–2004 were near normal, albeit with some year-to-year variability in the waveguide. Fig. 8 shows the 12-year SSH along zonal sections at 10N, 5N and 5S. Westward propagation of Rossby waves is evident along these transects. The estimated propagation speed is about 0.6 m s1, slightly less than

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Fig. 8. Longitude-time plots of SSH along zonal transects at 10N (left panel), 5N (middle panel) and 5S (right panel) showing westward propagation of Rossby waves in the equatorial waveguide.

the 0.7–0.9 m s1 value for the first baroclinic mode Rossby wave. The Kelvin wave speed (Fig. 7) is about 2.5 m s1 compared to a quoted value of 2–2.76 m s1 for the first baroclinic mode Kelvin wave (Yang et al., 1998; Le Blanc and Boulanger, 2001). Fig. 9 shows the salinity at three stations along the equator: 65E, 80.5E and 90E. A strong semiannual variability can be seen at both 65E and 90E, whereas the variability at 80.5E is predominantly annual. The

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Fig. 9. Salinity profiles in the upper 250 m at 90E (top panel), 80.5E (middle panel) and 65E (bottom panel) along the equator (contour interval is 0.3 psu). Relatively fresher waters overlie saline waters in the eastern equatorial region, with saline and less saline waters alternating in the near-surface layers in the western portion. The variability is principally semiannual in both the eastern and western parts, whereas it is predominantly annual in the central portion. The anomalous 1997–1998 period is clearly seen at both 80.5E and 90E, but not as clearly at 65E.

low near-surface salinities at 90E due to the large fresh water input into the eastern part of the North Indian Ocean are a strong contrast to the high values at 65E, the difference between the two exceeding 1.5 psu at times. The high salinities seen at 80.5E towards the end of each year are noteworthy. The anomalous 1997–1998 years can be clearly seen as a strong increase in salinity in the near surface layers at both 80.5E and 90E, but not as clearly at 65E. The zonal currents at 65E, 80.5E and 90E along the equator are shown in Fig. 10. As expected, during normal years, strong eastward flowing WyJ can be seen during the transition periods between the two monsoons. The EUC is weak and flows westward at a depth of 100–150 m during most of the years. However, during the anomalous 1997–1998 period a strong eastward flowing EUC can be seen during this anomalous period at all three stations at a depth of 100–150 m at 90E, and 100–200 m at 80.5E and 65E. Fig. 11 shows salinities at three stations north of the equator: the Bay of Bengal (88E, 18N), the southern tip of Sri Lanka (80.5E, 5N), and the Arabian Sea (61.5E, 15.5N) (panels (a), (b), and (c), respectively). Semiannual variability due to alternating forcing by summer and winter monsoons is clearly evident in both the Arabian Sea and the Bay of Bengal. Saltier waters overlie less saline waters in the Arabian Sea; whereas the opposite occurs in the Bay of Bengal. These patterns are due to high evaporation in the Arabian Sea and high river runoff in the Bay of Bengal. Surface signatures of salinity extend to a depth of roughly 50–100 m in the Bay of Bengal during the summer monsoon, and somewhat less during the winter monsoon. In contrast, the surface signatures of high salinity extend to 70–120 m depths in the Arabian Sea. At 80.5E, 5N station, more saline water is present during the summer monsoon, with fresher water the rest of the year, due to seasonally

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Fig. 10. Same as in Fig. 9 but for zonal currents. Strong eastward WyJ during the transitions between the two monsoons can be seen in most years throughout the equatorial waveguide. The EUC is weak and westward during most years. The anomalous 1997–1998 period with an eastward-flowing EUC at 100–150 m depth can be seen clearly at all three longitudes.

reversing monsoon currents, the westward NMC transporting relatively fresh waters from the Bay of Bengal during the northeast monsoon and the SMC transporting more saline Arabian Sea waters during the southwest monsoon. 5.1. The southern gyre and the great whirl These are of course the most noticed and noteworthy features of the summer monsoon circulation in the North Indian Ocean. The hindcast indicates that prior to the formation of the SG, the EACC flows northeastward along the East African coast, merging with the southwestward SC and then turning eastward near the equator to become part of the equatorial current. The SG spins up once the eastward flow in the SC recirculates southward and forms a gyre, usually north of the equator and just prior to the summer monsoon season, typically during the May–June time period. During the summer monsoon, the SG often shifts northeastward along with the SC, while the SC extends northward to about 10N before recirculating southward to form another eddy, the GW, north of the SG. The onset, evolution and decay of both the SG and GW show significant year-to-year variability. The core of the GW is found between 5N and 7N, and 52E and has a radius of about 2, while the SG is usually found fully developed between 0N and 3N, 2–3 off the coast during the study period. During the fall transition period, the NMC flows westward across the Arabian Sea, and the GW dissipates. Examples of the SG and GW are shown in Fig. 12, panels (a), (b), (c) and (d), which show snapshots of these mesoscale features at their peaks during the summers of 1996, 1998, 2000, and 2004. The SG and GW were particularly strong and well developed during the summers of 1996, 1998,

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Fig. 11. Salinities at three salient stations: in the interior of the Bay of Bengal (top panel), near the southern tip of Sri Lanka (middle panel) and the middle of the Arabian Sea (bottom panel). Note the change in scale. The contour interval is 1.5 psu. The relatively fresh waters in the Bay of Bengal and the salty ones in the Arabian Sea are evident. The semiannual variability is pronounced at both stations. Alternating fresher and saltier waters near the southern tip of Sri Lanka are due to seasonally reversing monsoon currents that transport saltier Arabian Sea waters eastward during the summer and fresher Bay of Bengal waters westward during winter.

and 2004, while they were quite weak in 2000. The dynamical reason is not clear, although we suspect the underlying cause is the interannual variability in monsoonal winds. A mesoscale feature similar to the SG but opposite in its direction of rotation develops during the winter monsoon just south of the equator. This counter-clockwise eddy is formed at the southern end of the southwestward flowing SC, which meets the northward flowing EACC before turning eastward. The eddy is fully developed south of the equator between 1S and 3S just a few degrees east of the African coast around December-January every year and dissipates quickly when the southwestward flowing SC weakens. This is evident in panels (e) and (f) of Fig. 12. 5.2. AP anticyclone (APA) Unlike the transient but recurrent mesoscale features in western Indian Ocean such as the SG and GW, eddies occurring in the Bay of Bengal do not show a seasonal cycle (Schott and McCreary, 2001). Eigenheer and Quadfasel (2000) used ship drift data and T/P SSHA, and noticed that the EICC reversals lead the local reversal of winds by several months. Both CTD and ADCP data have been used to study warm/cold eddies in

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Fig. 12. The SSH and 30 m currents at various times in the western Arabian Sea (white area indicates positive SSH). The Southern GyreGreat Whirl system can be seen during the summer monsoons of 1996, 1998, 2000 and 2004, in panels (a) (b), (c), and (d), respectively. The system was particularly well developed during the summer monsoons of years 1996, 1998 and 2004, but was quite weak during that of the year 2000. Panels (e) and (f) show the gyre that develops south of the equator during the winter monsoons, but with rotation opposite to that of the SG that develops during the summer monsoon.

the Bay (Babu et al., 1991; Prasanna Kumar et al., 1992; Babu et al., 2003). T/P also has provided data to detect eddies in the Bay of Bengal (Gopalan et al., 2000; Madhusoodanan and James, 2003). In the hindcast, we find that a sea surface high invariably develops off the eastern part of the basin, propagates westward to the

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coast of India and then extends southward covering 15–20N in November–January of every year (see Fig. 13a). The high eventually splits into two anticyclonic eddies; one centered at 15N off the coast of Andhra Pradesh, a somewhat weaker one off the coast of Orissa around 18N. During this time, a low SSH develops at the eastern boundary and extends to the middle of the basin, which may be the cause of this split (see Fig. 13b– d). The APA is well developed by March–April, but dissipates rather quickly and disappears by around July. It was particularly well formed during the years 1993, 1996, 1998, 2000, 2001 and 2002 of the hindcast. 5.3. Eastern Indian Ocean The Bay of Bengal is also forced remotely by waves emanating from the equatorial region (Clarke and Liu, 1993). One such example is shown in Fig. 14, which shows the SSH and 30 m currents on May 19, 1997 (panel a). Starting around mid-May, a SSH high associated with strong eastward-flowing WyJ impinges on the eastern boundary of the waveguide resulting in elevated SSH all along the eastern boundary from the southern tip of Java to Bangladesh that persists until the end of June, with strong resulting currents along the eastern boundary of the Bay. Another such event occurred during November 29, 2001 (panel b). Similar events occur every year during the transition periods, but were particularly strong during May 1996 and May 2004. 5.4. Monsoon current south of Sri Lanka The seasonally reversing monsoon currents around the southern tip of Sri Lanka are important to the exchange between the Bay of Bengal and the Arabian Sea. Based on data from three moorings deployed from

Fig. 13. SSH and currents at 30 m depth in the Bay of Bengal showing the development of eddy features in the Bay. White areas indicate negative SSH.

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Fig. 14. SSH and currents at 30 m depth showing examples of the elevated SSH along the eastern boundary. On May 19, 1997 and November 29, 2001, the WyJs were particularly strong and piled up the water against the Sumatran coast raising the sea level 15–20 cm all along the eastern boundary of the Bay of Bengal.

January 1991 to February 1992 along 80.5E between 411 0 N and 539 0 N, Schott et al. (1994) report that during the winter monsoon, the NMC transported a mean of 10–12 Sv westward, while during the summer monsoon, the SMC transported a mean of 8 Sv eastward, with an annual-mean westward transport past the tip of Sri Lanka of about 2–3 Sv. The mass transport past the tip of Sri Lanka derived from integrating the hindcast currents to the north of 3.5N in the upper 300 m (to conform to the transport calculations reported by Schott et al., 1994) is shown in Fig. 15. Significant seasonal, intra-seasonal and inter-annual variability can be seen. While the model simulations do not include the time of the deployment of the above-mentioned moorings, the transport plot shows remarkable resemblance to Schott et al. (1994) plot (their Fig. 7). The seasonal and intraseasonal fluctuations are similar in nature. The transport averaged over the 12 years of the hindcast is 12 Sv westward during the winter monsoons (defined only here as the months DJF), 2.9 Sv westward during the transition from winter to summer monsoons (MAM), 8.3 Sv eastward during the summer monsoons (JJA) and 2.2 Sv eastward during the summer to winter transition (SON), with an overall mean transport of 0.8 Sv westward.

Fig. 15. Zonal mass transport across a meridional transect at the tip of Sri Lanka (80.5E) in the upper 300 m north of 3.5N from 7-day running mean of the daily currents from the 12-year hindcast.

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6. The ‘‘average’’ circulation Before discussing the variability, the ‘‘norm’’ needs to be defined. To accomplish this, we derived monthly averages of quantities such as currents, SSH and SST during each year of the hindcast. These describe the evolution of the circulation from the beginning of 1993 to the end of 2004. We then averaged these monthly values in the hindcast to define monthly, seasonal and annual means over the entire 12 years. We did not exclude the anomalous 1994 and 1997–1998 years, at the risk of a slight bias in the mean toward these years to avoid defining the norm apriori. The summer monsoon period is defined here as July–August–September (JAS), and the winter monsoon defined as January–February–March (JFM), and the rest being the transition periods between the two monsoons (months AMJ and OND). Because of the seasonally reversing currents, as expected, the annual mean currents (not shown) are weak. However, because of the persistent appearance of the SG and GW during the May–July timeframe, their signature can be seen in the annual mean. The mean SSH has prominent lows off the Arabian and Pakistani coasts, as well as in the western part just south of the equator. The SSH highs in the eastern part of the Indian Ocean, especially along the Sumatran coast are evident in the mean. Consequently, the SSH is typically high in the eastern equatorial Indian Ocean and low in the west, so that the SSH gradient is opposite of the gradient that prevails in the equatorial Pacific. Note that this mean SSH field should be added to the SSH anomaly fields derived from altimetry (e.g. Fig. 71 of Schott and McCreary, 2001) to obtain the absolute SSH needed often to infer the circulation. At 30 m depth, the strong northward flowing EACC and SC, the SG and the GW as well as the SMC flowing around Sri Lanka (not shown) are prominent features of the summer monsoon circulation. Southward flowing SC, and EACC, as well as the counter-clockwise SG, and the NMC flowing around Sri Lanka are notable features of the winter monsoon circulation. The anticyclonic gyre off the east coast of India in the Bay of Bengal is prominent during the winter monsoon. The LH can be seen off the southwestern tip of India during the winter. The circulation features seen in the hindcast are consistent with those depicted by the schematics of Fig. 1 as well as ship drift-derived currents (Figs. 31 and 44 of Schott and McCreary, 2001). However, because of the strong variability of the circulation in this part of the global ocean, these features are somewhat smeared and hence weaker when compared to those in the individual months of any given year.

Fig. 16. Monthly average mixed layer depth during the winter monsoon (February), the transition from winter to summer monsoon (May), the summer monsoon (August) and the transition from summer to winter monsoon (November) periods. The mixed layer is particularly deep in the Arabian Sea during the summer monsoon.

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Fig. 16 shows the average thermocline (mixed layer) depths for the months of February, May, August and November. The mixed layer depth is defined here as the depth at which the temperature falls below SST by 0.5 C. The deep mixed layer characteristic of the Arabian Sea during the summer monsoon, with values higher than 100 m off Somalia, can be seen. The mixed layer deepens in the northern sector of the Arabian Sea during the winter monsoon, but not as much as during summer. The transition seasons are typically low wind, high insolation days, leading to generally shallow mixed layers. These results are consistent with the seasonal evolution of the mixed layer presented by Rao et al. (1989). 7. The anomalous years The longitude-time and time series plots presented in Sections 4 and 5 clearly display anomalous events during the 12-year hindcast. We will now look at these anomalous periods in greater detail. Note that the anomalies are computed by removing the 12-year mean. It is the anomalies in the winds in the equatorial band that appear to have a predominant influence in creating anomalous conditions in the North Indian Ocean (Chambers et al., 1999; Ueda and Matsumoto, 2000; Ohba and Ueda, 2005). Strong anomalous easterly wind bursts occurred in the Indian Ocean in April, 1994 (Behera et al., 1999; Chambers et al., 1999; Vinayachandran et al., 1999a) and again in early 1997 (Chambers et al., 1999; Murthugudde et al., 2000; Yu and Rienecker, 2000; Rao and Yamagata, 2004). Both of these events have been documented in many publications (see Chambers et al., 1999; Vinayachandran et al., 1999a; Saji et al., 1999; Murthugudde et al., 2000; Yu and Rienecker, 2000; Rao and Yamagata, 2004). In the hindcast, the months of October–November 1997 were highly anomalous and stronger than the month of September 1994, the peak of the anomaly in 1994. The current anomalies during these periods were westward along the equator and were particularly strong. This was also accompanied by a lowering of SST along the coast of Sumatra by more than 2 C and of SSH by more than 15 cm! The SG was also anomalously strong in 1997. Fig. 17 shows the anomalies in sea surface currents and SST (panels a and b), the SSH and wind stress

Fig. 17. SST and SSC anomalies (panels a and b), and SSH and wind stress anomalies (panels c and d) during the months of September 1994 and November 1997. While the SST and SSH anomalies are evident in both cases, the stronger nature of the 1997 anomaly is clear.

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(panels c and d) during September 1994 and November 1997, corresponding to the peaks of the two anomalous periods. While it is obvious that the 1997–1998 anomalies were stronger than the 1994 ones, the patterns are somewhat similar. A few differences that can be seen are: the event in 1994 shows a pattern of anomalies

Fig. 18. Comparison of physical properties at 90E along the equator during the anomalous 1997–1998 years and the near-normal 2003– 2004 years: zonal velocity (top two panels), salinity (middle two panels) and temperature (bottom two panels). Eastward flowing EUC can be seen at a depth of 100–150 m from October 1997 to January 1998. The normally eastward WyJ also reversed during this period. High salinities at depths of 50–250 m from October 1997 to June 1998, and the near-surface temperature drop from October to December 1997 can be seen in the middle and bottom panels.

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south of the equator; while that in 1997 shows a SSH anomaly pattern roughly symmetric about the equator. Both events were essentially confined to the eastern part of the equatorial waveguide. Fig. 18 contrasts the zonal current, temperature and salinity in the upper 250 m of the water column at 90E, 0N during the anomalous 1997–1998 years with those during the near-normal 2003–2004 years. Most noticeable are the disappearance of WyJ and the appearance of strong eastward-flowing EUC during the latter part of 1997 (top two panels), elevated subsurface salinities toward the earlier part of 1998 (middle two panels) due to the eastward flowing EUC transporting saltier water masses from the western end of the waveguide to the eastern end, as well as the lowered near-surface temperatures (bottom two panels) during October– November 1997. These features are noticeably absent during the near-normal 2003–2004 years. 8. 2000–2004 Hindcast with QuikSCAT wind stress Out of necessity, we used the ECMWF winds for the 12-year hindcast of the years 1993–2004, since we wanted to hindcast the anomalous 1994 and 1997–1998 years during which satellite-observed (QS) wind stresses were not available. Observed wind stresses are available from the QS mission since July 1999. Since a priori we can expect ECMWF winds to be weaker than the actual winds, it is of interest to determine the degree of underestimate of the currents and fluxes resulting from their use. In order to do this, we ran the model from July 1999 to the end of 2004, with QS wind stresses, all else being kept the same. Fig. 19 compares the currents on the equator at 90E for the run with ECMWF winds (top two panels) and QS wind stresses (bottom two panels). While the patterns are roughly similar, the currents are underestimated in the former relative to the latter by about 20–30%. Note the stronger circulation features such as the WyJ

Fig. 19. Comparison of currents from the hindcast with ECMWF winds (top two panels) and that driven by QS wind stresses (bottom two panels) at 90E along the equator during 2000–2001. Note the change in scale between the zonal and meridional current plots. The current patterns are roughly similar, but the current magnitudes are often 30% higher in the hindcast with QS wind stress.

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Fig. 20. Surface currents and SST (left panels), and wind stress and SSH (right panels) on November 22, 2002 of the hindcast with ECMWF winds and QuikSCAT wind stress. The currents are stronger (by 20–30%) in the latter relative to the former, but the current patterns are roughly similar. Note the richer structure of QS stresses (including convergence regions) which is reflected in the currents.

during November 2000 and April–May 2001 and EUC during May 2001 in the latter. Westward subsurface zonal (panels a and c) as well as meridional (panels b and d) velocities are stronger in magnitude for the QS forcing than ECMWF forcing. Fig. 20 reinforces this. It shows the surface velocity for the two hindcasts on November 22, 2002. The patterns are roughly similar but the magnitudes of the surface currents are larger when the hindcast is driven by QS wind stress by a few tens of percent. Note also the rich structure in the QS wind stress fields (panels b and d), including surface convergence zones in the Bay of Bengal and Arabian Sea, which are reflected in the hindcast currents and SSH. The same is true in Fig. 21, which shows currents at 30 m depth plotted over SSH at various times (ECMWF in the left hand panels and QS in the right hand ones). The SG and GW on June 21, 2001 are better defined in the hindcast driven by QS (panel b) compared to that driven by ECMWF (panel a). The SSH in panel (d) is much higher than that in panel (c), and the eddy features in the Bay of Bengal are more noticeable; the Laccadive High which is hardly visible in panel (e) is very clear in panel (f). 9. Meridional heat fluxes The heat budget of the North Indian Ocean is of particular interest to the Asian monsoons. The surface transport is generally southward on both sides of the equator during summer, but northward in winter. It is believed that the net annual heat flux across the equator is southward and occurs predominantly via the cross-equatorial cell (Duing and Leetma, 1980; Schott and McCreary, 2001). While the annual signal is dominant, considerable intra-seasonal and interannual variability is present. Fig. 22 shows the weekly running means of daily meridional heat fluxes (in PW, 1 PW = 1015 W) across various zonal transects. As can be seen from Fig. 22, the heat flux at 20N transect is northward most of the year except during June–September with

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Fig. 21. Comparison of currents at 30 m depth and the SSH from the hindcast driven by ECMWF winds (left panels) and that by QuikSCAT wind stresses (right panels) in three different regions. The currents are stronger (by 20–30%) in the latter relative to the former, but the current patterns are roughly similar. However, features such as the SG and GW (top panels), AP (middle panels) and LH (bottom panels) are much stronger in the hindcast driven by QuikSCAT.

the highest heat flux during January–March. At 5N, 10N, and 15N, a southward heat flux occurs across these transects during April–September, with the highest northward (southward) heat fluxes during May–June (November–December). South of the equator, southward heat flux persists most of the year except during the winter period with the highest value during June–August. Table 1 shows the 12-year mean meridional heat flux across the various latitudes ranging from 1.11 to 0.10 PW (negative value indicates southward transport). The southward meridional heat flux across the equator has a minimum value of 0.22 PW in 1993 and a maximum of 0.57 PW in 1994. The seasonal means are +0.77 PW during the winter monsoon (months JFM), 0.82 PW during the spring transition (AMJ), 1.54 PW during the summer monsoon (JAS) and 0.06 PW during the fall transition (OND). Table 1 gives

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Fig. 22. Meridional heat fluxes across various zonal transects during the 12-year hindcast. The values shown are weekly running means of the daily values computed from the model fields (the red curves are from the hindcast with QuikSCAT wind stresses – see Section 8).

a detailed breakdown by seasons and years. Fig. 23 shows the meridional heat fluxes across various zonal transects. The heat flux values of Hastenrath and Greischar (1993) derived from air-sea flux calculations, and Lee and Marotzke (1998) derived from a numerical model agree reasonably well with our estimates, especially south of 10N, although the zero heat flux occurs at about 13N instead of 18N. The Hsiung (1985) fluxes are significantly lower, while the Garternicht and Schott (1997) and Wacongne and Pacanowski (1996) meridional fluxes are higher. Fig. 24 shows the mean monthly meridional heat flux values (averaged over the 12 years) from 5S to 20N compared with those from Hsiung et al. (1989), Hastenrath and Greischar (1993), and Garternicht and Schott

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Table 1 Seasonal (and annual) average meridional heat fluxes (in PW) across various zonal transects Years

1994

1995

1996

1997

1998

1999

Transect 20N Season 1 0.289 Season 2 0.164 Season 3 0.099 Season 4 0.028 Annual 0.094

1993

0.231 0.016 0.151 0.08 0.043

0.268 0.074 0.06 0.117 0.099

0.289 0.047 0.1 0.111 0.086

0.264 0.136 0.052 0.096 0.11

0.28 0.109 0.01 0.119 0.124

0.238 0.062 0.016 0.08 0.09

Transect 15N Season 1 1.076 Season 2 0.152 Season 3 0.442 Season 4 0.358 Annual 0.282

0.266 0.278 0.527 0.403 0.035

0.32 0.163 0.371 0.414 0.049

0.319 0.136 0.393 0.521 0.077

0.387 0.102 0.469 0.342 0.038

0.334 0.025 0.053 0.301 0.138

Transect 10N Season 1 1.178 Season 2 0.381 Season 3 0.942 Season 4 0.586 Annual 0.106

0.444 0.711 1.141 0.51 0.227

0.395 0.475 0.896 0.576 0.102

0.389 0.439 1.009 0.692 0.093

0.525 0.323 1.21 0.159 0.216

Transect 5N Season 1 1.511 Season 2 0.502 Season 3 1.135 Season 4 0.143 Annual 0.003

0.426 1.09 1.372 0.531 0.379

0.641 0.847 1.52 0.605 0.284

0.396 0.566 1.546 0.308 0.355

Transect 0N Season 1 1.681 Season 2 0.775 Season 3 1.473 Season 4 0.278 Annual 0.22

0.583 1.29 1.774 0.222 0.569

0.84 0.995 1.835 0.16 0.463

Transect 5S Season 1 0.052 Season 2 0.878 Season 3 1.539 Season 4 0.697 Annual 0.77

0.74 1.476 1.791 0.016 0.641

Transect 10S Season 1 1.277 Season 2 2.388 Season 3 2.726 Season 4 1.609 Annual 2.003

0.238 2.193 2.316 1.085 1.463

2000

2001

2002

2003

2004

All

0.265 0.158 0.009 0.083 0.128

0.292 0.088 0.019 0.058 0.104

0.266 0.071 0.004 0.061 0.097

0.229 0.114 0.008 0.109 0.11

0.246 0.093 0.041 0.119 0.103

0.263 0.094 0.046 0.088 0.099

0.255 0.237 0.17 0.463 0.077

0.421 0.078 0.191 0.363 0.128

0.372 0.239 0.258 0.467 0.085

0.31 0.091 0.3 0.347 0.065

0.436 0.128 0.25 0.469 0.131

0.385 0.116 0.301 0.458 0.105

0.407 0.12 0.311 0.409 0.095

0.364 0.32 0.463 0.436 0.003

0.384 0.762 0.764 0.54 0.152

0.534 0.425 0.703 0.434 0.042

0.396 0.689 0.761 0.699 0.09

0.262 0.5 0.704 0.293 0.163

0.438 0.363 0.821 0.666 0.021

0.292 0.381 0.733 0.557 0.067

0.467 0.481 0.846 0.512 0.089

0.709 0.448 1.313 0.065 0.252

0.764 0.403 0.917 0.287 0.071

0.311 1.026 1.032 0.528 0.306

0.54 0.772 0.968 0.29 0.23

0.373 0.891 1.097 0.45 0.293

0.265 0.597 1.11 0.255 0.299

0.68 0.507 1.244 0.713 0.093

0.314 0.612 1.309 0.614 0.251

0.577 0.688 1.214 0.399 0.235

0.584 0.862 1.606 0.253 0.54

0.904 0.628 1.7 0.279 0.432

0.527 0.444 1.293 0.001 0.307

0.608 1.159 1.52 0.007 0.524

0.896 0.813 1.244 0.137 0.33

0.568 0.823 1.497 0.019 0.448

0.673 0.759 1.507 0.246 0.465

0.758 0.573 1.534 0.149 0.305

0.656 0.724 1.531 0.024 0.411

0.773 0.82 1.543 0.059 0.418

1.192 1.202 1.947 0.025 0.503

1.007 0.927 1.831 0.12 0.475

0.984 0.967 1.709 0.506 0.557

0.599 0.296 1.297 0.18 0.298

0.93 1.112 1.503 0.092 0.404

1.348 0.786 1.299 0.168 0.233

0.924 0.879 1.543 0.045 0.392

1.026 0.826 1.541 0.052 0.354

1.119 0.662 1.738 0.189 0.279

1.105 0.874 1.545 0.041 0.324

0.919 0.907 1.607 0.124 0.436

0.344 1.527 2.357 0.947 1.129

0.222 1.242 2.152 0.968 1.041

0.308 1.451 2.021 1.017 1.051

0.012 1.022 1.849 0.847 0.937

0.223 1.337 2.285 0.949 1.094

0.681 1.15 1.701 0.943 0.785

0.16 1.123 1.921 0.708 0.903

0.358 1.254 1.928 0.859 0.927

0.399 1.219 2.102 0.797 0.936

0.439 1.354 2.261 0.896 1.025

0.134 1.438 2.135 0.969 1.108

Season 1: January–March, Season 2: April–June; Season 3: July–September; Season 4: October–December.

(1997). The heat flux is southward from April to October, with the highest values of 1.75 PW (ECMWF) and 2.25 PW (QS) south of the equator during July. The heat fluxes are positive during the rest of the year. These patterns of variability are in good agreement with other studies as shown in Fig. 24, but the fluxes are higher in magnitude, during both summer and winter monsoons. Fig. 25 shows latitude–time plots of the meridional heat and mass fluxes across various zonal transects over the 12 years. Note the poleward (positive values) heat flux during the winter and the equatorward ones (negative values) during the summer. Decrease in the northward heat flux south of the equator can be seen toward the end of years 1997 and 1998. The mass flux is northward between 8S and 2S, and north of 15N most of

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Fig. 23. Meridional heat fluxes across zonal transects from various studies redrawn from Schott and McCreary, 2001 (H – Hsiung, 1985; HG – Hastenrath and Greischar, 1993; LM – Lee and Marotzke, 1998; GS – Garternicht and Schott, 1997; WP – Wacongne and Pacanowski, 1996; E – Present study with ECMWF winds; QS – present study with QuikSCAT wind stresses).

Fig. 24. Monthly heat flux values in PW from various sources (right panels, adapted from Schott and McCreary, 2001 – Hsiung et al., 1989; Hastenrath and Greischar, 1993; Garternicht and Schott, 1997) compared to those from the hindcast (left panels: top – hindcast using ECMWF winds; bottom– QS wind stresses).

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Fig. 25. Latitude-time plots of meridional heat fluxes (left panel) and mass fluxes (right panel) over the 12 years of the hindcast. Note the weaker northward heat transport south of the equator during winter 1998 and increasing northward mass transport at 5N during fall 1997.

the year, with southward transport between roughly 2S and 12N during normal years. However, during both 1994 and 1997–1998, strong northward mass flux occurs in a band around 5N. Even more prominent is the

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southward mass flux between the equator and 8S during 1997–1998, when the mass flux is northward during normal years. Table 2 shows the seasonal and annual heat fluxes across various zonal transects with forcing by QS wind stress compared to those forced with ECMWF winds. The heat fluxes resulting from the latter forcing are generally about 20–30% (on the average) larger than those with the former forcing (see also Figs. 22 and 24). Note the overall average heat fluxes during season 4 (months OND) at 0N and 5S transects are northward with

Table 2 Comparison of meridional heat fluxes (in PW) across various zonal transects from the hindcast using ECMWF winds and QS wind stress Years

ECMWF 2000

QuikSCAT 2001

2002

2003

2004

All

2000

2001

2002

2003

2004

All

0.265 0.158 0.009 0.083 0.128

0.292 0.088 0.019 0.058 0.104

0.266 0.071 0.004 0.061 0.097

0.229 0.114 0.008 0.109 0.11

0.246 0.093 0.041 0.119 0.103

0.260 0.105 0.013 0.086 0.108

0.29 0.098 0.104 0.135 0.104

0.298 0.049 0.079 0.131 0.099

0.324 0.029 0.131 0.192 0.102

0.329 0.108 0.088 0.148 0.123

0.309 0.107 0.116 0.156 0.113

0.31 0.078 0.104 0.152 0.108

Transect 15N Season 1 0.421 Season 2 0.078 Season 3 0.191 Season 4 0.363 Annual 0.128

0.372 0.239 0.258 0.467 0.085

0.31 0.091 0.3 0.347 0.065

0.436 0.128 0.25 0.469 0.131

0.385 0.116 0.301 0.458 0.105

0.385 0.130 0.311 0.409 0.103

0.591 0.228 0.441 0.559 0.119

0.542 0.384 0.405 0.634 0.096

0.412 0.174 0.466 0.506 0.068

0.536 0.042 0.493 0.663 0.164

0.369 0.245 0.428 0.528 0.055

0.49 0.215 0.447 0.578 0.100

Transect 10N Season 1 0.534 Season 2 0.425 Season 3 0.703 Season 4 0.434 Annual 0.042

0.396 0.689 0.761 0.699 0.09

0.262 0.5 0.704 0.293 0.163

0.438 0.363 0.821 0.666 0.021

0.292 0.381 0.733 0.557 0.067

0.467 0.481 0.846 0.512 0.057

0.774 0.81 1.084 0.76 0.093

0.616 0.889 1.07 0.984 0.092

0.514 0.623 1.192 0.718 0.148

0.706 0.493 1.247 1.106 0.016

0.336 0.611 0.952 0.648 0.146

0.589 0.685 1.109 0.843 0.093

Transect 5N Season 1 0.54 Season 2 0.772 Season 3 0.968 Season 4 0.29 Annual 0.23

0.373 0.891 1.097 0.45 0.293

0.265 0.597 1.11 0.255 0.299

0.68 0.507 1.244 0.713 0.093

0.314 0.612 1.309 0.614 0.251

0.577 0.688 1.214 0.399 0.233

1.085 1.359 1.574 0.744 0.281

0.71 1.257 1.851 1.136 0.319

0.452 0.788 1.61 0.409 0.388

1 0.672 1.815 1.153 0.088

0.519 0.727 1.815 1.066 0.242

0.753 0.96 1.733 0.902 0.263

Transect Eq Season 1 Season 2 Season 3 Season 4 Annual

0.896 0.813 1.244 0.137 0.33

0.568 0.823 1.497 0.019 0.448

0.673 0.759 1.507 0.246 0.465

0.758 0.573 1.534 0.149 0.305

0.656 0.724 1.531 0.024 0.411

0.773 0.82 1.543 0.059 0.392

1.58 1.542 1.949 0.163 0.445

1.111 1.416 2.342 0.324 0.588

1.187 1.331 2.169 0.261 0.652

1.482 1.01 2.356 0.539 0.345

0.915 1.175 2.212 0.235 0.566

1.255 1.295 2.206 0.2 0.519

Transect 5S Season 1 Season 2 Season 3 Season 4 Annual

1.348 0.786 1.299 0.168 0.233

0.924 0.879 1.543 0.045 0.392

1.026 0.826 1.541 0.052 0.354

1.119 0.662 1.738 0.189 0.279

1.105 0.874 1.545 0.041 0.324

0.919 0.907 1.607 0.124 0.316

2.433 1.699 2.137 0.145 0.399

1.583 1.722 2.304 0.233 0.561

1.897 1.754 2.161 0.243 0.576

2.088 1.38 2.396 0.249 0.37

1.567 1.538 2.36 0.02 0.587

1.914 1.619 2.272 0.023 0.499

Transect 10S Season 1 0.681 Season 2 1.15 Season 3 1.701 Season 4 0.943 Annual 0.785

0.16 1.123 1.921 0.708 0.903

0.358 1.254 1.928 0.859 0.927

0.399 1.219 2.102 0.797 0.936

0.439 1.354 2.261 0.896 1.025

0.134 1.438 2.135 0.969 0.915

1.71 1.571 2.476 1.811 1.051

0.557 1.467 2.648 1.086 1.169

0.838 2.036 2.348 1.223 1.201

0.956 1.456 2.549 1.366 1.114

0.852 1.677 2.467 1.112 1.11

0.983 1.642 2.498 1.32 1.129

Transect 20N Season 1 Season 2 Season 3 Season 4 Annual

The heat fluxes are generally larger with the latter forcing.

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Fig. 26. Comparison of meridional heat flux (PW) across the equator from the hindcast (7-day running mean) with those from global models ECCO and SODA (monthly values). ECMWF, QuikSCAT, ECCO and SODA results are shown in black, red, blue and green, respectively.

QS forcing, while during other seasons, both forcings have the same overall average heat fluxes with a slightly higher value in the seasonal average with QS forcing. There are two studies, the results of which are publicly available and hence can be used for comparison with the current study. Both use relatively coarse-resolution data-assimilative global models. One is the University of Maryland SODA model, which uses the GFDL MOM2.b driven by monthly winds derived from COADS (1950–1991) and NCEP (1992–2001). To prevent anomalies due to change in the winds, a 2-year overlap period was used to correct the NCEP mean to make it consistent with the COADS mean. The model domain extends from 62S to 62N. The horizontal resolution is 1 · 1 in mid latitudes, increasing to 0.5 · 1 in the tropics. The model has 20 vertical levels on a stretched grid with 15 m resolution near the surface. It assimilates hydrographic data, SST and altimetric SSHA. For details, see Carton et al. (2000). The second study is the ECCO project that uses the MIT non-hydrostatic GCM driven by NCEP products, with adjustment of the surface fluxes to match ocean observations. The wind stress is twice daily and the heat and fresh water fluxes are daily. The domain is also global (80S to 80N) with 1 · 1 horizontal resolution. The model has 23 vertical levels with 10 m resolution near the surface. For details, see Koehl et al. (2002). The relatively coarse resolutions of the ECCO and SODA models do not permit accurate reproduction of mesoscale features such as the GW, SG, LH and LL. As such it is not possible to compare the variability of these features. However, gross features such as the meridional heat fluxes can be compared. Fig. 26 shows the monthly meridional heat flux across the equator in SODA and ECCO models compared with the 7-day running mean values of the daily heat fluxes from the current study. The variability is in substantial agreement. However, the overall mean value is different: 0.41 PW for SODA and 0.19 PW for ECCO models, compared to 0.42 PW for the present study with ECMWF winds and 0.52 PW with QS wind stresses. 10. Summary and conclusions The 12-year hindcast of the years 1993–2004, using a skillful, primitive equation, multi-level, data-assimilative model has enabled the North Indian Ocean circulation and its variability to be examined in detail. The study augments the sparse in situ observational database in the basin and supplements the satellite observations made over the last decade. Comparison of model fields with available in situ observations suggests that the hindcast skill is reasonable, although the currents are weaker than they should be. While the ECMWF wind patterns are reasonably accurate overall, the resulting wind stresses are underestimates, and since the region is strongly wind-driven, improvements are desirable. The use of measured wind stresses from QS SeaWinds scatterometer, available since mid-July 1999, in a hindcast from July 1999 to December 2004 showed that the QS wind stress-driven currents are 20–30% stronger than those driven by ECMWF winds. The meridional fluxes are also increased by similar percentage values. For example, the annual mean (over years 2000– 2004) meridional heat flux across the equator increases from 0.39 PW to 0.52 PW, a 33% increase. Also,

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small mesoscale features such as LL and LH, which were not clearly depicted in ECMWF hindcast were better depicted in the hindcast with QS forcing. These results suggest that an artificial increase in CD values when converting ECMWF winds to wind stress forcing might be one way to correct the underestimation problem in the 1993–2004 hindcast, although the resulting CD values will be at the very high end of the range of values in literature (see Kantha and Clayson, 2000a). For example, the CD value used here at 10 m s1 wind speed is 0.00124 and this will have to be increased to 0.0021! The hindcast has shed more light on the state of the water column during the anomalous 1994 and 1997– 1998 years, as well as the near-normal years such as 2001–2004. Overall, the 1997–1998 period stands out as the most anomalous over the past 12 years. The meridional heat fluxes from the hindcast are also in good agreement with those from two coarser resolution global models, suggesting that the open southern boundary has not corrupted the hindcast. The North Indian Ocean is rather unique in that the conditions in the Arabian Sea and the Bay of Bengal can also be influenced by remote processes in the equatorial waveguide (Clarke and Liu, 1993; Han et al., 2001) as well as the coastal waveguide (Clarke and Liu, 1993 and Clarke and Liu, 1994). As in other primary basins, local changes in conditions in the equatorial band (e.g. changes or anomalies in wind forcing) are communicated to the eastern boundary by equatorial Kelvin waves and to the western boundary by equatorial Rossby waves in the waveguide (Luyten et al., 1980; Luyten and Roemmich, 1982; Reverdin et al., 1983; Chambers et al., 1999; Han et al., 1999; Vinayachandran et al., 1999b; Han et al., 2001; Le Blanc and Boulanger, 2001). However, unlike the Pacific, the waveguide in the Indian Ocean is short and hence the changes are communicated from one end of the waveguide to the other in a very short time, less than 2–3 months. Also, in addition to being reflected at the eastern boundary, the disturbances in the waveguide can be transmitted to the adjoining coastal waveguide in the form of coastal Kelvin waves (Clarke and Liu, 1993; Yamagata et al., 1996; Iskander et al., 2005) that can travel around the Indian subcontinent affecting the Bay of Bengal. Furthermore, mid-latitude Rossby waves created locally, communicate changes from the eastern boundaries to the western in both the Bay of Bengal and the Arabian Sea. Superimposed on these are strong monsoon currents (NMC and SMC) that transport mass, heat and salt across the basin from the eastern part to the western part (and vice versa) in a narrow meridional ‘‘channel’’ between Sri Lanka and the equatorial waveguide. Consequently, the dynamics of the North Indian Ocean are quite complex, and the causes of variability in any given region are hard to discern with certainty, since they can be due to both local and remote forcing. A hindcast can only tell us the state of the ocean at any given point in time (and not the underlying dynamical causes) and hence is necessarily descriptive in nature. Dynamical explanations require further studies including process studies that can probe the dynamical causes through ‘‘What if’’ questions. The 1/2 resolution of the model is marginally eddy permitting for mesoscale features such as the SG, LH, LL and APA. A higher resolution should enable these features to be even more accurately reproduced. Nevertheless, the model produces a reasonable depiction of circulation in the North Indian Ocean. The meridional heat fluxes are in good agreement with previous estimates and this enhances the confidence in the hindcast. Another area of potential improvement is the depiction of salinity in the near-surface layers. TRMM observations available since 1997 could be used to improve the estimation of the salinity in the upper layers and this is one of the goals of a future follow-on study. Remotely sensed SSS from the NASA Aquarius mission to be launched in 2009 would help simulate near surface salinities more accurately. A nowcast/forecast capability using QS, MCSST and altimetric data is rather straightforward to set up. This would be of considerable help to the surrounding countries. Also, given the fact that a TAO-like array will be fully deployed in the Indian Ocean within the next 5 years, a model like this might be of some use in deciding the deployment strategy. Acknowledgements L.K. thanks Jeff Geehan for timely assistance with system and other problems, as well as with analysis of hindcast results. PODAAC is thanked for the data used in this study. Many thanks to Dr. Yukio Masumoto of the University of Tokyo for his generosity in letting us use his ADCP data from 90E mooring. ECMWF ERA-40 data used in this study have been kindly provided by ECMWF and have been obtained from the Data Support section of the Scientific Computing Division of the National Center for Atmospheric Research supported by

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Grants from the NSF. The AVHRR weekly 18 km gridded global MCSST data, TOPEX/Poseidon and Jason-1 SSHA data used in this study were kindly provided by Physical Oceanography DAAC of the NASA Jet Propulsion Laboratory, Pasadena, CA. We thank ECMWF, JPL and NCAR for making this study possible. Thanks to the US Office of Naval Research for partial support to LK under the grant N00014-06-10287. Appendix A. List of acronyms APA ADCP EACC ECMWF EICC ENSO EUC FGGE GW IIOE JC JGOFS LH LL NCEP NECC NEMC NMC NWP QS SC SE SEC SECC SEMC SG SMC SSC SSH SSS SST TAO T/P TRMM WICC WyJ WOCE

Andhra Pradesh anticyclone acoustic Doppler current profiler East African coastal current European Center for medium-range weather forecast East Indian coastal current El Nino southern oscillation equatorial undercurrent first GARP global experiment great whirl international Indian Ocean experiment south Java current joint global ocean flux study Laccadive (Lakshadweep) high Laccadive (Lakshadweep) low National Center for environmental prediction North Equatorial countercurrent Northeast Madagascar current Northeast monsoon current (also known as WMC, winter monsoon current) numerical weather prediction QuikSCAT Somali current Socotra Eddy south equatorial current south equatorial countercurrent southeast Madagascar current southern gyre southwest monsoon current (also known as Summer Monsoon Current) sea surface currents sea surface height sea surface salinity sea surface temperature tropical atmosphere–ocean TOPEX/Poseidon tropical rainfall measurement mission West India coastal current Wyrtki-Yoshida Jet world ocean circulation experiment

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