Behavior of the Wyrtki Jet observed with surface drifting buoys and satellite altimeter

Qiu, Yun; Li, Li; Yu, Weidong

doi:10.1029/2009gl039120

Cited by 48 publications

(56 citation statements)

References 35 publications

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“…In the Indian Ocean, the optimal correlation location is along the equatorial region where the Wyrki Jet is generated [i.e., Clark and Liu , 1994; Iskandar et al ., ; Qiu et al ., ; Schiller et al ., ; Wijffels and Meyers , ; Wyrtki , ]. Such a coincident is consistent with the field measurements that show that the ITF in the Makassar Strait is strongly influenced by intrusions of semiannual Kelvin waves from the Indian Ocean [ Sprintall et al ., ].…”

Section: Optimal Correlationsmentioning

confidence: 71%

Indonesian throughflow proxy from satellite altimeters and gravimeters

Susanto

Song

2015

JGR Oceans

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The Indonesian throughflow (ITF) from the Pacific to the Indian Ocean plays an important role in global ocean circulation and climate. Yet, continuous ITF measurement is difficult and expensive. The longest time series of in situ measurements of the ITF to date were taken in the Makassar Strait, the main pathway of the ITF. Here we have demonstrated a plausible approach to derive the ITF transport proxy using satellite altimetry sea surface height (SSH), gravimetry ocean bottom pressure (OBP) data, in situ measurements from the Makassar Strait from 1996 to 1998 and 2004 to 2011, and a theoretical formulation. We first identified the optimal locations of the correlation between the observed ITF transport through the Makassar Strait and the pressure gradients, represented by the SSH and OBP differences between the Pacific and Indian Oceans at a 1° × 1° horizontal resolution. The optimal locations were found centered at 162°E and 11°N in the Pacific Ocean and 80°E and 0° in the Indian Ocean, then were used in the theoretical formulation to estimate the throughflow. The proxy time series follow the observation time series quite well, with the 1993–2011 mean proxy transport of 11.6 ± 3.2 Sv southward, varying from 5.6 Sv during the strong 1997 El Niño to 16.9 Sv during the 2007 La Nina period, which are consistent with previous estimates. The observed Makassar mean transport is 13.0 ± 3.8 Sv southward over 2004–2011, while the SSH proxy (for the same period) gives an ITF mean transport of 13.9 ± 4.1 Sv and the SSH + OBP proxy (for 2004–2010) is 15.8 ± 3.2 Sv.

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Section: Optimal Correlationsmentioning

confidence: 71%

Indonesian throughflow proxy from satellite altimeters and gravimeters

Susanto

Song

2015

JGR Oceans

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“…In addition to semiannual, the IL also exhibits well-defined annual variability, deepening during austral winter (June-September) and shoaling in summer (January-April) months. The equatorial convergence of water in response to annual component of zonal westerlies in winter months (June-September), and vice-versa in summer is primarily responsible for this annual variation [Qu and Meyers, 2005;Qiu et al, 2009]. [11] In contrast to the western Indian Ocean, where the IL and ML seasonal variations are almost identical (Figures 1b and 1c), the ML depth is significantly shallower than the IL all year round in the east, because of local rainfall and a freshwater input from the Bay of Bengal and the Indonesian Throughflow [Sengupta et al, 2006].…”

Section: Seasonal Cyclementioning

confidence: 99%

Argo profiles variability of barrier layer in the tropical Indian Ocean and its relationship with the Indian Ocean Dipole

Qiu¹,

Cai²,

Li³

et al. 2012

Geophysical Research Letters

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[1] Interannual variability of the barrier layer (BL) in the southeastern tropical Indian Ocean (SETIO) is examined using temperature and salinity profiles derived from Argo floats since 2004. We show that a quasi-permanent BL exists off Sumatra with a semi-annual cycle and a maximum in November. Further, interannual variability of the BL is closely related to the Indian Ocean Dipole (IOD) with the IOD leading the BL by one month. During the 2006 positive IOD (pIOD) season, equatorial easterly-induced upwelling Kelvin waves raise the isothermal layer (IL) off Sumatra; a salinity-stratified mixed layer (ML) shoals due to a reduced eastward salty water transport by a weaker Wyrtki Jet, despite an offset by a reduced freshwater flux. Consequently, thinning of the BL is dominated by thinning of the IL. During the 2010 negative IOD (nIOD), similar processes operate but in an opposite direction. As thinning of the BL during a pIOD enhances the thermocline-ML coupling, our results reveal that an IOD-induced co-varying BL in turn enhances the IOD positive feedbacks. Citation: Qiu, Y., W. Cai, L. Li, and X. Guo (2012), Argo profiles variability of barrier layer in the tropical Indian Ocean and its relationship with the Indian Ocean Dipole, Geophys. Res. Lett., 39, L08605,

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“…Nagura and McPhaden [2008] found from four yearlong observational record that interannual variability in zonal momentum balance in the central equatorial Indian Ocean can largely be interpreted in terms of linear dynamics. Qiu et al [2009] reported the westward phase propagation in the equatorial currents, which they attributed to the westward phase propagation of zonal winds in the western equatorial Indian Ocean. Nagura and McPhaden [2010a] studied this westward propagation in detail using a linear continuous stratified model, and interpreted the westward propagation as a result of a superposition of Rossby waves on a wind forced jet.…”

Section: Introductionmentioning

confidence: 99%

Impact of Indian Ocean Dipole and El Niño/Southern Oscillation wind‐forcing on the Wyrtki jets

2012

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[1] Interannual variability of the Wyrtki jets is studied in the context of Indian Ocean Dipole (IOD) and El Niño and Southern Oscillation (ENSO) wind-forcing using a three dimensional numerical ocean model and observations. The boreal fall (October-November) Wyrtki jet is more significantly affected than the boreal spring (April-May) Wyrtki jet since both the IOD and ENSO tend to peak toward the end of the calendar year. Various statistical methods are used in an attempt to separate the impacts of the IOD and ENSO on these jets, with emphasis on the fall jet. The first two modes of an Empirical Orthogonal Function (EOF) decomposition account for about 90% and 85% of variability in zonal currents and wind stress respectively along the equator in the Indian Ocean, but EOF analysis does not cleanly separate out IOD and ENSO forcing and response. Partial correlation analysis reveals that IOD wind-forcing and zonal equatorial current response are stronger on average than for ENSO and extend further west across the basin. Composite analysis of IOD only, ENSO only, and combined IOD and ENSO years provides a complementary definition of the relative contributions of these two phenomena on Wyrtki jet variability and in general is consistent with the results of the partial correlation analysis.

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Behavior of the Wyrtki Jet observed with surface drifting buoys and satellite altimeter

Cited by 48 publications

References 35 publications

Indonesian throughflow proxy from satellite altimeters and gravimeters

Indonesian throughflow proxy from satellite altimeters and gravimeters

Argo profiles variability of barrier layer in the tropical Indian Ocean and its relationship with the Indian Ocean Dipole

Impact of Indian Ocean Dipole and El Niño/Southern Oscillation wind‐forcing on the Wyrtki jets

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