Makassar Strait throughflow, 2004 to 2006

Gordon, Arnold L.; Susanto, R. Dwi; Ffield, Amy; Huber, Bruce A.; Pranowo, Widodo Setiyo; Wirasantosa, Sugiarta

doi:10.1029/2008gl036372

Cited by 169 publications

(195 citation statements)

References 16 publications

(24 reference statements)

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“…1), which was slightly higher than that estimated from the sum of previous direct measurements at different times. During the INSTANT period, the total transport measured through the main entrance channel, the Makassar Strait, was 11.6Sv (Gordon et al 2008).…”

Section: The Itf Transport and Its Interannual And Decadal Variationsmentioning

confidence: 99%

The Indonesian throughflow, its variability and centennial change

et al. 2018

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The Indonesian Throughflow (ITF) is an important component of the upper cell of the global overturning circulation that provides a low-latitude pathway for warm, fresh waters from the Pacific to enter the Indian Ocean. Variability and changes of the ITF have significant impacts on Indo-Pacific oceanography and global climate. In this paper, the observed features of the ITF and its interannual to decadal variability are reviewed, and processes that influence the centennial change of the ITF under the influence of the global warming are discussed. The ITF flows across a region that comprises the intersection of two ocean waveguides-those of the equatorial Pacific and equatorial Indian Ocean. The ITF geostrophic transport is stronger during La Niñas and weaker during El Niños due to the influences through the Pacific waveguide. The Indian Ocean wind variability associated with the Indian Ocean Dipole (IOD) in many years offsets the Pacific ENSO influences on the ITF geostrophic transport during the developing and mature phases of El Niño and La Niña through the Indian Ocean waveguide, due to the co-varying IOD variability with ENSO. Decadal and multi-decadal changes of the geostrophic ITF transport have been revealed: there was a weakening change from the mid-1970s climate regime shift followed by a strengthening trend of about 1Sv every 10 year during 1984-2013. These decadal changes are mostly due to the ITF responses to decadal variations of the trade winds in the Pacific. Thus, Godfrey's Island Rule, as well as other ITF proxies, appears to be able to quantify decadal variations of the ITF. Climate models project a weakening trend of the ITF under the global warming. Both climate models and downscaled ocean model show that this ITF weakening is not directly associated with the changes of the trade winds in the Pacific into the future, and the reduction of deep upwelling in the Pacific basin is mainly responsible for the ITF weakening. There is a need to amend the Island Rule to take into account the contributions from the overturning circulation which the current ITF proxies fail to capture. The implication of a weakened ITF on the Indo-Pacific Ocean circulation still needs to be assessed.

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Section: The Itf Transport and Its Interannual And Decadal Variationsmentioning

confidence: 99%

The Indonesian throughflow, its variability and centennial change

et al. 2018

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“…Because 2004-2006 are considered normal years [38], there is no evident large interannual variability in the observed volume transports. However, Gordon et al [37] reported increasing transport during those three years in the Makassar Strait.…”

Section: Volume Transportmentioning

confidence: 99%

“…Observations of different passages or straits have been documented in separate papers, such as Gordon et al [38] for the Makassar Strait, Van Aken et al [39] for the Lifamatola Passage and Sprintall et al [4] for the three outflow passages. The INSTANT dataset provides an opportunity to resolve intraseasonal to interannual variability in the ITF, in the vertical structure of the transport and the volume budget of the Indonesian Seas.…”

Section: Instant Datasetmentioning

confidence: 99%

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Indonesian Throughflow in an eddy-resolving ocean model

et al. 2013

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The performance of the eddy-resolving LICOM2.0 in simulating the Indonesian Throughflow has been evaluated against the INSTANT data in the present study. The mean vertical structures of the along strait velocities are simulated well in LICOM2.0, but the large velocities at the bottom of the Lifamatola Passage and the Timor Passage cannot be reproduced by LICOM2.0. The causes are considered to be both the errors in the topography and the tidal mixing at the bottom. Despite several biases in the mean velocities, the mean inflow and outflow volume transports in LICOM2.0 are almost identical to the INSTANT data. Compared with the lower resolution LICOM, the most significant improvement is the better simulation of the partitions of the inflow and outflow transports in individual straits. The outflow for low-resolution LICOM is mainly through the Ombai and Lombok Strait, whereas that for LICOM2.0 is mainly through the Timor Passage. The variability of the vertical structure of velocities and the volume transport are also investigated. LICOM2.0 overestimates the magnitude of the upper-layer currents and the amplitude of the variation. We also found that the largest correlation coefficient occurs in the shallowest strait, the Lombok, whereas the lowest occurs in the Timor Passage, especially in the upper layer. The latter may be caused by the unrealistic transport through the Torres Strait in LICOM2.0.

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“…2d). This semiannual variability may also be enhanced by remote forcing of the pycnocline/ thermocline associated with the Wyrtki Jets in the equatorial Indian Ocean or with remotely generated signals from the Pacific Ocean (e.g., Wijffels and Meyers 2004;Qu et al 2008;Gordon et al 2008). Additional work is needed, e.g., model sensitivity experiments, to test/separate the role of remotely forced waves on MLT in this region.…”

Section: The Seasonal Mlt Budgetmentioning

confidence: 99%

Mechanisms controlling the seasonal mixed-layer temperature and salinity of the Indonesian seas

Halkides¹,

Lee

Kida

2011

Ocean Dynamics

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We examine the seasonal mixed-layer temperature (MLT) and salinity (MLS) budgets in the BandaArafura Seas region (120-138°E, 8-3°S) using an ECCO ocean-state estimation product. MLT in these seas is relatively high during November-May (austral spring through fall) and relatively low during June-September (austral winter and the period associated with the Asian summer monsoon). Surface heat flux makes the largest contribution to the seasonal MLT tendency, with significant reinforcement by subsurface processes, especially turbulent vertical mixing. Temperature declines (the MLT tendency is negative) in May-August when seasonal insolation is smallest and local winds are strong due to the southeast monsoon, which causes surface heat loss and cooling by vertical processes. In particular, Ekman suction induced by local wind stress curl raises the thermocline in the Arafura Sea, bringing cooler subsurface water closer to the base of the mixed layer where it is subsequently incorporated into the mixed layer through turbulent vertical mixing; this has a cooling effect. The MLT budget also has a small, but nonnegligible, semi-annual component since insolation increases and winds weaken during the spring and fall monsoon transitions near the equator. This causes warming via solar heating, reduced surface heat loss, and weakened turbulent mixing compared to austral winter and, to a lesser extent, compared to austral summer. Seasonal MLS is dominated by ocean processes rather than by local freshwater flux. The contributions by horizontal advection and subsurface processes have comparable magnitudes. The results suggest that ocean dynamics play a significant part in determining both seasonal MLT and MLS in the region, such that coupled model studies of the region should use a full ocean model rather than a slab ocean mixed-layer model.

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Makassar Strait throughflow, 2004 to 2006

Cited by 169 publications

References 16 publications

The Indonesian throughflow, its variability and centennial change

The Indonesian throughflow, its variability and centennial change

Indonesian Throughflow in an eddy-resolving ocean model

Mechanisms controlling the seasonal mixed-layer temperature and salinity of the Indonesian seas

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