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Abstract: The Indonesian Throughflow (ITF), which connects the tropical Pacific and Indian oceans, plays important roles in the inter-ocean water exchange and regional or even global climate variability. The Makassar Strait is the main inflow passage of the ITF, carrying about 77% of the total ITF volume transport. In this study, we analyze the simulated ITF in the Makassar Strait in the Simple Ocean Data Assimilation version 3 (SODA3) datasets. A total of nine ensemble members of the SODA3 datasets, of which are driven by different surface forcings and bulk formulas, and with or without data assimilation, are used in this study. The annual mean water transports (i.e., volume, heat and freshwater) are related to the combination of surface forcing and bulk formula, as well as whether data assimilation is employed. The phases of the seasonal and interannual variability in water transports cross the Makassar Strait, are basically consistent with each other among the SODA3 ensemble members. The interannual variability in Makassar Strait volume and heat transports are significantly correlated with El Niño-Southern Oscillation (ENSO) at time lags of −6 to 7 months. There is no statistically significant correlation between the freshwater transport and the ENSO. The Makassar Strait water transports are not significantly correlated with the Indian Ocean Dipole (IOD), which may attribute to model deficiency in simulating the propagation of semi-annual Kelvin waves from the Indian Ocean to the Makassar Strait.
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Figure 1. The sketch map of the Indonesian Throughflow (solid arrows) and the South China Sea branch (dashed arrows) of the Pacific to Indian Ocean Throughflow (following Fang et al. (2010)) (a), with red stars in donating the subsurface mooring stations of Mak-West (2°51.9′S, 118°27.3′E) and Mak-East (2°51.5′S, 118°37.7′E) during the INSTANT and MITF periods, and the integration route for the wind stress in the Island Rule calculation (red lines) (b).
Figure 2. The multi-dataset ensemble means of SODA3 (solid lines) and observed (dashed lines) velocity and temperature/salinity profiles in the Makassar Strait. a. Along-strait velocity; b. temperature (red lines) and salinity (blue lines). The error-bars indicate the standard deviation of the SODA3 products.
Figure 3. T-S diagram in the Makassar Strait. a. SODA3.3.0, b. SODA3.3.1, c. SODA3.3.2, d. SODA3.4.1, e. SODA3.4.2, f. SODA3.6.1, g. SODA3.7.2, h. SODA3.11.2, and i. SODA3.12.2.
Figure 4. The annual cycle of the along strait velocity in the Makassar Strait (left column) and the differences between the SODA3 and observation (right column). a. Observation and differences between SODA3 ensemble mean and observation; b–j. different SODA3 ensemble members as listed in Table 1. Red lines in the left column indicate the phase lines of the semi-annual Kelvin waves.
Figure 5. The along strait velocity anomalies in the Makassar Strait. a. Observation, b. SODA3.3.0, c. SODA3.3.1, d. SODA3.3.2, e. SODA3.4.1, f. SODA3.4.2, g. SODA3.6.1, h. SODA3.7.2, i. SODA3.11.2, and j. SODA3.12.2.
Figure 6. Annual mean transport of volume (a), heat (b), and freshwater (c) through the upper 700 m of the Makassar Strait in observations and SODA3 ensemble members. The cyan and pink bars in a are derived from the Island Rule and along strait velocity, respectively. Error bars indicate the standard deviation of the monthly transport time series.
Figure 7. Seasonal cycle of the volume (a), heat (b), and freshwater (c) transport per unit depth, and depth integrated volume (d), heat (e), and freshwater (f) transport in the upper 700 m through the Makassar Strait in SODA3 datasets. Shadings and contours in the left panels indicate the ensemble means and cross-ensemble member standard deviations of the SODA3 datasets. Solid black and red lines in d are calculated from the along strait velocity and Islands Rule based on SODA3 dataset, and blue line is from along strait velocity in observation. Error bars in d–f are the cross-ensemble member standard deviations of the SODA3 datasets. Unit: 1 Sv = 106 m3/s, 1 PW = 1015 W, 1 mSv = 10–3 Sv.
Figure 8. Interannual anomalies of the volume (a), heat (b), and freshwater (c) transport per unit depth through the Makassar Strait in SODA3 datasets. Shadings and contours indicate the ensemble means and cross-ensemble member standard deviations of the SODA3 datasets. Unit: 1 Sv = 10 6m3/s, 1 PW = 1015 W, 1 mSv = 10−3 Sv.
Figure 9. Correlation analysis between the Makassar Strait volume transport and the Indo-Pacific climate modes. a. Interannual anomaly of volume transport through the Makassar Strait (magenta), the Dipole Mode Index (DMI) (cyan) and Niño3.4 index (blue). b and c. lag correlations of the Makassar Strait volume transport anomaly with Niño3.4 and DMI, with error bars indicate the cross-ensemble member standard deviations of the SODA3 datasets. The horizontal lines in b and c indicate the 95% significance level. Unit: 1 Sv = 106 m3/s.
Figure 10. Correlation analysis between the Makassar Strait heat transport and the Indo-Pacific climate modes. a. Interannual anomaly of heat transport through the Makassar Strait (magenta), the Dipole Mode Index (DMI) (cyan) and Niño3.4 index (blue). b and c. lag correlations of the Makassar Strait heat transport anomaly with Niño3.4 and DMI, with error bars indicate the cross-ensemble member standard deviations of the SODA3 datasets. The horizontal lines in b and c indicate the 95% significance level. Unit: 1 PW = 1015 W.
Figure 11. Correlation analysis between the Makassar Strait freshwater transport and the Indo-Pacific climate modes. a. Interannual anomaly of freshwater transport through the Makassar Strait (magenta), the Dipole Mode Index (DMI) (cyan) and Niño3.4 index (blue). b and c. Lag correlations of the Makassar Strait freshwater transport anomaly with Niño3.4 and DMI, with error bars indicate the cross-ensemble member standard deviations of the SODA3 datasets. The horizontal lines in b and c indicate the 95% significance level. Unit: 1 mSv = 103 m3/s.
Figure 12. Climatological mean state (a), velocity anomaly induced variation (b), temperature anomaly induced variation (c), and higher-order terms of the total heat transport through the Makassar Strait (d). Unit: 1 TW = 1012 W.
Figure 13. Climatological mean state (a), velocity anomaly induced variation (b), salinity anomaly induced variation (c), and higher-order terms of the total freshwater transport (d) through the Makassar Strait. Unit: 1 mSv = 103 m3/s.
Figure 14. Annual mean transport of volume (a), heat (b), and freshwater (c) in the upper 700 m of the Makassar Strait in observations and ocean reanalysis products. Error bars indicate the standard deviation of the monthly transport time series.
Figure 15. Seasonal cycle of the depth integrated transport of volume (a), heat (b), and freshwater (c) in the upper 700 m of the Makassar Strait in observations and ocean reanalysis products.
Table 1. Details of the SODA3 reanalysis products used in the present study
No. Dataset Assimilation Forcing Forcing resolution Bulk formula Period 1 SODA3.3.0 no assimulation MERRA2 ~0.5° × 0.625° Large-Yeager 1980–2015 2 SODA3.3.1 optimum interpolation MERRA2 ~0.5° × 0.625° Large-Yeager 1980–2015 3 SODA3.3.2 optimum interpolation MERRA2 ~0.5° × 0.625° COARE4 1980–2017 4 SODA3.4.1 optimum interpolation ERA-Interim ~80 km (T255) Large-Yeager 1980–2016 5 SODA3.4.2 optimum interpolation ERA-Interim ~80 km (T255) COARE4 1980–2017 6 SODA3.6.1 optimum interpolation COREv2 1° × 1° Large-Yeager 1980–2009 7 SODA3.7.2 optimum interpolation JRA-55 ~55 km (TL319) COARE4 1980–2016 8 SODA3.11.2 optimum interpolation DFS5.2 ~0.7° × 0.625° COARE4 1980–2015 9 SODA3.12.2 optimum interpolation JRA-55DO ~55 km (TL319) COARE4 1980–2016 
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Atlas R, Hoffman R N, Ardizzone J, et al. 2011. A cross-calibrated, multiplatform ocean surface wind velocity product for meteorological and oceanographic applications. Bulletin of the American Meteorological Society, 92(2): 157–174, doi: 10.1175/2010BAMS2946.1 Balmaseda M A, Mogensen K, Weaver A T. 2013. Evaluation of the ECMWF ocean reanalysis system ORAS4. Quarterly Journal of the Royal Meteorological Society, 139(674): 1132–1161, doi: 10.1002/qj.2063 Balmaseda M A, Vidard A, Anderson D L T. 2008. The ECMWF ocean analysis system: ORA-S3. Monthly Weather Review, 136(8): 3018–3034, doi: 10.1175/2008MWR2433.1 Bleck R, Boudra D B. 1981. Initial testing of a numerical ocean circulation model using a hybrid (quasi-isopycnic) vertical coordinate. Journal of Physical Oceanography, 11(6): 755–770, doi: 10.1175/1520-0485(1981)011<0755:ITOANO>2.0.CO;2 Boyer T P, Antonov J I, Baranova O K, et al. 2013. World ocean database 2013. Silver Spring: National Oceanographic Data Center Ocean Climate Laboratory Broecker W S. 1991. The great ocean conveyor. Oceanography, 4(2): 79–89, doi: 10.5670/oceanog.1991.07 Carton J A, Chepurin G A, Chen Ligang. 2018. SODA3: a new ocean climate reanalysis. Journal of Climate, 31(17): 6967–6983, doi: 10.1175/JCLI-D-18-0149.1 Carton J A, Giese B S. 2008. A reanalysis of ocean climate using Simple Ocean Data Assimilation (SODA). Monthly Weather Review, 136(8): 2999–3017, doi: 10.1175/2007MWR1978.1 Casey K S, Brandon T B, Cornillon P, et al. 2010. The past, present, and future of the AVHRR Pathfinder SST Program. In: Barale V, Gower J F R, Alberotanza L, eds. Oceanography from Space: Revisited. Dordrecht: Springer, 273–287, Dee D P, Uppala S M, Simmons A J, et al. 2011. The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Quarterly Journal of the Royal Meteorological Society, 137(656): 553–597, doi: 10.1002/qj.828 Delworth T L, Rosati A, Anderson W, et al. 2012. Simulated climate and climate change in the GFDL CM2.5 high-resolution coupled climate model. Journal of Climate, 25(8): 2755–2781, doi: 10.1175/JCLI-D-11-00316.1 Du Yan, Qu Tangdong. 2010. Three inflow pathways of the Indonesian throughflow as seen from the simple ocean data assimilation. Dynamics of Atmospheres and Oceans, 50(2): 233–256, doi: 10.1016/j.dynatmoce.2010.04.001 Dussin R, Barnier B, Brodeau L, et al. 2016. The making of the DRAKKAR FORCING SET DFS5. Grenoble, France: Laboratoire de Glaciologie et Géophysique de l'Environnement Fairall C W, Bradley E F, Hare J E, et al. 2003. Bulk parameterization of air-sea fluxes: updates and verification for the COARE algorithm. Journal of Climate, 16(4): 571–591, doi: 10.1175/1520-0442(2003)016<0571:BPOASF>2.0.CO;2 Fang Guohong, Susanto R D, Wirasantosa S, et al. 2010. Volume, heat, and freshwater transports from the South China Sea to Indonesian seas in the boreal winter of 2007–2008. Journal of Geophysical Research: Oceans, 115(C12): C12020, doi: 10.1029/2010JC006225 Feng Ming, Zhang Ningning, Liu Qinyan, et al. 2018. The Indonesian throughflow, its variability and centennial change. Geoscience Letters, 5(1): 3, doi: 10.1186/s40562-018-0102-2 Gelaro R, McCarty W, Suárez M J, et al. 2017. The modern-era retrospective analysis for research and applications, version 2 (MERRA-2). Journal of Climate, 30(14): 5419–5454, doi: 10.1175/JCLI-D-16-0758.1 Godfrey J S. 1989. A Sverdrup model of the depth-integrated flow for the world ocean allowing for island circulations. Geophysical & Astrophysical Fluid Dynamics, 45(1–2): 89–112, Gordon A L. 1986. Interocean exchange of thermocline water. Journal of Geophysical Research: Oceans, 91(C4): 5037–5046, doi: 10.1029/JC091iC04p05037 Gordon A L. 2005. Oceanography of the Indonesian seas and their throughflow. Oceanography, 18(4): 14–27, doi: 10.5670/oceanog.2005.01 Gordon A L, Fine R A. 1996. Pathways of water between the Pacific and Indian oceans in the Indonesian seas. Nature, 379(6561): 146–149, doi: 10.1038/379146a0 Gordon A L, Huber B A, Metzger E J, et al. 2012. South China Sea throughflow impact on the Indonesian throughflow. Geophysical Research Letters, 39(11): L11602, doi: 10.1029/2012GL052021 Gordon A L, Napitu A, Huber B A, et al. 2019. Makassar Strait throughflow seasonal and interannual variability: an overview. Journal of Geophysical Research: Oceans, 124(6): 3724–3736, doi: 10.1029/2018JC014502 Gordon A L, Sprintall J, Van Aken H M, et al. 2010. The Indonesian throughflow during 2004–2006 as observed by the INSTANT program. Dynamics of Atmospheres and Oceans, 50(2): 115–128, doi: 10.1016/j.dynatmoce.2009.12.002 Gordon A L, Susanto R D, Ffield A. 1999. Throughflow within Makassar Strait. Geophysical Research Letters, 26(21): 3325–3328, doi: 10.1029/1999GL002340 Griffies S M, Biastoch A, Böning C, et al. 2009. Coordinated ocean-ice reference experiments (COREs). Ocean Modelling, 26(1–2): 1–46, Gruenburg L K, Gordon A L. 2018. Variability in Makassar Strait heat flux and its effect on the eastern tropical Indian Ocean. Oceanography, 31(2): 80–87, doi: 10.5670/oceanog.2018.220 Harada Y, Kamahori H, Kobayashi C, et al. 2016. The JRA-55 Reanalysis: representation of atmospheric circulation and climate variability. Journal of the Meteorological Society of Japan, 94(3): 269–302, doi: 10.2151/jmsj.2016-015 Hirst A C, Godfrey J S. 1993. The role of Indonesian throughflow in a global ocean GCM. Journal of Physical Oceanography, 23(6): 1057–1086, doi: 10.1175/1520-0485(1993)023<1057:TROITI>2.0.CO;2 Hu Shijian, Sprintall J. 2016. Interannual variability of the Indonesian Throughflow: the salinity effect. Journal of Geophysical Research: Oceans, 121(4): 2596–2615, doi: 10.1002/2015jc011495 Hu Shijian, Sprintall J. 2017. Observed strengthening of interbasin exchange via the Indonesian seas due to rainfall intensification. Geophysical Research Letters, 44(3): 1448–1456, doi: 10.1002/2016gl072494 Humphries U W, Webb D J. 2008. On the Indonesian Throughflow in the OCCAM 1/4 degree ocean model. Ocean Science, 4(3): 183–198, doi: 10.5194/os-4-183-2008 Ilahude A G, Gordon A L. 1996. Thermocline stratification within the Indonesian Seas. Journal of Geophysical Research: Oceans, 101(C5): 12401–12409, doi: 10.1029/95JC03798 Jiang Guoqing, Wei Jun, Malanotte-Rizzoli P, et al. 2019. Seasonal and interannual variability of the subsurface velocity profile of the Indonesian throughflow at Makassar Strait. Journal of Geophysical Research: Oceans, 124(12): 9644–9657, doi: 10.1029/2018jc014884 Kobayashi S, Ota Y, Harada Y, et al. 2015. The JRA-55 Reanalysis: general specifications and basic characteristics. Journal of the Meteorological Society of Japan, 93(1): 5–48, doi: 10.2151/jmsj.2015-001 Large W G, Yeager S G. 2004. Diurnal to decadal global forcing for ocean and sea-ice models: the data sets and flux climatologies. Boulder: University Corporation for Atmospheric Research. Large W G, Yeager S G. 2009. The global climatology of an interannually varying air–sea flux data set. Climate Dynamics, 33(2): 341–364, doi: 10.1007/s00382-008-0441-3 Lee T, Awaji T, Balmaseda M, et al. 2010. Consistency and fidelity of Indonesian-throughflow total volume transport estimated by 14 ocean data assimilation products. Dynamics of Atmospheres and Oceans, 50(2): 201–223, doi: 10.1016/j.dynatmoce.2009.12.004 Lee T, Fournier S, Gordon A L, et al. 2019. Maritime Continent water cycle regulates low-latitude chokepoint of global ocean circulation. Nature Communications, 10(1): 2103, doi: 10.1038/s41467-019-10109-z Li Mingting, Gordon A L, Gruenburg L K, et al. 2020. Interannual to decadal response of the Indonesian Throughflow vertical profile to Indo-Pacific forcing. Geophysical Research Letters, 47(11): e2020GL087679, doi: 10.1029/2020GL087679 Li Mingting, Wei Jun, Wang Dongxiao, et al. 2019. Exploring the importance of the Mindoro-Sibutu pathway to the upper-layer circulation of the South China Sea and the Indonesian throughflow. Journal of Geophysical Research: Oceans, 124(7): 5054–5066, doi: 10.1029/2018jc014910 Liang Linlin, Xue Huijie, Shu Yeqiang. 2019. The Indonesian throughflow and the circulation in the Banda Sea: a modeling study. Journal of Geophysical Research: Oceans, 124(5): 3089–3106, doi: 10.1029/2018JC014926 Liu Yun, Feng Ming, Church J, et al. 2005. Effect of salinity on estimating geostrophic transport of the Indonesian throughflow along the IX1 XBT section. Journal of Oceanography, 61(4): 795–801, doi: 10.1007/s10872-005-0086-3 Liu Qinyan, Feng Ming, Wang Dongxiao, et al. 2015. Interannual variability of the Indonesian Throughflow transport: a revisit based on 30 year expendable bathythermograph data. Journal of Geophysical Research: Oceans, 120(12): 8270–8282, doi: 10.1002/2015JC011351 Mears C A, Scott J, Wentz F J, et al. 2019. A near-real-time version of the cross-calibrated multiplatform (CCMP) ocean surface wind velocity data set. Journal of Geophysical Research: Oceans, 124(10): 6997–7010, doi: 10.1029/2019JC015367 Metzger E J, Hurlburt H E, Xu Xiaobiao, et al. 2010. Simulated and observed circulation in the Indonesian Seas: 1/12° global HYCOM and the INSTANT observations. Dynamics of Atmospheres and Oceans, 50(2): 275–300, doi: 10.1016/j.dynatmoce.2010.04.002 Meyers G, Bailey R J, Worby A P. 1995. Geostrophic transport of Indonesian Throughflow. Deep-Sea Research Part I: Oceanographic Research Papers, 42(7): 1163–1174, doi: 10.1016/0967-0637(95)00037-7 Napitu A M, Pujiana K, Gordon A L. 2019. The Madden-Julian Oscillation’s impact on the Makassar Strait surface layer transport. Journal of Geophysical Research: Oceans, 124(6): 3538–3550, doi: 10.1029/2018JC014729 Nie Xunwei, Gao Shan, Wang Fan, et al. 2019. Origins and pathways of the Pacific Equatorial Undercurrent identified by a simulated adjoint tracer. Journal of Geophysical Research: Oceans, 124(4): 2331–2347, doi: 10.1029/2018JC014212 Nur’utami M N, Hidayat R. 2016. Influences of IOD and ENSO to Indonesian rainfall variability: role of atmosphere-ocean interaction in the Indo-Pacific Sector. Procedia Environmental Sciences, 33: 196–203, doi: 10.1016/j.proenv.2016.03.070 Peng Qihua, Xie Shangping, Huang Ruixin, et al. 2023. Indonesian throughflow slowdown under global warming: remote AMOC effect versus regional surface forcing. Journal of Climate, 36(5): 1301–1318, Potemra J. 2005. Indonesian Throughflow transport variability estimated from satellite altimetry. Oceanography, 18(4): 98–107, doi: 10.5670/oceanog.2005.10 Pujiana K, Gordon A L, Sprintall J. 2013. Intraseasonal Kelvin wave in Makassar Strait. Journal of Geophysical Research: Oceans, 118(4): 2023–2034, doi: 10.1002/jgrc.20069 Pujiana K, McPhaden M J. 2020. Intraseasonal Kelvin waves in the equatorial Indian ocean and their propagation into the Indonesian seas. Journal of Geophysical Research: Oceans, 125(5): e2019JC015839, doi: 10.1029/2019JC015839 Pujiana K, McPhaden M J, Gordon A L, et al. 2019. Unprecedented response of Indonesian throughflow to anomalous Indo-Pacific climatic forcing in 2016. Journal of Geophysical Research: Oceans, 124(6): 3737–3754, doi: 10.1029/2018JC014574 Saji N H, Goswami B N, Vinayachandran P N, et al. 1999. A dipole mode in the tropical Indian Ocean. Nature, 401(6751): 360–363, doi: 10.1038/43854 Schiller A, Godfrey J S, McIntosh P C, et al. 1998. Seasonal near-surface dynamics and thermodynamics of the Indian Ocean and Indonesian Throughflow in a global ocean general circulation model. Journal of Physical Oceanography, 28(11): 2288–2312, doi: 10.1175/1520-0485(1998)028<2288:SNSDAT>2.0.CO;2 Song Qian, Gordon A L, Visbeck M. 2004. Spreading of the Indonesian throughflow in the Indian Ocean. Journal of Physical Oceanography, 34(4): 772–792, doi: 10.1175/1520-0485(2004)034<0772:SOTITI>2.0.CO;2 Sprintall J, Gordon A L, Wijffels S E, et al. 2019. Detecting change in the Indonesian seas. Frontiers in Marine Science, 6: 257, doi: 10.3389/fmars.2019.00257 Sprintall J, Révelard A. 2014. The Indonesian throughflow response to Indo-Pacific climate variability. Journal of Geophysical Research: Oceans, 119(2): 1161–1175, doi: 10.1002/2013JC009533 Sprintall J, Wijffels S, Gordon A L, et al. 2004. INSTANT: a new international array to measure the Indonesian Throughflow. Eos, Transactions American Geophysical Union, 85(39): 369–376, Sprintall J, Wijffels S E, Molcard R, et al. 2009. Direct estimates of the Indonesian Throughflow entering the Indian Ocean: 2004–2006. Journal of Geophysical Research: Oceans, 114(C7): C07001, doi: 10.1029/2008JC005257 Susanto R D, Ffield A, Gordon A L, et al. 2012. Variability of Indonesian throughflow within Makassar Strait, 2004–2009. Journal of Geophysical Research: Oceans, 117(C9): C09013, doi: 10.1029/2012JC008096 Susanto R D, Gordon A L. 2005. Velocity and transport of the Makassar Strait throughflow. Journal of Geophysical Research: Oceans, 110(C1): C01005, doi: 10.1029/2004JC002425 Susanto R D, Song Y T. 2015. Indonesian throughflow proxy from satellite altimeters and gravimeters. Journal of Geophysical Research: Oceans, 120(4): 2844–2855, doi: 10.1002/2014jc010382 Susanto R D, Wei Zexun, Adi R T, et al. 2013. Observations of the Karimata Strait throughflow from December 2007 to November 2008. Acta Oceanologica Sinica, 32(5): 1–6, doi: 10.1007/s13131-013-0307-3 Talley L D. 2013. Closure of the global overturning circulation through the Indian, Pacific, and Southern Oceans: schematics and transports. Oceanography, 26(1): 80–97, doi: 10.5670/oceanog.2013.07 Tillinger D, Gordon A L. 2009. Fifty years of the Indonesian throughflow. Journal of Climate, 22(23): 6342–6355, doi: 10.1175/2009JCLI2981.1 Tillinger D, Gordon A L. 2010. Transport weighted temperature and internal energy transport of the Indonesian throughflow. Dynamics of Atmospheres and Oceans, 50(2): 224–232, doi: 10.1016/j.dynatmoce.2010.01.002 Tsujino H, Urakawa S, Nakano H, et al. 2018. JRA-55 based surface dataset for driving ocean–sea-ice models (JRA55-do). Ocean Modelling, 130: 79–139, doi: 10.1016/j.ocemod.2018.07.002 van Sebille E, Sprintall J, Schwarzkopf F U, et al. 2014. Pacific-to-Indian Ocean connectivity: Tasman leakage, Indonesian Throughflow, and the role of ENSO. Journal of Geophysical Research: Oceans, 119(2): 1365–1382, doi: 10.1002/2013JC009525 Wang Yan, Xu Tengfei, Li Shujiang, et al. 2019. Seasonal variation of water transport through the Karimata Strait. Acta Oceanologica Sinica, 38(4): 47–57, doi: 10.1007/s13131-018-1224-2 Wei Jun, Li Mingting, Malanotte-Rizzoli P, et al. 2016. Opposite variability of Indonesian Throughflow and South China Sea throughflow in the Sulawesi Sea. Journal of Physical Oceanography, 46(10): 3165–3180, doi: 10.1175/jpo-d-16-0132.1 Wei Zexun, Li Shujiang, Susanto R D, et al. 2019. An overview of 10-year observation of the South China Sea branch of the Pacific to Indian Ocean throughflow at the Karimata Strait. Acta Oceanologica Sinica, 38(4): 1–11, doi: 10.1007/s13131-019-1410-x Wijffels S E, Meyers G, Godfrey J S. 2008. A 20-Yr average of the Indonesian throughflow: regional currents and the interbasin exchange. Journal of Physical Oceanography, 38(9): 1965–1978, doi: 10.1175/2008jpo3987.1 Woodruff S D, Worley S J, Lubker S J, et al. 2011. ICOADS Release 2.5: extensions and enhancements to the surface marine meteorological archive. International Journal of Climatology, 31(7): 951–967, doi: 10.1002/joc.2103 Wyrtki K. 1961. Physical Oceanography of the Southeast Asian Waters. La Jolla: Scripps Institution of Oceanography Wyrtki K. 1987. Indonesian through flow and the associated pressure gradient. Journal of Geophysical Research: Oceans, 92(C12): 12941–12946, doi: 10.1029/JC092iC12p12941 Xie Tengxiang, Newton R, Schlosser P, et al. 2019. Long-term mean mass, heat and nutrient flux through the Indonesian seas, based on the tritium inventory in the Pacific and Indian oceans. Journal of Geophysical Research: Oceans, 124(6): 3859–3875, doi: 10.1029/2018jc014863 Xu Tengfei, Wei Zexun, Susanto R D, et al. 2021. Observed water exchange between the South China Sea and Java Sea through Karimata Strait. Journal of Geophysical Research: Oceans, 126(2): e2020JC016608, doi: 10.1029/2020JC016608 Yuan Dongliang, Zhou Hui, Zhao Xia. 2013. Interannual climate variability over the tropical Pacific Ocean induced by the Indian Ocean dipole through the Indonesian Throughflow. Journal of Climate, 26(9): 2845–2861, doi: 10.1175/jcli-d-12-00117.1 Zhang Tiecheng, Wang Weiqiang, Xie Qiang, et al. 2019. Heat contribution of the Indonesian throughflow to the Indian Ocean. Acta Oceanologica Sinica, 38(4): 72–79, doi: 10.1007/s13131-019-1414-6 Zhao Yunxia, Wei Zexun, Wang Yonggang, et al. 2015. Correlation analysis of the North Equatorial Current bifurcation and the Indonesian Throughflow. Acta Oceanologica Sinica, 34(9): 1–11, doi: 10.1007/s13131-015-0736-2 -
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