Annamalai H.,R. Murtugudde, 2004: Role of the Indian Ocean in regional climate variability. Earth's Climate: The Ocean-Atmosphere Interaction, C. Wang et al., Eds., American Geophysical Union, 213- 246.10.1029/147GM139935b152e45428ac054d3890f6d9a252http%3A%2F%2Fonlinelibrary.wiley.com%2Fdoi%2F10.1029%2F147GM13%2Fpdfhttp://onlinelibrary.wiley.com/doi/10.1029/147GM13/pdfThe role of the Indian Ocean in regional climate variability has been studied for a long time. Whether the Indian Ocean plays an active role or simply responds passively to the wind and heat flux variability generated elsewhere remains somewhat of an open question. Here we attempt a fairly comprehensive review of the literature relating to the Indian Ocean variability at all time-scales and to the current understanding of the role of this tropical ocean in the coupled climate system. Despite an investigative history of more than a century, it is fair to say that the role of the Indian Ocean in regional monsoon variability, the most important climate process in this sector, remains to be fully understood and remains an active area of diagnostic and modeling research. This translates into limited success of the state-of-the-art monsoon forecast systems, statistical and dynamical. Much attention in the last few years has been focused on the east-west mode of variability, referred to as the dipole or the zonal mode. While there is incontrovertible evidence that the Indian Ocean plays an active role in some of these dipole/zonal mode events, the self-sustainability of this mode and its impact on regional and global climate is still a matter of debate. The most significant impediment to improving the predictive understanding of the region is the fact that at all time-scales sea surface temperature variability of the Indian Ocean is most often in the range of observational errors. The need for coordinated and sustained observations and diagnostic studies along with continued investigations using a hierarchy of models has been well-recognized, because monsoons form an integral part of the global climate system and the ENSO cycles. It is thus hoped that the role of the Indian Ocean in the coupled climate system will be much better quantified in the coming years, leading to significant improvements in regional coupled climate forecasts. |
Ansell T.,C. J. C. Reason, and G. Meyers, 2000: Variability in the tropical southeast Indian Ocean and links with southeast Australian winter rainfall. Geophys. Res. Lett., 27, 3977-3980, https://doi.org/10.1029/2000GL011856 |
Behera S. K.,J. J. Luo, S. Masson, P. Delecluse, S. Gualdi, A. Navarra, and T. Yamagata, 2005: Paramount impact of the Indian Ocean dipole on the East African short rains: A CGCM study. J. Climate, 18, 4514-4530, https://doi.org/10.1175/JCLI3541.1 |
Black E.,J. Slingo, and K. P. Sperber, 2003: An observational study of the relationship between excessively strong short rains in coastal east Africa and Indian Ocean SST. Mon. Wea. Rev., 131(1), 74, https://doi.org/10.1175/1520-0493(2003)131<0074:AOSOTR>2.0.CO;2 |
Cai W.,T. Cowan, and A. Sullivan, 2009: Recent unprecedented skewness towards positive Indian Ocean Dipole occurrences and its impact on Australian rainfall. Geophys. Res. Lett., 36, L11705, https://doi.org/10.1029/2009GL037604 |
Cai W. J.,H. H. Hendon, and G. Meyers, 2005: Indian Ocean dipolelike variability in the CSIRO Mark 3 coupled climate model. J. Climate, 18, 1449-1468, https://doi.org/10.1175/JCLI3332.1 |
Chen D. K.,2011: Indo-Pacific tripole: An intrinsic mode of tropical climate variability. Advances in Geosciences, 24, 1- 18.10.1142/9789814355353a92fd7f305ac4230d80a47c0b48cb61bhttp%3A%2F%2Fwww.cambridgeindia.org%2Fshowbookdetails1.asp%3FISBN%3D9789814355292%26amp%3Bcategory_id%3D75Ehttp://ebooks.worldscinet.com/ISBN/9789814355353/9789814355353.html |
Chowdary J. S.,C. Gnanaseelan, 2007: Basin-wide warming of the Indian Ocean during El NiÑo and Indian Ocean dipole years. International Journal of Climatology, 27, 1421-1438, https://doi.org/10.1002/joc.1482 |
Duan W. S.,Y. S. Yu, H. Xu, and P. Zhao, 2013: Behaviors of nonlinearities modulating the El NiÑno events induced by optimal precursory disturbances. Climate Dyn., 40, 1399-1413, https://doi.org/10.1007/s00382-012-1557-z |
Feng R.,W. S. Duan, 2018: Investigating the initial errors that cause predictability barriers for Indian Ocean Dipole events using CMIP5 model outputs. Adv. Atmos. Sci., 35(10), 1305-1320, https://doi.org/10.1007/s00376-018-7214-7 |
Feng R.,W. S. Duan, and M. Mu, 2014a: The "winter predictability barrier" for IOD events and its error growth dynamics: Results from a fully coupled GCM. J. Geophys. Res., 119, 8688-8708, https://doi.org/10.1002/2014JC010473 |
Feng R.,M. Mu, and W. S. Duan, 2014b: Study on the "winter persistence barrier" of Indian Ocean dipole events using observation data and CMIP5 model outputs. Theor. Appl. Climatol., 118(3), 523-534, https://doi.org/10.1007/s00704-013-1083-x |
Feng R.,W. S. Duan, and M. Mu, 2017: Estimating observing locations for advancing beyond the winter predictability barrier of Indian Ocean dipole event predictions. Climate Dyn., 48, 1173-1185, https://doi.org/10.1007/s00382-016-3134-3 |
GFDL Global Atmospheric Model Development Team, 2004: The new GFDL global atmosphere and land model AM2-LM2: Evaluation with prescribed SST simulations. J. Climate, 17, 4641-4673, https://doi.org/10.1175/JCLI-3223.1 |
Griffies S. M.,2009: Elements of MOM4p1: GFDL ocean group. Technical Report No.6, 444 pp. |
Gualdi S.,E. Guilyardi, A. Navarra, S. Masina, and P. Delecluse, 2003: The interannual variability in the tropical Indian Ocean as simulated by a CGCM. Climate Dyn., 20, 567-582, https://doi.org/10.1007/s00382-002-0295-z |
Kaplan A.,M. A. Cane, Y. Kushnir, A. C. Clement, M. B. Blumenthal, and B. Rajagopalan, 1998: Analyses of global sea surface temperature 1856-1991. J. Geophys. Res., 103, 18 567-185 89, https://doi.org/10.1029/97JC01736 |
Li T.,B. Wang, C. P. Chang, and Y. S. Zhang, 2003: A theory for the Indian Ocean dipole-zonal mode. J. Atmos. Sci., 60(17), 2119, https://doi.org/10.1175/1520-0469(2003)060<2119:ATFTIO>2.0.CO;2 |
Lian T.,D. K. Chen, Y. M. Tang, and B. G. Jin, 2014: A theoretical investigation of the tropical Indo-Pacific tripole mode. Science China Earth Sciences, 57, 174-188, https://doi.org/10.1007/s11430-013-4762-7 |
Liu D.,W. S. Duan, R. Feng, and Y. M. Tang, 2018: Summer Predictability Barrier of Indian Ocean dipole events and corresponding error growth dynamics. J. Geophys. Res., 123, 3635-3650, https://doi.org/10.1029/2017JC013739 |
Loschnigg J.,G. A. Meehl, P. J. Webster, J. M. Arblaster, and G. P. Compo, 2003: The Asian monsoon, the tropospheric biennial oscillation, and the Indian Ocean zonal mode in the NCAR CSM. J. Climate, 16, 1617-1642, https://doi.org/10.1175/1520-0442(2003)016<1617:TAMTTB>2.0.CO;2 |
Luo J. J.,S. Masson, S. Behera, S. Shingu, and T. Yamagata, 2005: Seasonal climate predictability in a coupled OAGCM using a different approach for ensemble forecasts. J. Climate, 18(21), 4474-4497, https://doi.org/10.1175/JCLI3526.1 |
Luo J. J.,S. Masson, S. Behera, and T. Yamagata, 2007: Experimental forecasts of the Indian Ocean dipole using a coupled OAGCM. J. Climate, 20(10), 2178-2190, https://doi.org/10.1175/JCLI4132.1 |
Murtugudde R.,J. P. McCreary Jr., and A. J. Busalacchi, 2000: Oceanic processes associated with anomalous events in the Indian Ocean with relevance to 1997-1998. J. Geophys. Res., 105(C2), 3295-3306, https://doi.org/10.1029/1999JC900294 |
Saji N. H.,T. Yamagata, 2003: Possible impacts of Indian Ocean Dipole mode events on global climate. Climate Research, 25, 151-169, https://doi.org/10.3354/cr025151 |
Saji N. H.,B. N. Goswami, P. N. Vinayachand ran, and T. Yamagata, 1999: A dipole mode in the tropical Indian Ocean. Nature, 401(6751), 360-363, https://doi.org/10.1038/43854 |
Sayantani O.,C. Gnanaseelan, and J. S. Chowdary, 2014: The role of Arabian Sea in the evolution of Indian Ocean Dipole. International Journal of Climatology, 34, 1845-1859, https://doi.org/10.1002/joc.3805 |
Shi L.,H. H. Hendon, O. Alves, J. J. Luo, M. Balmaseda, and D. Anderson, 2012: How predictable is the Indian Ocean dipole? Mon. Wea. Rev., 140(12), 3867-3884, https://doi.org/10.1175/MWR-D-12-00001.1 |
Song Q.,G. A. Vecchi, and A. J. Rosati, 2007: Indian Ocean variability in the GFDL coupled climate model. J. Climate, 20, 2895-2916, https://doi.org/10.1175/JCLI4159.1 |
Stuecker M. F.,A. Timmermann, F. F. Jin, Y. Chikamoto, W. J. Zhang, A. T. Wittenberg, E. Widiasih, and S. Zhao, 2017: Revisiting ENSO/Indian Ocean Dipole phase relationships, Geophys. Res. Lett., 44, 2481-2492, https://doi.org/10.1002/2016GL072308 |
Vinayachand ran, P. N., S. Iizuka, T. Yamagata, 2002: Indian Ocean dipole mode events in an ocean general circulation model. Deep Sea Research Part II: Topical Studies in Oceanography, 49(7-8), 1573-1596, https://doi.org/10.1016/S0967-0645(01)00157-6 |
Wajsowicz R. C.,2004: Climate variability over the tropical Indian Ocean sector in the NSIPP seasonal forecast system. J. Climate, 17(24), 4783-4804, https://doi.org/10.1175/JCLI-3239.1 |
Wajsowicz R. C.,2005: Potential predictability of tropical Indian Ocean SST anomalies. Geophys. Res. Lett., 32(24), L24702. https://doi.org/10.1029/2005GL024169 |
Wang Q.,M. Mu, and H. A. Dijkstra, 2012: Application of the conditional nonlinear optimal perturbation method to the predictability study of the Kuroshio large meander. Adv. Atmos. Sci., 29(1), 118-134, https://doi.org/10.1007/s00376-011-0199-0 |
Webster P. J.,A. M. Moore, J. P. Loschnigg, and R. R. Leben, 1999: Coupled ocean-atmosphere dynamics in the Indian Ocean during 1997-98. Nature, 401(6751), 356-360, https://doi.org/10.1038/43848 |
Weller E.,W. J. Cai, 2013: Asymmetry in the IOD and ENSO teleconnection in a CMIP5 model ensemble and its relevance to regional rainfall. J. Climate, 26, 5139-5149, https://doi.org/10.1175/JCLI-D-12-00789.1 |
Yamagata T.,S. K. Behera, J. J. Luo, S. Masson, M. R. Jury, and S. A. Rao, 2004: Coupled ocean-atmosphere variability in the tropical Indian Ocean. Earth's Climate: The Ocean-Atmosphere Interaction, C. Wang, Eds., American Geophysical Union, 189- 212.10.1029/147GM12db3d36f04953443b49ec865060a3f489http%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F2004GMS...147..189Yhttp://adsabs.harvard.edu/abs/2004GMS...147..189YThe Indian Ocean Dipole (IOD) is a natural ocean tmosphere coupled mode that plays important roles in seasonal and interannual climate variations. The coupled mode locked to boreal summer and fall is distinguished as a dipole in the SST anomalies that are coupled to zonal winds. The equatorial winds reverse their direction from westerlies to easterlies during the peak phase of the positive IOD events when SST is cool in the east and warm in the west. In response to changes in the wind, the thermocline rises in the east and subsides in the west. Subsurface equatorial long Rossby waves play a major role in strengthening SST anomalies in (he central and western parts. The SINTEX-F1 coupled model results support the observational finding that these equatorial Rossby waves are coupled to the surface wind forcing associated with IOD rather than ENSO. The ENSO influence is only distinct in off-equatorial latitudes south of 10 S. Although IOD events dominate the ocean tmosphere variability during its evolution, their less frequent occurrence compared to ENSO events leads the mode to the second seat in the interannual variability. Therefore, it is necessary to remove the most dominant uniform mode to capture the IOD statistically. The seasonally stratified correlation between the indices of IOD and ENSO peaks at 0.53 in September ovember. This means that only one third of IOD events are associated with ENSO events. Since a large number of IOD events are not associated with ENSO events, the independent nature of IOD is examined using partial correlation and pure composite techniques. Through changes in atmospheric circulation and water vapor transport, a positive IOD event causes drought in Indonesia, above normal rainfall in Africa, India, Bangladesh and Vietnam, and dry as well as hot summer in Europe, Japan, Korea and East China. In the Southern Hemisphere, the positive IOD causes dry winter in Australia, and dry as well as warm conditions in Brazil. The identification of IOD events has raised a new possibility to make a real advance in the predictability of seasonal and interannual climate variations that originate in the tropics. |
Yu J. Y.,K. M. Lau, 2005: Contrasting Indian Ocean SST variability with and without ENSO influence: A coupled atmosphere-ocean GCM study. Meteor. Atmos. Phys., 90(3-4), 179-191, https://doi.org/10.1007/s00703-004-0094-7 |
Yu Y. S.,W. S. Duan, and M. Mu, 2009: Dynamics of nonlinear error growth and season-dependent predictability of El NiÑo events in the Zebiak-Cane model. Quart. J. Roy. Meteor. Soc., 135, 2146-2160, https://doi.org/10.1002/qj.526 |
Zhang W. J.,Y. L. Wang, F. F. Jin, M. F. Stuecker, and A. G. Turner, 2015: Impact of different El NiÑo types on the El NiÑo/IOD relationship. Geophys. Res. Lett., 42(20), 8570-8576, https://doi.org/10.1002/2015GL065703 |
Zubair L.,S. A. Rao, and T. Yamagata, 2003: Modulation of Sri Lankan Maharainfall by the Indian Ocean dipole. Geophys. Res. Lett., 30(2), 1063, https://doi.org/10.1029/2002GL015639 |