Indian Ocean Basin Warming in 2020 Forced by Thermocline Anomalies of the 2019 Indian Ocean Dipole

Jing Wang aCAS Key Laboratory of Ocean Circulation and Waves, Center for Ocean Mega-Science, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, China
bLaoshan Laboratory, Qingdao, Shandong, China
cUniversity of Chinese Academy of Sciences, Beijing, China

Search for other papers by Jing Wang in
Current site
Google Scholar
PubMed
Close
,
Shouwen Zhang dSouthern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, China

Search for other papers by Shouwen Zhang in
Current site
Google Scholar
PubMed
Close
,
Hua Jiang eNational Marine Environmental Forecasting Center, Ministry of Natural Resources, Beijing, China

Search for other papers by Hua Jiang in
Current site
Google Scholar
PubMed
Close
, and
Dongliang Yuan fKey Laboratory of Marine Science and Numerical Modeling, First Institute of Oceanography, Ministry of Natural Resources, Qingdao, China
bLaoshan Laboratory, Qingdao, Shandong, China
cUniversity of Chinese Academy of Sciences, Beijing, China
gShandong Key Laboratory of Marine Science and Numerical Modeling, Qingdao, China

Search for other papers by Dongliang Yuan in
Current site
Google Scholar
PubMed
Close
https://orcid.org/0000-0002-1588-7332
Restricted access

Abstract

The Indian Ocean basin (IOB) mode is the dominant mode of the interannual sea surface temperature (SST) variability in the Indian Ocean, with the Indian Ocean dipole (IOD) as the second mode. An IOB event normally occurs after an El Niño or a concurrent IOD–El Niño event, the dynamics of which are traditionally believed as forced by ENSO through the Walker circulation anomalies over the tropical Indian Ocean. A strong IOB in 2020 took place after the strongest 2019 IOD on record but independent of El Niño, which challenges the traditional atmospheric bridge dynamics of the IOB event. In this study, the dynamics of the 2020 IOB event are investigated using the numerical seasonal climate prediction system of the National Marine Environmental Forecasting Center of China. It is found that the initialization of the Indian Ocean subsurface temperature during the 2019 IOD event has led to the outburst of the 2020 IOB event successfully, the dynamics of which are the propagation and the western boundary reflection of the equatorial and off-equatorial Rossby waves, inducing heat content recharge over the tropical Indian Ocean upper thermocline. In comparison, experiments of SST initialization over the tropical Indian Ocean, with the subsurface temperature in a climatological state, were unable to reproduce the onset of the 2020 IOB event, suggesting that the local air–sea interaction within the Indian Ocean basin is of secondary importance. The numerical experiments suggest that the thermocline ocean wave dynamics play an important role in forcing the IOB event. The revealed thermocline dynamics are potentially useful in climate prediction associated with IOB events.

© 2023 American Meteorological Society. This published article is licensed under the terms of the default AMS reuse license. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding authors: Shouwen Zhang, zhangshouwen@sml-zhuhai.cn; Dongliang Yuan, dyuan@fio.org.cn

Abstract

The Indian Ocean basin (IOB) mode is the dominant mode of the interannual sea surface temperature (SST) variability in the Indian Ocean, with the Indian Ocean dipole (IOD) as the second mode. An IOB event normally occurs after an El Niño or a concurrent IOD–El Niño event, the dynamics of which are traditionally believed as forced by ENSO through the Walker circulation anomalies over the tropical Indian Ocean. A strong IOB in 2020 took place after the strongest 2019 IOD on record but independent of El Niño, which challenges the traditional atmospheric bridge dynamics of the IOB event. In this study, the dynamics of the 2020 IOB event are investigated using the numerical seasonal climate prediction system of the National Marine Environmental Forecasting Center of China. It is found that the initialization of the Indian Ocean subsurface temperature during the 2019 IOD event has led to the outburst of the 2020 IOB event successfully, the dynamics of which are the propagation and the western boundary reflection of the equatorial and off-equatorial Rossby waves, inducing heat content recharge over the tropical Indian Ocean upper thermocline. In comparison, experiments of SST initialization over the tropical Indian Ocean, with the subsurface temperature in a climatological state, were unable to reproduce the onset of the 2020 IOB event, suggesting that the local air–sea interaction within the Indian Ocean basin is of secondary importance. The numerical experiments suggest that the thermocline ocean wave dynamics play an important role in forcing the IOB event. The revealed thermocline dynamics are potentially useful in climate prediction associated with IOB events.

© 2023 American Meteorological Society. This published article is licensed under the terms of the default AMS reuse license. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding authors: Shouwen Zhang, zhangshouwen@sml-zhuhai.cn; Dongliang Yuan, dyuan@fio.org.cn
Save
  • Alexander, M. A., I. Blade, M. Newman, J. R. Lanzante, N. C. Lau and J. D. Scott, 2002: The atmospheric bridge: The influence of ENSO teleconnections on air–sea interaction over the global oceans. J. Climate, 15, 22052231, https://doi.org/10.1175/1520-0442(2002)015<2205:TABTIO>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Behera, S. K., J. J. Luo, S. Masson, S. A. Rao, H. Sakum, and T. Yamagata, 2006: A CGCM study on the interaction between IOD and ENSO. J. Climate, 19, 16881705, https://doi.org/10.1175/JCLI3797.1.

    • Search Google Scholar
    • Export Citation
  • Cai, W., and Coauthors, 2019: Pantropical climate interactions. Science, 363, eaav4236, https://doi.org/10.1126/science.aav4236.

  • Chen, G., W. Han, Y. Shu, Y. Li, D. Wang, and Q. Xie, 2016: The role of equatorial undercurrent in sustaining the eastern Indian Ocean upwelling. Geophys. Res. Lett., 43, 64446451, https://doi.org/10.1002/2016GL069433.

    • Search Google Scholar
    • Export Citation
  • Chowdary, J. S., and C. Gnanaseelan, 2007: Basin-wide warming of the Indian Ocean during El Niño and Indian Ocean dipole years. Int. J. Climatol., 27, 14211438, https://doi.org/10.1002/joc.1482.

    • Search Google Scholar
    • Export Citation
  • Danabasoglu, G., S. C. Bates, B. P. Briegleb, S. R. Jayne, M. Jochum, W. G. Large, S. Peacock and S. G. Yeager, 2012: The CCSM4 ocean component. J. Climate, 25, 13611389, https://doi.org/10.1175/JCLI-D-11-00091.1.

    • Search Google Scholar
    • Export Citation
  • Ding, R., I. Kang, R. Farneti, F. Kucharski, F. D. Sante, J. Xuan, F. Zhou, and T. Zhang, 2022: The internal and ENSO-forced modes of the Indian Ocean sea surface temperature. J. Climate, 35, 41914206, https://doi.org/10.1175/JCLI-D-21-0403.1.

    • Search Google Scholar
    • Export Citation
  • Doi, T., S. K. Behera, and T. Yamagata, 2020: Predictability of the super IOD event in 2019 and its link with El Niño Modoki. Geophys. Res. Lett., 47, e2019GL086713, https://doi.org/10.1029/2019GL086713.

    • Search Google Scholar
    • Export Citation
  • Dommenget, D., and M. Latif, 2002: A cautionary note on the interpretation of EOFs. J. Climate, 15, 216225, https://doi.org/10.1175/1520-0442(2002)015<0216:ACNOTI>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Du, Y., S.-P. Xie, G. Huang, and K. Hu, 2009: Role of air–sea interaction in the long persistence of El Niño–induced north Indian Ocean warming. J. Climate, 22, 20232038, https://doi.org/10.1175/2008JCLI2590.1.

    • Search Google Scholar
    • Export Citation
  • Du, Y., Y. Zhang, L.-Y. Zhang, T. Tozuka, B. Ng, and W. Cai, 2020: Thermocline warming induced extreme Indian Ocean dipole in 2019. Geophys. Res. Lett., 47, e2020GL090079, https://doi.org/10.1029/2020GL090079.

    • Search Google Scholar
    • Export Citation
  • Fedorov, A. V., and J. N. Brown, 2009: Equatorial waves. Encyclopedia of Ocean Sciences, 2nd ed. Academic Press, 3679–3695.

  • Guo, F., Q. Liu, J. Yang, and L. Fan, 2018: Three types of Indian Ocean basin modes. Climate Dyn., 51, 43574370, https://doi.org/10.1007/s00382-017-3676-z.

    • Search Google Scholar
    • Export Citation
  • Hong, C.-C., T. Li, LinHo, and Y.-C. Chen, 2010: Asymmetry of the Indian Ocean basinwide SST anomalies: Roles of ENSO and IOD. J. Climate, 23, 35633576, https://doi.org/10.1175/2010JCLI3320.1.

    • Search Google Scholar
    • Export Citation
  • Huang, B., and J. L. Kinter III, 2002: Interannual variability in the tropical Indian Ocean. J. Geophys. Res., 107, 3199, https://doi.org/10.1029/2001JC001278.

    • Search Google Scholar
    • Export Citation
  • Kajtar, J. B., A. Santoso, M. H. England, and W. Cai, 2017: Tropical climate variability: Interactions across the Pacific, Indian, and Atlantic Oceans. Climate Dyn., 48, 21732190, https://doi.org/10.1007/s00382-016-3199-z.

    • Search Google Scholar
    • Export Citation
  • Klein, S. A., B. J. Soden, and N.-C. Lau, 1999: Remote sea surface temperature variations during ENSO: Evidence for a tropical atmospheric bridge. J. Climate, 12, 917932, https://doi.org/10.1175/1520-0442(1999)012<0917:RSSTVD>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Lau, N.-C., and M. J. Nath, 1996: The role of the “atmospheric bridge” in linking tropical Pacific ENSO events to extratropical SST anomalies. J. Climate, 9, 20362057, https://doi.org/10.1175/1520-0442(1996)009<2036:TROTBI>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Lau, N.-C., and M. J. Nath, 2003: Atmosphere–ocean variations in the Indo-Pacific sector during ENSO episodes. J. Climate, 16, 320, https://doi.org/10.1175/1520-0442(2003)016<0003:AOVITI>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Li, T., B. Wang, C.-P. Chang, and Y. Zhang, 2003: A theory for the Indian Ocean dipole–zonal mode. J. Atmos. Sci., 60, 21192135, https://doi.org/10.1175/1520-0469(2003)060<2119:ATFTIO>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Masumoto, Y., and G. Meyers, 1998: Forced Rossby waves in the southern tropical Indian Ocean. J. Geophys. Res., 103, 27 58927 602, https://doi.org/10.1029/98JC02546.

    • Search Google Scholar
    • Export Citation
  • McPhaden, M. J., and M. Nagura, 2014: Indian Ocean dipole interpreted in terms of recharge oscillator theory. Climate Dyn., 42, 15691586, https://doi.org/10.1007/s00382-013-1765-1.

    • Search Google Scholar
    • Export Citation
  • 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, 32953306, https://doi.org/10.1029/1999JC900294.

    • Search Google Scholar
    • Export Citation
  • Nigam, S., and H.-S. Shen, 1993: Structure of oceanic and atmospheric low-frequency variability over the tropical Pacific and Indian Oceans. Part I: COADS observations. J. Climate, 6, 657676, https://doi.org/10.1175/1520-0442(1993)006<0657:SOOAAL>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Reason, C. J. C., R. J. Allan, J. A. Lindesay, and T. J. Ansell, 2000: ENSO and climatic signals across the Indian Ocean basin in the global context: Part I, interannual composite patterns. Int. J. Climatol., 20, 12851327, https://doi.org/10.1002/1097-0088(200009)20:11<1285::AID-JOC536>3.0.CO;2-R.

    • Search Google Scholar
    • Export Citation
  • Saji, N. H., and T. Yamagata, 2003: Possible impacts of Indian Ocean dipole mode events on global climate. Climate Res., 25, 151169, https://doi.org/10.3354/cr025151.

    • Search Google Scholar
    • Export Citation
  • Saji, N. H., B. N. Goswami, P. N. Vinayachandran, and T. Yamagata, 1999: A dipole mode in the tropical Indian Ocean. Nature, 401, 360363, https://doi.org/10.1038/43854.

    • Search Google Scholar
    • Export Citation
  • Santoso, A., M. H. England, and W. Cai, 2012: Impact of Indo-Pacific feedback interactions on ENSO dynamics diagnosed using ensemble climate simulations. J. Climate, 25, 77437763, https://doi.org/10.1175/JCLI-D-11-00287.1.

    • Search Google Scholar
    • Export Citation
  • Schott, F. A., S.-P. Xie, and J. P. McCreary Jr., 2009: Indian Ocean circulation and climate variability. Rev. Geophys., 47, RG1002, https://doi.org/10.1029/2007RG000245.

    • Search Google Scholar
    • Export Citation
  • Song, X., X. Li, S. Zhang, Y. Li, X. Chen, Y. Tang, and D. Chen, 2022: A new nudging scheme for the current operational climate prediction system in National Marine Environmental Forecasting Center of China. Acta Oceanol. Sin., 41, 5164, https://doi.org/10.1007/s13131-021-1857-4.

    • Search Google Scholar
    • Export Citation
  • Tokinaga, H., and Y. Tanimoto, 2004: Seasonal transition of SST anomalies in the tropical Indian Ocean during El Niño and Indian Ocean dipole years. J. Meteor. Soc. Japan, 82, 10071018, https://doi.org/10.2151/jmsj.2004.1007.

    • Search Google Scholar
    • Export Citation
  • Venzke, S., M. Latif, and A. Villwock, 2000: The coupled GCMECHO-2. Part II: Indian Ocean response to ENSO. J. Climate, 13, 13711383, https://doi.org/10.1175/1520-0442(2000)013<1371:TCGE>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Wang, C., 2019: Three-ocean interactions and climate variability: A review and perspective. Climate Dyn., 53, 51195136, https://doi.org/10.1007/s00382-019-04930-x.

    • Search Google Scholar
    • Export Citation
  • Wang, G., W. Cai, K. Yang, A. Santoso, and T. Yamagata, 2020: A unique feature of the 2019 extreme positive Indian Ocean dipole event. Geophys. Res. Lett., 47, e2020GL088615, https://doi.org/10.1029/2020GL088615.

    • Search Google Scholar
    • Export Citation
  • Wang, J., and D. Yuan, 2015: Roles of western and eastern boundary reflections in the interannual sea level variations during negative Indian Ocean dipole events. J. Phys. Oceanogr., 45, 18041821, https://doi.org/10.1175/JPO-D-14-0124.1.

    • Search Google Scholar
    • Export Citation
  • Wang, J., S. Zhang, H. Jiang, and D. Yuan, 2023: Effects of 2019 subsurface Indian Ocean initialization on the forecast of the 2020/2021 La Niña event. Climate Dyn., 60, 24192435, https://doi.org/10.1007/s00382-022-06442-7.

    • Search Google Scholar
    • Export Citation
  • 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, 356360, https://doi.org/10.1038/43848.

    • Search Google Scholar
    • Export Citation
  • Xie, S.-P., H. Annamalai, F. A. Schott and J. P. McCreary, 2002: Structure and mechanisms of South Indian Ocean climate variability. J. Climate, 15, 864878, https://doi.org/10.1175/1520-0442(2002)015<0864:SAMOSI>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Xie, S.-P., K. Hu, J. Hafner, H. Tokinaga, Y. Du, G. Huang, and T. Sampe, 2009: Indian Ocean capacitor effect on Indo–western Pacific climate during the summer following El Niño. J. Climate, 22, 730747, https://doi.org/10.1175/2008JCLI2544.1.

    • Search Google Scholar
    • Export Citation
  • Yang, J., Q. Liu, S.-P. Xie, Z. Liu, and L. Wu, 2007: Impact of the Indian Ocean SST basin mode on the Asian summer monsoon. Geophys. Res. Lett., 34, L02708, https://doi.org/10.1029/2006GL028571.

    • Search Google Scholar
    • Export Citation
  • Yao, Z., Y. Tang, D. Chen, L. Zhou, X. Li, T. Lian, and S. Ul Islam, 2016: Assessment of the simulation of Indian Ocean dipole in the CESM—Impacts of atmospheric physics and model resolution. J. Adv. Model. Earth Syst., 8, 19321952, https://doi.org/10.1002/2016MS000700.

    • Search Google Scholar
    • Export Citation
  • Yuan, D., and H. Liu, 2009: Long-wave dynamics of sea level variations during Indian Ocean dipole events. J. Phys. Oceanogr., 39, 11151132, https://doi.org/10.1175/2008JPO3900.1.

    • Search Google Scholar
    • Export Citation
  • Zhang, S., H. Jiang, and H. Wang, 2019: Assessment of the sea surface temperature predictability based on multimodel hindcasts. Wea. Forecasting, 34, 19651977, https://doi.org/10.1175/WAF-D-19-0040.1.

    • Search Google Scholar
    • Export Citation
  • Zhang, S., J. Wang, H. Jiang, H. Wang, and D. Yuan, 2023: Effects of Indian Ocean dipole initialization on the forecasting of La Niña 1 year in advance. Climate Dyn., 61, 46614677, https://doi.org/10.1007/s00382-023-06816-5.

    • Search Google Scholar
    • Export Citation
  • Zhang, W., W. Mao, F. Jiang, M. F. Stuecker, F.-F. Jin, and L. Qi, 2021: Tropical Indo-Pacific compounding thermal conditions drive the 2019 Australian extreme drought. Geophys. Res. Lett., 48, e2020GL090323, https://doi.org/10.1029/2020GL090323.

    • Search Google Scholar
    • Export Citation
  • Zhang, Y., and Y. Du, 2021: Extreme IOD induced tropical Indian Ocean warming in 2020. Geosci. Lett., 8, 37, https://doi.org/10.1186/s40562-021-00207-6.

    • Search Google Scholar
    • Export Citation
  • Zhao, X., G. Yang, D. Yuan, and Y. Zhang, 2022: Linking the tropical Indian Ocean basin mode to the central-Pacific type of ENSO: Observations and CMIP5 reproduction. Climate Dyn., 60, 17051727, https://doi.org/10.1007/s00382-022-06387-x.

    • Search Google Scholar
    • Export Citation
  • Zhao, X., D. Yuan, and J. Wang, 2023: Sea level anomalies in the southeastern tropical Indian Ocean as a potential predictor of La Niña beyond one-year lead. Front. Mar. Sci., 10, 1141961, https://doi.org/10.3389/fmars.2023.1141961.

    • Search Google Scholar
    • Export Citation
  • Zheng, X.-T., S.-P. Xie, and Q. Liu, 2011: Response of the Indian Ocean basin mode and its capacitor effect to global warming. J. Climate, 24, 61466164, https://doi.org/10.1175/2011JCLI4169.1.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 448 448 20
Full Text Views 195 195 23
PDF Downloads 242 242 26