Editorial Type:
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Article Type:
Research Article

Weakened Impact of the Developing El Niño on Tropical Indian Ocean Climate Variability under Global Warming

Chao He Institute for Environmental and Climate Research, Jinan University, Guangzhou, and Key Laboratory of Meteorological Disaster of Ministry of Education, Nanjing University of Information Science and Technology, Nanjing, China

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https://orcid.org/0000-0001-5842-9617
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Yuhao Wang Key Laboratory of Meteorological Disaster of Ministry of Education, Nanjing University of Information Science and Technology, Nanjing, China

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Tim Li Key Laboratory of Meteorological Disaster of Ministry of Education, Nanjing University of Information Science and Technology, Nanjing, China, and International Pacific Research Center, and Department of Atmospheric Sciences, University of Hawai‘i at Mānoa, Honolulu, Hawaii

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Print Publication:
01 Nov 2019
DOI:
https://doi.org/10.1175/JCLI-D-19-0165.1
Page(s):
7265–7279
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Abstract

El Niño induces an anomalous easterly wind along the equator and a pair of anomalous anticyclones straddling the equator over the tropical Indian Ocean (TIO) during the autumn of its developing phase. Based on 30 coupled models participating in CMIP5, these atmospheric circulation anomalies over TIO are substantially weakened by about 12%–13% K−1 under global warming scenarios, associated with a weakened zonal gradient of the sea surface temperature (SST) anomaly. The mechanism for the response is investigated based on a hierarchy of model experiments. Based on stand-alone atmospheric model experiments under uniform and patterned mean-state SST warming, the atmospheric circulation anomaly over TIO during the autumn of the developing El Niño is also substantially weakened by about 8% K−1 even if the interannual variability of SST remains exactly unchanged, suggesting that the primary cause resides in the atmosphere rather than the SST anomaly. The tropospheric static stability is robustly enhanced under global warming, and experiments performed by a linear baroclinic model show that a much weaker atmospheric circulation anomaly over TIO is stimulated by an unchanged diabatic heating anomaly under a more stable atmosphere. The weakened atmospheric circulation anomaly due to enhanced static stability weakens the zonal gradient of the SST anomaly within TIO through local air–sea interaction, and it acts to further weaken the atmospheric circulation anomaly. The enhanced static stability of the troposphere is probably the primary cause and the air–sea interaction within TIO is a secondary cause for the weakened impact of the developing El Niño on atmospheric circulation variability over TIO.

Supplemental information related to this paper is available at the Journals Online website: https://doi.org/10.1175/JCLI-D-19-0165.s1.

© 2019 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Dr. Tim Li, timli@hawaii.edu

Abstract

El Niño induces an anomalous easterly wind along the equator and a pair of anomalous anticyclones straddling the equator over the tropical Indian Ocean (TIO) during the autumn of its developing phase. Based on 30 coupled models participating in CMIP5, these atmospheric circulation anomalies over TIO are substantially weakened by about 12%–13% K−1 under global warming scenarios, associated with a weakened zonal gradient of the sea surface temperature (SST) anomaly. The mechanism for the response is investigated based on a hierarchy of model experiments. Based on stand-alone atmospheric model experiments under uniform and patterned mean-state SST warming, the atmospheric circulation anomaly over TIO during the autumn of the developing El Niño is also substantially weakened by about 8% K−1 even if the interannual variability of SST remains exactly unchanged, suggesting that the primary cause resides in the atmosphere rather than the SST anomaly. The tropospheric static stability is robustly enhanced under global warming, and experiments performed by a linear baroclinic model show that a much weaker atmospheric circulation anomaly over TIO is stimulated by an unchanged diabatic heating anomaly under a more stable atmosphere. The weakened atmospheric circulation anomaly due to enhanced static stability weakens the zonal gradient of the SST anomaly within TIO through local air–sea interaction, and it acts to further weaken the atmospheric circulation anomaly. The enhanced static stability of the troposphere is probably the primary cause and the air–sea interaction within TIO is a secondary cause for the weakened impact of the developing El Niño on atmospheric circulation variability over TIO.

Supplemental information related to this paper is available at the Journals Online website: https://doi.org/10.1175/JCLI-D-19-0165.s1.

© 2019 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Dr. Tim Li, timli@hawaii.edu

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  • Adler, R. F., and Coauthors, 2003: The Version-2 Global Precipitation Climatology Project (GPCP) monthly precipitation analysis (1979–present). J. Hydrometeor., 4, 1147–1167, https://doi.org/10.1175/1525-7541(2003)004<1147:TVGPCP>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Cai, W., and Coauthors, 2014: Increasing frequency of extreme El Niño events due to greenhouse warming. Nat. Climate Change, 4, 111–116, https://doi.org/10.1038/nclimate2100.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Cai, W., and Coauthors, 2015: Increased frequency of extreme La Niña events under greenhouse warming. Nat. Climate Change, 5, 132–137, https://doi.org/10.1038/nclimate2492.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Cash, B. A., and Coauthors, 2017: Sampling variability and the changing ENSO–monsoon relationship. Climate Dyn., 48, 4071–4079, https://doi.org/10.1007/s00382-016-3320-3.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Chen, L., T. Li, and Y. Yu, 2015: Causes of strengthening and weakening of ENSO amplitude under global warming in four CMIP5 models. J. Climate, 28, 3250–3274, https://doi.org/10.1175/JCLI-D-14-00439.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Chen, L., T. Li, Y. Yu, and S. K. Behera, 2017: A possible explanation for the divergent projection of ENSO amplitude change under global warming. Climate Dyn., 49, 3799–3811, https://doi.org/10.1007/s00382-017-3544-x.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Cherchi, A., and A. Navarra, 2013: Influence of ENSO and of the Indian Ocean dipole on the Indian summer monsoon variability. Climate Dyn., 41, 81–103, https://doi.org/10.1007/s00382-012-1602-y.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Collins, M., and Coauthors, 2010: The impact of global warming on the tropical Pacific Ocean and El Niño. Nat. Geosci., 3, 391–397, https://doi.org/10.1038/ngeo868.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Coumou, D., J. Lehmann, and J. Beckmann, 2015: The weakening summer circulation in the Northern Hemisphere mid-latitudes. Science, 348, 324–327, https://doi.org/10.1126/science.1261768.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Deser, C., A. Phillips, V. Bourdette, and H. Teng, 2012: Uncertainty in climate change projections: the role of internal variability. Climate Dyn., 38, 527–546, https://doi.org/10.1007/s00382-010-0977-x.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Eyring, V., and Coauthors, 2019: Taking climate model evaluation to the next level. Nat. Climate Change, 9, 102–110, https://doi.org/10.1038/s41558-018-0355-y.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Fan, L., Q. Liu, C. Wang, and F. Guo, 2017: Indian Ocean dipole modes associated with different types of ENSO development. J. Climate, 30, 2233–2249, https://doi.org/10.1175/JCLI-D-16-0426.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Feng, R., and W. Duan, 2018: The role of initial signals in the tropical Pacific Ocean in predictions of negative Indian Ocean dipole events. Sci. China Earth Sci., 61, 1832–1843, https://doi.org/10.1007/s11430-018-9296-2.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Gates, W. L., and Coauthors, 1999: An overview of the results of the Atmospheric Model Intercomparison Project (AMIP I). Bull. Amer. Meteor. Soc., 80, 29–55, https://doi.org/10.1175/1520-0477(1999)080<0029:AOOTRO>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Gill, A. E., 1980: Some simple solutions for heat-induced tropical circulation. Quart. J. Roy. Meteor. Soc., 106, 447–462, https://doi.org/10.1002/qj.49710644905.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Gleckler, P. J., K. E. Taylor, and C. Doutriaux, 2008: Performance metrics for climate models. J. Geophys. Res., 113, D06104, https://doi.org/10.1029/2007JD008972.

    • Search Google Scholar
    • Export Citation

  • Ham, Y.-G., J.-Y. Choi, and J.-S. Kug, 2017: The weakening of the ENSO–Indian Ocean dipole (IOD) coupling strength in recent decades. Climate Dyn., 49, 249–261, https://doi.org/10.1007/s00382-016-3339-5.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • He, C., and T. Li, 2019: Does global warming amplify interannual climate variability? Climate Dyn., 52, 2667–2684, https://doi.org/10.1007/s00382-018-4286-0.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • He, C., B. Wu, L. Zou, and T. Zhou, 2017: Responses of the summertime subtropical anticyclones to global warming. J. Climate, 30, 6465–6479, https://doi.org/10.1175/JCLI-D-16-0529.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • He, C., A. Lin, D. Gu, C. Li, B. Zheng, B. Wu, and T. Zhou, 2018: Using eddy geopotential height to measure the western North Pacific subtropical high in a warming climate. Theor. Appl. Climatol., 131, 681–691, https://doi.org/10.1007/s00704-016-2001-9.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • He, C., T. Zhou, and T. Li, 2019: Weakened anomalous western North Pacific anticyclone during an El Niño–decaying summer under a warmer climate: Dominant role of the weakened impact of the tropical Indian Ocean on the atmosphere. J. Climate, 32, 213–230, https://doi.org/10.1175/JCLI-D-18-0033.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Hu, H., Q. Wu, and Z. Wu, 2018: Influences of two types of El Niño event on the northwest Pacific and tropical Indian Ocean SST anomalies. J. Oceanol. Limnol., 36, 33–47, https://doi.org/10.1007/s00343-018-6296-5.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Huang, B., and Coauthors, 2017: Extended Reconstructed Sea Surface Temperature, version 5 (ERSSTv5): Upgrades, validations, and intercomparisons. J. Climate, 30, 8179–8205, https://doi.org/10.1175/JCLI-D-16-0836.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Hui, C., and X.-T. Zheng, 2018: Uncertainty in Indian Ocean dipole response to global warming: The role of internal variability. Climate Dyn., 51, 3597–3611, https://doi.org/10.1007/s00382-018-4098-2.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Izumo, T., M. Lengaigne, J. Vialard, J.-J. Luo, T. Yamagata, and G. Madec, 2014: Influence of Indian Ocean dipole and Pacific recharge on following year’s El Niño: Interdecadal robustness. Climate Dyn., 42, 291–310, https://doi.org/10.1007/S00382-012-1628-1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Jiang, W., G. Huang, P. Huang, and K. Hu, 2018: Weakening of northwest Pacific anticyclone anomalies during post–El Niño summers under global warming. J. Climate, 31, 3539–3555, https://doi.org/10.1175/JCLI-D-17-0613.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Kalnay, E., and Coauthors, 1996: The NCEP/NCAR 40-Year Reanalysis Project. Bull. Amer. Meteor. Soc., 77, 437–471, https://doi.org/10.1175/1520-0477(1996)077<0437:TNYRP>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Knutson, T. R., and S. Manabe, 1995: Time-mean response over the tropical Pacific to Increased C02 in a coupled ocean–atmosphere model. J. Climate, 8, 2181–2199, https://doi.org/10.1175/1520-0442(1995)008<2181:TMROTT>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Kripalani, R. H., J. H. Oh, and H. S. Chaudhari, 2010: Delayed influence of the Indian Ocean dipole mode on the East Asia–west Pacific monsoon: Possible mechanism. Int. J. Climatol., 30, 197–209, https://doi.org/10.1002/JOC.1890.

    • Search Google Scholar
    • Export Citation

  • Kug, J.-S., T. Li, S.-I. An, I.-S. Kang, J.-J. Luo, S. Masson, and T. Yamagata, 2006: Role of the ENSO–Indian Ocean coupling on ENSO variability in a coupled GCM. Geophys. Res. Lett., 33, L09710, https://doi.org/10.1029/2005GL024916.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Kumar, K. K., B. Rajagopalan, and M. A. Cane, 1999: On the weakening relationship between the Indian monsoon and ENSO. Science, 284, 2156–2159, https://doi.org/10.1126/science.284.5423.2156.

    • Crossref
    • 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, 3–20, https://doi.org/10.1175/1520-0442(2003)016<0003:AOVITI>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • 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, 2119–2135, https://doi.org/10.1175/1520-0469(2003)060<2119:ATFTIO>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Li, T., L. Zhang, and H. Murakami, 2015: Strengthening of the Walker circulation under global warming in an aqua-planet general circulation model simulation. Adv. Atmos. Sci., 32, 1473–1480, https://doi.org/10.1007/s00376-015-5033-7.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Liu, L., G. Yang, X. Zhao, L. Feng, G. Han, Y. Wu, and W. Yu, 2017: Why was the Indian Ocean dipole weak in the context of the extreme El Niño in 2015? J. Climate, 30, 4755–4761, https://doi.org/10.1175/JCLI-D-16-0281.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Lu, J., K. Sakaguchi, Q. Yang, L. R. Leung, G. Chen, C. Zhao, E. Swenson, and Z. J. Hou, 2017: Examining the hydrological variations in an aquaplanet world using wave activity transformation. J. Climate, 30, 2559–2576, https://doi.org/10.1175/JCLI-D-16-0561.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Luo, J. J., R. C. Zhang, S. K. Behera, Y. Masumoto, F. F. Jin, R. Lukas, and T. Yamagata, 2010: Interaction between El Niño and extreme Indian Ocean dipole. J. Climate, 23, 726–742, https://doi.org/10.1175/2009JCLI3104.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Ma, J., S.-P. Xie, and Y. Kosaka, 2012: Mechanisms for tropical tropospheric circulation change in response to global warming. J. Climate, 25, 2979–2994, https://doi.org/10.1175/JCLI-D-11-00048.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Maher, N., D. Matei, S. Milinski, and J. Marotzke, 2018: ENSO change in climate projections: Forced response or internal variability? Geophys. Res. Lett., 45, 11 390–11 398, https://doi.org/10.1029/2018GL079764.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Ni, Y., and P.-C. Hsu, 2018: Inter-annual variability of global monsoon precipitation in present-day and future warming scenarios based on 33 Coupled Model Intercomparison Project Phase 5 models. Int. J. Climatol., 38, 4875–4890, https://doi.org/10.1002/joc.5704.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Power, S. B., F. Delage, R. Colman, and A. Moise, 2012: Consensus on twenty-first-century rainfall projections in climate models more widespread than previously thought. J. Climate, 25, 3792–3809, https://doi.org/10.1175/JCLI-D-11-00354.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Power, S. B., F. Delage, C. Chung, G. Kociuba, and K. Keay, 2013: Robust twenty-first-century projections of El Nino and related precipitation variability. Nature, 502, 541–545, https://doi.org/10.1038/nature12580.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Qu, X., and G. Huang, 2016: The global warming–induced South Asian high change and its uncertainty. J. Climate, 29, 2259–2273, https://doi.org/10.1175/JCLI-D-15-0638.1.

    • Crossref
    • 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, 360–363, https://doi.org/10.1038/43854.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Schneider, T., P. A. O’Gorman, and X. J. Levine, 2010: Water vapor and the dynamics of climate changes. Rev. Geophys., 48, RG3001, https://doi.org/10.1029/2009RG000302.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Taylor, K. E., R. J. Stouffer, and G. A. Meehl, 2012: An overview of CMIP5 and the experiment design. Bull. Amer. Meteor. Soc., 93, 485–498, https://doi.org/10.1175/BAMS-D-11-00094.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Ummenhofer, C. C., A. Sen Gupta, Y. Li, A. S. Taschetto, and M. H. England, 2011: Multi-decadal modulation of the El Niño–Indian monsoon relationship by Indian Ocean variability. Environ. Res. Lett., 6, 034006, https://doi.org/10.1088/1748-9326/6/3/034006.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Van Vuuren, D., and Coauthors, 2011: The representative concentration pathways: An overview. Climatic Change, 109, 5–31, https://doi.org/10.1007/s10584-011-0148-z.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Wang, L., A. Deng, and R. Huang, 2019: Wintertime internal climate variability over Eurasia in the CESM large ensemble. Climate Dyn., 52, 6735–6748, https://doi.org/10.1007/S00382-018-4542-3.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Wang, X., and C. Wang, 2014: Different impacts of various El Niño events on the Indian Ocean dipole. Climate Dyn., 42, 991–1005, https://doi.org/10.1007/s00382-013-1711-2.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Watanabe, M., and M. Kimoto, 2000: Atmosphere–ocean thermal coupling in the North Atlantic: A positive feedback. Quart. J. Roy. Meteor. Soc., 126, 3343–3369, https://doi.org/10.1002/qj.49712657017.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Xavier, P. K., C. Marzin, and B. N. Goswami, 2007: An objective definition of the Indian summer monsoon season and a new perspective on the ENSO–monsoon relationship. Quart. J. Roy. Meteor. Soc., 133, 749–764, https://doi.org/10.1002/qj.45.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Xie, S.-P., and Coauthors, 2015: Towards predictive understanding of regional climate change. Nat. Climate Change, 5, 921–930, https://doi.org/10.1038/nclimate2689.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Xu, K., C. Zhu, and W. Wang, 2016: The cooperative impacts of the El Niño–Southern Oscillation and the Indian Ocean dipole on the interannual variability of autumn rainfall in China. Int. J. Climatol., 36, 1987–1999, https://doi.org/10.1002/joc.4475.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • 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, Geophys. Monogr., Vol. 147, Amer. Geophys. Union, 189–211, https://doi.org/10.1029/147GM12.

    • Crossref
    • Export Citation

  • Yanai, M., and T. Tomita, 1998: Seasonal and interannual variability of atmospheric heat sources and moisture sinks as determined from NCEP–NCAR reanalysis. J. Climate, 11, 463–482, https://doi.org/10.1175/1520-0442(1998)011<0463:SAIVOA>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Yang, S., Z. Li, J.-Y. Yu, X. Hu, W. Dong, and S. He, 2018: El Niño–Southern Oscillation and its impact in the changing climate. Natl. Sci. Rev., 5, 840–857, https://doi.org/10.1093/nsr/nwy046.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Yuan, Y., and C. Li, 2008: Decadal variability of the IOD-ENSO relationship. Chin. Sci. Bull., 53, 1745–1752, https://doi.org/10.1007/S11434-008-0196-6.

    • Search Google Scholar
    • Export Citation

  • Zheng, X.-T., S.-P. Xie, Y. Du, L. Liu, G. Huang, and Q. Liu, 2013: Indian Ocean dipole response to global warming in the CMIP5 multimodel ensemble. J. Climate, 26, 6067–6080, https://doi.org/10.1175/JCLI-D-12-00638.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Zhou, Z.-Q., S.-P. Xie, X.-T. Zheng, Q. Liu, and H. Wang, 2014: Global warming–induced changes in El Niño teleconnections over the North Pacific and North America. J. Climate, 27, 9050–9064, https://doi.org/10.1175/JCLI-D-14-00254.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Zhou, Z.-Q., S.-P. Xie, G. J. Zhang, and W. Zhou, 2018: Evaluating AMIP skill in simulating interannual variability over the Indo–western Pacific. J. Climate, 31, 2253–2265, https://doi.org/10.1175/JCLI-D-17-0123.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
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