Abstract
The dominant interannual SST variability in the eastern equatorial Atlantic is referred to as the Atlantic Zonal Mode (AZM), which peaks in boreal summer impacts global weather patterns. The cold (warm) phase of this ocean-atmospheric coupled phenomenon enhances (weakens) the intensity of the Indian Summer Monsoon Rainfall (ISMR). Observational studies show a strengthening relationship between AZM and ISMR in recent decades, providing a predictive signal for the ISMR. However, a suite of Coupled Model Intercomparison Project Phase 6 (CMIP6) model simulations in the highest emission scenario (SSP58.5) show a weakening relationship between ISMR and AZM in the future (2050–2099). The strengthening of atmospheric thermal stability over the tropical Atlantic in the warming scenario weakens the associated convection over the eastern equatorial Atlantic in response to the warm phase of AZM. This leads to weakening velocity potential response over the Indian subcontinent, resulting in a weak AZM–ISMR relationship. There is no convincing evidence to indicate that either the tropical Atlantic SST bias or the AZM–ISMR teleconnection bias plays a crucial role in the potential weakening of this relationship. These results imply that ISMR prediction will become more challenging in a warming scenario as one of the major external boundary forces that influence monsoon weakens.
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References
Ajayamohan RS, Goswami BN (2000) A common spatial mode for intra-seasonal and inter-annual variation and predictability of the Indian summer monsoon. Curr Sci 79(8):1106–1111. http://repository.ias.ac.in/93641/
Allen RJ, Sherwood SC (2008) Warming maximum in the tropical upper troposphere deduced from thermal winds. Nat Geosci 1(6):399–403. https://doi.org/10.1038/ngeo208
Ashok K, Guan Z, Yamagata T (2001) Impact of the Indian ocean dipole on the relationship between the Indian monsoon rainfall and ENSO. Geophys Res Lett 28(23):4499–4502. https://doi.org/10.1029/2001GL013294
Azad S, Rajeevan M (2016) Possible shift in the ENSO-Indian monsoon rainfall relationship under future global warming. Sci Rep 6(20):145. https://doi.org/10.1038/srep20145
Bjerknes J (1969) Atmospheric teleconnections from the equatorial Pacific. Mon Weather Rev 97(3):163–172
Carton JA, Huang B (1994) Warm events in the tropical Atlantic. J Phys Oceanogr 24(5):888–903
Chang CY, Carton JA, Grodsky SA, Nigam S (2007) Seasonal climate of the tropical Atlantic sector in the NCAR community climate system model 3: error structure and probable causes of errors. J Clim 20(6):1053–1070. https://doi.org/10.1175/JCLI4047.1
Chattopadhyay R, Phani R, Sabeerali CT, Dhakate AR, Salunke KD, Mahapatra S, Rao AS, Goswami BN (2015) Influence of extratropical sea-surface temperature on the Indian summer monsoon: an unexplored source of seasonal predictability. Q J R Meteorol Soc 141(692):2760–2775. https://doi.org/10.1002/qj.2562
Ding H, Keenlyside NS, Latif M (2010) Equatorial Atlantic interannual variability: role of heat content. J Geophys Res 115(C9):C09,020. https://doi.org/10.1029/2010JC006304
Ding H, Keenlyside NS, Latif M (2012) Impact of the equatorial Atlantic on the El Niño southern oscillation. Clim Dyn 38(9–10):1965–1972. https://doi.org/10.1007/s00382-011-1097-y
Ding H, Greatbatch RJ, Latif M, Park W (2015a) The impact of sea surface temperature bias on equatorial Atlantic interannual variability in partially coupled model experiments. Geophys Res Lett 42(13):5540–5546. https://doi.org/10.1002/2015GL064799
Ding H, Keenlyside N, Latif M, Park W, Wahl S (2015b) The impact of mean state errors on equatorial Atlantic interannual variability in a climate model. J Geophys Res 120(2):1133–1151. https://doi.org/10.1002/2014JC010384
Eyring V, Bony S, Meehl GA, Senior CA, Stevens B, Stouffer RJ, Taylor KE (2016) Overview of the coupled model Intercomparison Project Phase 6 (CMIP6) experimental design and organization. Geosci Model Dev 9:1937–1958. https://doi.org/10.5194/gmd-9-1937-2016
Foltz GR, McPhaden MJ (2010) Interaction between the Atlantic meridional and niño modes. Geophys Res Lett. https://doi.org/10.1029/2010GL044001
Gadgil S, Gadgil S (2006) The Indian monsoon, gdp and agriculture. Econ Polit Wkly 41(47):4887–4895
Gill AE (1980) Some simple solutions for heat-induced tropical circulation. Q J R Meteorol Soc 106:447–462. https://doi.org/10.1002/qj.49710644905
Goswami BN, Ajayamohan RS (2001) Intraseasonal oscillations and interannual variability of the Indian summer monsoon. J Clim 14:1180–1198
Goswami BN, Ajayamohan RS (2001b) Intraseasonal oscillations and predictability of the Indian summer monsoon. Proc Indian Natl Sci Acad 67A(3):369–383
Ham YG, Kug JS, Park JY, Jin FF (2013) Sea surface temperature in the north tropical Atlantic as a trigger for El Niño/Southern oscillation events. Nat Geosci 6(2):112–116. https://doi.org/10.1038/ngeo1686
Jansen MF, Dommenget D, Keenlyside N (2009) Tropical atmosphere-ocean interactions in a conceptual framework. J Clim 22(3):550–567. https://doi.org/10.1175/2008JCLI2243.1
Jia F, Cai W, Wu L, Gan B, Wang G, Kucharski F, Chang P, Keenlyside N (2019) Weakening Atlantic Niño–Pacific connection under greenhouse warming. Sci Adv 5(8):eaax4111. https://doi.org/10.1126/sciadv.aax4111
Keenlyside NS, Latif M (2007) Understanding equatorial Atlantic interannual variability. J Clim 20(1):131–142. https://doi.org/10.1175/JCLI3992.1
Keenlyside NS, Ding H, Latif M (2013) Potential of equatorial Atlantic variability to enhance El Niño prediction. Geophys Res Lett 40(10):2278–2283. https://doi.org/10.1002/grl.50362
Krishnamurthy V, Shukla J (2007) Intraseasonal and seasonally persisting patterns of Indian monsoon. J Clim 20:3–20. https://doi.org/10.1175/JCLI3981.1
Kucharski F, Joshi MK (2017) Influence of tropical south Atlantic sea-surface temperatures on the Indian summer monsoon in CMIP5 models. Q J R Meteorol Soc 143(704):1351–1363. https://doi.org/10.1002/qj.3009
Kucharski F, Bracco A, Yoo J, Molteni F (2008) Atlantic forced component of the Indian monsoon interannual variability. Geophys Res Lett. https://doi.org/10.1029/2007GL033037
Li X, Ting M (2015) Recent and future changes in the Asian monsoon-ENSO relationship: Natural or forced? Geophys Res Lett 42(9):3502–3512. https://doi.org/10.1002/2015GL063557
Lorenz EN (1965) A study of the predictability of a 28-variable atmospheric model. Tellus 17(3):321–333. https://doi.org/10.3402/tellusa.v17i3.9076
Lorenz EN (1982) Atmospheric predictability experiments with a large numerical model. Tellus 34(6):505–513. https://doi.org/10.3402/tellusa.v3416.10836
Losada T, Rodríguez-Fonseca B, Polo I, Janicot S, Gervois S, Chauvin F, Ruti P (2010) Tropical response to the Atlantic Equatorial mode: AGCM multimodel approach. Clim Dyn 35(1):45–52. https://doi.org/10.1007/s00382-009-0624-6
Lübbecke JF, Böning CW, Keenlyside NS, Xie SP (2010) On the connection between benguela and equatorial atlantic niños and the role of the south atlantic anticyclone. J Geophys Res 115(C9):C09,015. https://doi.org/10.1029/2009JC005964
Mohino E, Losada T (2015) Impacts of the Atlantic Equatorial Mode in a warmer climate. Clim Dyn 45(7):2255–2271. https://doi.org/10.1007/s00382-015-2471-y
O’Neill BC, Claudia T, PvV Detlef, Veronika E, Pierre F, George H, Reto K, Elmar K, Jean-Francois L, Jason L, Gerald AM, Richard M, Keywan R, Benjamin MS (2016) The Scenario Model Intercomparison Project (ScenarioMIP) for CMIP6. Geosci Model Dev 9:3461–3482. https://doi.org/10.5194/gmd-9-3461-2016
O’Neill BC, Kriegler E, Ebi KL, Kemp-Benedict E, Riahi K, Rothman DS, van Ruijven BJ, van Vuuren DP, Birkmann J, Kok K et al (2017) The roads ahead: Narratives for shared socioeconomic pathways describing world futures in the 21st century. Glob Environ Change 42:169–180. https://doi.org/10.1016/j.gloenvcha.2015.01.004
Pai DS, Sridhar L, Rajeevan M, Sreejith OP, Satbhai N, Mukhopadhyay B (2014) Development of a new high spatial resolution (0.25\(\times\) 0.25) long period (1901–2010) daily gridded rainfall data set over India and its comparison with existing data sets over the region. Mausam 65(1):1–18
Philander SG (1990) El Niño, La Niña, and the Southern Oscillation. International geophysics Series, vol 46. Academic Press, New York, pp 1–293. https://doi.org/10.1016/S0074-6142(13)60002-9
Pottapinjara V, Girishkumar MS, Ravichandran M, Murtugudde R (2014) Influence of the Atlantic zonal mode on monsoon depressions in the Bay of Bengal during boreal summer. J Geophys Res 119(11):6456–6469. https://doi.org/10.1002/2014JD021494
Pottapinjara V, Girishkumar MS, Sivareddy S, Ravichandran M, Murtugudde R (2016) Relation between the upper ocean heat content in the equatorial Atlantic during boreal spring and the Indian monsoon rainfall during June-September. Int J Climatol 36(6):2469–2480. https://doi.org/10.1002/joc.4506
Rasmusson EM, Wallace JM (1983) Meteorological aspects of the ElNiño/Southern oscillation. Science 222:1195–1202. https://doi.org/10.1126/science.222.4629.1195
Rayner NA, Parker DE, Horton EB, Folland CK, Alexander LV, Rowell DP, Kent EC, Kaplan A (2003) Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century. J Geophys Res 108(D14):4407. https://doi.org/10.1029/2002JD002670
Richter I, Xie SP (2008) On the origin of equatorial Atlantic biases in coupled general circulation models. Clim Dyn 31(5):587–598. https://doi.org/10.1007/s00382-008-0364-z
Richter I, Xie SP, Behera SK, Doi T, Masumoto Y (2014) Equatorial Atlantic variability and its relation to mean state biases in CMIP5. Clim Dyn 42(1–2):171–188. https://doi.org/10.1007/s00382-012-1624-5
Rodríguez-Fonseca B, Polo I, García-Serrano J, Losada T, Mohino E, Mechoso CR, Kucharski F (2009) Are Atlantic Niños enhancing Pacific ENSO events in recent decades? Geophys Res Lett. https://doi.org/10.1029/2009GL040048
Roy I, Tedeschi RG, Collins M (2019) ENSO teleconnections to the Indian summer monsoon under changing climate. Int J Climatol 39(6):3031–3042. https://doi.org/10.1002/joc.5999
Sabeerali CT, Ajayamohan RS, Rao SA (2018) Loss of predictive skill of Indian summer monsoon rainfall in NCEP CFSv2 due to misrepresentation of Atlantic zonal mode. Clim Dyn. https://doi.org/10.1007/s00382-018-4390-1
Sabeerali CT, Ajayamohan RS, Bangalath HK, Chen N (2019) Atlantic zonal mode: An emerging source of Indian summer monsoon variability in a warming world. Geophys Res Lett 46(8):4460–4467. https://doi.org/10.1029/2019GL082379
Saji NH, Goswami BN, Vinayachandran P, Yamagata T (1999) A dipole mode in the tropical Indian ocean. Nature 401:360–363. https://doi.org/10.1038/43854
Sharmila S, Joseph S, Sahai A, Abhilash S, Chattopadhyay R (2015) Future projection of Indian summer monsoon variability under climate change scenario: An assessment from CMIP5 climate models. Glob Planet Change 124:62–78. https://doi.org/10.1016/j.gloplacha.2014.11.004
Shukla J (1987) Interannual variability of monsoon. In: Fein JS, Stephens PL (eds) Monsoons. Wiley and Sons, New York, pp 399–464
Stockdale TN, Balmaseda MA, Vidard A (2006) Tropical Atlantic SST prediction with coupled ocean-atmosphere GCMs. J Clim 19(23):6047–6061. https://doi.org/10.1175/JCLI3947.1
Tozuka T, Doi T, Miyasaka T, Keenlyside N, Yamagata T (2011) Key factors in simulating the equatorial Atlantic zonal sea surface temperature gradient in a coupled general circulation model. J Geophys Res. https://doi.org/10.1029/2010JC006717
Wahl S, Latif M, Park W, Keenlyside N (2011) On the tropical atlantic sst warm bias in the kiel climate model. Clim Dyn 36(5–6):891–906. https://doi.org/10.1007/s00382-009-0690-9
Wang C, Kucharski F, Barimalala R, Bracco A (2009) Teleconnections of the tropical atlantic to the tropical Indian and Pacific oceans: a review of recent findings. Meteorol Zeitschrift 18(4):445–454. https://doi.org/10.1127/0941-2948/2009/0394
Wang C, Zhang L, Lee SK, Wu L, Mechoso CR (2014) A global perspective on CMIP5 climate model biases. Nat Clim Change 4(3):201–205. https://doi.org/10.1007/s00382-009-0690-9
Yadav RK, Srinivas G, Chowdary JS (2018) Atlantic Niño modulation of the Indian summer monsoon through Asian jet. NPJ Clim Atmos Sci 1(1):1–11. https://doi.org/10.1038/s41612-018-0029-5
Yang Y, Xie SP, Wu L, Kosaka Y, Li J (2018) ENSO forced and local variability of north tropical Atlantic SST: model simulations and biases. Clim Dynam 51(11–12):4511–4524. https://doi.org/10.1007/s00382-017-3679-9
Yeh SW, Cai W, Min SK, McPhaden MJ, Dommenget D, Dewitte B, Collins M, Ashok K, An SI, Yim BY et al (2018) ENSO atmospheric teleconnections and their response to greenhouse gas forcing. Rev Geophys 56(1):185–206. https://doi.org/10.1002/2017RG000568
Zebiak SE (1993) Air-sea interaction in the equatorial Atlantic region. J Clim 6(8):1567–1586
Zheng XT, Xie SP, Du Y, Liu L, Huang G, Liu Q (2013) Indian ocean dipole response to global warming in the CMIP5 multimodel ensemble. J Clim 26(16):6067–6080. https://doi.org/10.1175/JCLI-D-12-00638.1
Acknowledgements
This research is fully funded by the Center for Prototype Climate Modeling, New York University Abu Dhabi (NYUAD) through the Research Institute Grant. The authors declare no competing financial interests. All datasets used in this study are publicly available. India Meteorological Department (IMD) high resolution gridded rainfall data (0.25\(^{\circ }\)X 0.25\(^{\circ }\)) are available to download from the IMD Pune website (http://www.imdpune.gov.in/Clim_Pred_LRF_New/Grided_Data_Download.html). The HadISST used in this study are available on https://www.metoffice.gov.uk/hadobs/hadisst/. We thank the Editor and two anonymous reviewers for their constructive comments. The authors thank the World Climate Research Programme's Working Group on Coupled Modelling, which is coordinated and promoted CMIP6. We also acknowledge the climate modeling groups (listed in Table 1) for producing and making available their model output, the Earth System Grid Federation (ESGF) for archiving the data and providing access, and the multiple funding agencies who support CMIP6 and ESGF.
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Sabeerali, C.T., Ajayamohan, R.S. & Praveen, V. Atlantic zonal mode-monsoon teleconnection in a warming scenario. Clim Dyn 58, 1829–1843 (2022). https://doi.org/10.1007/s00382-021-05996-2
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DOI: https://doi.org/10.1007/s00382-021-05996-2