Abstract
The impacts of tropical interbasin interaction (TBI) on the characteristics and predictability of sea surface temperature (SST) in the tropics are assessed with a linear inverse modelling (LIM) framework that uses SST and sea surface height anomalies in the tropical Pacific (PO), Atlantic (AO), and Indian Ocean (IO). The TBI pathways are shown to be successfully isolated in stochastically-forced simulations that modify off-diagonal elements of the linear operators. The removal of TBI leads to a substantial increase in the amplitude of El Niño-Southern Oscillation (ENSO) and related variability. Partial decoupling experiments that eliminate specific coupling components reveal that PO-IO interaction is the dominant contributor, whereas PO-AO and AO-IO interactions play a minor role. A series of retrospective forecast experiments with different operators shows that decoupling leads to a substantial decrease in ENSO prediction skill especially at longer lead times. The relative contributions of individual pathways to forecast skill are generally consistent with the results from the stochastically-forced experiments. Qualitatively similar results are obtained from an additional set of forecast experiments that partially apply initial conditions over specific basins, but several important differences were also found due to differences in the representations of each TBI pathway. Finally, the cause of contrasting SST anomalies over the AO after the extreme 1982/83 and 1997/98 El Niño events is explored using LIM forecast experiments to demonstrate the strength and flexibility of our LIM-based approach.
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Data Availability
The ECMWF ocean reanalysis ORAS4 and ORAS3 data were obtained from (http://apdrc.soest.hawaii.edu/datadoc/ecmwf_oras4.php) and (http://apdrc.soest.hawaii.edu/datadoc/ecmwf_oras3.php), respectively. Source codes and outputs from LIM used in this study are available from the corresponding author (S.K.) upon request.
References
Alexander MA, Matrosova L, Penland C et al (2008) Forecasting Pacific SSTs: Linear inverse model predictions of the PDO. J Clim 21:385–402. https://doi.org/10.1175/2007JCLI1849.1
Alexander MA, Shin S, Battisti DS (2022) The Influence of the Trend, Basin Interactions, and Ocean Dynamics on Tropical Ocean Prediction. Geophys Res Lett 49. https://doi.org/10.1029/2021GL096120
Annamalai H, Murtugudde R, Potemra J et al (2003) Coupled dynamics over the Indian Ocean: spring initiation of the Zonal Mode. Deep Sea Res Part II Top Stud Oceanogr 50:2305–2330. https://doi.org/10.1016/S0967-0645(03)00058-4
Annamalai H, Xie S-P, McCreary JP, Murtugudde R (2005) Impact of Indian Ocean Sea surface temperature on developing El Niño. J Clim 18:302–320. https://doi.org/10.1175/JCLI-3268.1
Balmaseda MA, Mogensen K, Weaver AT (2013) Evaluation of the ECMWF ocean reanalysis system ORAS4. Q J R Meteorol Soc 139:1132–1161. https://doi.org/10.1002/qj.2063
Balmaseda MA, Vidard A, Anderson DLT (2008) The ECMWF ocean analysis system: ORA-S3. Mon Weather Rev 136:3018–3034. https://doi.org/10.1175/2008MWR2433.1
Barnston AG, Tippett MK, L’Heureux ML et al (2012) Skill of Real-Time Seasonal ENSO Model Predictions during 2002–11: Is Our Capability Increasing? Bull Am Meteorol Soc 93:631–651. https://doi.org/10.1175/BAMS-D-11-00111.1
Cai W, Wu L, Lengaigne M et al (2019) Pantropical climate interactions. Sci (80-) 363:eaav4236. https://doi.org/10.1126/science.aav4236
Carton JA, Giese BS (2008) A reanalysis of ocean climate using Simple Ocean Data Assimilation (SODA). Mon Weather Rev 136:2999–3017. https://doi.org/10.1175/2007MWR1978.1
Chang P, Fang Y, Saravanan R et al (2006a) The cause of the fragile relationship between the Pacific El Niño and the Atlantic Niño. Nature 443:324–328. https://doi.org/10.1038/nature05053
Chang P, Ji L, Li H (1997) A decadal climate variation in the tropical Atlantic Ocean from thermodynamic air-sea interactions. Nature 385:516–518. https://doi.org/10.1038/385516a0
Chang P, Yamagata T, Schopf PS et al (2006b) Climate fluctuations of tropical coupled systems - The role of ocean dynamics. J Clim 19:5122–5174. https://doi.org/10.1175/JCLI3903.1
Chikamoto Y, Johnson ZF, Wang SYS et al (2020) El Niño–Southern Oscillation Evolution Modulated by Atlantic Forcing. J Geophys Res Ocean 125:1–15. https://doi.org/10.1029/2020JC016318
Dayan H, Vialard J, Izumo T, Lengaigne M (2014) Does sea surface temperature outside the tropical Pacific contribute to enhanced ENSO. predictability? Clim Dyn 43:1311–1325. https://doi.org/10.1007/s00382-013-1946-y
Ding H, Keenlyside NS, Latif M (2012) Impact of the Equatorial Atlantic on the El Niño Southern Oscillation. Clim Dyn. https://doi.org/10.1007/s00382-011-1097-y
Dommenget D, Semenov V, Latif M (2006) Impacts of the tropical Indian and Atlantic Oceans on ENSO. Geophys Res Lett 33:18–21. https://doi.org/10.1029/2006GL025871
Dommenget D, Yu Y (2017) The effects of remote SST forcings on ENSO dynamics, variability and diversity. Clim Dyn 49:2605–2624. https://doi.org/10.1007/s00382-016-3472-1
Enfield DB, Mayer DA (1997) Tropical atlantic sea surface temperature variability and its relation to El Niño-Southern Oscillation. J Geophys Res C Ocean 102:929–945. https://doi.org/10.1029/96jc03296
Ewald B, Penland C (2009) Numerical Generation of Stochastic Differential Equations in Climate Models. In: Handbook of Numerical Analysis
Exarchou E, Ortega P, Rodríguez-Fonseca B et al (2021) Impact of equatorial Atlantic variability on ENSO predictive skill. Nat Commun 12:1612. https://doi.org/10.1038/s41467-021-21857-2
Frauen C, Dommenget D (2012) Influences of the tropical Indian and Atlantic Oceans on the predictability of ENSO. Geophys Res Lett 39:2–7. https://doi.org/10.1029/2011GL050520
Gebbie G, Eisenman I, Wittenberg A, Tziperman E (2007) Modulation of westerly wind bursts by sea surface temperature: A semistochastic feedback for ENSO. J Atmos Sci 64:3281–3295. https://doi.org/10.1175/JAS4029.1
Giannini A, Saravanan R, Chang P (2004) The preconditioning role of Tropical Atlantic Variability in the development of the ENSO teleconnection: implications for the prediction of Nordeste rainfall. Clim Dyn 22:839–855. https://doi.org/10.1007/s00382-004-0420-2
Ham Y-G, Kug J-S, Park J-Y (2013a) Two distinct roles of Atlantic SSTs in ENSO variability: North Tropical Atlantic SST and Atlantic Niño. Geophys Res Lett 40:4012–4017. https://doi.org/10.1002/grl.50729
Ham Y-G, Kug J-S, Park J-Y, Jin F-F (2013b) Sea surface temperature in the north tropical Atlantic as a trigger for El Niño/Southern Oscillation events. Nat Geosci 6:112–116. https://doi.org/10.1038/ngeo1686
Izumo T, Vialard J, Lengaigne M et al (2010) Influence of the state of the Indian Ocean Dipole on the following year’s El Niño. Nat Geosci 3:168–172. https://doi.org/10.1038/ngeo760
Jansen MF, Dommenget D, Keenlyside N (2009) Tropical atmosphere - Ocean interactions in a conceptual framework. J Clim 22:550–567. https://doi.org/10.1175/2008JCLI2243.1
Jourdain NC, Lengaigne M, Vialard J et al (2016) Further Insights on the Influence of the Indian Ocean Dipole on the Following Year’s ENSO from Observations and CMIP5 Models. J Clim 29:637–658. https://doi.org/10.1175/JCLI-D-15-0481.1
Kajtar JB, Santoso A, England MH, Cai W (2017) Tropical climate variability: interactions across the Pacific, Indian, and Atlantic Oceans. Clim Dyn 48:2173–2190. https://doi.org/10.1007/s00382-016-3199-z
Keenlyside NS, Ding H, Latif M (2013) Potential of equatorial Atlantic variability to enhance El Niño prediction. Geophys Res Lett 40:2278–2283. https://doi.org/10.1002/grl.50362
Kido S, Richter I, Tozuka T, Chang P (2021) Using linear inverse modelling to assess tropical interbasin interaction. CLIVAR Exch 80:31–35. https://doi.org/10.36071/clivar.80.2021
Kosaka Y, Xie SP (2013) Recent global-warming hiatus tied to equatorial Pacific surface cooling. Nature 501. https://doi.org/10.1038/nature12534
Kug J-S, Kang I-S (2006) Interactive Feedback between ENSO and the Indian Ocean. J Clim 19:1784–1801. https://doi.org/10.1175/JCLI3660.1
Latif M, Anderson DLT, Barnett TP et al (1998) A review of the predictability and prediction of ENSO. J Geophys Res Ocean 103:14375–14393. https://doi.org/10.1029/97JC03413
Levine A, Jin FF, McPhaden MJ (2016) Extreme noise–extreme El Niño: How state-dependent noise forcing creates El Niño–La Niña asymmetry. J Clim 29:5483–5499. https://doi.org/10.1175/JCLI-D-16-0091.1
Li C, Dommenget D, McGregor S (2020) Trans-basin Atlantic-Pacific connections further weakened by common model Pacific mean SST biases. Nat Commun 11:5677. https://doi.org/10.1038/s41467-020-19338-z
Li X, Xie SP, Gille ST, Yoo C (2016) Atlantic-induced pan-tropical climate change over the past three decades. Nat Clim Chang 6:275–279. https://doi.org/10.1038/nclimate2840
Liao H, Wang C (2021) Sea Surface Temperature Anomalies in the Western Indian Ocean as a Trigger for Atlantic Niño Events. Geophys Res Lett 48. https://doi.org/10.1029/2021GL092489
Lübbecke JF, McPhaden MJ (2012) On the inconsistent relationship between Pacific and Atlantic Niños. J Clim 25:4294–4303. https://doi.org/10.1175/JCLI-D-11-00553.1
Luo J-J, Wang G, Dommenget D (2018) May common model biases reduce CMIP5’s ability to simulate the recent Pacific La Niña-like cooling? Clim Dyn 50:1335–1351. https://doi.org/10.1007/s00382-017-3688-8
Luo JJ, Liu G, Hendon H et al (2017) Inter-basin sources for two-year predictability of the multi-year la Niña event in 2010–2012. Sci Rep 7:1–7. https://doi.org/10.1038/s41598-017-01479-9
Luo JJ, Masson S, Behera SK, Yamagata T (2008) Extended ENSO predictions using a fully coupled ocean-atmosphere model. J Clim 21. https://doi.org/10.1175/2007JCLI1412.1
Luo JJ, Zhang R, Behera SK et al (2010) Interaction between El Niño and extreme Indian Ocean dipole. J Clim 23:726–742. https://doi.org/10.1175/2009JCLI3104.1
Martín-Rey M, Rodríguez-Fonseca B, Polo I (2015) Atlantic opportunities for ENSO prediction. Geophys Res Lett 42:6802–6810. https://doi.org/10.1002/2015GL065062
Martín-Rey M, Rodríguez-Fonseca B, Polo I, Kucharski F (2014) On the Atlantic–Pacific Niños connection: a multidecadal modulated mode. Clim Dyn 43:3163–3178. https://doi.org/10.1007/s00382-014-2305-3
Martinez-Villalobos C, Vimont DJ, Penland C et al (2018) Calculating state-dependent noise in a linear inverse model framework. J Atmos Sci 75:479–496. https://doi.org/10.1175/JAS-D-17-0235.1
McGregor S, Stuecker MF, Kajtar JB et al (2018) Model tropical Atlantic biases underpin diminished Pacific decadal variability. Nat Clim Chang 8:493–498. https://doi.org/10.1038/s41558-018-0163-4
McPhaden MJ, Santoso A, Cai W (2020) Introduction to El Niño Southern Oscillation in a Changing Climate. In: El Niño Southern Oscillation in a Changing Climate
Neelin JD, Battisti DS, Hirst AC et al (1998) ENSO theory. J Geophys Res Ocean 103:14261–14290. https://doi.org/10.1029/97JC03424
Newman M (2007) Interannual to decadal predictability of tropical and North Pacific sea surface temperatures. J Clim 20:2333–2356. https://doi.org/10.1175/JCLI4165.1
Newman M, Alexander MA, Scott JD (2011) An empirical model of tropical ocean dynamics. Clim Dyn 37:1823–1841. https://doi.org/10.1007/s00382-011-1034-0
Newman M, Sardeshmukh PD (2017) Are we near the predictability limit of tropical Indo-Pacific sea surface temperatures? Geophys Res Lett 44:8520–8529. https://doi.org/10.1002/2017GL074088
Newman M, Sardeshmukh PD, Penland C (2009) How important is air-sea coupling in ENSO and MJO evolution? J Clim 22:2958–2977. https://doi.org/10.1175/2008JCLI2659.1
Okumura YM, Deser C (2010) Asymmetry in the duration of El Niño and la Niña. J Clim 23:5826–5843. https://doi.org/10.1175/2010JCLI3592.1
OrtizBeviá MJ (1997) Estimation of the cyclostationary dependence in geophysical data fields. J Geophys Res Atmos 102:13473–13486. https://doi.org/10.1029/97JD00243
Perez CL, Moore AM, Zavala-Garay J, Kleeman R (2005) A Comparison of the Influence of Additive and Multiplicative Stochastic Forcing on a Coupled Model of ENSO. J Clim 18:5066–5085. https://doi.org/10.1175/JCLI3596.1
Philander SGH (1990) El Nino, La Nina, and the Southern Oscillation. Academic Press
Richter I, Chang P, Liu X (2020) Impact of systematic GCM errors on prediction skill as estimated by linear inverse modeling. J Clim 33:10073–10095. https://doi.org/10.1175/JCLI-D-20-0209.1
Richter I, Tokinaga H, Kosaka Y et al (2021) Revisiting the Tropical Atlantic Influence on El Niño–Southern Oscillation. J Clim 34. https://doi.org/10.1175/jcli-d-21-0088.1
Rodríguez-Fonseca B, Polo I, García-Serrano J et al (2009) Are Atlantic Niños enhancing Pacific ENSO events in recent decades? Geophys Res Lett 36. https://doi.org/10.1029/2009GL040048
Saji NH, Goswami BN, Vinayachandran PN, Yamagata T (1999) A dipole mode in the tropical Indian Ocean. Nature 401:360–363. https://doi.org/10.1038/43854
Saravanan R, Chang P (1999) Oceanic mixed layer feedback and tropical Atlantic variability. Geophys Res Lett 26:3629–3632. https://doi.org/10.1029/1999GL010468
Shin S-I, Sardeshmukh PD, Newman M et al (2020) Impact of Annual Cycle on ENSO Variability and Predictability. J Clim 1–84. https://doi.org/10.1175/jcli-d-20-0291.1
Stuecker MF, Timmermann A, Jin FF et al (2017) Revisiting ENSO/Indian Ocean Dipole phase relationships. Geophys Res Lett 44:2481–2492. https://doi.org/10.1002/2016GL072308
Vimont DJ (2012) Analysis of the Atlantic meridional mode using linear inverse modeling: Seasonality and regional influences. J Clim 25:1194–1212. https://doi.org/10.1175/JCLI-D-11-00012.1
Vimont DJ, Alexander MA, Newman M (2014) Optimal growth of Central and East Pacific ENSO events. Geophys Res Lett 41:4027–4034. https://doi.org/10.1002/2014GL059997
Wang C (2019) Three-ocean interactions and climate variability: a review and perspective. Clim Dyn 53:5119–5136. https://doi.org/10.1007/s00382-019-04930-x
Wang L, Yu JY, Paek H (2017) Enhanced biennial variability in the Pacific due to Atlantic capacitor effect. Nat Commun 8. https://doi.org/10.1038/ncomms14887
Webster PJ, Moore AM, Loschnigg JP, Leben RR (1999) Coupled ocean-atmosphere dynamics in the Indian Ocean during 1997-98. Nature 401:356–360. https://doi.org/10.1038/43848
Xie S-P, Hu K, Hafner J et al (2009) Indian Ocean capacitor effect on Indo-Western pacific climate during the summer following El Niño. J Clim. https://doi.org/10.1175/2008JCLI2544.1
Yang J, Liu Q, Xie S-P et al (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
Zhang L, Han W (2021) Indian Ocean Dipole leads to Atlantic Niño. Nat Commun 12:5952. https://doi.org/10.1038/s41467-021-26223-w
Zhang L, Han W, Karnauskas KB et al (2019) Indian Ocean Warming Trend Reduces Pacific Warming Response to Anthropogenic Greenhouse Gases: An Interbasin Thermostat Mechanism. Geophys Res Lett 46:10882–10890. https://doi.org/10.1029/2019GL084088
Zhang L, Wang G, Newman M, Han W (2021a) Interannual to decadal variability of tropical indian ocean sea surface temperature: Pacific influence versus local internal variability. J Clim 34:2669–2684. https://doi.org/10.1175/JCLI-D-20-0807.1
Zhang W, Jiang F, Stuecker MF et al (2021b) Spurious North Tropical Atlantic precursors to El Niño. Nat Commun 12. https://doi.org/10.1038/s41467-021-23411-6
Saravanan R, Chang P (1999) Oceanic mixed layer feedback and tropical Atlantic variability. Geophys Res Lett 26:3629–3632. https://doi.org/10.1029/1999GL010468
Schopf PS, Suarez MJ (1988) Vacillations in a coupled ocean–atmosphere model. J Atmos Sci 45:549–566. https://doi.org/10.1175/1520-0469(1988)045<0549:VIACOM>2.0.CO;2
Shin S-I, Sardeshmukh PD, Newman M, et al (2020) Impact of Annual Cycle on ENSO Variability and Predictability. J Clim 1–84. https://doi.org/10.1175/jcli-d-20-0291.1
Stuecker MF, Timmermann A, Jin FF, et al (2017) Revisiting ENSO/Indian Ocean Dipole phase relationships. Geophys Res Lett 44:2481–2492. https://doi.org/10.1002/2016GL072308
Vimont DJ (2012) Analysis of the Atlantic meridional mode using linear inverse modeling: Seasonality and regional influences. J Clim 25:1194–1212. https://doi.org/10.1175/JCLI-D-11-00012.1
Vimont DJ, Alexander MA, Newman M (2014) Optimal growth of Central and East Pacific ENSO events. Geophys Res Lett 41:4027–4034. https://doi.org/10.1002/2014GL059997
Wang C (2019) Three-ocean interactions and climate variability: a review and perspective. Clim Dyn 53:5119–5136. https://doi.org/10.1007/s00382-019-04930-x
Wang L, Yu JY, Paek H (2017) Enhanced biennial variability in the Pacific due to Atlantic capacitor effect. Nat Commun 8:. https://doi.org/10.1038/ncomms14887
Webster PJ, Moore AM, Loschnigg JP, Leben RR (1999) Coupled ocean-atmosphere dynamics in the Indian Ocean during 1997-98. Nature 401:356–360. https://doi.org/10.1038/43848
Xie S-P, Hu K, Hafner J, et al (2009) Indian Ocean capacitor effect on Indo-Western pacific climate during the summer following El Niño. J Clim. https://doi.org/10.1175/2008JCLI2544.1
Yang J, Liu Q, Xie S-P, et al (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
Zebiak SE (1993) Air-sea interaction in the equatorial Atlantic region. J Clim 6:1567–1586. https://doi.org/10.1175/1520-0442(1993)006<1567:AIITEA>2.0.CO;2
Zhang L, Han W (2021) Indian Ocean Dipole leads to Atlantic Niño. Nat Commun 12:5952. https://doi.org/10.1038/s41467-021-26223-w
Zhang L, Han W, Karnauskas KB, et al (2019) Indian Ocean Warming Trend Reduces Pacific Warming Response to Anthropogenic Greenhouse Gases: An Interbasin Thermostat Mechanism. Geophys Res Lett 46:10882–10890. https://doi.org/10.1029/2019GL084088
Zhang L, Wang G, Newman M, Han W (2021a) Interannual to decadal variability of tropical indian ocean sea surface temperature: Pacific influence versus local internal variability. J Clim 34:2669–2684. https://doi.org/10.1175/JCLI-D-20-0807.1
Zhang W, Jiang F, Stuecker MF, et al (2021b) Spurious North Tropical Atlantic precursors to El Niño. Nat Commun 12:. https://doi.org/10.1038/s41467-021-23411-6
Acknowledgements
We would like to thank Dr. Yuko Okumura and Dr. Mike Alexander as well as two anonymous reviewers for providing helpful comments. The present study is supported by KAKENHI Grant 18H01281 and 21K13997, Department of Commence Grant NA20OAR4310409, National Science Foundation Grant AGS-1462127, Department of Energy Grant DE-SC0020072 and the International Laboratory for High-Resolution Earth System Prediction (iHESP).
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Kido, S., Richter, I., Tozuka, T. et al. Understanding the interplay between ENSO and related tropical SST variability using linear inverse models. Clim Dyn 61, 1029–1048 (2023). https://doi.org/10.1007/s00382-022-06484-x
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DOI: https://doi.org/10.1007/s00382-022-06484-x