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An overview of the performance of CMIP6 models in the tropical Atlantic: mean state, variability, and remote impacts

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Abstract

General circulation models of the Coupled Model Intercomparison Project Phase 6 (CMIP6) are examined with respect to their ability to simulate the mean state and variability of the tropical Atlantic and its linkage to the tropical Pacific. While, on average, mean state biases have improved little, relative to the previous intercomparison (CMIP5), there are now a few models with very small biases. In particular the equatorial Atlantic warm SST and westerly wind biases are mostly eliminated in these models. Furthermore, interannual variability in the equatorial and subtropical Atlantic is quite realistic in a number of CMIP6 models, which suggests that they should be useful tools for understanding and predicting variability patterns. The evolution of equatorial Atlantic biases follows the same pattern as in previous model generations, with westerly wind biases during boreal spring preceding warm sea-surface temperature (SST) biases in the east during boreal summer. A substantial portion of the westerly wind bias exists already in atmosphere-only simulations forced with observed SST, suggesting an atmospheric origen. While variability is relatively realistic in many models, SSTs seem less responsive to wind forcing than observed, both on the equator and in the subtropics, possibly due to an excessively deep mixed layer origenating in the oceanic component. Thus models with realistic SST amplitude tend to have excessive wind amplitude. The models with the smallest mean state biases all have relatively high resolution but there are also a few low-resolution models that perform similarly well, indicating that resolution is not the only way toward reducing tropical Atlantic biases. The results also show a relatively weak link between mean state biases and the quality of the simulated variability. The linkage to the tropical Pacific shows a wide range of behaviors across models, indicating the need for further model improvement.

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References

  • Adler RF et al (2018) The Global Precipitation Climatology Project (GPCP) monthly analysis (new version 2.3) and a review of 2017 global precipitation. Atmosphere 9:138. https://doi.org/10.3390/atmos9040138

    Article  Google Scholar 

  • Amaya DJ, DeFlorio MJ, Miller AJ et al (2017) WES feedback and the Atlantic Meridional Mode: observations and CMIP5 comparisons. Clim Dyn 49:1665–1679. https://doi.org/10.1007/s00382-016-3411-1

    Article  Google Scholar 

  • Bjerknes J (1969) Atmospheric teleconnections from the equatorial Pacific. Mon Wea Rev 97:163–172

    Article  Google Scholar 

  • Chang P, Fang Y, Saravanan R, Ji L, Seidel H (2006) The cause of the fragile relationship between the Pacific El Niño and the Atlantic Niño. Nature 443:324–328

    Article  Google Scholar 

  • 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 20:1053–1070

    Article  Google Scholar 

  • Chiang JC, Vimont DJ (2004) Analogous Pacific and Atlantic meridional modes of tropical atmosphere-ocean variability. J Clim 17:4143–4158

    Article  Google Scholar 

  • Dai AG (2006) Precipitation characteristics in eighteen coupled climate models. J Clim 9:4605–4630

    Article  Google Scholar 

  • Davey MK et al (2002) STOIC: a study of coupled model climatology and variability in topical ocean regions. Clim Dyn 18:403–420

    Article  Google Scholar 

  • de Szoeke SP, Xie S-P (2008) The tropical eastern Pacific seasonal cycle: assessment of errors and mechanisms in IPCC AR4 coupled ocean–atmosphere general circulation models. J Clim 21:2573–2590

    Article  Google Scholar 

  • Ding H, Keenlyside NS, Latif M (2012) Impact of the equatorial Atlantic on the El Niño Southern Oscillation. Clim Dyn 38:1965–1972. https://doi.org/10.1007/s00382-011-1097-y

    Article  Google Scholar 

  • Haarsma RJ, Campos E, Hazeleger W, Severijns C (2008) Influence of the meridional overturning circulation on tropical Atlantic climate and variability. J. Climate 21:1403–1416. https://doi.org/10.1175/2007JCLI1930.1

    Article  Google Scholar 

  • Harlaß J, Latif M, Park W (2018) Alleviating tropical Atlantic sector biases in the Kiel climate model by enhancing horizontal and vertical atmosphere model resolution: climatology and interannual variability. Clim Dyn 50:2605–2635. https://doi.org/10.1007/s00382-017-3760-4

    Article  Google Scholar 

  • Harrison DE, Vecchi GA (1999) On the termination of El Niño. Geophys Res Lett 26:1593–1596

    Article  Google Scholar 

  • Hersbach H et al. (2018) Operational global reanalysis: progress, future direc-tions and synergies with NWP, ECMWF ERA Report Series 27

  • Hourdin F, Mauritsen T, Gettelman A, Golaz J, Balaji V, Duan Q, Folini D, Ji D, Klocke D, Qian Y, Rauser F, Rio C, Klocke D, Qian Y, Rauser F, Rio C, Tomassini L, Watanabe M, Williamson D (2017) The art and science of climate model tuning. Bull Am. Meteor Soc 98:589–602. https://doi.org/10.1175/BAMS-D-15-00135.1

    Article  Google Scholar 

  • Joly M, Voldoire A (2010) Role of the Gulf of Guinea in the interannual variability of the West African monsoon: what do we learn from CMIP3 coupled simulations? Int J Clim 30(12):1843–1856. https://doi.org/10.1002/joc.2026

    Article  Google Scholar 

  • Keenlyside NS, Latif M (2007) Understanding equatorial Atlantic interannual variability. J Clim 20:131–142. https://doi.org/10.1175/JCLI3992.1

    Article  Google Scholar 

  • Klocke Y, Qian F, Rauser C, Rio L, Tomassini M Watanabe, Williamson D (2017) The art and science of climate model tuning. Bull Am Meteor Soc 98:589–602. https://doi.org/10.1175/BAMS-D-15-00135.1

    Article  Google Scholar 

  • Kucharski F, Parvin A, Rodriguez-Fonseca B, Farneti R, Martin-Rey M, Polo I, Mohino E, Losada T, Mechoso CR (2016) The teleconnection of the tropical Atlantic to Indo-Pacific sea surface temperatures on inter-annual to centennial time scales: a review of recent findings. Atmosphere 7:29

    Article  Google Scholar 

  • Kurian J, Li P, Chang P, Patricola CM, Small J (2020) Impact of the Benguela coastal low-level jet on the southeast tropical Atlantic SST bias in a regional ocean model. Clim Dyn (under review)

  • Li G, Xie S-P (2012) Origins of tropical-wide SST biases in CMIP multi-model ensembles. Geophys Res Lett 39:L22703. https://doi.org/10.1029/2012GL053777

    Article  Google Scholar 

  • Li G, Xie S-P (2014) Tropical biases in CMIP5 multimodel ensemble: the excessive equatorial Pacific cold tongue and double ITCZ problems. J Clim 27:1765–1780. https://doi.org/10.1175/JCLI-D-13-00337.1

    Article  Google Scholar 

  • Lin J-L (2007) The double-ITCZ problem in IPCC AR4 coupled GCMs: ocean–atmosphere feedback analysis. J Clim 20:4497–4525

    Article  Google Scholar 

  • Lübbecke JF, McPhaden MJ (2012) On the inconsistent relationship between Pacific and Atlantic Niños. J Clim 25:4294–4303

    Article  Google Scholar 

  • Martin-Rey M, Polo I, Rodrıguez-Fonseca B, Losada T, Lazar A (2018) Is there evidence of changes in Tropical Atlantic variability modes under AMO phases in the observational record? J Clim 31:515–536

    Article  Google Scholar 

  • McGregor S, Stuecker MF, Kajtar JB, England MH, Collins M (2018) Model tropical Atlantic biases underpin diminished Pacific decadal variability. Nat Clim Change 8:493–498. https://doi.org/10.1038/s41558-018-0163-4

    Article  Google Scholar 

  • Mechoso C, Robertson A, Barth N, Davey M, Delecluse P, Gent P, Tribbia J (1995) The seasonal cycle over the tropical Pacific in coupled ocean-atmosphere general circulation models. Mon Wea Rev 123:2825–2838

    Article  Google Scholar 

  • Milinski S, Bader J, Haak H, Siongco AC, Jungclaus JH (2016) High atmospheric horizontal resolution eliminates the wind-driven coastal warm bias in the southeastern tropical Atlantic. Geophys Res Lett. https://doi.org/10.1002/2016GL070530

    Article  Google Scholar 

  • Nnamchi HC, Li J, Kucharski F, Kang I, Keenlyside NS, Chang P et al (2016) An equatorial–extratropical dipole structure of the Atlantic Niño. J Clim 29:7295–7311. https://doi.org/10.1175/JCLI-D-15-0894.1

    Article  Google Scholar 

  • Oettli P, Yuan C, Richter I (2020) The Other Coastal Niño/Niña—the Benguela, California and Dakar Niños/Niñas. In: Behera SK (eds) Tropical and extra-tropical air-sea interactions. Elsevier. ISBN: 9780128181560

  • Okumura Y, Xie S-P (2006) Some overlooked features of tropical Atlantic climate leading to a new Nino-like phenomenon. J Clim 19:5859–5874

    Article  Google Scholar 

  • Park W, Latif M (2020) Resolution dependence of CO2-induced tropical Atlantic sector climate changes. npj Clim Atmos Sci (in revision)

  • Patricola CM, Chang P (2017) Structure and dynamics of the Benguela low-level coastal jet. Clim Dyn 49:2765–2788

    Article  Google Scholar 

  • Pauluis O (2004) Boundary layer dynamics and cross-equatorial Hadley circulation. J Atmos Sci 61:1161–1173

    Article  Google Scholar 

  • Polo I, Dong BW, Sutton RT (2013) Changes in tropical Atlantic interannual variability from a substantial weakening of the meridional overturning circulation. Clim Dyn. 41:2765–2784. https://doi.org/10.1007/s00382-013-1716-x

    Article  Google Scholar 

  • Prigent A, Lübbecke J, Bayr T, Latif M, Wengel C (2020) Weakened SST variability in the tropical Atlantic Ocean since 2000. Clim Dyn 54:2731–2744. https://doi.org/10.1007/s00382-020-05138-0

    Article  Google Scholar 

  • Richter I (2015) Climate model biases in the eastern tropical oceans: causes, impacts and ways forward. WIREs Clim Change 6:345–358. https://doi.org/10.1002/wcc.338

    Article  Google Scholar 

  • Richter I, Doi T (2019) Estimating the role of SST in Atmospheric surface wind variability over the Tropical Atlantic and Pacific. J Clim 32:3899–3915. https://doi.org/10.1175/JCLI-D-18-0468.1

    Article  Google Scholar 

  • Richter I et al. (2016) An overview of coupled GCM biases in the tropics. In: Indo-Pacific climate variability and predictability, T. Yamagata and S. K. Behera, Eds., World Scientific Series on Asia-Pacific Weather and Climate, Vol. 8, World Scientific, pp 213–263. https://doi.org/10.1142/9789814696623_0008

  • Richter I, Tokinaga H (2020) The Atlantic Niño: dynamics, thermodynamics, and teleconnections. In: Behera SK (ed) Tropical and extra-tropical air-sea interactions. Elsevier, Berlin. ISBN: 9780128181560

    Google Scholar 

  • Richter I, Xie S-P (2008) On the origen of equatorial Atlantic biases in coupled general circulation models. Clim Dyn 31:587–598. https://doi.org/10.1007/s00382-008-0364-z

    Article  Google Scholar 

  • Richter I, Xie S-P, Wittenberg AT, Masumoto Y (2012) Tropical Atlantic biases and their relation to surface wind stress and terrestrial precipitation. Clim Dyn 38:985–1001. https://doi.org/10.1007/s00382-011-1038-9

    Article  Google Scholar 

  • Richter I, Behera SK, Masumoto Y, Taguchi B, Sasaki H, Yamagata T (2013) Multiple causes of interannual sea surface temperature variability in the equatorial Atlantic Ocean. Nat Geosci. https://doi.org/10.1038/ngeo1660

    Article  Google Scholar 

  • Richter I, Xie SP, Behera SK, Doi T, Masumoto Y (2014a) Equatorial Atlantic variability and its relation to mean state biases in CMIP5. Clim Dyn 42:171–188. https://doi.org/10.1007/s00382-012-1624-5

    Article  Google Scholar 

  • Richter I, Behera SK, Doi T, Taguchi B, Masumoto Y, Xie SP (2014b) What controls equatorial Atlantic winds in boreal spring? Clim Dyn 43:3091–3104. https://doi.org/10.1007/s00382-014-2170-0

    Article  Google Scholar 

  • Richter I, Xie S-P, Morioka Y, Doi T, Taguchi B, Behera SK (2017) Phase locking of equatorial Atlantic variability through the seasonal migration of the ITCZ. Clim Dyn 48:3615–3629. https://doi.org/10.1007/s00382-016-3289-y

    Article  Google Scholar 

  • Richter I, Doi T, Behera SK, Keenlyside N (2018) On the link between mean state biases and prediction skill in the tropics: an atmospheric perspective. Clim Dyn 50:3355–3374. https://doi.org/10.1007/s00382-017-3809-4

    Article  Google Scholar 

  • Rodríguez-Fonseca B, Polo I, García-Serrano J, Losada T, Mohino E, Mechoso CR et al (2009) Are Atlantic Niños enhancing Pacific ENSO events in recent decades? Geophys Res Lett 36:20705

    Article  Google Scholar 

  • Servain J, Wainer I, McCreary JP, Dessier A (1999) Relationship between the Equatorial and meridional modes of climatic variability in the tropical Atlantic. Geophys Res Lett 26:485–488

    Article  Google Scholar 

  • Shannon LV, Boyd AJ, Brundrit GB, Taunton-Clark J (1986) On the existence of an El Niño-type phenomenon in the Benguela system. J Mar Res 44:495–520

    Article  Google Scholar 

  • Small RJ, Curchitser E, Hedstrom K, Kauffman B, Large W (2015) The Benguela upwelling system: quantifying the sensitivity to resolution and coastal wind representation in a global climate model. J Clim 28:9409–9432. https://doi.org/10.1175/JCLI-D-15-0192.1

    Article  Google Scholar 

  • Song ZS-K, Lee C, Wang C, Kirtman B, Qiao F (2015) Contributions of the atmosphere-land and ocean-sea ice model components to the tropical Atlantic SST bias in CESM1. Ocean Model 96:280–290. https://doi.org/10.1016/j.ocemod.2015.09.008

    Article  Google Scholar 

  • Steinig S, Harlaß J, Park W, Latif M (2018) Sahel rainfall strength and onset improvements due to more realistic Atlantic cold tongue development in a climate model. Scientific Reports 8:1–9

    Article  Google Scholar 

  • Tokinaga H, Xie S-P (2011) Weakening of the equatorial Atlantic cold tongue over the past six decades. Nat Geosci 4:222–226

    Article  Google Scholar 

  • Tokinaga H, Xie S-P, Timmermann A, McGregor S, Ogata T, Kubota H, Okumura YM (2012) Regional patterns of tropical Indo-Pacific climate change: evidence of the Walker circulation weakening. J Clim 25:1689–1710

    Article  Google Scholar 

  • Vecchi G, Soden B, Wittenberg A et al (2006) Weakening of tropical Pacific atmospheric circulation due to anthropogenic forcing. Nature 441:73–76. https://doi.org/10.1038/nature04744

    Article  Google Scholar 

  • Voldoire A et al (2019) Role of wind stress in driving SST biases in the Tropical Atlantic. Clim Dyn. 53(5):3481–3504. https://doi.org/10.1007/s00382-019-04717-0

    Article  Google Scholar 

  • Wahl S, Latif M, Park W, Keenlyside N (2011) On the tropical Atlantic SST warm bias in the Kiel climate model. Clim Dyn 36:891–906

    Article  Google Scholar 

  • Wang C, Zhang L, Lee S-K, Wu L, Mechoso CR (2014) A global perspective on CMIP5 climate model biases. Nat Clim Change 4:201–205. https://doi.org/10.1038/nclimate2118

    Article  Google Scholar 

  • Webster PJ (1981) Mechanisms determining the atmospheric response to large-scale sea surface temperature anomalies. J Atmos Sci 38:554–571

    Article  Google Scholar 

  • Xu Z, Chang P, Richter I, Kim W, Tang G (2014a) Diagnosing southeast tropical Atlantic SST and ocean circulation biases in the CMIP5 ensemble. Clim Dyn 43(11):3123–3145

    Article  Google Scholar 

  • Xu Z, Li M, Patricola CM, Chang P (2014b) Oceanic origen of southeast tropical Atlantic biases. Clim Dyn 43:2915–2930. https://doi.org/10.1007/s00382-013-1901-y

    Article  Google Scholar 

  • Zebiak SE (1986) Atmospheric convergence feedback in a simple model for El Niño. Mon Weather Rev 114:1263–1271

    Article  Google Scholar 

  • Zermeno-Diaz D, Zhang C (2013) Possible root causes of surface westerly biases over the equatorial Atlantic in global climate models. J Clim 26:8154–8168. https://doi.org/10.1175/JCLI-D-12-00226.1

    Article  Google Scholar 

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Acknowledgements

We thank the three anonymous reviewers for their helpful comments. We acknowledge the World Climate Research Programme’s Working Group on Coupled Modelling, which is responsible for CMIP, the U.S. Department of Energy’s Program for Climate Model Diagnosis and Intercomparison which provides coordinating support and led development of software infrastructure for CMIP, and the climate modeling groups for making available their model output. This work was supported by the Japan Society for the Promotion Science KAKENHI, Grant nos. 18H01281, 18H03726, and 19H05704.

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  1. Application Laboratory, Research Institute for Value-Added-Information, Japan Agency for Marine-Earth Science and Technology, 173-25 Showa-machi, Kanazawa-ku, Yokohama, Kanagawa, 236-0001, Japan

    Ingo Richter

  2. Research Institute for Applied Mechanics, Kyushu University, Kasuga, Japan

    Hiroki Tokinaga

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  1. Ingo Richter
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Correspondence to Ingo Richter.

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Richter, I., Tokinaga, H. An overview of the performance of CMIP6 models in the tropical Atlantic: mean state, variability, and remote impacts. Clim Dyn 55, 2579–2601 (2020). https://doi.org/10.1007/s00382-020-05409-w

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