Climate Dynamics

, Volume 41, Issue 11–12, pp 3301–3315 | Cite as

The Atlantic Multidecadal Oscillation in twentieth century climate simulations: uneven progress from CMIP3 to CMIP5

  • Alfredo Ruiz-Barradas
  • Sumant Nigam
  • Argyro Kavvada


Decadal variability in the climate system from the Atlantic Multidecadal Oscillation (AMO) is one of the major sources of variability at this temporal scale that climate models must properly incorporate because of its climate impact. The current analysis of historical simulations of the twentieth century climate from models participating in the CMIP3 and CMIP5 projects assesses how these models portray the observed spatiotemporal features of the sea surface temperature (SST) and precipitation anomalies associated with the AMO. A short sample of the models is analyzed in detail by using all ensembles available of the models CCSM3, GFDL-CM2.1, UKMO-HadCM3, and ECHAM5/MPI-OM from the CMIP3 project, and the models CCSM4, GFDL-CM3, UKMO-HadGEM2-ES, and MPI-ESM-LR from the CMIP5 project. The structure and evolution of the SST anomalies of the AMO have not progressed consistently from the CMIP3 to the CMIP5 models. While the characteristic period of the AMO (smoothed with a binomial filter applied fifty times) is underestimated by the three of the models, the e-folding time of the autocorrelations shows that all models underestimate the 44-year value from observations by almost 50 %. Variability of the AMO in the 10–20/70–80 year ranges is overestimated/underestimated in the models and the variability in the 10–20 year range increases in three of the models from the CMIP3 to the CMIP5 versions. Spatial variability and correlation of the AMO regressed precipitation and SST anomalies in summer and fall indicate that models are not up to the task of simulating the AMO impact on the hydroclimate over the neighboring continents. This is in spite of the fact that the spatial variability and correlations in the SST anomalies improve from CMIP3 to CMIP5 versions in two of the models. However, a multi-model mean from a sample of 14 models whose first ensemble was analyzed indicated there were no improvements in the structure of the SST anomalies of the AMO or associated regional precipitation anomalies in summer and fall from CMIP3 to CMIP5 projects.


Atlantic Multidecadal Oscillation IPCC CMIP3 CMIP5 Hydroclimate AMO in CMIP3 and CMIP5 projects NCAR GFDL UKMO MPI 



The authors acknowledge the support of NOAA Climate Program Office Modeling, Analysis, Predictions and Projections (MAPP) Program as part of the CMIP5 Task Force. Work was supported under grant # NA10OAR4310158. In the same way, we wish to acknowledge support from NSF award AGS1132259. We also want to acknowledge the World Climate Research Programme’s Working Group on Coupled Modeling, which is responsible for CMIP, and we thank the climate modeling groups (listed in the Data section) for producing and making available their model output. For CMIP the US Department of Energy’s Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals. We acknowledge the modeling groups, the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and the WCRP’s Working Group on Coupled Modelling (WGCM) for their roles in making available the WCRP CMIP3 multi-model dataset. Support of this dataset is provided by the Office of Science, US Department of Energy.


  1. Booth B, Dunstone NJ, Halloran PR, Andrews T, Bellouin N (2012) Aerosols implicated as a prime driver of twentieth century North Atlantic climate variability. Nature. doi: 10.1038/nature10946 Google Scholar
  2. Collins WD et al (2006) The community climate system model version 3 (CCSM3). J Clim 19:2122–2143. doi: 10.1175/JCLI3761.1 CrossRefGoogle Scholar
  3. Collins WJ et al (2008) Evaluation of the HadGEM2 model. Met office Hadley centre technical note no. HCTN 74, available from Met Office, FitzRoy Road, Exeter EX1 3 PB
  4. Delworth TL et al (2006) GFDL’s CM2 global coupled climate models—part 1: formulation and simulation characteristics. J Clim 19:643–674CrossRefGoogle Scholar
  5. Donner LJ et al (2011) The dynamical core, physical parameterizations, and basic simulation characteristics of the atmospheric component of the GFDL global coupled model CM3. J Clim 24:3484–3519. doi: 10.1175/2011JCLI3955.1 CrossRefGoogle Scholar
  6. Enfield DB, Mestas-Nunez AM, Trimble PJ (2001) The Atlantic Multidecadal Oscillation and its relation to rainfall and river flows in the continental US. Geophys Res Lett 28:2077–2080CrossRefGoogle Scholar
  7. Evan AT, Vimont DJ, Heidinger AK, Kossin JP, Bennartz R (2009) The role of aerosols in the evolution of tropical North Atlantic Ocean temperature anomalies. Science 324:778–781. doi: 10.1126/science.1167404 CrossRefGoogle Scholar
  8. Gent PR et al (2011) The community climate system model version 4. J Clim 24:4973–4991. doi: 10.1175/2011JCLI4083.1 CrossRefGoogle Scholar
  9. Gordon C, Cooper C, Senior CA, Banks H, Gregory JM, Johns TC, Mitchell JFB, Wood RA (2000) The simulation of SST, sea ice extents and ocean heat transports in a version of the Hadley centre coupled model without flux adjustments. Clim Dyn 16:147–168CrossRefGoogle Scholar
  10. Griffies SM et al (2011) The GFDL CM3 coupled climate model: characteristics of the ocean and sea ice simulations. J. Clim 24:3520–3544. doi: 10.1175/2011JCLI3964.1 CrossRefGoogle Scholar
  11. Guan B, Nigam S (2009) Analysis of Atlantic SST variability factoring inter-basin links and the secular trend: clarified structure of the Atlantic Multidecadal Oscillation. J Clim 22:4228–4240CrossRefGoogle Scholar
  12. Hughes SL et al (2009) Comparison on in situ time-series of temperature with gridded sea surface temperature datasets in the North Atlantic. J Mar Sci 66:1467–1479Google Scholar
  13. Hurrell J et al (2010) Decadal climate prediction: opportunities and challenges. In: Hall J, Harrison DE, Stammer D (eds) Proceedings of Ocean Obs’09: sustained ocean observations and information for society (vol. 2), Venice, Italy, 21–25 September 2009, ESA Publication WPP-306Google Scholar
  14. Kavvada A, Ruiz-Barradas A, Nigam S (2013) AMO’s structure and climate footprint in observations and IPCC AR5 climate simulations. Clim Dyn. doi: 10.1007/s00382-013-1712-1
  15. Kushnir Y, Seager R, Ting M, Naik N, Nakamura J (2010) Mechanisms of tropical Atlantic SST influence on North American precipitation variability. J Clim 23:5610–5628. doi: 10.1175/2010JCLI3172.1 CrossRefGoogle Scholar
  16. Latif M et al (2004) Reconstructing, monitoring, and predicting decadal-scale changes in the North Atlantic thermohaline circulation with sea surface temperature. J Clim 17:1605–1614CrossRefGoogle Scholar
  17. Mantua NJ, Hare SR, Zhang Y, Wallace JM, Francis RC (1997) A Pacific interdecadal climate oscillation with impacts on salmon production. Bull Amer Meteor Soc 78:1069–1079CrossRefGoogle Scholar
  18. Marsland SJ, Haak H, Jungclaus JH, Latif M, Roeske F (2003) The Max-Planck-Institute global ocean/sea ice model with orthogonal curvilinear coordinates. Ocean Modelling 5:91–127. HAMOCC: technical documentation Google Scholar
  19. McCabe GJ, Betancourt JL, Gray ST, Palecki MA, Hidalgo HG (2008) Associations of multi-decadal sea-surface temperature variability with US drought. Quat Int 188:31–40. doi: 10.1016/j.quaint.2007.07.001 CrossRefGoogle Scholar
  20. Medhaug I, Furevik T (2011) North Atlantic twentieth century multidecadal variability in coupled climate models: sea surface temperature and ocean overturning circulation. Ocean Sci Discuss 8:353–396CrossRefGoogle Scholar
  21. Meehl GA et al (2009) Decadal prediction. Can it be skillful? Bull Amer Meteor Soc 90:1467–1485CrossRefGoogle Scholar
  22. Mitchell TD, Jones PD (2005) An improved method of constructing a database of monthly climate observations and associated high resolution grids. Int J Climatol 25:693–712. doi: 10.1002/joc.1181 CrossRefGoogle Scholar
  23. Nigam S, Guan B, Ruiz-Barradas A (2011) Key role of the Atlantic Multidecadal Oscillation in twentieth century drought and wet periods over the great plains. Geophys Res Lett 38:L16713. doi: 10.1029/2011GL048650 CrossRefGoogle Scholar
  24. Pope VD, Gallani ML, Rowntree PR, Stratton RA (2000) The impact of new physical parametrizations in the Hadley Centre climate model–HadAM3. Clim Dyn 16:123–146CrossRefGoogle Scholar
  25. Raddatz TJ, Reick CH, Knorr W, Kattge J, Roeckner E, Schnur R, Schnitzler K-G, Wetzel P, Jungclaus J (2007) Will the tropical land biosphere dominate the climate-carbon cycle feedback during the twenty first century? Clim Dyn 29:565–574. doi: 10.1007/s00382-007-0247-8 CrossRefGoogle Scholar
  26. Rayner NA, DE Parker, 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. doi: 10.1029/2002JD002670 CrossRefGoogle Scholar
  27. Roeckner E et al (2003) The atmospheric general circulation model ECHAM5. Part I: model description. Max Planck Institute for Meteorology Rep 349, p 127. Available from MPI for Meteorology, Bundesstr. 53, 20146 Hamburg, GermanyGoogle Scholar
  28. Ruiz-Barradas A, Nigam S (2005) Warm season rainfall variability over the US great plains in observations, NCEP and ERA-40 reanalyses, and NCAR and NASA atmospheric model simulations. J Clim 18:1808–1830. doi: 10.1175/JCLI3343.1 CrossRefGoogle Scholar
  29. Shanahan TM, Overpeck JT, Anchukaitis KJ, Beck JW, Cole JE, Dettman DL, Peck JA, Scholz CA, King JW (2009) Atlantic forcing of persistent drought in West Africa. Science 324(5925):377–380. doi: 10.1126/science.1166352 CrossRefGoogle Scholar
  30. Sheffield J et al (2013) North America climate in CMIP5 experiments. Part II: evaluation of historical simulations of intra-seasonal to decadal variability. Submitted to the J ClimGoogle Scholar
  31. Taylor KE, Stouffer RJ, Meehl GA (2011) An overview of CMIP5 and the experiment design. Bull Amer Meteor Soc 93:485–498. doi: 10.1175/BAMS-D-11-00094.1 CrossRefGoogle Scholar
  32. Ting M, Kushnir Y, Seager R, Li C (2011) Robust features of Atlantic Multidecadal variability and its climate impacts. Geophys Res Lett 38. doi: 10.1029/2011GL048712
  33. Wang C, Enfield DB, Lee S-K, Landsea CW (2006) Influences of the Atlantic warm pool on western hemisphere summer rainfall and Atlantic hurricanes. J Clim 19:3011–3028. doi: 10.1175/JCLI3770.1 CrossRefGoogle Scholar
  34. Zhang R, Delworth TL (2006) Impact of Atlantic Multidecadal Oscillations on India/Sahel rainfall and Atlantic hurricanes. Geophys Res Lett 33:L17712. doi: 10.1029/2006GL026267 CrossRefGoogle Scholar
  35. Zhang R et al (2013) Have aerosols caused the observed Atlantic Multidecadal variability? J Atmos Sci 70:1135–1144CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Alfredo Ruiz-Barradas
    • 1
  • Sumant Nigam
    • 1
  • Argyro Kavvada
    • 1
  1. 1.Department of Atmospheric and Oceanic ScienceUniversity of Maryland, College ParkCollege ParkUSA

Personalised recommendations