The Pacific Decadal Oscillation less predictable under greenhouse warming


The Pacific Decadal Oscillation (PDO) is the most prominent form of decadal variability over the North Pacific, characterized by its horseshoe-shaped sea surface temperature anomaly pattern1,2. The PDO exerts a substantial influence on marine ecosystems, fisheries and agriculture1,2,3. Through modulating global mean temperature, the phase shift of the PDO at the end of the twentieth century is suggested to be an influential factor in the recent surface warming hiatus4,5. Determining the predictability of the PDO in a warming climate is therefore of great importance6. By analysing future climate under different emission scenarios simulated by the Coupled Model Intercomparison Project phase 5 (ref. 7), we show that the prediction lead time and the associated amplitude of the PDO decrease sharply under greenhouse warming conditions. This decrease is largely attributable to a warming-induced intensification of oceanic stratification, which accelerates the propagation of Rossby waves, shortening the PDO lifespan and suppressing its amplitude by limiting its growth time. Our results suggest that greenhouse warming will make prediction of the PDO more challenging, with far-reaching ramifications.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.

Fig. 1: Assessing predictability of the PDO.
Fig. 2: Reduced PDO predictability under greenhouse warming.
Fig. 3: Mechanisms for projected reduction in PDO predictability.

Data availability

Data related to this paper can be downloaded from the following websites: HadISST v1.1,; ERSST v5,; ERSST v4,; ERSST v3b,; COBE SST2,; Kaplan SST v2,; SODA,; and CMIP5 database,

Code availability

Codes for performing the APT analyses and conducting theoretical model experiments are available on reasonable request from the corresponding authors.


  1. 1.

    Mantua, N. J. et al. A Pacific interdecadal climate oscillation with impacts on salmon production. Bull. Am. Meteorol. Soc. 78, 1069–1080 (1997).

  2. 2.

    Newman, M. et al. The Pacific Decadal Oscillation, revisited. J. Clim. 29, 4399–4427 (2016).

  3. 3.

    Miller, A. J. & Schneider, N. Interdecadal climate regime dynamics in the North Pacific ocean: theories, observations and ecosystem impacts. Prog. Oceanogr. 47, 355–379 (2000).

  4. 4.

    Kosaka, Y. & Xie, S. P. Recent global-warming hiatus tied to equatorial Pacific surface cooling. Nature 501, 403 (2013).

  5. 5.

    Meehl, G. A., Teng, H. & Arblaster, J. M. Climate model simulations of the observed early-2000s hiatus of global warming. Nat. Clim. Change 4, 898–902 (2014).

  6. 6.

    Mochizuki, T. et al. Pacific Decadal Oscillation hindcasts relevant to near-term climate prediction. Proc. Natl Acad. Sci. USA 107, 1833–1837 (2010).

  7. 7.

    Taylor, KarlE., Ronald, J. Stouffer & Meehl, G. A. An overview of CMIP5 and the experiment design. Bull. Am. Meteorol. Soc. 93, 485–498 (2012).

  8. 8.

    Deser, C., Phillips, A. C. & Hurrell, J. W. Pacific interdecadal climate variability: linkages between the tropics and the North Pacific during boreal winter since 1900. J. Clim. 17, 3109–3124 (2004).

  9. 9.

    Mantua, N. J. & Hare, S. R. The Pacific Decadal Oscillation. J. Oceanogr. 58, 35–44 (2002).

  10. 10.

    Dai, A. Increasing drought under global warming in observations and models. Nat. Clim. Change 3, 52–58 (2013).

  11. 11.

    Wang, C. et al. A global perspective on CMIP5 climate model biases. Nat. Clim. Change 4, 201–205 (2014).

  12. 12.

    Kosaka, Y. & Xie, S. P. The tropical Pacific as a key pacemaker of the variable rates of global warming. Nat. Geosci. 9, 669–673 (2016).

  13. 13.

    Deser, C. et al. Uncertainty in climate change projections: the role of internal variability. Clim. Dynam. 38, 527–546 (2012).

  14. 14.

    Xie, S. P., Kosaka, Y. & Okumura, Y. M. Distinct energy budgets for anthropogenic and natural changes during global warming hiatus. Nat. Geosci. 9, 29–33 (2016).

  15. 15.

    Seager, R. et al. in Earth’s Climate: The Ocean–Atmosphere Interaction (eds Wang, C., Xie, S. P. & Carton, J. A.) 105–120 (American Geophysical Union, 2004).

  16. 16.

    Frankignoul, C. & Hasselmann, K. Stochastic climate models, Part II: application to sea-surface temperature anomalies and thermocline variability. Tellus 29, 289–305 (1977).

  17. 17.

    Jin, F. F. A theory of interdecadal climate variability of the North Pacific ocean–atmosphere system. J. Clim. 10, 1821–1835 (1997).

  18. 18.

    Wu, L. et al. Pacific decadal variability: the tropical Pacific mode and the North Pacific mode. J. Clim. 16, 1101–1120 (2003).

  19. 19.

    Liu, Z. & Wu, L. Atmospheric response to North Pacific SST: the role of ocean–atmosphere coupling. J. Clim. 17, 1859–1882 (2004).

  20. 20.

    Schneider, N., Miller, A. J. & Pierce, D. W. Anatomy of North Pacific decadal variability. J. Clim. 15, 586–605 (2002).

  21. 21.

    Kwon, Y. O. & Deser, C. North Pacific decadal variability in the Community Climate System Model version 2. J. Clim. 20, 2416–2433 (2007).

  22. 22.

    Yang, Y., Wu, L. & Fang, C. Will global warming suppress North Atlantic tripole decadal variability? J. Clim. 25, 2040–2055 (2012).

  23. 23.

    Fang, C., Wu, L. & Zhang, X. The impact of global warming on the Pacific Decadal Oscillation and the possible mechanism. Adv. Atmos. Sci. 31, 118–130 (2014).

  24. 24.

    Zhang, L. & Delworth, T. L. Simulated response of the Pacific Decadal Oscillation to climate change. J. Clim. 29, 5999–6018 (2016).

  25. 25.

    Geng, T., Yang, Y. & Wu, L. On the mechanisms of Pacific decadal oscillation modulation in a warming climate. J. Clim. 32, 1443–1459 (2019).

  26. 26.

    DelSole, T., Jia, L. & Tippett, M. K. Decadal prediction of observed and simulated sea surface temperatures. Geophys. Res. Lett. 40, 2773–2778 (2013).

  27. 27.

    Srivastava, A. & DelSole, T. Decadal predictability without ocean dynamics. Proc. Natl Acad. Sci. USA 114, 2177–2182 (2017).

  28. 28.

    Collins, M. Climate predictability on interannual to decadal time scales: the initial value problem. Clim. Dynam. 19, 671–692 (2002).

  29. 29.

    Chelton, D. B. et al. Geographical variability of the first baroclinic Rossby radius of deformation. J. Phys. Oceanogr. 28, 433–460 (1998).

  30. 30.

    Miller, A. J., Cayan, D. R. & White, W. B. A westward-intensified decadal change in the North Pacific thermocline and gyre-scale circulation. J. Clim. 11, 3112–3127 (1998).

  31. 31.

    Goodman, J. & Marshall, J. A model of decadal middle latitude atmosphere–ocean coupled modes. J. Clim. 12, 621–641 (1999).

  32. 32.

    Rayner, N. A. et al. Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century. J. Geophys. Res. 108, 4407 (2003).

  33. 33.

    Smith, T. M., Reynolds, R. W., Peterson, T. C. & Lawrimore, J. Improvements to NOAAs historical merged land–ocean temp analysis (1880–2006). J. Clim. 21, 2283–2296 (2008).

  34. 34.

    Huang, B. et al. Extended Reconstructed Sea Surface Temperature version 4 (ERSST.v4). Part I: upgrades and intercomparisons. J. Clim. 28, 911–930 (2014).

  35. 35.

    Huang, B. et al. Extended Reconstructed Sea Surface Temperature version 5 (ERSSTv5), upgrades, validations, and intercomparisons. J. Clim. 30, 8179–8205 (2017).

  36. 36.

    Kaplan, A. et al. Analyses of global sea surface temperature 1856–1991. J. Geophys. Res. 103, 18567–18589 (1998).

  37. 37.

    Hirahara, S., Ishii, M. & Fukuda, Y. Centennial-scale sea surface temperature analysis and its uncertainty. J. Clim. 27, 57–75 (2014).

  38. 38.

    Carton, J. A. & Giese, B. S. A reanalysis of ocean climate using simple ocean data assimilation (SODA). Mon. Weather Rev. 136, 2999–3017 (2008).

  39. 39.

    DelSole, T. & Tippett, M. K. Average predictability time. Part I: theory. J. Atmos. Sci. 66, 1172–1187 (2009).

  40. 40.

    DelSole, T. & Tippett, M. K. Average predictability time. Part II: seamless diagnoses of predictability on multiple time scales. J. Atmos. Sci. 66, 1188–1204 (2009).

  41. 41.

    Lorenzo, E. N. Empirical Orthogonal Functions and Statistical Weather Prediction Statistical Forecast Project Report 1 (MIT Department of Meteorology, 1956).

  42. 42.

    Zhang, L., Delworth, T. L. & Jia, L. Diagnosis of decadal predictability of southern ocean sea surface temperature in the GFDL CM2.1 model. J. Clim. 30, 6309–6328 (2017).

  43. 43.

    Jia, L. & DelSole, T. Diagnosis of multiyear predictability on continental scales. J. Clim. 24, 5108–5124 (2011).

  44. 44.

    Boer, G. J. Long time-scale potential predictability in an ensemble of coupled climate models. Clim. Dynam. 23, 29–44 (2004).

  45. 45.

    Boer, G. J. Decadal potential predictability of twenty-first century climate. Clim. Dynam. 36, 1119–1133 (2011).

  46. 46.

    Fang, J. B. & Yang, X. Q. The relative roles of different physical processes in unstable midlatitude ocean–atmosphere interactions. J. Clim. 24, 1542–1558 (2011).

Download references


L.W. is supported by a National Natural Science Foundation of China (NSFC) major project (grant nos 41490640 and 41490643). W.C. and G.W. are supported by CSHOR and the Earth Systems and Climate Change Hub of the Australian Government’s National Environmental Science Program. The Centre for Southern Hemisphere Oceans Research is a research partnership between QNLM and CSIRO. Y.Y and B.G are supported by NSFC projects (grant nos 41976005, 41606008, 41922039 and 91858102) and the National Key R&D Programme of China (grant no. 2016YFA0601803). We acknowledge the WCRP’s Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modelling groups for producing and making available their model output.

Author information

L.W. and S.L. conceived and wrote the initial manuscript in discussion with W.C., Y.Y. and T.G. S.L. performed model analysis and generated final figures. T.G. conducted analysis of the theoretical coupled model. All authors contributed to interpreting results, discussion of the associated dynamics and improvement of this paper.

Correspondence to Lixin Wu or Wenju Cai.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary Information

Supplementary Figs. 1–6 and Tables 1 and 2.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Li, S., Wu, L., Yang, Y. et al. The Pacific Decadal Oscillation less predictable under greenhouse warming. Nat. Clim. Chang. 10, 30–34 (2020) doi:10.1038/s41558-019-0663-x

Download citation

Further reading