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Evaluating the potential for statistical decadal predictions of sea surface temperatures with a perfect model approach

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Abstract

We explore the potential for making statistical decadal predictions of sea surface temperatures (SSTs) in a perfect model analysis, with a focus on the Atlantic basin. Various statistical methods (Lagged correlations, Linear Inverse Modelling and Constructed Analogue) are found to have significant skill in predicting the internal variability of Atlantic SSTs for up to a decade ahead in control integrations of two different global climate models (GCMs), namely HadCM3 and HadGEM1. Statistical methods which consider non-local information tend to perform best, but which is the most successful statistical method depends on the region considered, GCM data used and prediction lead time. However, the Constructed Analogue method tends to have the highest skill at longer lead times. Importantly, the regions of greatest prediction skill can be very different to regions identified as potentially predictable from variance explained arguments. This finding suggests that significant local decadal variability is not necessarily a prerequisite for skillful decadal predictions, and that the statistical methods are capturing some of the dynamics of low-frequency SST evolution. In particular, using data from HadGEM1, significant skill at lead times of 6–10 years is found in the tropical North Atlantic, a region with relatively little decadal variability compared to interannual variability. This skill appears to come from reconstructing the SSTs in the far north Atlantic, suggesting that the more northern latitudes are optimal for SST observations to improve predictions. We additionally explore whether adding sub-surface temperature data improves these decadal statistical predictions, and find that, again, it depends on the region, prediction lead time and GCM data used. Overall, we argue that the estimated prediction skill motivates the further development of statistical decadal predictions of SSTs as a benchmark for current and future GCM-based decadal climate predictions.

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Notes

  1. These forecasts are available at: http://www.esrl.noaa.gov/psd/forecasts/sstlim/.

  2. The leading EOFs of the two GCMs are compared to the observations in the Supplementary Information.

  3. van den Dool (1994) showed that, for the atmospheric flow at 500mb to match over an entire hemisphere, one would need a library of 1030 years to find an analogue within the observational errors. Making a similar estimate, with optimistic assumptions, for Atlantic SST would require more than 105 years of data to provide a natural analogue. Given 140 years of data, the chance of finding a natural analogue is remote.

  4. This choice of artificial damping is motivated by noting that a forecast time series with zero correlation skill, but with the same variance as the true time series will produce an RMS error that is a factor of \(\sqrt{2}\) larger than a climatological forecast, assuming Gaussian distributions. It would be possible to derive optimal damping factors if the mean RMS error was known before the forecasts are made, but in this case, it is not known.

  5. For the LIM method, the estimated EOFs can be extended into the masked regions through regression onto the SSTs, allowing a prediction to subsequently be made for all regions. For the CA method, the estimation of the weights in Eq. 10 does not include the masked regions, but Eq. 11 can use all the data to make a prediction.

References

  • Arnell NW, Delaney EK (2006) Adapting to climate change: public water supply in England and Wales. Clim Change 78:227–255. doi:10.1007/s10584-006-9067-9

    Article  Google Scholar 

  • Barnston AG, van den Dool HM, Rodenhuis DR, Ropelewski CR, Kousky VE, O’Lenic EA, Livezey RE, Zebiak SE, Cane MA, Barnett TP, Graham NE, Ji M, Leetmaa A (1994) Long-lead seasonal forecasts? Where do we stand? Bull Am Meteorol Soc 75:2097–2114

    Article  Google Scholar 

  • Biastoch A, Boning CW, Lutjeharms JRE (2008) Agulhas leakage dynamics affects decadal variability in Atlantic overturning circulation. Nature 456:489–492. doi:10.1038/nature07426

    Google Scholar 

  • Boer GJ (2004) Long time-scale potential predictability in an ensemble of coupled climate models. Clim Dyn 23:29–44. doi:10.1007/s00382-004-0419-8

    Article  Google Scholar 

  • Boer GJ, Lambert SJ (2008) Multi-model decadal potential predictability of precipitation and temperature. Geophys Res Lett 35:L05706. doi:10.1029/2008GL033234

    Article  Google Scholar 

  • Collins M, Botzet M, Carril AF, Drange H, Jouzeau A, Latif M, Masina S, Otteraa OH, Pohlmann H, Sorteberg A, Sutton R, Terray L (2006) Interannual to decadal climate predictability in the North Atlantic: a multimodel-ensemble study. J Clim 19:1195–1202. doi:10.1175/JCLI3654.1

    Article  Google Scholar 

  • Collins M, Sinha B (2003) Predictability of decadal variations in the thermohaline circulation and climate. Geophys Res Lett 30:1306. doi:10.1029/2002GL016504

    Article  Google Scholar 

  • Colman A, Davey M (1999) Prediction of summer temperature, rainfall and pressure in Europe from preceding winter North Atlantic Ocean temperature. Int J Clim 19:513–536

    Article  Google Scholar 

  • Colman A, Davey M (2003) Statistical prediction of global sea-surface temperature anomalies. Int J Clim 23:1677–1697. doi:10.1002/joc.956

    Article  Google Scholar 

  • Delworth TL, Mann ME (2000) Observed and simulated multi-decadal variability in the Northern Hemisphere. Clim Dyn 16:661–676. doi:10.1007/s003820000075

    Article  Google Scholar 

  • Dong B, Sutton RT (2005) Mechanism of interdecadal thermohaline circulation variability in a coupled ocean-atmosphere GCM. J Clim 18:1117–1135

    Article  Google Scholar 

  • Dunstone NJ, Smith DM (2010) Impact of atmosphere and sub-surface ocean data on decadal climate prediction. Geophys Res Lett 37:L02709. doi:10.1029/2009GL041609

    Article  Google Scholar 

  • Emanuel K (2005) Increasing destructiveness of tropical cyclones over the past 30 years. Nature 436:686–688. doi:10.1038/nature03906

    Google Scholar 

  • Folland CK, Palmer TN, Parker DE (1986) Sahel rainfall and worldwide sea temperatures, 1901–85. Nature 320:602–607. doi:10.1038/320602a0

    Google Scholar 

  • Goldenberg SB, Landsea CW, Mestas-Nuñez AM, Gray WM (2001) The recent increase in Atlantic hurricane activity: causes and implications. Science 293:474–479. doi:10.1126/science.1060040

    Google Scholar 

  • 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 16:147–168

    Article  Google Scholar 

  • Griffies SM, Bryan K (1997) A predictability study of simulated North Atlantic multidecadal variability. Clim Dyn 13:459–487

    Article  Google Scholar 

  • Haarsma RJ, Campos EJD, Drijfhout S, Hazeleger W, Severijns C (2011) Impacts of interruption of the Agulhas leakage on the tropical Atlantic in coupled ocean-atmosphere simulations. Clim Dyn (in press). doi:10.1007/s00382-009-0692-7

  • Hawkins E, Sutton R (2007) Variability of the Atlantic thermohaline circulation described by three-dimensional empirical orthogonal functions. Clim Dyn 29:745–762. doi:10.1007/s00382-007-0263-8

    Article  Google Scholar 

  • Hawkins E, Sutton R (2009a) Decadal predictability of the Atlantic Ocean in a coupled GCM: estimation of optimal perturbations using linear inverse modelling. J Clim 22:3960–3978. doi:10.1175/2009JCLI2720.1

    Article  Google Scholar 

  • Hawkins E, Sutton R (2009b) The potential to narrow uncertainty in regional climate predictions. Bull Am Meteorol Soc 90:1095–1107. doi:10.1175/2009BAMS2607.1

    Article  Google Scholar 

  • Hodson DLR, Sutton RT (2011) The impact of model resolution on MOC adjustment in a coupled climate model. Clim Dyn (in prep)

  • Jewson S, Hawkins E (2009) Improving the expected accuracy of forecasts of future climate using a simple bias-variance tradeoff available from http://arxiv.org/abs/0911.1904

  • Johns TC, Durman CF, Banks HT, Roberts MJ, McLaren AJ, Ridley JK, Senior CA, Williams KD, Jones A, Rickard GJ, Cusack S, Ingram WJ, Crucifix M, Sexton DMH, Joshi MM, Dong BW, Spencer H, Hill RSR, Gregory JM, Keen AB, Pardaens AK, Lowe JA, Bodas-Salcedo A, Stark S, Searl Y (2006) The New Hadley centre climate model (HadGEM1): evaluation of coupled simulations. J Clim 19:1327–1353. doi:10.1175/JCLI3712.1

    Article  Google Scholar 

  • Johnson HL, Marshall DP (2002) A theory for the surface Atlantic response to thermohaline variability. J Phys Ocean 32:1121–1132

    Article  Google Scholar 

  • Keenlyside NS, Latif M, Jungclaus J, Kornblueh L, Roeckner E (2008) Advancing decadal-scale climate prediction in the North Atlantic sector. Nature 453:84–88. doi:10.1038/nature06921

    Google Scholar 

  • Laepple T, Jewson S, Coughlin K (2008) Interannual temperature predictions using the CMIP3 multi-model ensemble mean. Geophys Res Lett 35:L10701. doi:10.1029/2008GL033576

    Article  Google Scholar 

  • Lean JL, Rind DH (2009) How will Earth’s surface temperature change in future decades? Geophys Res Lett 36:L15708. doi:10.1029/2009GL038932

    Article  Google Scholar 

  • Lee TCK, Zwiers FW, Zhang X, Tsao M (2006) Evidence of decadal climate prediction skill resulting from changes in anthropogenic forcing. J Clim 19:5305–5318. doi:10.1175/JCLI3912.1

    Article  Google Scholar 

  • Liu G, Matrosova LE, Penland C, Gledhill DK, Eakin C, Webb RS, Christensen TRL, Heron SF, Morgan JA, Skirving WJ, Strong AE (2009) NOAA coral reef watch coral bleaching outlook system in proceedings of the 11th international coral reef symposium, Ft. Lauderdale, Florida, pp 951–955

  • Lorenz EN (1973) On the existence of extended range predictability. J Atmos Sci 12:543–546

    Google Scholar 

  • Meehl GA, Goddard L, Murphy J, Stouffer RJ, Boer G, Danabasoglu G, Dixon K, Giorgetta MA, Greene AM, Hawkins E, Hegerl G, Karoly D, Keenlyside N, Kimoto M, Kirtman B, Navarra A, Pulwarty R, Smith D, Stammer D, Stockdale T (2009) Decadal prediction: can it be skillful. Bull Am Meteorol Soc 90:1467–1485. doi:10.1175/2009BAMS2607.1

    Article  Google Scholar 

  • Meehl GA, Stocker TF, Collins W, Friedlingstein P, Gaye AT, Gregory JM, Kitoh A, Knutti R, Murphy JM, Noda A, Raper SCB, Watterson IG, Weaver AJ, Zhao ZC (2007) Global climate projections. In: Climate change 2007: the physical science basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge

  • Michaels A, Close A, Malmquist D, Knap A (1997) Climate science and insurance risk. Nature 389:225–227. doi:10.1038/38378

    Google Scholar 

  • Minobe S, Maeda A (2005) A 1° monthly gridded sea-surface temperature dataset compiled from ICOADS from 1850 to 2002 and Northern Hemisphere frontal variability. Int J Climatol 25:881–894. doi:10.1002/joc.1170

    Article  Google Scholar 

  • Newman M, Alexander MA, Scott JD (2010) An empirical model of tropical ocean dynamics. Clim Dyn (submitted)

  • Penland C, Magorian T (1993) Prediction of Niño 3 sea surface temperatures using linear inverse modelling. J Clim 6:1067–1076

    Article  Google Scholar 

  • 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 108:4407. doi:10.1029/2002JD002670

    Article  Google Scholar 

  • Robson JI (2010) Understanding the performance of a decadal prediction system. Ph.D. thesis, University of Reading, UK

  • Saha S, Nadiga S, Thiaw C, Wang J, Wang W, Zhang Q, Vanden Dool HM, Pan HL, Moorthi S, Behringer D, Stokes D, Peña M, Lord S, White G, Ebisuzaki W, Peng P, Xie P (2006) The NCEP climate forecast system. J Clim 19(15):3483–3517. doi:10.1175/JCLI3812.1

    Article  Google Scholar 

  • Scaife A, Kucharski F, Folland C, Kinter J, Bronnimann S, Fereday D, Fischer A, Grainger S, Jin E, Kang I, Knight J, Kusunoki S, Lau N, Nath M, Nakaegawa T, Pegion P, Schubert S, Sporyshev P, Syktus J, Yoon J, Zeng N, Zhou T (2009) The CLIVAR C20C project: selected twentieth century climate events. Clim Dyn 33:603–614. doi:10.1007/s00382-008-0451-1

    Article  Google Scholar 

  • Shaffrey LC, Stevens I, Norton WA, Roberts MJ, Vidale PL, Harle JD, Jrrar A, Stevens DP, Woodage MJ, Demory ME, Donners J, Clark DB, Clayton A, Cole JW, Wilson SS, Connolley WM, Davies TM, Iwi AM, Johns TC, King JC, New AL, Slingo JM, Slingo A, Steenman-Clark L, Martin GM (2009) U.K. HiGEM: the new U.K. high-resolution global environment model: model description and basic evaluation. J Clim 22:1861–1896. doi:10.1175/2008JCLI2508.1

    Article  Google Scholar 

  • Smith DM, Cusack S, Colman AW, Folland CK, Harris GR, Murphy JM (2007) Improved surface temperature prediction for the coming decade from a global climate model. Science 317:796–799. doi:10.1126/science.1139540

    Google Scholar 

  • Smith DM, Eade R, Dunstone NJ, Fereday D, Murphy JM, Pohlmann H, Scaife A (2010) Skilful multi-year predictions of Atlantic hurricane frequency. Nature Geosci 3:846–849. doi:10.1038/ngeo1004

    Google Scholar 

  • Sutton RT, Hodson DLR (2005) Atlantic Ocean forcing of North American and European summer climate. Science 309:115–118. doi:10.1126/science.1109496

    Google Scholar 

  • Tziperman E, Zanna L, Penland C (2008) Non-normal thermohaline circulation dynamics in a coupled ocean-atmosphere GCM. J Phys Ocean 38:588–604. doi:10.1175/2007JPO3769.1

    Article  Google Scholar 

  • van den Dool H (1994) Searching for analogues, how long must we wait. Tellus 46A:314–324

    Google Scholar 

  • van den Dool H (2007) Empirical methods in short-term climate prediction. Oxford University Press, Oxford

    Google Scholar 

  • van den Dool H, Huang J, Fan Y (2003) Performance and analysis of the constructed analogue method applied to U.S. soil moisture over 1981–2001. J Geophys Res 108:8617. doi:10.1029/2002JD003114

    Article  Google Scholar 

  • Vecchi GA, Swanson KL, Soden BJ (2008) Whither hurricane activity. Science 322:687–689. doi:10.1126/science.1164396

    Google Scholar 

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Acknowledgments

We thank Chun-Kit Ho, Fiona Underwood, Len Shaffrey, Dan Hodson and Manoj Joshi for useful suggestions. The two anonymous reviewers provided valuable comments which helped improve the paper. The authors are supported by NCAS-Climate (EH, JR, RS) and the NERC VALOR project (JR). The research leading to these results has received funding (EH, NK) from the European Community’s 7th framework programme (FP7/2007–2013) under grant agreement No. GA212643 (THOR: ‘Thermohaline Overturning—at Risk’, 2008–2012).

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Authors and Affiliations

  1. NCAS-Climate, Department of Meteorology, University of Reading, Reading, UK

    Ed Hawkins, Jon Robson & Rowan Sutton

  2. Met Office Hadley Centre, Exeter, UK

    Doug Smith

  3. IFM-GEOMAR, Kiel, Germany

    Noel Keenlyside

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  1. Ed Hawkins
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Correspondence to Ed Hawkins.

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Hawkins, E., Robson, J., Sutton, R. et al. Evaluating the potential for statistical decadal predictions of sea surface temperatures with a perfect model approach. Clim Dyn 37, 2495–2509 (2011). https://doi.org/10.1007/s00382-011-1023-3

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