Climate Dynamics

, Volume 41, Issue 11, pp 2875-2888

First online:

Real-time multi-model decadal climate predictions

  • Doug M. SmithAffiliated withMet Office Hadley Centre Email author 
  • , Adam A. ScaifeAffiliated withMet Office Hadley Centre
  • , George J. BoerAffiliated withCanadian Centre for Climate Modelling and Analysis, Environment Canada
  • , Mihaela CaianAffiliated withRossby Centre, Swedish Meteorological and Hydrological Institute
  • , Francisco J. Doblas-ReyesAffiliated withInstitut Català de Ciències del Clima
  • , Virginie GuemasAffiliated withInstitut Català de Ciències del Clima
  • , Ed HawkinsAffiliated withNCAS-Climate, Department of Meteorology, University of Reading
  • , Wilco HazelegerAffiliated withRoyal Netherlands Meteorological Institute (KNMI)Wageningen University
  • , Leon HermansonAffiliated withMet Office Hadley Centre
    • , Chun Kit HoAffiliated withNCAS-Climate, Department of Meteorology, University of Reading
    • , Masayoshi IshiiAffiliated withMeteorological Research Institute, Japan Meteorological Agency
    • , Viatcheslav KharinAffiliated withCanadian Centre for Climate Modelling and Analysis, Environment Canada
    • , Masahide KimotoAffiliated withAtmosphere and Ocean Research Institute, University of Tokyo
    • , Ben KirtmanAffiliated withRSMAS/MPO, University of Miami
    • , Judith LeanAffiliated withSpace Science Division, Naval Research Laboratory
    • , Daniela MateiAffiliated withMax-Planck-Institut für Meteorologie
    • , William J. MerryfieldAffiliated withCanadian Centre for Climate Modelling and Analysis, Environment Canada
    • , Wolfgang A. MüllerAffiliated withMax-Planck-Institut für Meteorologie
    • , Holger PohlmannAffiliated withMax-Planck-Institut für Meteorologie
    • , Anthony RosatiAffiliated withGeophysical Fluid Dynamics Laboratory, Princeton University
    • , Bert WoutersAffiliated withRoyal Netherlands Meteorological Institute (KNMI)
    • , Klaus WyserAffiliated withRossby Centre, Swedish Meteorological and Hydrological Institute

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We present the first climate prediction of the coming decade made with multiple models, initialized with prior observations. This prediction accrues from an international activity to exchange decadal predictions in near real-time, in order to assess differences and similarities, provide a consensus view to prevent over-confidence in forecasts from any single model, and establish current collective capability. We stress that the forecast is experimental, since the skill of the multi-model system is as yet unknown. Nevertheless, the forecast systems used here are based on models that have undergone rigorous evaluation and individually have been evaluated for forecast skill. Moreover, it is important to publish forecasts to enable open evaluation, and to provide a focus on climate change in the coming decade. Initialized forecasts of the year 2011 agree well with observations, with a pattern correlation of 0.62 compared to 0.31 for uninitialized projections. In particular, the forecast correctly predicted La Niña in the Pacific, and warm conditions in the north Atlantic and USA. A similar pattern is predicted for 2012 but with a weaker La Niña. Indices of Atlantic multi-decadal variability and Pacific decadal variability show no signal beyond climatology after 2015, while temperature in the Niño3 region is predicted to warm slightly by about 0.5 °C over the coming decade. However, uncertainties are large for individual years and initialization has little impact beyond the first 4 years in most regions. Relative to uninitialized forecasts, initialized forecasts are significantly warmer in the north Atlantic sub-polar gyre and cooler in the north Pacific throughout the decade. They are also significantly cooler in the global average and over most land and ocean regions out to several years ahead. However, in the absence of volcanic eruptions, global temperature is predicted to continue to rise, with each year from 2013 onwards having a 50 % chance of exceeding the current observed record. Verification of these forecasts will provide an important opportunity to test the performance of models and our understanding and knowledge of the drivers of climate change.


Decadal climate prediction Multi-model ensemble Forecast