The use of the multi-model ensemble in probabilistic climate projections
Abstract
Recent coordinated efforts, in which numerous climate models have been run for a common set of experiments, have produced large datasets of projections of future climate for various scenarios. Those multi-model ensembles sample initial condition, parameter as well as structural uncertainties in the model design, and they have prompted a variety of approaches to quantify uncertainty in future climate in a probabilistic way. This paper outlines the motivation for using multi-model ensembles, reviews the methodologies published so far and compares their results for regional temperature projections. The challenges in interpreting multi-model results, caused by the lack of verification of climate projections, the problem of model dependence, bias and tuning as well as the difficulty in making sense of an ‘ensemble of opportunity’, are discussed in detail.
References
-
Allen M.R, Stott P.A, Mitchell J.F.B, Schnur R& Delworth T.L . 2000 Quantifying the uncertainty in forecasts of anthropogenic climate change. Nature. 407, 617–620.doi:10.1038/35036559. . Crossref, PubMed, ISI, Google Scholar -
Andronova N& Schlesinger M.E . 2001 Objective estimation of the probability distribution for climate sensitivity. J. Geophys. Res. 106, 22 605–22 612.doi:10.1029/2000JD000259. . Crossref, ISI, Google Scholar -
Annan J.D, Hargreaves J.C, Edwards N.R& Marsh R Parameter estimation in an intermediate complexity Earth system model using an ensemble Kalman filter. Ocean Model. 8, 2005a 135–154.doi:10.1016/j.ocemod.2003.12.004. . Crossref, ISI, Google Scholar -
Annan J.D, Hargreaves J.C, Ohgaito R, Abe-Ouchi A& Emori S Efficiently constraining climate sensitivity with paleoclimate simulations. Sci. Online Lett. Atmos. 1, 2005b 181–184. Google Scholar -
Benestad R . 2004 Tentative probabilistic temperature scenarios for northern Europe. Tellus A. 56, 89–101.doi:10.1111/j.1600-0870.2004.00039.x. . Crossref, Google Scholar -
Berger J.O Statistical decision theory and Bayesian analysis. 2nd edn. 1993 New York, NY:Springer p. 617. Google Scholar -
Bryan F.O, Danabasoglu G, Nakashiki N, Yoshida Y, Kim D.-H& Tsutsui J . 2006 Response of the North Atlantic thermohaline circulation and ventilation to increasing carbon dioxide in CCSM3. J. Clim. 19, 2382–2397.doi:10.1175/JCLI3757.1. . Crossref, ISI, Google Scholar -
Cantelaube P& Terres J.-M . 2005 Seasonal weather forecasts for crop yield modelling in Europe. Tellus A. 57, 476–487.doi:10.1111/j.1600-0870.2005.00125.x. . Crossref, Google Scholar -
Collins M, Booth B.B.B, Harris G, Murphy J.M, Sexton D.M.H& Webb M.J . 2006 Towards quantifying uncertainty in transient climate change. Clim. Dynam. 27, 127–147.doi:10.1007/s00382-006-0121-0. . Crossref, ISI, Google Scholar -
Dettinger M . 2005 From climate-change spaghetti to climate-change distributions for 21st century California. San Francisco Estuary Watershed Sci. 3, article 4. Crossref, Google Scholar -
Doblas-Reyes F.J, Pavan V& Stephenson D.B . 2003 The skill of multimodel seasonal forecasts of the wintertime North Atlantic Oscillation. Clim. Dynam. 21, 501–514.doi:10.1007/s00382-003-0350-4. . Crossref, ISI, Google Scholar -
Evensen G . 1993 The ensemble Kalman filter: theoretical formulation and practical implementation. Ocean Dynam. 53, 343–367.doi:10.1007/s10236-003-0036-9. . Crossref, Google Scholar -
Evensen G . 1994 Sequential data assimilation with a nonlinear quasigeostrophic model using Monte Carlo methods to forecast error statistics. J. Geophys. Res. 99, 10 143–10 162.doi:10.1029/94JC00572. . Crossref, ISI, Google Scholar -
Forest C.E, Stone P.H, Sokolov A.P, Allen M.R& Webster M.D . 2002 Quantifying uncertainties in climate system properties with the use of recent climate observations. Science. 295, 113–117.doi:10.1126/science.1064419. . Crossref, PubMed, ISI, Google Scholar -
Forest C.E, Stone P.H& Sokolov A.P . 2006 Estimated PDFs of climate system properties including natural and anthropogenic forcings. Geophys. Res. Lett. 33, L01705 doi:10.1029/2005GL023977. . Crossref, ISI, Google Scholar -
Frame D.J, Booth B.B.B, Kettleborough J.A, Stainforth D.A, Gregory J.M, Collins M& Allen M.R . 2005 Constraining climate forecasts: the role of prior assumptions. Geophys. Res. Lett. 32, L09702 doi:10.1029/2004GL022241. . Crossref, ISI, Google Scholar -
Furrer, R., Sain, S., Nychka, D. & Meehl, G. In press. Multivariate Bayesian analysis of atmosphere–ocean general circulation models. Environ. Ecol. Stat. Google Scholar
-
Gates W.L . 1992 AMIP: the atmospheric model intercomparison project. Bull. Am. Meteorol. Soc. 73, 1962–1970.doi:10.1175/1520-0477(1992)073<1962:ATAMIP>2.0.CO;2. . Crossref, ISI, Google Scholar -
Gent P.R& McWilliams J.C . 1990 Isopycnal mixing in ocean circulation models. J. Phys. Oceanogr. 20, 150–155.doi:10.1175/1520-0485(1990)020<0150:IMIOCM>2.0.CO;2. . Crossref, ISI, Google Scholar -
Gent P.R, Willebrand J, McDougall T.J& McWilliams J.C . 1995 Parameterizing eddy-induced tracer transports in ocean circulation models. J. Phys. Oceanogr. 25, 463–474.doi:10.1175/1520-0485(1995)025<0463:PEITTI>2.0.CO;2. . Crossref, ISI, Google Scholar -
Gillett N.P, Zwiers F.W, Weaver A.J, Hegerl G.C, Allen M.R& Stott P.A . 2002 Detecting anthropogenic influence with a multi-model ensemble. Geophys. Res. Lett. 29, 1970 doi:10.1029/2002GL015836. . Crossref, ISI, Google Scholar -
Giorgi F& Francisco R . 2000 Uncertainties in regional climate change predictions. A regional analysis of ensemble simulations with the HADCM2 GCM. Clim. Dynam. 16, 169–182.doi:10.1007/PL00013733. . Crossref, ISI, Google Scholar -
Giorgi F& Mearns L . 2002 Calculation of average, uncertainty range and reliability of regional climate changes from AOGCM simulations via the ‘reliability ensemble averaging’ (REA) method. J. Clim. 15, 1141–1158.doi:10.1175/1520-0442(2002)015<1141:COAURA>2.0.CO;2. . Crossref, ISI, Google Scholar -
Giorgi F& Mearns L . 2003 Probability of regional climate change calculated using the reliability ensemble average (REA) method. Geophys. Res. Lett. 30, 1629–1632.doi:10.1029/2003GL017130. . Crossref, ISI, Google Scholar -
Goldstein M& Rougier J . 2004 Probabilistic formulations for transferring inferences from mathematical models to physical systems. SIAM J. Sci. Comput. 26, 467–487.doi:10.1137/S106482750342670X. . Crossref, ISI, Google Scholar -
Greene A, Goddard L& Lall U . 2006 Probabilistic multimodel regional temperature change projections. J. Clim. 19, 4326–4343.doi:10.1175/JCLI3864.1. . Crossref, ISI, Google Scholar -
Hagedorn R, Doblas-Reyes F.J& Palmer T.N . 2005 The rationale behind the success of multi-model ensembles in seasonal forecasting—I. Basic concept. Tellus A. 57, 219–233.doi:10.1111/j.1600-0870.2005.00103.x. . Google Scholar -
Hegerl G.C, Crowley T.J, Hyde W.T& Frame D.J . 2006 Climate sensitivity constrained by temperature reconstructions over the past seven centuries. Nature. 440, 1029–1032.doi:10.1038/nature04679. . Crossref, PubMed, ISI, Google Scholar -
IPCCp. 881 Eds.
Houghton J.T, Ding Y, Griggs D.J, Noguer M, van der Linden P.J, Xiaosu D, Dai X, Maskell K& Johnson C.A . 2001 Cambridge, UK:Cambridge University Press. Google Scholar -
Kiehl J.T& Shields C.A . 2005 Climate simulation of the latest Permian: implications for mass extinction. Geology. 33, 757–760.doi:10.1130/G21654.1. . Crossref, ISI, Google Scholar -
Knutti R, Stocker T.F, Joos F& Plattner G.-K . 2002 Constraints on radiative forcing and future climate change from observations and climate model ensembles. Nature. 416, 719–723.doi:10.1038/416719a. . Crossref, PubMed, ISI, Google Scholar -
Knutti R, Stocker T.F, Joos F& Plattner G.-K . 2003 Probabilistic climate change projections using neural networks. Clim. Dynam. 21, 257–272.doi:10.1007/s00382-003-0345-1. . Crossref, ISI, Google Scholar -
Knutti R, Joos F, Müller S.A, Plattner G.-K& Stocker T.F . 2005 Probabilistic climate change projections for CO2 stabilization profiles. Geophys. Res. Lett. 32, L20 707 doi:10.1029/2005GL023294. . Crossref, ISI, Google Scholar -
Knutti R, Meehl G.A, Allen M.R& Stainforth D.A . 2006 Constraining climate sensitivity from the seasonal cycle in surface temperature. J. Clim. 19, 4224–4233.doi:10.1175/JCLI3865.1. . Crossref, ISI, Google Scholar -
Krishnamurti T.N, Kishtawal C.M, Zhang Z, Larow T, Bachiochi D, Williford E, Gadgil S& Surendran S . 2000 Multimodel ensemble forecasts for weather and seasonal climate. J. Clim. 13, 4196–4216.doi:10.1175/1520-0442(2000)013<4196:MEFFWA>2.0.CO;2. . Crossref, ISI, Google Scholar -
Lambert S.J& Boer G.J . 2001 CMIP1 evaluation and intercomparison of coupled climate models. Clim. Dynam. 17, 83–106.doi:10.1007/PL00013736. . Crossref, ISI, Google Scholar -
Lopez A, Tebaldi C, New M, Stainforth D.A, Allen M.R& Kettleborough J . 2006 Two approaches to quantifying uncertainty in global temperature changes. J. Clim. 19, 4785–4796.doi:10.1175/JCLI3895.1. . Crossref, ISI, Google Scholar -
Luo Q, Jones R, Williams M, Bryan B& Bellotti W . 2005 Probabilistic distributions of regional climate change and their application in risk analysis of wheat production. Clim. Res. 29, 41–52. Crossref, ISI, Google Scholar -
Meehl G, Boer G.J, Covey C, Latif M& Stouffer R.J . 2000 The Coupled Model Intercomparison Project (CMIP). Bull. Am. Meteorol. Soc. 81, 313–318.doi:10.1175/1520-0477(2000)081<0313:TCMIPC>2.3.CO;2. . Crossref, Google Scholar -
Meinshausen M What does a 2°C target mean for greenhouse gas concentrations? A brief analysis based on multi-gas emission pathways and several climate sensitivity uncertainty estimates. Avoiding dangerous climate change, Schellnhuber H.J, Cramer W, Nakicenovic N, Wigley T& Yohe G . 2005pp. 265–279. Eds. Cambridge, UK:Cambridge University Press. Google Scholar -
Min S.-K& Hense A . 2006 A Bayesian approach to climate model evaluation and multi-model averaging with an application to global mean surface temperatures from IPCC AR4 coupled climate models. Geophys. Res. Lett. 33, L08708 doi:10.1029/2006GL025779. . Crossref, ISI, Google Scholar -
Murphy J.M, Sexton D.M.H, Barnett D.N, Jones G.S, Webb M.J, Collins M& Stainforth D.A . 2004 Quantification of modelling uncertainties in a large ensemble of climate change simulations. Nature. 429, 768–772.doi:10.1038/nature02771. . Crossref, ISI, Google Scholar -
Nakićenović N, Special report on emission scenarios: Intergovernmental Panel on Climate Change. 2000 Cambridge, UK:Cambridge University Press. Google Scholar -
Nychka D& Tebaldi C . 2003 Comments on calculation of average, uncertainty range, and reliability of regional climate changes from AOGCM simulations via the reliability ensemble averaging (REA) method. J. Clim. 16, 883–884.doi:10.1175/1520-0442(2003)016<0883:COCOAU>2.0.CO;2. . Crossref, ISI, Google Scholar -
Otto-Bliesner B.L, Brady E, Clauzet G, Tomas R, Levis S& Kothavala Z Last Glacial Maximum and Holocene climate in CCSM3. J. Clim. 19, 2006a 2526–2544.doi:10.1175/JCLI3748.1. . Crossref, ISI, Google Scholar -
Otto-Bliesner, B. L., Marshall, S. J., Overpeck, J. T., Miller, G. H., Hu, A. & CAPE Last Interglacial Project members. 2006b Simulating Arctic climate warmth and icefield retreat in the last interglaciation. Science 311, 1751–1753. (doi:10.1126/science.1120808). Google Scholar
-
Palmer T . 2005 Global warming in a nonlinear climate—can we be sure?. Europhys. News. 2, 42–46. Crossref, Google Scholar -
Palmer T.N& Räisänen J . 2002 Quantifying the risk of extreme seasonal precipitation events in a changing climate. Nature. 415, 512–514.doi:10.1038/415512a. . Crossref, PubMed, ISI, Google Scholar -
Palmer T, Shutts G, Hagedorn R, Doblas-Reyes F, Jung T& Leutbecher M Representing model uncertainty in weather and climate prediction. Annu. Rev. Earth Planet. Sci. 33, 2005a 163–193.doi:10.1146/annurev.earth.33.092203.122552. . Crossref, ISI, Google Scholar -
Palmer T.N, Doblas-Reyes F.J, Hagedorn R& Weisheimer A Probabilistic prediction of climate using multi-model ensembles: from basics to applications. Phil. Trans. R. Soc. B. 360, 2005b 1991–1998.doi:10.1098/rstb.2005.1750. . Link, ISI, Google Scholar -
Piani C, Frame D.J, Stainforth D.A& Allen M.R . 2005 Constraints on climate change from a multi-thousand member ensemble of simulations. Geophys. Res. Lett. 32, L23 825 doi:10.1029/2005GL024452. . Crossref, ISI, Google Scholar -
Räisänen J . 1997 Objective comparison of patterns of CO2 induced climate change in coupled GCM experiments. Clim. Dynam. 13, 197–211.doi:10.1007/s003820050160. . Crossref, ISI, Google Scholar -
Räisänen J& Palmer T.N . 2001 A probability and decision-model analysis of a multimodel ensemble of climate change simulations. J. Clim. 14, 3212–3226.doi:10.1175/1520-0442(2001)014<3212:APADMA>2.0.CO;2. . Crossref, ISI, Google Scholar -
Redi M.H . 1982 Oceanic isopycnal mixing by coordinate rotation. J. Phys. Oceanogr. 12, 1154–1158.doi:10.1175/1520-0485(1982)012<1154:OIMBCR>2.0.CO;2. . Crossref, ISI, Google Scholar -
Robertson A.W, Lall U, Zebiak S.E& Goddard L . 2004 Improved combination of multiple atmospheric GCM ensembles for seasonal predition. Mon. Weather Rev. 132, 2732–2744.doi:10.1175/MWR2818.1. . Crossref, ISI, Google Scholar -
Rougier, J. In press. Probabilistic inference for future climate using an ensemble of climate model evaluations. Clim. Change. Google Scholar
-
Schneider S.H . 2001 What is ‘dangerous’ in climate change?. Nature. 411, 17–19.doi:10.1038/35075167. . Crossref, PubMed, ISI, Google Scholar -
Smith, R., Tebaldi, C., Nychka, D. & Mearns, L. Submitted. Bayesian modeling of uncertainty in ensembles of climate models. Google Scholar
-
Stainforth D.A, 2005 Uncertainty in predictions of the climate response to rising levels of greenhouse gases. Nature. 433, 403–406.doi:10.1038/nature03301. . Crossref, PubMed, ISI, Google Scholar -
Stott P.A& Kettleborough J.A . 2002 Origins and estimates of uncertainty in predictions of twenty-first century temperature rise. Nature. 416, 723–726.doi:10.1038/416723a. . Crossref, PubMed, ISI, Google Scholar -
Tebaldi C, Mearns L, Nychka D& Smith R . 2004 Regional probabilities of precipitation change: a Bayesian analysis of multimodel simulations. Geophys. Res. Lett. 31, L24 213 doi:10.1029/2004GL021276. . Crossref, ISI, Google Scholar -
Tebaldi C, Smith R, Nychka D& Mearns L . 2005 Quantifying uncertainty in projections of regional climate change: a Bayesian approach to the analysis of multi-model ensembles. J. Clim. 18, 1524–1540.doi:10.1175/JCLI3363.1. . Crossref, ISI, Google Scholar -
Thomson M.C, Doblas-Reyes F.J, Mason S.J, Hagedorn R, Connor S.J, Phindela T, Morse A.P& Palmer T.N . 2006 Malaria early warnings based on seasonal climate forecasts from multi-model ensembles. Nature. 439, 576–579.doi:10.1038/nature04503. . Crossref, PubMed, ISI, Google Scholar -
von Deimling T.S, Held H, Ganopolski A& Rahmstorf S . 2006 Climate sensitivity estimated from ensemble simulations of glacial climate. Clim. Dynam. 27, 149–163.doi:10.1007/s00382-006-0126-8. . Crossref, ISI, Google Scholar -
Wigley T.M.L& Raper S.C.B . 2001 Interpretation of high projections for global-mean warming. Science. 293, 451–454.doi:10.1126/science.1061604. . Crossref, PubMed, ISI, Google Scholar -
Wild M . 2005 Solar radiation budgets in atmospheric model intercomparisons from a surface perspective. Geophys. Res. Lett. 32, L07704 doi:10.1029/2005GL022421. . Crossref, ISI, Google Scholar -
Wild M, Long C.N& Ohmura A . 2006 Evaluation of clear-sky solar fluxes in GCMs participating in AMIP and IPCC-AR4 from a surface perspective. J. Geophys. Res. 111, D01104 doi:10.1029/2005JD006118. . Crossref, ISI, Google Scholar -
Yun W.T, Stefanova L& Krishnamurti T.N . 2003 Improvement of the multimodel supersensemble technique for seasonal forecasts. J. Clim. 16, 3834–3840.doi:10.1175/1520-0442(2003)016<3834:IOTMST>2.0.CO;2. . Crossref, ISI, Google Scholar