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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.
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“The best climate predictions are synthesized from ensembles of 20+ climate models [782].”
From Tackling climate change with machine learning (2023) · cites this paper as [782]
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Cites
Statistical Decision Theory and Bayesian Analysis
Berger, J. O. (1985) · Springer Series in Statistics · doi:10.1007/978-1-4757-4286-2 · Cited by 7,722
Special report on emissions scenarios
Nakićenović, N., Alcamo, J., Davis, G. R., de Vries, B. J. M., Fenhann, J. V., Gaffin, S., Gregory, K., Grübler, A., Jung, T. Y., Kram, T., et al. (2000) · Cited by 6,089
Evensen, G. (1994) · Journal of Geophysical Research: Oceans · doi:10.1029/94jc00572 · Cited by 5,371
The Ensemble Kalman Filter: theoretical formulation and practical implementation
Evensen, G. (2003) · Ocean Dynamics · doi:10.1007/s10236-003-0036-9 · Cited by 4,606
Quantification of modelling uncertainties in a large ensemble of climate change simulations.
Murphy, J. M., Sexton, D. M. H., Barnett, D. N., Jones, G. S., Webb, M. J., Collins, M., & Stainforth, D. A. (2004) · Nature · doi:10.1038/nature02771 · Cited by 1,655
Uncertainty in predictions of the climate response to rising levels of greenhouse gases
Stainforth, D. A., Aina, T., Christensen, C., Collins, M. D., Faull, N., Frame, D. J., Kettleborough, J. A., Knight, S. H. E., Martin, A., Murphy, J. M., et al. (2005) · Nature · doi:10.1038/nature03301 · Cited by 1,167
Simulating Arctic Climate Warmth and Ice Field Retreat in the Last Interglaciation
Otto‐Bliesner, B. L., Marshall, S. J., Overpeck, J. T., Miller, G. H., Hu, A., & CAPE Last Interglacial Project members (2006) · Science · doi:10.1126/science.1120808 · Cited by 936
AN AMS CONTINUING SERIES: GLOBAL CHANGE--AMIP: The Atmospheric Model Intercomparison Project
Gates, W. L. (1992) · Bulletin of the American Meteorological Society · Cited by 744
The rationale behind the success of multi-model ensembles in seasonal forecasting - I. Basic concept
Hagedorn, R., Doblas-Reyes, F. J., & Palmer, T. N. (2005) · Tellus A: Dynamic Meteorology and Oceanography · doi:10.3402/tellusa.v57i3.14657 · Cited by 710
Quantifying the uncertainty in forecasts of anthropogenic climate change
Allen, M. R., Stott, P. A., Mitchell, J. F. B., Schnur, R., & Delworth, T. L. (2000) · Nature · doi:10.1038/35036559 · Cited by 657
Flagged first, then by citations
Research works printed but not linked: 3
- Annan J.D, 2005, Efficiently constraining climate sensitivity with paleoclimate simulations, Sci. Online Lett. Atmos, 1, 181
- 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.
- 10.1175/1520-0442(2003)016<3834:IOTMST>2.0.CO;2 · DOI
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Items 601–700 of 1,000
Sung, H. M., Kim, J., Lee, J.-H., Shim, S., Boo, K., Ha, J.-C., & Kim, Y.-H. (2021) · Atmosphere · doi:10.3390/atmos12010090 · Cited by 39
Eekhout, J., Millares, A., Martínez‐Salvador, A., García‐Lorenzo, R., Pérez‐Cutillas, P., García, C. C., & de Vente, J. (2021) · Land Degradation and Development · doi:10.1002/ldr.3920 · Cited by 39
Model independence in multi-model ensemble prediction
Abramowitz, G. (2010) · Australian Meteorological and Oceanographic Journal · doi:10.22499/2.5901.002 · Cited by 39
Investigating the application of climate models in flood projection across the UK
Smith, A. P., Bates, P., Freer, J. E., & Wetterhall, F. (2013) · Hydrological Processes · doi:10.1002/hyp.9815 · Cited by 39
Zanna, L., Brankart, J., Huber, M., Leroux, S., Penduff, T., & Williams, P. D. (2018) · Quarterly Journal of the Royal Meteorological Society · doi:10.1002/qj.3397 · Cited by 39
Understanding the Diversity of CMIP6 Models in the Projection of Precipitation Over Tibetan Plateau
Qiu, H., Zhou, T., Chen, X., Wu, B., & Jiang, J. (2024) · Geophysical Research Letters · doi:10.1029/2023gl106553 · Cited by 38
Past climate change effects on human evolution
Timmermann, A., Raia, P., Mondanaro, A., Zollikofer, C. P. E., de León, M. S. P., Zeller, E., & Yun, K. (2024) · Nature Reviews Earth & Environment · doi:10.1038/s43017-024-00584-4 · Cited by 38
Sensitivity of the regional climate model RegCM4.2 to planetary boundary layer parameterisation
Güttler, I., Branković, Č., O'Brien, T. A., Coppola, E., Grisogono, B., & Giorgi, F. (2013) · Climate Dynamics · doi:10.1007/s00382-013-2003-6 · Cited by 38
High-Resolution Probabilistic Projections of Temperature Changes over Ontario, Canada
Wang, X., Huang, G., Lin, Q., & Liu, J. (2014) · Journal of Climate · doi:10.1175/jcli-d-13-00717.1 · Cited by 38
Ishida, K., Görgüner, M., Ercan, A., Trinh, T., & Kavvas, M. L. (2017) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2017.03.086 · Cited by 38
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Bauer, B., Horbowy, J., Rahikainen, M., Kulatska, N., Müller‐Karulis, B., Tomczak, M. T., & Bartolino, V. (2019) · PLoS ONE · doi:10.1371/journal.pone.0211320 · Cited by 38
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Maksic, J., Venancio, I. M., Shimizu, M. H., Chiessi, C. M., Piacsek, P., Sampaio, G., Cruz, F. W., & Alexandre, F. (2021) · Palaeogeography Palaeoclimatology Palaeoecology · doi:10.1016/j.palaeo.2021.110717 · Cited by 39
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Haguma, D., Leconte, R., Côté, P., Krau, S., & Brissette, F. P. (2014) · Water Resources Management · doi:10.1007/s11269-014-0763-3 · Cited by 38
Wisetjindawat, W., Kermanshah, A., Derrible, S., & Fujita, M. (2017) · Journal of Infrastructure Systems · doi:10.1061/(asce)is.1943-555x.0000391 · Cited by 38
Burke, M., Dykema, J. A., Lobell, D. B., Miguel, E. A., & Satyanath, S. (2011) · National Bureau of Economic Research · doi:10.3386/w17092 · Cited by 38
Fernández, M., Hamilton, H., & Kueppers, L. M. (2015) · Global Change Biology · doi:10.1111/gcb.13027 · Cited by 41
Ekström, M., Kuruppu, N., Wilby, R. L., Fowler, H. J., Chiew, F. H. S., Dessai, S., & Young, W. J. (2012) · Global Environmental Change · doi:10.1016/j.gloenvcha.2012.11.003 · Cited by 37
Comparing climate change impacts on cereals based on CMIP3 and EU-ENSEMBLES climate scenarios
Vanuytrecht, E., Raes, D., Willems, P., & Semenov, M. A. (2014) · Agricultural and Forest Meteorology · doi:10.1016/j.agrformet.2014.04.017 · Cited by 37
Westhoff, J. T., & Paukert, C. P. (2014) · PLoS ONE · doi:10.1371/journal.pone.0111438 · Cited by 37
Episodic and non-uniform shifts of thermal habitats in a warming ocean
Gupta, A. S., Brown, J. N., Jourdain, N. C., van Sebille, E., Ganachaud, A. S., & Vergés, A. (2013) · Deep Sea Research Part II Topical Studies in Oceanography · doi:10.1016/j.dsr2.2013.12.002 · Cited by 40
Demirel, M. C., & Moradkhani, H. (2015) · Climatic Change · doi:10.1007/s10584-015-1559-z · Cited by 37
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Samee, M. A. H., Lim, B., Samper, N., Lu, H., Rushlow, C. A., Jiménez, G., Shvartsman, S. Y., & Sinha, S. (2015) · Cell Systems · doi:10.1016/j.cels.2015.12.002 · Cited by 37
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Wang, L., Deng, A., & Huang, R. (2018) · Climate Dynamics · doi:10.1007/s00382-018-4542-3 · Cited by 37
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Yang, X., Yu, X., Wang, Y., He, X., Pan, M., Zhang, M., Liu, Y., Ren, L., & Sheffield, J. (2020) · Journal of Hydrometeorology · doi:10.1175/jhm-d-19-0141.1 · Cited by 37
Amrhein, D. E., Hakim, G. J., & Parsons, L. A. (2020) · Geophysical Research Letters · doi:10.1029/2020gl090485 · Cited by 37
Katzav, J., Thompson, E., Risbey, J. S., Stainforth, D. A., Bradley, S., & Frisch, M. (2021) · Climatic Change · doi:10.1007/s10584-021-03267-x · Cited by 37
Chowell, G., Dahal, S., Tariq, A., Roosa, K. M., Hyman, J. M., & Luo, R. (2022) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1010602 · Cited by 37
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Chen, Z., Zhang, H., & Liao, M. (2019) · Processes · doi:10.3390/pr7010025 · Cited by 36
Shevchenko, V., Lukashevich, A., Taniushkina, D., Bulkin, A., Grinis, R., Kovalev, K., Narozhnaia, V., Sotiriadi, N., Krenke, A. N., & Maximov, Y. (2024) · IEEE Access · doi:10.1109/access.2024.3358865 · Cited by 42
Khosravi, Y., Ouarda, T. B. M. J., & Homayouni, S. (2025) · npj Climate and Atmospheric Science · doi:10.1038/s41612-025-01033-9 · Cited by 38
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Degener, J. (2015) · Frontiers in Environmental Science · doi:10.3389/fenvs.2015.00048 · Cited by 36
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Leith, N., & Chandler, R. E. (2009) · Journal of the Royal Statistical Society Series C (Applied Statistics) · doi:10.1111/j.1467-9876.2009.00694.x · Cited by 36
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Borodina, A., Fischer, E. M., & Knutti, R. (2017) · Journal of Climate · doi:10.1175/jcli-d-16-0662.1 · Cited by 37
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Moradian, S., Haghighi, A. T., Asadi, M., & Mirbagheri, S. A. (2022) · Water Resources Management · doi:10.1007/s11269-022-03272-4 · Cited by 36
Garbrecht, J. D., Nearing, M. A., Steiner, J. L., Zhang, X., & Nichols, M. H. (2015) · Weather and Climate Extremes · doi:10.1016/j.wace.2015.06.002 · Cited by 36
Anandhi, A., & Nanjundiah, R. S. (2014) · Theoretical and Applied Climatology · doi:10.1007/s00704-013-1043-5 · Cited by 36
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Hesse, C., Krysanova, V., Stefanova, A., Bielecka, M., & Domnin, D. A. (2014) · Hydrological Sciences Journal · doi:10.1080/02626667.2014.967247 · Cited by 35
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Kotova, L., Leißner, J., Winkler, M., Kilian, R., Bichlmair, S., Antretter, F., Moßgraber, J., Reuter, J., Hellmund, T., Matheja, K., et al. (2023) · Heritage Science · doi:10.1186/s40494-022-00853-9 · Cited by 35
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Mills, D., Jones, R., Wobus, C. W., Ekstrom, J. A., Jantarasami, L., Juliana, A. S., & Crimmins, A. R. (2018) · Environmental Health Perspectives · doi:10.1289/ehp2594 · Cited by 35
Li, W., He, X., Scaioni, M., Yao, D., Mi, C., Jing, Z., Chen, Y., Zhang, K., Gao, J., & Li, X. (2019) · Geomatics Natural Hazards and Risk · doi:10.1080/19475705.2019.1609604 · Cited by 34
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O’Brien, J. P., & Deser, C. (2022) · Journal of Climate · doi:10.1175/jcli-d-22-0101.1 · Cited by 42
Wilson, A. M., & Silander, J. A. (2013) · International Journal of Climatology · doi:10.1002/joc.3859 · Cited by 33
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Kamae, Y., Shiogama, H., Watanabe, M., Ogura, T., Yokohata, T., & Kimoto, M. (2016) · Journal of Climate · doi:10.1175/jcli-d-16-0042.1 · Cited by 33
Kerr, G. H., DeGaetano, A. T., Stoof, C. R., & Ward, D. S. (2016) · Theoretical and Applied Climatology · doi:10.1007/s00704-016-1994-4 · Cited by 33
Wang, B., Liu, D. L., Asseng, S., Macadam, I., YANG, X., & Yu, Q. (2017) · Climate Research · doi:10.3354/cr01458 · Cited by 33
Innocenti, S., Mailhot, A., Leduc, M., Cannon, A. J., & Frigon, A. (2019) · Journal of Geophysical Research Atmospheres · doi:10.1029/2019jd031210 · Cited by 33
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Moise, A. F., Colman, R. A., & Brown, J. R. (2012) · Journal of Geophysical Research Atmospheres · doi:10.1029/2011jd017365 · Cited by 33
Egger, C., & Maurer, M. (2015) · Water Research · doi:10.1016/j.watres.2014.12.050 · Cited by 33
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Preston, B. L., & Jones, R. N. (2008) · Advances in Water Resources · doi:10.1016/j.advwatres.2008.01.006 · Cited by 33
Pauci ex tanto numero: reduce redundancy in multi-model ensembles
Solazzo, E., Riccio, A., Kioutsioukis, I., & Galmarini, S. (2013) · Atmospheric chemistry and physics · doi:10.5194/acp-13-8315-2013 · Cited by 33
McNeall, D., Challenor, P., Gattiker, J., & Stone, E. J. (2013) · Geoscientific model development · doi:10.5194/gmd-6-1715-2013 · Cited by 33
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Metadata
- Authors
- Tebaldi, C., & Knutti, R.
- Affiliations
- NSF National Center for Atmospheric Research (US)
- ETH Zurich (CH)
- Venue
- Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences
- Publisher
- The Royal Society
- Published
- 2007-06-14
- Volume
- 365
- Issue
- 1857
- Pages
- 2053-2075
- ISSN
- 1364-503X (ISSN-L)
- 1471-2962
- OpenAlex
- W2100956194
- Cited by
- 1,862
- References
- 69
- Citations by year
- 2026: 124 · 2025: 115 · 2024: 112 · 2023: 110 · 2022: 132 · 2021: 117 · 2020: 122 · 2019: 121 · 2018: 107 · 2017: 111 · 2016: 116 · 2015: 112 · 2014: 102 · 2013: 82 · 2012: 65
- FWCI
- 35.13
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Environmental Science › Global and Planetary Change › Climate variability and models
- Physical Sciences › Earth and Planetary Sciences › Atmospheric Science › Meteorological Phenomena and Simulations
- Physical Sciences › Environmental Science › Global and Planetary Change › Climate Change and Geoengineering
- Keywords
- multi-model ensemble, probabilistic climate projections, uncertainty quantification, model dependence, model bias, model calibration, climate model intercomparison
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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