The DOI matches its Crossref record.
THE WCRP CMIP3 Multimodel Dataset: A New Era in Climate Change Research
Open accessAbstract
A coordinated set of global coupled climate model [atmosphere–ocean general circulation model (AOGCM)] experiments for twentieth- and twenty-first-century climate, as well as several climate change commitment and other experiments, was run by 16 modeling groups from 11 countries with 23 models for assessment in the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4). Since the assessment was completed, output from another model has been added to the dataset, so the participation is now 17 groups from 12 countries with 24 models. This effort, as well as the subsequent analysis phase, was organized by the World Climate Research Programme (WCRP) Climate Variability and Predictability (CLIVAR) Working Group on Coupled Models (WGCM) Climate Simulation Panel, and constitutes the third phase of the Coupled Model Intercomparison Project (CMIP3). The dataset is called the WCRP CMIP3 multimodel dataset, and represents the largest and most comprehensive international global coupled climate model experiment and multimodel analysis effort ever attempted. As of March 2007, the Program for Climate Model Diagnostics and Intercomparison (PCMDI) has collected, archived, and served roughly 32 TB of model data. With oversight from the panel, the multimodel data were made openly available from PCMDI for analysis and academic applications. Over 171 TB of data had been downloaded among the more than 1000 registered users to date. Over 200 journal articles, based in part on the dataset, have been published AMERICAN METEOROLOGICAL SOCIETY so far. Though initially aimed at the IPCC AR4, this unique and valuable resource will continue to be maintained for at least the next several years. Never before has such an extensive set of climate model simulations been made available to the international climate science community for study. The ready access to the multimodel dataset opens up these types of model analyses to researchers, including students, who previously could not obtain state-of-the-art climate model output, and thus represents a new era in climate change research. As a direct consequence, these ongoing studies are increasing the body of knowledge regarding our understanding of how the climate system currently works, and how it may change in the future.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
An Overview of CMIP5 and the Experiment Design
Taylor, K. E., Stouffer, R. J., & Meehl, G. A. (2012) · Bulletin of the American Meteorological Society · doi:10.1175/bams-d-11-00094.1 · Cited by 14,052
Self-citationEyring, V., Bony, S., Meehl, G. A., Senior, C. A., Stevens, B., Stouffer, R. J., & Taylor, K. E. (2016) · Geoscientific Model Development · doi:10.5194/gmd-9-1937-2016 · Cited by 11,981
Self-citationThe Scenario Model Intercomparison Project (ScenarioMIP) for CMIP6
O'Neill, B. C., Tebaldi, C., van Vuuren, D. P., Eyring, V., Friedlingstein, P., Hurtt, G., Knutti, R., Kriegler, E., Lamarque, J.-F., Lowe, J., et al. (2016) · Geoscientific Model Development · doi:10.5194/gmd-9-3461-2016 · Cited by 5,241
“…(SRES; Nakicénovi´c et al., 2000) formed the basis for climate model projections in Phase 3 of the Coupled Model Intercomparison Project (CMIP3; Meehl et al., 2007) and their assessment in the IPCC AR4 Working Group I (IPCC, 2007a), and were used to model impacts on society and ecosystems…”
Self-citationDrought under global warming: a review
Dai, A. (2011) · WIREs Climate Change · doi:10.1002/wcc.81 · Cited by 3,523
Irreversible climate change due to carbon dioxide emissions
Solomon, S., Plattner, G.-K., Knutti, R., & Friedlingstein, P. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0812721106 · Cited by 3,217
Increasing frequency of extreme El Niño events due to greenhouse warming.
Cai, W., Borlace, S., Lengaigne, M., van Rensch, P., Collins, M., Vecchi, G., Timmermann, A., Santoso, A., McPhaden, M. J., Wu, L., et al. (2014) · Nature Climate Change · doi:10.1038/nclimate2100 · Cited by 2,198
Quantifying the influence of climate on human conflict
Hsiang, S. M., Burke, M., & Miguel, E. (2013) · Science · doi:10.1126/science.1235367 · Cited by 1,827
The shared socio-economic pathway (SSP) greenhouse gas concentrations and their extensions to 2500
Meinshausen, M., Nicholls, Z. R. J., Lewis, J., Gidden, M. J., Vogel, E., Freund, M., Beyerle, U., Gessner, C., Nauels, A., Bauer, N., et al. (2020) · Geoscientific Model Development · doi:10.5194/gmd-13-3571-2020 · Cited by 1,815
“…periodically undertakes large model intercomparison exercises with the latest and most sophisticated set of climate models, to gain a better understanding of the response of the climate system to a range of potential emission or concentration scenarios (Taylor et al., 2012; Meehl et al., 2007).”
BackgroundYeh, S.-W., Kug, J.-S., Dewitte, B., Kwon, M.-H., Kirtman, B. P., & Jin, F.-F. (2009) · Nature · doi:10.1038/nature08316 · Cited by 1,592
Robustness and uncertainties in the new CMIP5 climate model projections
Knutti, R., & Sedláček, J. (2013) · Nature Climate Change · doi:10.1038/nclimate1716 · Cited by 1,569
Atmospheric Warming and the Amplification of Precipitation Extremes
Allan, R. P., & Soden, B. J. (2008) · Science · doi:10.1126/science.1160787 · Cited by 1,562
Sillmann, J., Kharin, V. V., Zhang, X., Zwiers, F. W., & Bronaugh, D. (2013) · Journal of Geophysical Research: Atmospheres · doi:10.1002/jgrd.50203 · Cited by 1,461
Challenges in combining projections from multiple climate models.
Knutti, R., Furrer, R., Tebaldi, C., Cermak, J., & Meehl, G. A. (2010) · Journal of Climate · doi:10.1175/2009jcli3361.1 · Cited by 1,270
Self-citationThe impact of global warming on the tropical Pacific Ocean and El Niño
Collins, M., An, S.-I., Cai, W., Ganachaud, A., Guilyardi, E., Jin, F.-F., Jochum, M., Lengaigne, M., Power, S., Timmermann, A., et al. (2010) · Nature Geoscience · doi:10.1038/ngeo868 · Cited by 1,230
Ocean salinities reveal strong global water cycle intensification during 1950 to 2000.
Durack, P. J., Wijffels, S. E., & Matear, R. J. (2012) · Science · doi:10.1126/science.1212222 · Cited by 1,070
Climate change and disruptions to global fire activity
Moritz, M. A., Parisien, M.-A., Batllori, E., Krawchuk, M. A., Van Dorn, J., Ganz, D. J., & Hayhoe, K. (2012) · Ecosphere · doi:10.1890/es11-00345.1 · Cited by 959
Seager, R., Naik, N., & Vecchi, G. A. (2010) · Journal of Climate · doi:10.1175/2010jcli3655.1 · Cited by 925
Perkins, S. E. (2015) · Atmospheric Research · doi:10.1016/j.atmosres.2015.05.014 · Cited by 875
Taking climate model evaluation to the next level
Eyring, V., Cox, P. M., Flato, G. M., Gleckler, P. J., Abramowitz, G., Caldwell, P., Collins, W. D., Gier, B. K., Hall, A. D., Hoffman, F. M., et al. (2019) · Nature Climate Change · doi:10.1038/s41558-018-0355-y · Cited by 748
Self-citationUsing weather data and climate model output in economic analyses of climate change
Auffhammer, M., Hsiang, S. M., Schlenker, W., & Sobel, A. (2013) · Review of Environmental Economics and Policy · doi:10.1093/reep/ret016 · Cited by 662
Burke, M., Hsiang, S. M., & Miguel, E. (2015) · Annual Review of Economics · doi:10.1146/annurev-economics-080614-115430 · Cited by 655
The Detection and Attribution Model Intercomparison Project (DAMIP v1.0) contribution to CMIP6
Gillett, N. P., Shiogama, H., Funke, B., Hegerl, G., Knutti, R., Matthes, K., Santer, B. D., Stone, D., & Tebaldi, C. (2016) · Geoscientific Model Development · doi:10.5194/gmd-9-3685-2016 · Cited by 597
The backbone of the climate network
Donges, J. F., Zou, Y., Marwan, N., & Kurths, J. (2009) · EPL (Europhysics Letters) · doi:10.1209/0295-5075/87/48007 · Cited by 473
McSweeney, C., New, M., Lizcano, G., & Lu, X. (2010) · Bulletin of the American Meteorological Society · doi:10.1175/2009bams2826.1 · Cited by 456
Robust twenty-first-century projections of El Niño and related precipitation variability
Power, S., Delage, F., Chung, C., Kociuba, G., & Keay, K. (2013) · Nature · doi:10.1038/nature12580 · Cited by 448
Forest fire occurrence and climate change in Canada
Wotton, B. M., Nock, C. A., & Flannigan, M. D. (2010) · International Journal of Wildland Fire · doi:10.1071/wf09002 · Cited by 436
Donohoe, A., Marshall, J., Ferreira, D., & Mcgee, D. (2013) · Journal of Climate · doi:10.1175/jcli-d-12-00467.1 · Cited by 404
Extratropical Cooling, Interhemispheric Thermal Gradients, and Tropical Climate Change
Chiang, J. C. H., & Friedman, A. R. (2012) · Annual Review of Earth and Planetary Sciences · doi:10.1146/annurev-earth-042711-105545 · Cited by 379
Mixed responses of tropical Pacific fisheries and aquaculture to climate change
Bell, J. D., Ganachaud, A., Gehrke, P. C., Griffiths, S. P., Hobday, A. J., Hoegh-Guldberg, O., Johnson, J. E., Le Borgne, R., Lehodey, P., Lough, J. M., et al. (2013) · Nature Climate Change · doi:10.1038/nclimate1838 · Cited by 321
Hourdin, F., Foujols, M.-A., Codron, F., Guemas, V., Dufresne, J.-L., Bony, S., Denvil, S., Guez, L., Lott, F., Ghattas, J., et al. (2013) · Climate Dynamics · doi:10.1007/s00382-012-1411-3 · Cited by 302
Diffenbaugh, N. S., & Scherer, M. (2011) · Climatic Change · doi:10.1007/s10584-011-0112-y · Cited by 282
Should we believe model predictions of future climate change?
Knutti, R. (2008) · Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences · doi:10.1098/rsta.2008.0169 · Cited by 279
Pattern scaling: Its strengths and limitations, and an update on the latest model simulations
Tebaldi, C., & Arblaster, J. M. (2014) · Climatic Change · doi:10.1007/s10584-013-1032-9 · Cited by 274
Analysis of the non-linearity in the pattern and time evolution of El Niño southern oscillation
Dommenget, D., Bayr, T., & Frauen, C. (2013) · Climate Dynamics · doi:10.1007/s00382-012-1475-0 · Cited by 252
Ryan, S. J., Lippi, C. A., & Zermoglio, F. (2020) · Malaria Journal · doi:10.1186/s12936-020-03224-6 · Cited by 238
Ma, J., & Xie, S.-P. (2013) · Journal of Climate · doi:10.1175/jcli-d-12-00283.1 · Cited by 233
Intensification of future severe heat waves in India and their effect on heat stress and mortality
Murari, K. K., Ghosh, S., Patwardhan, A., Daly, E., & Salvi, K. (2015) · Regional Environmental Change · doi:10.1007/s10113-014-0660-6 · Cited by 216
A Nonstationary Flood Frequency Analysis Method to Adjust for Future Climate Change and Urbanization
Gilroy, K. L., & McCuen, R. H. (2012) · Journal of Hydrology · doi:10.1016/j.jhydrol.2011.10.009 · Cited by 214
Fiedler, S., Crueger, T., D’Agostino, R., Peters, K., Becker, T., Leutwyler, D., Paccini, L., Burdanowitz, J., Buehler, S. A., Cortes, A. U., et al. (2020) · Monthly Weather Review · doi:10.1175/mwr-d-19-0404.1 · Cited by 166
Giannini, A., Salack, S., Lodoun, T., Ali, A., Gaye, A. T., & Ndiaye, O. (2013) · Environmental Research Letters · doi:10.1088/1748-9326/8/2/024010 · Cited by 178
Response of Tropical Precipitation to Global Warming
Romps, D. M. (2011) · Journal of the Atmospheric Sciences · doi:10.1175/2010jas3542.1 · Cited by 166
Knutson, T. R., Zeng, F., & Wittenberg, A. T. (2013) · Journal of Climate · doi:10.1175/jcli-d-12-00567.1 · Cited by 165
Climate change‐induced shifts in fire for Mediterranean ecosystems
Batllori, E., Parisien, M., Krawchuk, M. A., & Moritz, M. A. (2013) · Global Ecology and Biogeography · doi:10.1111/geb.12065 · Cited by 159
Observed and Projected Hydroclimate Changes in the Andes
Pabón-Caicedo, J. D., Arias, P. A., Carril, A. F., Espinoza, J. C., Borrel, L. F., Goubanova, K., Lavado-Casimiro, W., Masiokas, M., Solman, S., & Villalba, R. (2020) · Frontiers in Earth Science · doi:10.3389/feart.2020.00061 · Cited by 158
Uncertainty of ENSO-amplitude projections in CMIP5 and CMIP6 models
Beobide-Arsuaga, G., Bayr, T., Reintges, A., & Latif, M. (2021) · Climate Dynamics · doi:10.1007/s00382-021-05673-4 · Cited by 149
Self-citationManaging uncertainty in climate-driven ecological models to inform adaptation to climate change
Littell, J. S., McKenzie, D., Kerns, B. K., Cushman, S., & Shaw, C. G. (2011) · Ecosphere · doi:10.1890/es11-00114.1 · Cited by 138
Ramirez-Villegas, J., Cuesta, F., Devenish, C., Peralvo, M., Jarvis, A., & Arnillas, C. A. (2014) · Journal for Nature Conservation · doi:10.1016/j.jnc.2014.03.007 · Cited by 138
Singh, D., Tsiang, M., Rajaratnam, B., & Diffenbaugh, N. S. (2013) · Journal of Geophysical Research: Atmospheres · doi:10.1002/jgrd.50543 · Cited by 137
Biofuels, environmental sustainability and food security: A review of 51 countries
Subramaniam, Y., Masron, T. A., & Azman, N. H. N. (2020) · Energy Research & Social Science · doi:10.1016/j.erss.2020.101549 · Cited by 130
Benchmarking the performance of pairwise homogenization of surface temperatures in the United States
Williams, C. N., Menne, M. J., & Thorne, P. W. (2012) · Journal of Geophysical Research: Atmospheres · doi:10.1029/2011jd016761 · Cited by 121
Projected Changes in East African Rainy Seasons
Cook, K. H., & Vizy, E. K. (2013) · Journal of Climate · doi:10.1175/jcli-d-12-00455.1 · Cited by 121
Lauer, A., & Hamilton, K. (2013) · Journal of Climate · doi:10.1175/jcli-d-12-00451.1 · Cited by 120
Waha, K., Müller, C., & Rolinski, S. (2013) · Global and Planetary Change · doi:10.1016/j.gloplacha.2013.02.009 · Cited by 106
Sensitivity of SWAT simulated streamflow to climatic changes within the Eastern Nile River basin
(2012) · doi:10.5194/hess-16-391-2012 · Cited by 98
Exploring the future change space for fire weather in southeast Australia
Clarke, H., & Evans, J. P. (2019) · Theoretical and Applied Climatology · doi:10.1007/s00704-018-2507-4 · Cited by 98
McMahon, T. A., Peel, M. C., & Karoly, D. J. (2015) · Hydrology and Earth System Sciences · doi:10.5194/hess-19-361-2015 · Cited by 89
Projections of future summertime ozone over the U.S.
Pfister, G. G., Walters, S., Lamarque, J. ‐., Fast, J., Barth, M. C., Wong, J., Done, J., Holland, G., & Bruyère, C. L. (2014) · Journal of Geophysical Research Atmospheres · doi:10.1002/2013jd020932 · Cited by 87
Tuning without over-tuning: parametric uncertainty quantification for the NEMO ocean model
Williamson, D. B., Blaker, A. T., & Sinha, B. (2017) · Geoscientific Model Development · doi:10.5194/gmd-10-1789-2017 · Cited by 75
Seth, A., Thibeault, J., Garcia, M., & Valdivia, C. (2010) · Annals of the Association of American Geographers · doi:10.1080/00045608.2010.500193 · Cited by 72
de Szoeke, S. P., Fairall, C. W., Wolfe, D. E., Bariteau, L., & Zuidema, P. (2010) · Journal of Climate · doi:10.1175/2010jcli3411.1 · Cited by 71
A robust increase in the eddy length scale in the simulation of future climates
Kidston, J., Dean, S. M., Renwick, J. A., & Vallis, G. K. (2010) · Geophysical Research Letters · doi:10.1029/2009gl041615 · Cited by 70
Son, S.-W., Han, B.-R., Garfinkel, C. I., Kim, S.-Y., Park, R., Abraham, N. L., Akiyoshi, H., Archibald, A. T., Butchart, N., Chipperfield, M. P., et al. (2018) · Environmental Research Letters · doi:10.1088/1748-9326/aabf21 · Cited by 58
Critical impacts of global warming on land ecosystems
(2013) · doi:10.5194/esd-4-347-2013 · Cited by 58
Evaluation of CORDEX- South Asia regional climate models for heat wave simulations over India
Singh, S., Mall, R. K., Dadich, J., Verma, S., Singh, J. V., & Gupta, A. (2021) · Atmospheric Research · doi:10.1016/j.atmosres.2020.105228 · Cited by 35
Yue, X., Strada, S., Unger, N., & Wang, A. (2017) · Atmospheric Chemistry and Physics · doi:10.5194/acp-17-13699-2017 · Cited by 31
Helaire, L. T., Talke, S. A., Jay, D. A., & Chang, H. (2020) · Journal of Geophysical Research: Oceans · doi:10.1029/2019jc015928 · Cited by 28
Metadata
- Authors
- Meehl, G. A., Covey, C., Delworth, T., Latif, M., McAvaney, B., Mitchell, J. F. B., Stouffer, R. J., & Taylor, K. E.
- Venue
- Bulletin of the American Meteorological Society
- Publisher
- American Meteorological Society
- Published
- 2007-09-01
- Volume
- 88
- Issue
- 9
- Pages
- 1383-1394
- ISSN
- 0003-0007 (ISSN-L)
- 1520-0477
- OpenAlex
- W2062217294
- Cited by
- 2,826
- References
- 0
- FWCI
- 101.38
- Type
- journal article
- Language
- en
- Open access
- bronze
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.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.