The Pliocene Model Intercomparison Project Phase 2: Large-scale climate features and climate sensitivity

Alan M. Haywood, Julia C. Tindall*, Harry J. Dowsett, Aisling M. Dolan, Kevin M. Foley, Stephen J. Hunter, Daniel J. Hill, Wing Le Chan, Ayako Abe-Ouchi, Christian Stepanek, Gerrit Lohmann, Deepak Chandan, W. Richard Peltier, Ning Tan, Camille Contoux, Gilles Ramstein, Xiangyu Li, Zhongshi Zhang, Chuncheng Guo, Kerim H. NisanciogluQiong Zhang, Qiang Li, Youichi Kamae, Mark A. Chandler, Linda E. Sohl, Bette L. Otto-Bliesner, Ran Feng, Esther C. Brady, Anna S. Von Der Heydt, Michiel L.J. Baatsen, Daniel J. Lunt

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

75 Citations (Scopus)


The Pliocene epoch has great potential to improve our understanding of the long-term climatic and environmental consequences of an atmospheric CO2 concentration near ~ 400 parts per million by volume. Here we present the large-scale features of Pliocene climate as simulated by a new ensemble of climate models of varying complexity and spatial resolution based on new reconstructions of boundary conditions (the Pliocene Model Intercomparison Project Phase 2; PlioMIP2). As a global annual average, modelled surface air temperatures increase by between 1.7 and 5.2 °C relative to the pre-industrial era with a multi-model mean value of 3.2 °C. Annual mean total precipitation rates increase by 7 % (range: 2 %-13 %). On average, surface air temperature (SAT) increases by 4.3 °C over land and 2.8 ° C over the oceans. There is a clear pattern of polar amplification with warming polewards of 60° N and 60° S exceeding the global mean warming by a factor of 2.3. In the Atlantic and Pacific oceans, meridional temperature gradients are reduced, while tropical zonal gradients remain largely unchanged. There is a statistically significant relationship between a model's climate response associated with a doubling in CO2 (equilibrium climate sensitivity; ECS) and its simulated Pliocene surface temperature response. The mean ensemble Earth system response to a doubling of CO2 (including ice sheet feedbacks) is 67 % greater than ECS; this is larger than the increase of 47 % obtained from the PlioMIP1 ensemble. Proxy-derived estimates of Pliocene sea surface temperatures are used to assess model estimates of ECS and give an ECS range of 2.6-4.8 °C. This result is in general accord with the ECS range presented by previous Intergovernmental Panel on Climate Change (IPCC) Assessment Reports.

Original languageEnglish
Pages (from-to)2095-2123
Number of pages29
JournalClimate of the Past
Issue number6
Publication statusPublished - 4 Nov 2020

Bibliographical note

Funding Information:
Acknowledgements. We acknowledge the use of NOAA_ERSST_V5 data provided by the NOAA/OAR/ESRL PSD, Boulder, Colorado, USA, from their website at (last access: 12 September 2019). Alan M. Haywood, Julia C. Tindall, Aisling M. Dolan, Stephen J. Hunter and Daniel J. Hill acknowledge the FP7 Ideas programme: European Research Council (grant no. PLIO-ESS, 278636), the Past Earth Network (EPSRC grant no. EP/M008.363/1) and the University of Leeds Advanced Research Computing service. Julia C. Tindall was also supported through the Centre for Environmental Modelling and Computation (CEMAC), University of Leeds. Harry J. Dowsett and Kevin M. Foley acknowledge support from the USGS Climate Research and Development Program. This research used samples and/or data provided by the Ocean Drilling Program (ODP) and International Ocean Discovery Program (IODP). Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. Bette L. Otto-Bliesner, Esther C. Brady and Ran Feng acknowledge that material for their participation is based upon work supported by the National Center for Atmospheric Research, which is a major facility sponsored by the National Science Foundation (NSF) (cooperative agreement no. 1852977 and NSF OPP grant no. 1418411). The CESM project is supported primarily by the National Science Foundation. Computing and data storage resources, including the Cheyenne supercomputer (, were provided by the Computational and Information Systems Laboratory (CISL) at NCAR. NCAR is sponsored by the National Science Foundation. Ning Tan, Camille Contoux and Gilles Ramstein were granted access to the HPC resources of TGCC under the allocations 2016-A0030107732, 2017-R0040110492 and 2018-R0040110492 (gencmip6) and 2019-A0050102212 (gen2212) provided by GENCI. The IPSL-CM6 team of the IPSL Climate Modelling Centre (, last access: 16 September 2020) is acknowledged for having developed, tested, evaluated and tuned the IPSL climate model, as well as per- formed and published the CMIP6 experiments. Christian Stepanek acknowledges funding from the Helmholtz Climate Initiative REKLIM. Christian Stepanek and Gerrit Lohmann acknowledge funding via the Alfred Wegener Institute’s research programme Marine, Coastal and Polar Systems. Qiong Zhang acknowledge support from the Swedish Research Council (2013-06476 and 2017-04232). Simulations with EC-Earth were performed on resources provided by the Swedish National Infrastructure for Computing (SNIC) at the National Supercomputer Centre (NSC). Wing-Le Chan and Ayako Abe-Ouchi acknowledge funding from JSPS (KAKENHI grant no. 17H06104 and MEXT KAKENHI grant no. 17H06323). Their simulations with MIROC4m were performed on the Earth Simulator at JAMSTEC, Yokohama, Japan. The work by Anna S. von der Heydt and Michiel L. J. Baatsen was carried out under the program of the Netherlands Earth System Science Centre (NESSC), financially supported by the Ministry of Education, Culture and Science (OCW grant no. 024.002.001). Simulations with CCSM4-Utr were performed at the SURFsara Dutch national computing facilities and were sponsored by NWO-EW (Netherlands Organisation for Scientific Research, Exact Sciences) (project no. 17189). W. Richard Peltier and Deepak Chandan were supported by Canadian NSERC Discovery Grant A9627, and they wish to acknowledge the support of SciNet HPC Consortium for providing computing facilities. SciNet is funded by the Canada Foundation for Innovation under the auspices of Compute Canada, the Government of Ontario, the Ontario Research Fund – Research Excellence, and the University of Toronto. Xiangyu Li acknowledges financial support from the China Scholarship Council (201804910023) and the China Postdoctoral Science Foundation (project no. 2015M581154). The NorESM simulations benefitted from resources provided by UNINETT Sigma2 – the National Infrastructure for High Performance Computing and Data Storage in Norway. The authors would also like to thank Tim Herbert and an anonymous reviewer for helpful comments on an earlier version of this paper.

Funding Information:
Financial support. This research has been supported by the Past Earth Network (EPSRC grant no. EP/M008.363/1).

Publisher Copyright:
© Author(s) 2020.

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