Geosci. Model Dev., 12, 3149–3206, 2019 https://doi.org/10.5194/gmd-12-3149-2019 © Author(s) 2019. This work is distributed under the Creative Commons Attribution 4.0 License. The DeepMIP contribution to PMIP4: methodologies for selection, compilation and analysis of latest Paleocene and early Eocene climate proxy data, incorporating version 0.1 of the DeepMIP database Christopher J. Hollis1, Tom Dunkley Jones2, Eleni Anagnostou3,4, Peter K. Bijl5, Margot J. Cramwinckel5, Ying Cui6, Gerald R. Dickens7, Kirsty M. Edgar2, Yvette Eley2, David Evans8, Gavin L. Foster3, Joost Frieling5, Gordon N. Inglis9, Elizabeth M. Kennedy1, Reinhard Kozdon10, Vittoria Lauretano9, Caroline H. Lear11, Kate Littler12, Lucas Lourens5, A. Nele Meckler13, B. David A. Naafs9, Heiko Pälike14, Richard D. Pancost9, Paul N. Pearson11, Ursula Röhl14, Dana L. Royer15, Ulrich Salzmann16, Brian A. Schubert17, Hannu Seebeck1, Appy Sluijs5, Robert P. Speijer18, Peter Stassen18, Jessica Tierney19, Aradhna Tripati20, Bridget Wade21, Thomas Westerhold14, Caitlyn Witkowski22, James C. Zachos23, Yi Ge Zhang24, Matthew Huber25, and Daniel J. Lunt26 1GNS Science, Lower Hutt, New Zealand 2School of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham, UK 3Ocean and Earth Science, National Oceanography Centre Southampton, University of Southampton, Southampton, UK 4GEOMAR Helmholtz Centre for Ocean Research, Kiel, Kiel, Germany 5Department of Earth Sciences, Faculty of Geosciences, Utrecht University, Utrecht, the Netherlands 6Department of Earth and Environmental Studies, Montclair State University, Montclair, New Jersey, USA 7Department of Earth, Environmental and Planetary Sciences, Rice University, Houston, Texas, USA 8Institute of Geosciences, Goethe University Frankfurt, Frankfurt am Main, Frankfurt, Germany 9School of Chemistry & School of Earth Sciences, University of Bristol, Bristol, UK 10Lamont–Doherty Earth Observatory of Columbia University, Pallisades, New York, USA 11School of Earth and Ocean Sciences, Cardiff University, Cardiff, UK 12Camborne School of Mines & Environment and Sustainability Institute, University of Exeter, Exeter, UK 13Bjerknes Centre for Climate Research and Department of Earth Science, University of Bergen, Bergen, Norway 14MARUM – Center for Marine and Environmental Sciences, University of Bremen, Bremen, Germany 15Department of Earth & Environmental Sciences, Wesleyan University, Middletown, Connecticut, USA 16Department of Geography, Northumbria University, Newcastle, UK 17School of Geosciences, University of Louisiana at Lafayette, Louisiana, Lafayette, USA 18Department of Earth and Environmental Sciences, KU Leuven, Leuven, Belgium 19Department of Geosciences, University of Arizona, Tucson, Arizona, USA 20Department of Earth and Planetary Sciences, Institute of the Environment and Sustainability, Department of Atmospheric and Oceanic Sciences, Center for Diverse Leadership in Science, University of California, Los Angeles, California, USA 21Department of Earth Sciences, University College London, London, UK 22Department of Marine Microbiology and Biogeochemistry (MMB), NIOZ Royal Netherlands Institute for Sea Research and Utrecht University, Den Burg, the Netherlands 23Earth and Planetary Sciences Department, University of California, Santa Cruz, California, USA 24Department of Oceanography, Texas A&M University, College Station, Texas, USA 25Department of Earth, Atmospheric, and Planetary Sciences, Purdue University, West Lafayette, Indiana, USA 26School of Geographical Sciences, University of Bristol, Bristol, UK Correspondence: Christopher J. Hollis ([email protected]) Published by Copernicus Publications on behalf of the European Geosciences Union. 3150 C. J. Hollis et al.: The DeepMIP contribution to PMIP4 Received: 10 December 2018 – Discussion started: 17 January 2019 Revised: 23 June 2019 – Accepted: 3 July 2019 – Published: 25 July 2019 Abstract. The early Eocene (56 to 48 million years ago) is greater confidence in their skill in predicting our future cli- inferred to have been the most recent time that Earth’s at- mate. Similarly, differences between models and data could mospheric CO2 concentrations exceeded 1000 ppm. Global indicate aspects of models and/or data that require further mean temperatures were also substantially warmer than those development. of the present day. As such, the study of early Eocene cli- This is the rationale behind DeepMIP – the Deep-time mate provides insight into how a super-warm Earth system Model Intercomparison Project (https://www.deepmip.org/, behaves and offers an opportunity to evaluate climate models last access: 30 June 2019) – which brings together climate under conditions of high greenhouse gas forcing. The Deep modelers and paleoclimatologists from a wide range of disci- Time Model Intercomparison Project (DeepMIP) is a system- plines in a coordinated, international effort to improve under- atic model–model and model–data intercomparison of three standing of the climate of these time intervals, to improve the early Paleogene time slices: latest Paleocene, Paleocene– skill of climate models, and to improve the accuracy and pre- Eocene thermal maximum (PETM) and early Eocene cli- cision of climate proxies. The term “deep-time” as applied matic optimum (EECO). A previous article outlined the here refers to the history of Earth prior to the Pliocene, or be- model experimental design for climate model simulations. fore 5 million years ago (Ma). DeepMIP is a working group In this article, we outline the methodologies to be used for in the wider Paleoclimate Modelling Intercomparison Project the compilation and analysis of climate proxy data, primarily (PMIP4), which itself is a part of the sixth phase of the Cou- proxies for temperature and CO2. This paper establishes the pled Model Intercomparison Project (CMIP6). In DeepMIP, protocols for a concerted and coordinated effort to compile we focus on three warm greenhouse time periods in the latest the climate proxy records across a wide geographic range. Paleocene and early Eocene (∼ 57–48 Ma), and for the first The resulting climate “atlas” will be used to constrain and time, carry out formal coordinated model–model and model– evaluate climate models for the three selected time intervals proxy intercomparisons. and provide insights into the mechanisms that control these We previously have outlined the model experimental de- warm climate states. We provide version 0.1 of this database, sign of this project (Lunt et al., 2017). Here we outline the in anticipation that this will be expanded in subsequent pub- recommended methodologies for selection, compilation and lications. analysis of climate proxy datasets for three selected time intervals: latest Paleocene (LP), Paleocene–Eocene ther- mal maximum (PETM) and early Eocene climatic opti- 1 Introduction mum (EECO). Section 2 outlines previous compilations, and Sect. 3 formally defines the time periods of interest. Sec- Over much of the last 100 million years of Earth’s history, tions 4 and 5 describe the proxies for sea surface and land greenhouse gas levels and global temperatures were higher air temperature (SST and LAT), respectively. Section 6 de- than those of the present day (Zachos et al., 2008; Foster et scribes the proxies for atmospheric carbon dioxide (CO2). al., 2017). Because greenhouse gas levels are currently well For each proxy, we highlight the underlying science, the above anything experienced during the modern natural cli- strengths and weaknesses, and recommendations for analyt- mate state, ancient climate archives hold important clues to ical methodologies. We focus on temperature in this article our possible future climate (IPCC, 2013). This is particu- because it is the most commonly and readily reconstructed larly true for those past times when climate was consider- climatic variable and it is one of the most accurately rep- ably warmer and greenhouse gas levels considerably higher resented variables in climate models. When combined with than those of the present day. For instance, such intervals can CO2, it allows assessment of climate sensitivity, a key met- provide information about the sensitivity of the climate to ric that integrates the behavior of the whole Earth system. greenhouse gas forcing (e.g., Rohling et al., 2012; Zeebe, However, the DeepMIP database will provide a structure for 2013; Caballero and Huber, 2013; Anagnostou et al., 2016) future compilations of other climate proxies, such as precip- or reveal the behavior of carbon cycle feedbacks under super- itation, evaporation, salinity, upwelling, bathymetry, circu- warm climate states (e.g., Carmichael et al., 2017). These lation, currents and vegetation cover, but these are not dis- times of past warmth also provide a powerful means to test cussed or compiled here. Section 7 outlines the structure of the outputs of climate models because they represent actual the planned DeepMIP database, which will accommodate the realizations of how the Earth system functions under condi- data presented in Supplement Data Files 2–7 (which consti- tions of greenhouse forcing comparable to the coming cen- tute Version 0.1 of the database) and additional datasets as tury and beyond. If the models can match the geological they become available. Section 8 presents a preliminary syn- evidence of the prevailing climatic conditions, we can have thesis of the paleotemperature data from these tables and in- Geosci. Model Dev., 12, 3149–3206, 2019 www.geosci-model-dev.net/12/3149/2019/