Articles | Volume 18, issue 8
https://doi.org/10.5194/cp-18-1883-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/cp-18-1883-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
18 Aug 2022
Research article |
| 18 Aug 2022
| 18 Aug 2022
A new global surface temperature reconstruction for the Last Glacial Maximum
James D. Annan
CORRESPONDING AUTHOR
Blue Skies Research Ltd, The Old Chapel, Albert Hill, Settle, BD24 9HE, UK
Julia C. Hargreaves
Blue Skies Research Ltd, The Old Chapel, Albert Hill, Settle, BD24 9HE, UK
Thorsten Mauritsen
Department of Meteorology, Stockholm University, Stockholm, Sweden
Related authors
James D. Annan, Julia C. Hargreaves, Thorsten Mauritsen, Erin McClymont, and Sze Ling Ho
Clim. Past, 20, 1989–1999, https://doi.org/10.5194/cp-20-1989-2024, https://doi.org/10.5194/cp-20-1989-2024, 2024
Short summary
Short summary
We have created a new global surface temperature reconstruction of the climate of the mid-Pliocene Warm Period, representing the period roughly 3.2 million years before the present day. We estimate that the globally averaged mean temperature was around 3.9 °C warmer than it was in pre-industrial times, but there is significant uncertainty in this value.
Chris M. Brierley, Anni Zhao, Sandy P. Harrison, Pascale Braconnot, Charles J. R. Williams, David J. R. Thornalley, Xiaoxu Shi, Jean-Yves Peterschmitt, Rumi Ohgaito, Darrell S. Kaufman, Masa Kageyama, Julia C. Hargreaves, Michael P. Erb, Julien Emile-Geay, Roberta D'Agostino, Deepak Chandan, Matthieu Carré, Partrick J. Bartlein, Weipeng Zheng, Zhongshi Zhang, Qiong Zhang, Hu Yang, Evgeny M. Volodin, Robert A. Tomas, Cody Routson, W. Richard Peltier, Bette Otto-Bliesner, Polina A. Morozova, Nicholas P. McKay, Gerrit Lohmann, Allegra N. Legrande, Chuncheng Guo, Jian Cao, Esther Brady, James D. Annan, and Ayako Abe-Ouchi
Clim. Past, 16, 1847–1872, https://doi.org/10.5194/cp-16-1847-2020, https://doi.org/10.5194/cp-16-1847-2020, 2020
Short summary
Short summary
This paper provides an initial exploration and comparison to climate reconstructions of the new climate model simulations of the mid-Holocene (6000 years ago). These use state-of-the-art models developed for CMIP6 and apply the same experimental set-up. The models capture several key aspects of the climate, but some persistent issues remain.
Martin Renoult, James Douglas Annan, Julia Catherine Hargreaves, Navjit Sagoo, Clare Flynn, Marie-Luise Kapsch, Qiang Li, Gerrit Lohmann, Uwe Mikolajewicz, Rumi Ohgaito, Xiaoxu Shi, Qiong Zhang, and Thorsten Mauritsen
Clim. Past, 16, 1715–1735, https://doi.org/10.5194/cp-16-1715-2020, https://doi.org/10.5194/cp-16-1715-2020, 2020
Short summary
Short summary
Interest in past climates as sources of information for the climate system has grown in recent years. In particular, studies of the warm mid-Pliocene and cold Last Glacial Maximum showed relationships between the tropical surface temperature of the Earth and its sensitivity to an abrupt doubling of atmospheric CO2. In this study, we develop a new and promising statistical method and obtain similar results as previously observed, wherein the sensitivity does not seem to exceed extreme values.
Thomas Hocking, Linda Megner, Maria Hakuba, and Thorsten Mauritsen
EGUsphere, https://doi.org/10.5194/egusphere-2025-829, https://doi.org/10.5194/egusphere-2025-829, 2025
Short summary
Short summary
The imbalance between the energy the Earth absorbs from the Sun and emits back to space gives rise to climate change, but measuring the small imbalance is challenging. The Earth surface reflects sunlight more in some directions than in others, as with e.g. ocean sunglint. We simulate satellites to investigate how this uneven reflection impacts estimates of the imbalance. We identify orbits that cover all directions well, so that the impact is small.
Hans Segura, Xabier Pedruzo-Bagazgoitia, Philipp Weiss, Sebastian K. Müller, Thomas Rackow, Junhong Lee, Edgar Dolores-Tesillos, Imme Benedict, Matthias Aengenheyster, Razvan Aguridan, Gabriele Arduini, Alexander J. Baker, Jiawei Bao, Swantje Bastin, Eulàlia Baulenas, Tobias Becker, Sebastian Beyer, Hendryk Bockelmann, Nils Brüggemann, Lukas Brunner, Suvarchal K. Cheedela, Sushant Das, Jasper Denissen, Ian Dragaud, Piotr Dziekan, Madeleine Ekblom, Jan Frederik Engels, Monika Esch, Richard Forbes, Claudia Frauen, Lilli Freischem, Diego García-Maroto, Philipp Geier, Paul Gierz, Álvaro González-Cervera, Katherine Grayson, Matthew Griffith, Oliver Gutjahr, Helmuth Haak, Ioan Hadade, Kerstin Haslehner, Shabeh ul Hasson, Jan Hegewald, Lukas Kluft, Aleksei Koldunov, Nikolay Koldunov, Tobias Kölling, Shunya Koseki, Sergey Kosukhin, Josh Kousal, Peter Kuma, Arjun U. Kumar, Rumeng Li, Nicolas Maury, Maximilian Meindl, Sebastian Milinski, Kristian Mogensen, Bimochan Niraula, Jakub Nowak, Divya Sri Praturi, Ulrike Proske, Dian Putrasahan, René Redler, David Santuy, Domokos Sármány, Reiner Schnur, Patrick Scholz, Dmitry Sidorenko, Dorian Spät, Birgit Sützl, Daisuke Takasuka, Adrian Tompkins, Alejandro Uribe, Mirco Valentini, Menno Veerman, Aiko Voigt, Sarah Warnau, Fabian Wachsmann, Marta Wacławczyk, Nils Wedi, Karl-Hermann Wieners, Jonathan Wille, Marius Winkler, Yuting Wu, Florian Ziemen, Janos Zimmermann, Frida A.-M. Bender, Dragana Bojovic, Sandrine Bony, Simona Bordoni, Patrice Brehmer, Marcus Dengler, Emanuel Dutra, Saliou Faye, Erich Fischer, Chiel van Heerwaarden, Cathy Hohenegger, Heikki Järvinen, Markus Jochum, Thomas Jung, Johann H. Jungclaus, Noel S. Keenlyside, Daniel Klocke, Heike Konow, Martina Klose, Szymon Malinowski, Olivia Martius, Thorsten Mauritsen, Juan Pedro Mellado, Theresa Mieslinger, Elsa Mohino, Hanna Pawłowska, Karsten Peters-von Gehlen, Abdoulaye Sarré, Pajam Sobhani, Philip Stier, Lauri Tuppi, Pier Luigi Vidale, Irina Sandu, and Bjorn Stevens
EGUsphere, https://doi.org/10.5194/egusphere-2025-509, https://doi.org/10.5194/egusphere-2025-509, 2025
Short summary
Short summary
The nextGEMS project developed two Earth system models that resolve processes of the order of 10 km, giving more fidelity to the representation of local phenomena, globally. In its fourth cycle, nextGEMS performed simulations with coupled ocean, land, and atmosphere over the 2020–2049 period under the SSP3-7.0 scenario. Here, we provide an overview of nextGEMS, insights into the model development, and the realism of multi-decadal, kilometer-scale simulations.
Thomas Hocking, Thorsten Mauritsen, and Linda Megner
Atmos. Meas. Tech., 17, 7077–7095, https://doi.org/10.5194/amt-17-7077-2024, https://doi.org/10.5194/amt-17-7077-2024, 2024
Short summary
Short summary
The imbalance between the energy the Earth absorbs from the Sun and the energy the Earth emits back into space gives rise to climate change, but measuring the small imbalance is challenging. We simulate satellites in various orbits to investigate how well they sample the imbalance and find that the best option is to combine at least two satellites that see complementary parts of the Earth and cover the daily and annual cycles. This information is useful when planning future satellite missions.
Alejandro Uribe, Frida A.-M. Bender, and Thorsten Mauritsen
Atmos. Chem. Phys., 24, 13371–13384, https://doi.org/10.5194/acp-24-13371-2024, https://doi.org/10.5194/acp-24-13371-2024, 2024
Short summary
Short summary
Our study explores climate feedbacks, vital for understanding global warming. It links them to shifts in Earth's energy balance at the atmosphere's top due to natural temperature variations. It takes roughly 50 years to establish this connection. Combined satellite observations and reanalysis suggest that Earth cools more than expected under carbon dioxide influence. However, continuous satellite data until at least the mid-2030s are crucial for refining our understanding of climate feedbacks.
Andrea Mosso, Thomas Hocking, and Thorsten Mauritsen
Atmos. Chem. Phys., 24, 12793–12806, https://doi.org/10.5194/acp-24-12793-2024, https://doi.org/10.5194/acp-24-12793-2024, 2024
Short summary
Short summary
Clouds play a crucial role in the Earth's energy balance, as they can either warm up or cool down the area they cover depending on their height and depth. They are expected to alter their behaviour under climate change, affecting the warming generated by greenhouse gases. This paper proposes a new method to estimate their overall effect on this warming by simulating a climate where clouds are transparent. Results show that with the model used, clouds have a stabilising effect on climate.
Martin Renoult, Navjit Sagoo, Johannes Hörner, and Thorsten Mauritsen
EGUsphere, https://doi.org/10.5194/egusphere-2024-2981, https://doi.org/10.5194/egusphere-2024-2981, 2024
Short summary
Short summary
Geological evidence indicate persistent tropical sea-ice cover in the deep past, often called Snowball Earth. Using a climate model, we show here that clouds substantially cool down the tropics and facilitate the advance of sea-ice into lower latitudes. We identify a critical threshold temperature of 0 °C from where cooling down the Earth is accelerated. This value can be used as a constraint on Earth's sensitivity to CO2, as recent cold paleoclimates never entered Snowball Earth.
Antoine Hermant, Linnea Huusko, and Thorsten Mauritsen
Atmos. Chem. Phys., 24, 10707–10715, https://doi.org/10.5194/acp-24-10707-2024, https://doi.org/10.5194/acp-24-10707-2024, 2024
Short summary
Short summary
Aerosol particles, from natural and human sources, have a cooling effect on the climate, partially offsetting global warming. They do this through direct (sunlight reflection) and indirect (cloud property alteration) mechanisms. Using a global climate model, we found that, despite declining emissions, the direct effect of human aerosols has increased while the indirect effect has decreased, which is attributed to the shift in emissions from North America and Europe to Southeast Asia.
James D. Annan, Julia C. Hargreaves, Thorsten Mauritsen, Erin McClymont, and Sze Ling Ho
Clim. Past, 20, 1989–1999, https://doi.org/10.5194/cp-20-1989-2024, https://doi.org/10.5194/cp-20-1989-2024, 2024
Short summary
Short summary
We have created a new global surface temperature reconstruction of the climate of the mid-Pliocene Warm Period, representing the period roughly 3.2 million years before the present day. We estimate that the globally averaged mean temperature was around 3.9 °C warmer than it was in pre-industrial times, but there is significant uncertainty in this value.
Raphael Grodofzig, Martin Renoult, and Thorsten Mauritsen
Earth Syst. Dynam., 15, 913–927, https://doi.org/10.5194/esd-15-913-2024, https://doi.org/10.5194/esd-15-913-2024, 2024
Short summary
Short summary
We investigate whether the Amazon rainforest has lost substantial resilience since 1990. This assertion is based on trends in the observational record of vegetation density. We calculate the same metrics in a large number of climate model simulations and find that several models behave indistinguishably from the observations, suggesting that the observed trend could be caused by internal variability and that the cause of the ongoing rapid loss of Amazon rainforest is not mainly global warming.
Clare Marie Flynn, Linnea Huusko, Angshuman Modak, and Thorsten Mauritsen
Atmos. Chem. Phys., 23, 15121–15133, https://doi.org/10.5194/acp-23-15121-2023, https://doi.org/10.5194/acp-23-15121-2023, 2023
Short summary
Short summary
The latest-generation climate models show surprisingly cold mid-20th century global-mean temperatures, often despite exhibiting more realistic late 20th/early 21st century temperatures. A too-strong aerosol forcing in many models was thought to the be primary cause of these too-cold mid-century temperatures, but this was found to only be a partial explanation. This also partly undermines the hope to construct a strong relationship between the mid-century temperatures and aerosol forcing.
Sushant Das, Frida Bender, and Thorsten Mauritsen
EGUsphere, https://doi.org/10.5194/egusphere-2023-1605, https://doi.org/10.5194/egusphere-2023-1605, 2023
Preprint archived
Short summary
Short summary
Quantifying global and Indian precipitation responses to anthropogenic aerosol and CO2 forcings using multiple models is needed for reducing climate uncertainty. The response to global warming from CO2 increases precipitation both globally and over India, whereas the cooling response to sulfate aerosol leads to a reduction in precipitation in both cases. An opposite response to black carbon is noted i.e., a global decrease but an increase of precipitation over India implying changes in dynamics.
Angshuman Modak and Thorsten Mauritsen
Atmos. Chem. Phys., 23, 7535–7549, https://doi.org/10.5194/acp-23-7535-2023, https://doi.org/10.5194/acp-23-7535-2023, 2023
Short summary
Short summary
We provide an improved estimate of equilibrium climate sensitivity (ECS) constrained based on the instrumental temperature record including the corrections for the pattern effect. The improved estimate factors in the uncertainty caused by the underlying sea-surface temperature datasets used in the estimates of pattern effect. This together with the inter-model spread lifts the corresponding IPCC AR6 estimate to 3.2 K [1.8 to 11.0], which is lower and better constrained than in past studies.
Martin Renoult, Navjit Sagoo, Jiang Zhu, and Thorsten Mauritsen
Clim. Past, 19, 323–356, https://doi.org/10.5194/cp-19-323-2023, https://doi.org/10.5194/cp-19-323-2023, 2023
Short summary
Short summary
The relationship between the Last Glacial Maximum and the sensitivity of climate models to a doubling of CO2 can be used to estimate the true sensitivity of the Earth. However, this relationship has varied in successive model generations. In this study, we assess multiple processes at the Last Glacial Maximum which weaken this relationship. For example, how models respond to the presence of ice sheets is a large contributor of uncertainty.
Cathy Hohenegger, Peter Korn, Leonidas Linardakis, René Redler, Reiner Schnur, Panagiotis Adamidis, Jiawei Bao, Swantje Bastin, Milad Behravesh, Martin Bergemann, Joachim Biercamp, Hendryk Bockelmann, Renate Brokopf, Nils Brüggemann, Lucas Casaroli, Fatemeh Chegini, George Datseris, Monika Esch, Geet George, Marco Giorgetta, Oliver Gutjahr, Helmuth Haak, Moritz Hanke, Tatiana Ilyina, Thomas Jahns, Johann Jungclaus, Marcel Kern, Daniel Klocke, Lukas Kluft, Tobias Kölling, Luis Kornblueh, Sergey Kosukhin, Clarissa Kroll, Junhong Lee, Thorsten Mauritsen, Carolin Mehlmann, Theresa Mieslinger, Ann Kristin Naumann, Laura Paccini, Angel Peinado, Divya Sri Praturi, Dian Putrasahan, Sebastian Rast, Thomas Riddick, Niklas Roeber, Hauke Schmidt, Uwe Schulzweida, Florian Schütte, Hans Segura, Radomyra Shevchenko, Vikram Singh, Mia Specht, Claudia Christine Stephan, Jin-Song von Storch, Raphaela Vogel, Christian Wengel, Marius Winkler, Florian Ziemen, Jochem Marotzke, and Bjorn Stevens
Geosci. Model Dev., 16, 779–811, https://doi.org/10.5194/gmd-16-779-2023, https://doi.org/10.5194/gmd-16-779-2023, 2023
Short summary
Short summary
Models of the Earth system used to understand climate and predict its change typically employ a grid spacing of about 100 km. Yet, many atmospheric and oceanic processes occur on much smaller scales. In this study, we present a new model configuration designed for the simulation of the components of the Earth system and their interactions at kilometer and smaller scales, allowing an explicit representation of the main drivers of the flow of energy and matter by solving the underlying equations.
Jule Radtke, Thorsten Mauritsen, and Cathy Hohenegger
Atmos. Chem. Phys., 21, 3275–3288, https://doi.org/10.5194/acp-21-3275-2021, https://doi.org/10.5194/acp-21-3275-2021, 2021
Short summary
Short summary
Shallow trade wind clouds are a key source of uncertainty to projections of the Earth's changing climate. We perform high-resolution simulations of trade cumulus and investigate how the representation and climate feedback of these clouds depend on the specific grid spacing. We find that the cloud feedback is positive when simulated with kilometre but near zero when simulated with hectometre grid spacing. These findings suggest that storm-resolving models may exaggerate the trade cloud feedback.
Chris M. Brierley, Anni Zhao, Sandy P. Harrison, Pascale Braconnot, Charles J. R. Williams, David J. R. Thornalley, Xiaoxu Shi, Jean-Yves Peterschmitt, Rumi Ohgaito, Darrell S. Kaufman, Masa Kageyama, Julia C. Hargreaves, Michael P. Erb, Julien Emile-Geay, Roberta D'Agostino, Deepak Chandan, Matthieu Carré, Partrick J. Bartlein, Weipeng Zheng, Zhongshi Zhang, Qiong Zhang, Hu Yang, Evgeny M. Volodin, Robert A. Tomas, Cody Routson, W. Richard Peltier, Bette Otto-Bliesner, Polina A. Morozova, Nicholas P. McKay, Gerrit Lohmann, Allegra N. Legrande, Chuncheng Guo, Jian Cao, Esther Brady, James D. Annan, and Ayako Abe-Ouchi
Clim. Past, 16, 1847–1872, https://doi.org/10.5194/cp-16-1847-2020, https://doi.org/10.5194/cp-16-1847-2020, 2020
Short summary
Short summary
This paper provides an initial exploration and comparison to climate reconstructions of the new climate model simulations of the mid-Holocene (6000 years ago). These use state-of-the-art models developed for CMIP6 and apply the same experimental set-up. The models capture several key aspects of the climate, but some persistent issues remain.
Martin Renoult, James Douglas Annan, Julia Catherine Hargreaves, Navjit Sagoo, Clare Flynn, Marie-Luise Kapsch, Qiang Li, Gerrit Lohmann, Uwe Mikolajewicz, Rumi Ohgaito, Xiaoxu Shi, Qiong Zhang, and Thorsten Mauritsen
Clim. Past, 16, 1715–1735, https://doi.org/10.5194/cp-16-1715-2020, https://doi.org/10.5194/cp-16-1715-2020, 2020
Short summary
Short summary
Interest in past climates as sources of information for the climate system has grown in recent years. In particular, studies of the warm mid-Pliocene and cold Last Glacial Maximum showed relationships between the tropical surface temperature of the Earth and its sensitivity to an abrupt doubling of atmospheric CO2. In this study, we develop a new and promising statistical method and obtain similar results as previously observed, wherein the sensitivity does not seem to exceed extreme values.
Cited articles
Annan, J. and Hargreaves, J.: A perspective on model-data surface temperature
comparison at the Last Glacial Maximum, Quaternary Sci. Rev., 107,
1–10, 2015. a
Annan, J. D. and Hargreaves, J. C.: On the meaning of independence in climate science, Earth Syst. Dynam., 8, 211–224, https://doi.org/10.5194/esd-8-211-2017, 2017. a, b
Braconnot, P., Otto-Bliesner, B., Harrison, S., Joussaume, S., Peterchmitt, J.-Y., Abe-Ouchi, A., Crucifix, M., Driesschaert, E., Fichefet, Th., Hewitt, C. D., Kageyama, M., Kitoh, A., Laîné, A., Loutre, M.-F., Marti, O., Merkel, U., Ramstein, G., Valdes, P., Weber, S. L., Yu, Y., and Zhao, Y.: Results of PMIP2 coupled simulations of the Mid-Holocene and Last Glacial Maximum – Part 1: experiments and large-scale features, Clim. Past, 3, 261–277, https://doi.org/10.5194/cp-3-261-2007, 2007. a, b
Bartlein, P., Harrison, S., Brewer, S., Connor, S., Davis, B., Gajewski, K.,
Guiot, J., Harrison-Prentice, T., Henderson, A., Peyron, O., Prentice, I. C.,
Scholze, M., Seppaä, H., Shuman, B., Sugita, S., Thompson, R. S., Viau,
A. E., Williams, J., and Wu, H.: Pollen-based continental climate
reconstructions at 6 and 21 ka: a global synthesis, Clim. Dynam., 37,
775–802, 2011. a, b, c, d, e, f, g, h
Braconnot, P., Harrison, S. P., Kageyama, M., Bartlein, P. J., Masson-Delmotte,
V., Abe-Ouchi, A., Otto-Bliesner, B., and Zhao, Y.: Evaluation of climate
models using palaeoclimatic data, Nat. Clim. Change, 2, 417–424, 2012. a
Burgers, G., van Leeuwen, P. J., and Evensen, G.: On the analysis scheme in the
ensemble Kalman filter, Mon. Weather Rev., 126, 1719–1724, 1998. a
Conkright, M., Levitus, S., O’Brien, T., Boyer, T., Antonov, J., and
Stephens, C.: World ocean atlas 1998, National Oceanographic Data Center
(NODC) Internal Report, Silver Spring, Maryland,
http://ingrid.ldeo.columbia.edu/SOURCES/.NOAA/.NODC/.WOA98/ (last access: 24 February 2021),
1998. a
Evensen, G.: The ensemble Kalman filter: theoretical formulation and practical
implementation, Ocean Dynam., 53, 343–367, 2003. a
Gaspari, G. and Cohn, S. E.: Construction of correlation functions in two and
three dimensions, Q. J. Roy. Meteorol. Soc., 125, 723–757, 1999. a
Hamill, T.: Interpretation of rank histograms for verifying ensemble
forecasts, Mon. Weather Rev., 129, 550–560, 2001. a
Huang, B., Thorne, P. W., Banzon, V. F., Boyer, T., Chepurin, G., Lawrimore,
J. H., Menne, M. J., Smith, T. M., Vose, R. S., and Zhang, H.-M.: NOAA
extended reconstructed sea surface temperature (ERSST), version 5, NOAA
National Centers for Environmental Information, 30, 8179–8205, 2017. a
Kageyama, M., Braconnot, P., Harrison, S. P., Haywood, A. M., Jungclaus, J. H.,
Otto-Bliesner, B. L., Peterschmitt, J.-Y., Abe-Ouchi, A., Albani, S.,
Bartlein, P. J., Brierley, C., Crucifix, M., Dolan, A., Fernandez-Donado, L.,
Fischer, H., Hopcroft, P. O., Ivanovic, R. F., Lambert, F., Lunt, D. J.,
Mahowald, N. M., Peltier, W. R., Phipps, S. J., Roche, D. M., Schmidt, G. A.,
Tarasov, L., Valdes, P. J., Zhang, Q., and Zhou, T.: The PMIP4 contribution
to CMIP6 – Part 1: Overview and over-arching analysis plan, Geosc.
Model Dev., 11, 1033–1057, https://doi.org/10.5194/gmd-11-1033-2018, 2018. a
Kageyama, M., Harrison, S. P., Kapsch, M.-L., Lofverstrom, M., Lora, J. M.,
Mikolajewicz, U., Sherriff-Tadano, S., Vadsaria, T., Abe-Ouchi, A., Bouttes,
N., Chandan, D., Gregoire, L. J., Ivanovic, R. F., Izumi, K., LeGrande,
A. N., Lhardy, F., Lohmann, G., Morozova, P. A., Ohgaito, R., Paul, A.,
Peltier, W. R., Poulsen, C. J., Quiquet, A., Roche, D. M., Shi, X., Tierney,
J. E., Valdes, P. J., Volodin, E., and Zhu, J.: The PMIP4 Last Glacial
Maximum experiments: preliminary results and comparison with the PMIP3
simulations, Clim. Past, 17, 1065–1089,
https://doi.org/10.5194/cp-17-1065-2021, 2021. a
Kalman, R. E.: A new approach to linear filtering and prediction problems, J.
Basic Eng. D, 82, 33–45, 1960. a
Kirchgessner, P., Nerger, L., and Bunse-Gerstner, A.: On the choice of an
optimal localization radius in ensemble Kalman filter methods, Mon.
Weather Rev., 142, 2165–2175, 2014. a
Knutti, R.: The end of model democracy?, J. Clim., 102, 395–404,
https://doi.org/10.1007/s10584-010-9800-2, 2010. a
Knutti, R., Masson, D., and Gettelman, A.: Climate model genealogy: Generation
CMIP5 and how we got there, Geophys. Res. Lett., 40, 1194–1199,
2013. a
Kurahashi-Nakamura, T., Paul, A., and Losch, M.: Dynamical reconstruction of
the global ocean state during the Last Glacial Maximum, Paleoceanography, 32,
326–350, https://doi.org/10.1002/2016PA003001, 2017. a
MARGO Project Members: Constraints on the magnitude and patterns of ocean
cooling at the Last Glacial Maximum, Nat. Geosci., 2, 127–132,
https://doi.org/10.1038/NGEO411, 2009. a, b
Parsons, L. A., Amrhein, D. E., Sanchez, S. C., Tardif, R., Brennan, M. K., and
Hakim, G. J.: Do Multi-Model Ensembles Improve Reconstruction Skill in
Paleoclimate Data Assimilation?, Earth Space Sci., 8, e2020EA001467, https://doi.org/10.1029/2020EA001467,
2021. a
Paul, A., Mulitza, S., Stein, R., and Werner, M.: A global climatology of the
ocean surface during the Last Glacial Maximum mapped on a regular grid
(GLOMAP), Clim. Past, 17, 805–824, https://doi.org/10.5194/cp-17-805-2021,
2021. a
Peterschmitt, J. Y. and PMIP modellers: PMIP4 climatological fields,
https://dods.lsce.ipsl.fr/cgi-bin/nph-dods/pmip1db/, last access: 24 February 2021. a
PMIP modellers: The PMIP2 database,
https://pmip2.lsce.ipsl.fr/database/access/opendap.shtml (last access: 24 February 2021),
1998. a
PMIP modellers: The PMIP3 database held on ESGF,
https://esgf-node.llnl.gov/search/cmip5/ (last access: 24 February 2021), 2017. a
Rind, D. and Peteet, D.: Terrestrial conditions at the Last Glacial
Maximum and CLIMAP sea-surface temperature estimates: Are they
consistent?, Quaternary Res., 24, 1–22, 1985. a
Schmidt, G. A., Annan, J. D., Bartlein, P. J., Cook, B. I., Guilyardi, E., Hargreaves, J. C., Harrison, S. P., Kageyama, M., LeGrande, A. N., Konecky, B., Lovejoy, S., Mann, M. E., Masson-Delmotte, V., Risi, C., Thompson, D., Timmermann, A., Tremblay, L.-B., and Yiou, P.: Using palaeo-climate comparisons to constrain future projections in CMIP5, Clim. Past, 10, 221–250, https://doi.org/10.5194/cp-10-221-2014, 2014. a
Schneider von Deimling, T., Held, H., Ganopolski, A., and Rahmstorf, S.:
Climate sensitivity estimated from ensemble simulations of glacial climate,
Clim. Dynam., 27, 149–163, 2006. a
Sherwood, S., Webb, M. J., Annan, J. D., Armour, K., Forster, P. M.,
Hargreaves, J. C., Hegerl, G., Klein, S. A., Marvel, K. D., Rohling, E. J.,
Watanabe, M., Andrews, T., Braconnot, P., Bretherton, C. S., Foster, G. L., Hausfather, Z., von der Heydt, A. S., Knutti, R., Mauritsen, T., Norris, J. R., Proistosescu, C., Rugenstein, M., Schmidt, G. A., Tokarska, K. B., and Zelinka, M. D.: An assessment of Earth's climate sensitivity using multiple lines of
evidence, Rev. Geophys., 58, e2019RG000678, https://doi.org/10.1029/2019RG000678, 2020. a, b
Tebaldi, C. and Knutti, R.: The use of the multi-model ensemble in
probabilistic climate projections, Philos. T. R.
Soc. A, 365,
2053–2075, 2007. a
Tokarska, K. B., Stolpe, M. B., Sippel, S., Fischer, E. M., Smith, C. J.,
Lehner, F., and Knutti, R.: Past warming trend constrains future warming in
CMIP6 models, Sci. Adv., 6, eaaz9549, https://doi.org/10.1126/sciadv.aaz9549,
2020. a
Yokohata, T., Annan, J., Collins, M., Jackson, C., Tobis, M., Webb, M. J., and
Hargreaves, J. C.: Reliability of multi-model and structurally different
single-model ensembles, Clim. Dynam., 39, 599–616,
https://doi.org/10.1007/s00382-011-1203-1, 2011. a
Yokohata, T., Annan, J. D., Collins, M., Jackson, C. S., Shiogama, H.,
Watanabe, M., Emori, S., Yoshimori, M., Abe, M., Webb, M., and
Hargreaves, J.:
Reliability and importance of structural diversity of climate model
ensembles, Clim. Dynam., 41, 1–19, 2013. a
Zhu, J., Otto‐Bliesner, B. L., Brady, E. C., Poulsen, C. J., Tierney, J. E.,
Lofverstrom, M., and DiNezio, P.: Assessment of Equilibrium Climate
Sensitivity of the Community Earth System Model Version 2
Through Simulation of the Last Glacial Maximum, Geophys.
Res. Lett., 48, e2020GL091220, https://doi.org/10.1029/2020GL091220, 2021. a
Short summary
We have created a new global surface temperature reconstruction of the climate of the Last Glacial Maximum, representing the period 19–23 000 years before the present day. We find that the globally averaged mean temperature was roughly 4.5 °C colder than it was in pre-industrial times, albeit there is significant uncertainty on this value.
We have created a new global surface temperature reconstruction of the climate of the Last...
