Articles | Volume 15, issue 6
https://doi.org/10.5194/gmd-15-2475-2022
© 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/gmd-15-2475-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Analysing the PMIP4-CMIP6 collection: a workflow and tool (pmip_p2fvar_analyzer v1)
Department of Geography, University College London, London, WC1E 6BT, UK
Chris M. Brierley
Department of Geography, University College London, London, WC1E 6BT, UK
Zhiyi Jiang
Department of Geography, University College London, London, WC1E 6BT, UK
Rachel Eyles
Department of Geography, University College London, London, WC1E 6BT, UK
Damián Oyarzún
Department of Geography, University College London, London, WC1E 6BT, UK
Jose Gomez-Dans
Department of Geography, University College London, London, WC1E 6BT, UK
Related authors
Anni Zhao, Chris Brierley, Venni Arra, Xiaoxu Shi, and Yongyun Hu
EGUsphere, https://doi.org/10.5194/egusphere-2025-3140, https://doi.org/10.5194/egusphere-2025-3140, 2025
This preprint is open for discussion and under review for Climate of the Past (CP).
Short summary
Short summary
The North Atlantic Oscillation has large impacts on the European climate, whose future behaviour remains uncertain. We assess the NAO response in three past experiments (midHolocene, lig127k, lgm) and an abrupt quadrupled CO2 scenario (abrupt4xCO2). Our results show that NAO weakens (enhances) in response to cooling (warming), while it is not sensitive to orbital configurations. The associated teleconnections change consistently with the theory and are sensitive to the change in NAO amplitude.
Anni Zhao, Ran Feng, Chris M. Brierley, Jian Zhang, and Yongyun Hu
Clim. Past, 20, 1195–1211, https://doi.org/10.5194/cp-20-1195-2024, https://doi.org/10.5194/cp-20-1195-2024, 2024
Short summary
Short summary
We analyse simulations with idealised aerosol scenarios to examine the importance of aerosol forcing on mPWP precipitation and how aerosol uncertainty could explain the data–model mismatch. We find further warming, a narrower and stronger ITCZ, and monsoon domain rainfall change after removal of industrial emissions. Aerosols have more impacts on tropical precipitation than the mPWP boundary conditions. This highlights the importance of prescribed aerosol scenarios in simulating mPWP climate.
Xiaoxu Shi, Martin Werner, Carolin Krug, Chris M. Brierley, Anni Zhao, Endurance Igbinosa, Pascale Braconnot, Esther Brady, Jian Cao, Roberta D'Agostino, Johann Jungclaus, Xingxing Liu, Bette Otto-Bliesner, Dmitry Sidorenko, Robert Tomas, Evgeny M. Volodin, Hu Yang, Qiong Zhang, Weipeng Zheng, and Gerrit Lohmann
Clim. Past, 18, 1047–1070, https://doi.org/10.5194/cp-18-1047-2022, https://doi.org/10.5194/cp-18-1047-2022, 2022
Short summary
Short summary
Since the orbital parameters of the past are different from today, applying the modern calendar to the past climate can lead to an artificial bias in seasonal cycles. With the use of multiple model outputs, we found that such a bias is non-ignorable and should be corrected to ensure an accurate comparison between modeled results and observational records, as well as between simulated past and modern climates, especially for the Last Interglacial.
Bette L. Otto-Bliesner, Esther C. Brady, Anni Zhao, Chris M. Brierley, Yarrow Axford, Emilie Capron, Aline Govin, Jeremy S. Hoffman, Elizabeth Isaacs, Masa Kageyama, Paolo Scussolini, Polychronis C. Tzedakis, Charles J. R. Williams, Eric Wolff, Ayako Abe-Ouchi, Pascale Braconnot, Silvana Ramos Buarque, Jian Cao, Anne de Vernal, Maria Vittoria Guarino, Chuncheng Guo, Allegra N. LeGrande, Gerrit Lohmann, Katrin J. Meissner, Laurie Menviel, Polina A. Morozova, Kerim H. Nisancioglu, Ryouta O'ishi, David Salas y Mélia, Xiaoxu Shi, Marie Sicard, Louise Sime, Christian Stepanek, Robert Tomas, Evgeny Volodin, Nicholas K. H. Yeung, Qiong Zhang, Zhongshi Zhang, and Weipeng Zheng
Clim. Past, 17, 63–94, https://doi.org/10.5194/cp-17-63-2021, https://doi.org/10.5194/cp-17-63-2021, 2021
Short summary
Short summary
The CMIP6–PMIP4 Tier 1 lig127k experiment was designed to address the climate responses to strong orbital forcing. We present a multi-model ensemble of 17 climate models, most of which have also completed the CMIP6 DECK experiments and are thus important for assessing future projections. The lig127ksimulations show strong summer warming over the NH continents. More than half of the models simulate a retreat of the Arctic minimum summer ice edge similar to the average for 2000–2018.
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.
Josephine R. Brown, Chris M. Brierley, Soon-Il An, Maria-Vittoria Guarino, Samantha Stevenson, Charles J. R. Williams, Qiong Zhang, Anni Zhao, Ayako Abe-Ouchi, Pascale Braconnot, Esther C. Brady, Deepak Chandan, Roberta D'Agostino, Chuncheng Guo, Allegra N. LeGrande, Gerrit Lohmann, Polina A. Morozova, Rumi Ohgaito, Ryouta O'ishi, Bette L. Otto-Bliesner, W. Richard Peltier, Xiaoxu Shi, Louise Sime, Evgeny M. Volodin, Zhongshi Zhang, and Weipeng Zheng
Clim. Past, 16, 1777–1805, https://doi.org/10.5194/cp-16-1777-2020, https://doi.org/10.5194/cp-16-1777-2020, 2020
Short summary
Short summary
El Niño–Southern Oscillation (ENSO) is the largest source of year-to-year variability in the current climate, but the response of ENSO to past or future changes in climate is uncertain. This study compares the strength and spatial pattern of ENSO in a set of climate model simulations in order to explore how ENSO changes in different climates, including past cold glacial climates and past climates with different seasonal cycles, as well as gradual and abrupt future warming cases.
Anni Zhao, Chris Brierley, Venni Arra, Xiaoxu Shi, and Yongyun Hu
EGUsphere, https://doi.org/10.5194/egusphere-2025-3140, https://doi.org/10.5194/egusphere-2025-3140, 2025
This preprint is open for discussion and under review for Climate of the Past (CP).
Short summary
Short summary
The North Atlantic Oscillation has large impacts on the European climate, whose future behaviour remains uncertain. We assess the NAO response in three past experiments (midHolocene, lig127k, lgm) and an abrupt quadrupled CO2 scenario (abrupt4xCO2). Our results show that NAO weakens (enhances) in response to cooling (warming), while it is not sensitive to orbital configurations. The associated teleconnections change consistently with the theory and are sensitive to the change in NAO amplitude.
Mara Y. McPartland, Tomas Lovato, Charles D. Koven, Jamie D. Wilson, Briony Turner, Colleen M. Petrik, José Licón-Saláiz, Fang Li, Fanny Lhardy, Jaclyn Clement Kinney, Michio Kawamiya, Birgit Hassler, Nathan P. Gillett, Cheikh Modou Noreyni Fall, Christopher Danek, Chris M. Brierley, Ana Bastos, and Oliver Andrews
EGUsphere, https://doi.org/10.5194/egusphere-2025-3246, https://doi.org/10.5194/egusphere-2025-3246, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Short summary
The Coupled Model Intercomparison Project (CMIP) is an international consortium of climate modeling groups that produce coordinated experiments in order to evaluate human influence on the climate and test knowledge of Earth systems. This paper describes the data requested for Earth systems research in CMIP7. We detail the request for model output of the carbon cycle, the flows of energy among the atmosphere, land and the oceans, and interactions between these and the global climate.
Philip E. Lewis, Feng Yin, Jose Luis Gómez-Dans, Thomas Weiß, and Elhadi Adam
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., X-3-2024, 199–206, https://doi.org/10.5194/isprs-annals-X-3-2024-199-2024, https://doi.org/10.5194/isprs-annals-X-3-2024-199-2024, 2024
Anni Zhao, Ran Feng, Chris M. Brierley, Jian Zhang, and Yongyun Hu
Clim. Past, 20, 1195–1211, https://doi.org/10.5194/cp-20-1195-2024, https://doi.org/10.5194/cp-20-1195-2024, 2024
Short summary
Short summary
We analyse simulations with idealised aerosol scenarios to examine the importance of aerosol forcing on mPWP precipitation and how aerosol uncertainty could explain the data–model mismatch. We find further warming, a narrower and stronger ITCZ, and monsoon domain rainfall change after removal of industrial emissions. Aerosols have more impacts on tropical precipitation than the mPWP boundary conditions. This highlights the importance of prescribed aerosol scenarios in simulating mPWP climate.
Tom Keel, Chris Brierley, and Tamsin Edwards
Geosci. Model Dev., 17, 1229–1247, https://doi.org/10.5194/gmd-17-1229-2024, https://doi.org/10.5194/gmd-17-1229-2024, 2024
Short summary
Short summary
Jet streams are an important control on surface weather as their speed and shape can modify the properties of weather systems. Establishing trends in the operation of jet streams may provide some indication of the future of weather in a warming world. Despite this, it has not been easy to establish trends, as many methods have been used to characterise them in data. We introduce a tool containing various implementations of jet stream statistics and algorithms that works in a standardised manner.
Dominik Rains, Isabel Trigo, Emanuel Dutra, Sofia Ermida, Darren Ghent, Petra Hulsman, Jose Gómez-Dans, and Diego G. Miralles
Earth Syst. Sci. Data, 16, 567–593, https://doi.org/10.5194/essd-16-567-2024, https://doi.org/10.5194/essd-16-567-2024, 2024
Short summary
Short summary
Land surface temperature and surface net radiation are vital inputs for many land surface and hydrological models. However, current remote sensing datasets of these variables come mostly at coarse resolutions, and the few high-resolution datasets available have large gaps due to cloud cover. Here, we present a continuous daily product for both variables across Europe for 2018–2019 obtained by combining observations from geostationary as well as polar-orbiting satellites.
Chris Brierley, Kaustubh Thirumalai, Edward Grindrod, and Jonathan Barnsley
Clim. Past, 19, 681–701, https://doi.org/10.5194/cp-19-681-2023, https://doi.org/10.5194/cp-19-681-2023, 2023
Short summary
Short summary
Year-to-year variations in the weather conditions over the Indian Ocean have important consequences for the substantial fraction of the Earth's population that live near it. This work looks at how these variations respond to climate change – both past and future. The models rarely agree, suggesting a weak, uncertain response to climate change.
Zhiyi Jiang, Chris Brierley, David Thornalley, and Sophie Sax
Clim. Past, 19, 107–121, https://doi.org/10.5194/cp-19-107-2023, https://doi.org/10.5194/cp-19-107-2023, 2023
Short summary
Short summary
This work looks at a series of model simulations of two past warm climates. We focus on the deep overturning circulation in the Atlantic Ocean. We show that there are no robust changes in the overall strength of the circulation. We also show that the circulation hardly plays a role in changes in the surface climate across the globe.
Jose Luis Gómez-Dans, Philip Edward Lewis, Feng Yin, Kofi Asare, Patrick Lamptey, Kenneth Kobina Yedu Aidoo, Dilys Sefakor MacCarthy, Hongyuan Ma, Qingling Wu, Martin Addi, Stephen Aboagye-Ntow, Caroline Edinam Doe, Rahaman Alhassan, Isaac Kankam-Boadu, Jianxi Huang, and Xuecao Li
Earth Syst. Sci. Data, 14, 5387–5410, https://doi.org/10.5194/essd-14-5387-2022, https://doi.org/10.5194/essd-14-5387-2022, 2022
Short summary
Short summary
We provide a data set to support mapping croplands in smallholder landscapes in Ghana. The data set contains information on crop location on three agroecological zones for 2 years, temporal series of measurements of leaf area index and leaf chlorophyll concentration for maize canopies and yield. We demonstrate the use of these data to validate cropland masks, create a maize mask using satellite data and explore the relationship between satellite measurements and yield.
Feng Yin, Philip E. Lewis, and Jose L. Gómez-Dans
Geosci. Model Dev., 15, 7933–7976, https://doi.org/10.5194/gmd-15-7933-2022, https://doi.org/10.5194/gmd-15-7933-2022, 2022
Short summary
Short summary
The proposed SIAC atmospheric correction method provides consistent surface reflectance estimations from medium spatial-resolution satellites (Sentinel 2 and Landsat 8) with per-pixel uncertainty information. The outputs from SIAC have been validated against a wide range of ground measurements, and it shows that SIAC can provide accurate estimations of both surface reflectance and atmospheric parameters, with meaningful uncertainty information.
Xiaoxu Shi, Martin Werner, Carolin Krug, Chris M. Brierley, Anni Zhao, Endurance Igbinosa, Pascale Braconnot, Esther Brady, Jian Cao, Roberta D'Agostino, Johann Jungclaus, Xingxing Liu, Bette Otto-Bliesner, Dmitry Sidorenko, Robert Tomas, Evgeny M. Volodin, Hu Yang, Qiong Zhang, Weipeng Zheng, and Gerrit Lohmann
Clim. Past, 18, 1047–1070, https://doi.org/10.5194/cp-18-1047-2022, https://doi.org/10.5194/cp-18-1047-2022, 2022
Short summary
Short summary
Since the orbital parameters of the past are different from today, applying the modern calendar to the past climate can lead to an artificial bias in seasonal cycles. With the use of multiple model outputs, we found that such a bias is non-ignorable and should be corrected to ensure an accurate comparison between modeled results and observational records, as well as between simulated past and modern climates, especially for the Last Interglacial.
Maryam Ilyas, Douglas Nychka, Chris Brierley, and Serge Guillas
Atmos. Meas. Tech., 14, 7103–7121, https://doi.org/10.5194/amt-14-7103-2021, https://doi.org/10.5194/amt-14-7103-2021, 2021
Short summary
Short summary
Instrumental temperature records are fundamental to climate science. There are spatial gaps in the distribution of these measurements across the globe. This lack of spatial coverage introduces coverage error. In this research, a methodology is developed and used to quantify the coverage errors. It results in a data product that, for the first time, provides a full description of both the spatial coverage uncertainties along with the uncertainties in the modeling of these spatial gaps.
Alexander Koch, Chris Brierley, and Simon L. Lewis
Biogeosciences, 18, 2627–2647, https://doi.org/10.5194/bg-18-2627-2021, https://doi.org/10.5194/bg-18-2627-2021, 2021
Short summary
Short summary
Estimates of large-scale tree planting and forest restoration as a carbon sequestration tool typically miss a crucial aspect: the Earth system response to the increased land carbon sink from new vegetation. We assess the impact of tropical forest restoration using an Earth system model under a scenario that limits warming to 2 °C. Almost two-thirds of the carbon impact of forest restoration is offset by negative carbon cycle feedbacks, suggesting a more modest benefit than in previous studies.
Bette L. Otto-Bliesner, Esther C. Brady, Anni Zhao, Chris M. Brierley, Yarrow Axford, Emilie Capron, Aline Govin, Jeremy S. Hoffman, Elizabeth Isaacs, Masa Kageyama, Paolo Scussolini, Polychronis C. Tzedakis, Charles J. R. Williams, Eric Wolff, Ayako Abe-Ouchi, Pascale Braconnot, Silvana Ramos Buarque, Jian Cao, Anne de Vernal, Maria Vittoria Guarino, Chuncheng Guo, Allegra N. LeGrande, Gerrit Lohmann, Katrin J. Meissner, Laurie Menviel, Polina A. Morozova, Kerim H. Nisancioglu, Ryouta O'ishi, David Salas y Mélia, Xiaoxu Shi, Marie Sicard, Louise Sime, Christian Stepanek, Robert Tomas, Evgeny Volodin, Nicholas K. H. Yeung, Qiong Zhang, Zhongshi Zhang, and Weipeng Zheng
Clim. Past, 17, 63–94, https://doi.org/10.5194/cp-17-63-2021, https://doi.org/10.5194/cp-17-63-2021, 2021
Short summary
Short summary
The CMIP6–PMIP4 Tier 1 lig127k experiment was designed to address the climate responses to strong orbital forcing. We present a multi-model ensemble of 17 climate models, most of which have also completed the CMIP6 DECK experiments and are thus important for assessing future projections. The lig127ksimulations show strong summer warming over the NH continents. More than half of the models simulate a retreat of the Arctic minimum summer ice edge similar to the average for 2000–2018.
Wesley de Nooijer, Qiong Zhang, Qiang Li, Qiang Zhang, Xiangyu Li, Zhongshi Zhang, Chuncheng Guo, Kerim H. Nisancioglu, Alan M. Haywood, Julia C. Tindall, Stephen J. Hunter, Harry J. Dowsett, Christian Stepanek, Gerrit Lohmann, Bette L. Otto-Bliesner, Ran Feng, Linda E. Sohl, Mark A. Chandler, Ning Tan, Camille Contoux, Gilles Ramstein, Michiel L. J. Baatsen, Anna S. von der Heydt, Deepak Chandan, W. Richard Peltier, Ayako Abe-Ouchi, Wing-Le Chan, Youichi Kamae, and Chris M. Brierley
Clim. Past, 16, 2325–2341, https://doi.org/10.5194/cp-16-2325-2020, https://doi.org/10.5194/cp-16-2325-2020, 2020
Short summary
Short summary
The simulations for the past climate can inform us about the performance of climate models in different climate scenarios. Here, we analyse Arctic warming in an ensemble of 16 simulations of the mid-Pliocene Warm Period (mPWP), when the CO2 level was comparable to today. The results highlight the importance of slow feedbacks in the model simulations and imply that we must be careful when using simulations of the mPWP as an analogue for future climate change.
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.
Josephine R. Brown, Chris M. Brierley, Soon-Il An, Maria-Vittoria Guarino, Samantha Stevenson, Charles J. R. Williams, Qiong Zhang, Anni Zhao, Ayako Abe-Ouchi, Pascale Braconnot, Esther C. Brady, Deepak Chandan, Roberta D'Agostino, Chuncheng Guo, Allegra N. LeGrande, Gerrit Lohmann, Polina A. Morozova, Rumi Ohgaito, Ryouta O'ishi, Bette L. Otto-Bliesner, W. Richard Peltier, Xiaoxu Shi, Louise Sime, Evgeny M. Volodin, Zhongshi Zhang, and Weipeng Zheng
Clim. Past, 16, 1777–1805, https://doi.org/10.5194/cp-16-1777-2020, https://doi.org/10.5194/cp-16-1777-2020, 2020
Short summary
Short summary
El Niño–Southern Oscillation (ENSO) is the largest source of year-to-year variability in the current climate, but the response of ENSO to past or future changes in climate is uncertain. This study compares the strength and spatial pattern of ENSO in a set of climate model simulations in order to explore how ENSO changes in different climates, including past cold glacial climates and past climates with different seasonal cycles, as well as gradual and abrupt future warming cases.
Cited articles
Adler, R. F., Huffman, G. J., Chang, A., Ferraro, R., Xie, P.-P., Janowiak, J.,
Rudolf, B., Schneider, U., Curtis, S., Bolvin, D., Gruber, A., Susskind, J.,
Arkin, P., and Nelkin, E.: The version-2 global precipitation climatology
project (GPCP) monthly precipitation analysis (1979–present), J.
Hydrometeorol., 4, 1147–1167,
https://doi.org/10.1175/1525-7541(2003)004<1147:TVGPCP>2.0.CO;2, 2003. a
Andrews, T., Gregory, J. M., Webb, M. J., and Taylor, K. E.: Forcing, feedbacks
and climate sensitivity in CMIP5 coupled atmosphere-ocean climate models,
Geophys. Res. Lett., 39, L09712, https://doi.org/10.1029/2012GL051607, 2012. a
Arias, P. A., Bellouin, N., Coppola, E., Jones, R. G., Krinner, G., Marotzke,
J., Naik, V., Palmer, M. D., Plattner, G.-K., Rogelj, J., Rojas, M.,
Sillmann, J., Storelvmo, T., Thorne, P. W., Trewin, B., Achuta Rao, K.,
Adhikary, B., Allan, R. P., Armour, K., Bala, G., Barimalala, R., Berger, S.,
Canadell, J. G., Cassou, C., Cherchi, A., Collins, W., Collins, W. D.,
Connors, S. L., Corti, S., Cruz, F., Dentener, F. J., Dereczynski, C.,
Di Luca, A., Diongue Niang, A., Doblas-Reyes, F. J., Dosio, A., Douville, H.,
Engelbrecht, F., Eyring, V., Fischer, E., Forster, P., Fox-Kemper, B.,
Fuglestvedt, J. S., Fyfe, J. C., Gillett, N. P., Goldfarb, L., Gorodetskaya,
I., Gutierrez, J. M., Hamdi, R., Hawkins, E., Hewitt, H. T., Hope, P., Islam,
A. S., Jones, C., Kaufman, D. S., Kopp, R. E., Kosaka, Y., Kossin, J.,
Krakovska, S., Lee, J.-Y., Li, J., Mauritsen, T., Maycock, T. K.,
Meinshausen, M., Min, S.-K., Monteiro, P. M. S., Ngo-Duc, T., Otto, F.,
Pinto, I., Pirani, A., Raghavan, K., Ranasinghe, R., Ruane, A. C., Ruiz, L.,
Sallée, J.-B., Samset, B. H., Sathyendranath, S., Seneviratne, S. I.,
Sörensson, A. A., Szopa, S., Takayabu, I., Treguier, A.-M., van den Hurk,
B., Vautard, R., von Schuckmann, K., Zaehle, S., Zhang, X., and Zickfeld, K.:
Technical Summary, in: Climate Change 2021: The Physical Science Basis.
Contribution of Working Group I to the Sixth Assessment Report of the
Intergovernmental Panel on Climate Change, edited by: Masson-Delmotte, V.,
Zhai, P., Pirani, A., Connors, S. L., Péan, C., Berger, S., Caud, N., Chen,
Y., Goldfarb, L., Gomis, M. I., Huang, M., Leitzell, K., Lonnoy, E.,
Matthews, J., Maycock, T. K., Waterfield, T., Yelekçi, O., Yu, R., and
Zhou, B., Cambridge University Press, in press, 2022. a
Balaji, V., Taylor, K. E., Juckes, M., Lawrence, B. N., Durack, P. J., Lautenschlager, M., Blanton, C., Cinquini, L., Denvil, S., Elkington, M., Guglielmo, F., Guilyardi, E., Hassell, D., Kharin, S., Kindermann, S., Nikonov, S., Radhakrishnan, A., Stockhause, M., Weigel, T., and Williams, D.: Requirements for a global data infrastructure in support of CMIP6, Geosci. Model Dev., 11, 3659–3680, https://doi.org/10.5194/gmd-11-3659-2018, 2018. a
Bartlein, P.: pjbartlein/PaleoCalAdjust: (v1.1), Zenodo [code], https://doi.org/10.5281/zenodo.1478824, 2021. a
Bartlein, P. and Brierley, C.: pmip4/PaleoCalAdjust: Publishing revisions associated with Zhao et al. manuscript (v1.0.Zhaoetal), Zenodo [code], https://doi.org/10.5281/zenodo.5931062, 2022. a
Bartlein, P. J. and Shafer, S. L.: Paleo calendar-effect adjustments in time-slice and transient climate-model simulations (PaleoCalAdjust v1.0): impact and strategies for data analysis, Geosci. Model Dev., 12, 3889–3913, https://doi.org/10.5194/gmd-12-3889-2019, 2019. a, b
Bartlein, P. J., Harrison, S., Brewer, S., Connor, S., Davis, B., Gajewski, K.,
Guiot, J., Harrison-Prentice, T., Henderson, A., and Peyron, O.: Pollen-based
continental climate reconstructions at 6 and 21 ka: a global synthesis,
Clim. Dynam., 37, 775–802, https://doi.org/10.1007/s00382-010-0904-1, 2011. a
Boettiger, C. and Eddelbuettel, D.: An Introduction to Rocker: Docker
Containers for R, The R Journal, 9, 527–536, https://doi.org/10.32614/RJ-2017-065,
2017. a
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,
https://doi.org/10.1038/nclimate1456, 2012. a
Braconnot, P., Zhu, D., Marti, O., and Servonnat, J.: Strengths and challenges for transient Mid- to Late Holocene simulations with dynamical vegetation, Clim. Past, 15, 997–1024, https://doi.org/10.5194/cp-15-997-2019, 2019. a
Brierley, C.: pmip4/UCL_curated_ESGF_replica: Publishing status associated with Zhao et al. manuscript (Version v1), Zenodo [code], https://doi.org/10.5281/zenodo.5931086, 2022. a
Brierley, C. M., Zhao, A., Harrison, S. P., Braconnot, P., Williams, C. J. R., Thornalley, D. J. R., Shi, X., Peterschmitt, J.-Y., Ohgaito, R., Kaufman, D. S., Kageyama, M., Hargreaves, J. C., Erb, M. P., Emile-Geay, J., D'Agostino, R., Chandan, D., Carré, M., Bartlein, P. J., Zheng, W., Zhang, Z., Zhang, Q., Yang, H., Volodin, E. M., Tomas, R. A., Routson, C., Peltier, W. R., Otto-Bliesner, B., Morozova, P. A., McKay, N. P., Lohmann, G., Legrande, A. N., Guo, C., Cao, J., Brady, E., Annan, J. D., and Abe-Ouchi, A.: Large-scale features and evaluation of the PMIP4-CMIP6 midHolocene simulations, Clim. Past, 16, 1847–1872, https://doi.org/10.5194/cp-16-1847-2020, 2020. a, b, c, d, e, f, g, h, i, j, k, l, m, n, o, p
Brown, J. R., Brierley, C. M., An, S.-I., Guarino, M.-V., Stevenson, S., Williams, C. J. R., Zhang, Q., Zhao, A., Abe-Ouchi, A., Braconnot, P., Brady, E. C., Chandan, D., D'Agostino, R., Guo, C., LeGrande, A. N., Lohmann, G., Morozova, P. A., Ohgaito, R., O'ishi, R., Otto-Bliesner, B. L., Peltier, W. R., Shi, X., Sime, L., Volodin, E. M., Zhang, Z., and Zheng, W.: Comparison of past and future simulations of ENSO in CMIP5/PMIP3 and CMIP6/PMIP4 models, Clim. Past, 16, 1777–1805, https://doi.org/10.5194/cp-16-1777-2020, 2020. a, b, c, d, e
Christensen, J., Krishna Kumar, K., Aldrian, E., An, S.-I., Cavalcanti, I.,
de Castro, M., Dong, W.and Goswami, P., Hall, A., Kanyanga, J., Kitoh, A.,
Kossin, J., Lau, N.-C., Renwick, J., Stephenson, D., Xie, S.-P., and Zhou,
T.: Climate phenomena and their relevance for future regional climate change,
in: Climate change 2013: the physical science basis. Contribution of Working
Group I to the Fifth Assessment Report of the Intergovernmental Panel on
Climate Change, edited by: Stocker, T., Qin, D., Plattner, G.-K., Tignor, M.,
Allen, S., Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley, P.,
1217–1308, Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 2013. a, b
Collins, M., Knutti, R., Arblaster, J., Dufresne, J.-L., Fichefet, T.,
Friedlingstein, P., Gao, X., Gutowski, W. J., Johns, T., Krinner, G.,
Shongwe, M., Tebaldi, C., Weaver, A., and Wehner, M.: Long-term climate
change: projections, commitments and irreversibility, in: Climate Change
2013-The Physical Science Basis: Contribution of Working Group I to the Fifth
Assessment Report of the Intergovernmental Panel on Climate Change, edited by:
Stocker, T., Qin, D., Plattner, G.-K., Tignor, M., Allen, S., Boschung, J.,
Nauels, A., Xia, Y., Bex, V., and Midgley, P., 1029–1136, Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 2013. a, b
Danabasoglu, G., Yeager, S. G., Kwon, Y.-O., Tribbia, J. J., Phillips, A. S.,
and Hurrell, J. W.: Variability of the Atlantic meridional overturning
circulation in CCSM4, J. Climate, 25, 5153–5172, 2012. a
Douville, H., Raghavan, K., Renwick, J., Allan, R. P., Arias, P. A., Barlow,
M., Cerezo-Mota, R., Cherchi, A., Gan, T. Y., Gergis, J., Jiang, D., Khan,
A., Pokam Mba, W., Rosenfeld, D., Tierney, J., and Zolina, O.: Water Cycle
Changes, in: Climate Change 2021: The Physical Science Basis. Contribution of
Working Group I to the Sixth Assessment Report of the Intergovernmental Panel
on Climate Change, edited by: Masson-Delmotte, V., Zhai, P., Pirani, A.,
Connors, S. L., Péan, C., Berger, S., Caud, N., Chen, Y., Goldfarb, L.,
Gomis, M. I., Huang, M., Leitzell, K., Lonnoy, E., Matthews, J., Maycock,
T. K., Waterfield, T., Yelekçi, O., Yu, R., and Zhou, B., Cambridge
University Press, in press, 2022. a, b
Eyring, V., Bony, S., Meehl, G. A., Senior, C. A., Stevens, B., Stouffer, R. J., and Taylor, K. E.: Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization, Geosci. Model Dev., 9, 1937–1958, https://doi.org/10.5194/gmd-9-1937-2016, 2016. a, b, c
Eyring, V., Gillett, N. P., Achuta Rao, K. M., Barimalala, R.,
Barreiro Parrillo, M., Bellouin, N., Cassou, C., Durack, P. J., Kosaka, Y.,
McGregor, S., Min, S., Morgenstern, O., and Sun, Y.: Human Influence on the
Climate System, in: Climate Change 2021: The Physical Science Basis.
Contribution of Working Group I to the Sixth Assessment Report of the
Intergovernmental Panel on Climate Change, edited by: Masson-Delmotte, V.,
Zhai, P., Pirani, A., Connors, S. L., Péan, C., Berger, S., Caud, N., Chen,
Y., Goldfarb, L., Gomis, M. I., Huang, M., Leitzell, K., Lonnoy, E.,
Matthews, J., Maycock, T. K., Waterfield, T., Yelekçi, O., Yu, R, and
Zhou, B., Cambridge University Press, in press, 2021. a, b, c, d, e, f, g
Fasullo, J. T., Phillips, A., and Deser, C.: Evaluation of leading modes of
climate variability in the CMIP archives, J. Climate, 33, 5527–5545,
https://doi.org/10.1175/JCLI-D-19-1024.1, 2020. a
Fox-Kemper, B., Hewitt, H. T., Xiao, C., Aðalgeirsdóttir, G., Drijfhout,
S. S., Edwards, T. L., Golledge, N. R., Hemer, M., Kopp, R. E., Krinner, G.,
Mix, A., Notz, D., Nowicki, S., Nurhati, I. S., Ruiz, L., Sallée, J.-B.,
Slangen, A. B. A., and Yu, Y.: Ocean, Cryosphere and Sea Level Change, in:
Climate Change 2021: The Physical Science Basis. Contribution of Working
Group I to the Sixth Assessment Report of the Intergovernmental Panel on
Climate Change, edited by: Masson-Delmotte, V., Zhai, P., Pirani, A., Connors,
S. L., Péan, C., Berger, S., Caud, N., Chen, Y., Goldfarb, L., Gomis, M. I.,
Huang, M., Leitzell, K., Lonnoy, E., Matthews, J., Maycock, T. K.,
Waterfield, T., Yelekçi, O., Yu, R., and Zhou, B., Cambridge University
Press, in press, 2021. a
Gulev, S. K., Thorne, P., Ahn, J., Dentener, F., Domingues, C., Gerland, S.,
Gong, D., Kaufman, D., Nnamchi, H., Quaas, J., Rivera, J., Sathyendranath,
S., Smith, S., Trewin, B., von Shuckmann, K., and Vose, R.: Changing State of
the Climate System, in: Climate Change 2021: The Physical Science Basis.
Contribution of Working Group I to the Sixth Assessment Report of the
Intergovernmental Panel on Climate Change, edited by: Masson-Delmotte, V.,
Zhai, P., Pirani, A., Connors, S. L., Péan, C., Berger, S., Caud, N., Chen,
Y., Goldfarb, L., Gomis, M. I., Huang, M., Leitzell, K., Lonnoy, E.,
Matthews, J., Maycock, T. K., Waterfield, T., Yelekçi, O., Yu, R., and
Zhou, B., Cambridge University Press, in press, 2021. a, b, c
Gutiérrez, J. M., Iturbide, M., Alvarez, E. C., Diez-Sierra, J., Bedia, J.,
Manzanas, R., no Medina, J. B., Hauser, M., García-Díez, M.,
Ozge Yelecki, Felice, M. D., and Trenham, C.: PMIP4-midHolocene,
GitHub, https://github.com/IPCC-WG1/Atlas, last access: 12 July 2021. a
Gutiérrez, J. M., Jones, R. G., Narisma, G. T., Alves, L. M., Amjad, M.,
Gorodetskaya, I. V., Grose, M., Klutse, N. A. B., Krakovska, S., Li, J.,
Martínez-Castro, D., Mearns, L. O., Mernild, S. H., Ngo-Duc, T., van den
Hurk, B., and Yoon, J.-H.: Atlas, in: Climate Change 2021: The Physical
Science Basis. Contribution of Working Group I to the Sixth Assessment Report
of the Intergovernmental Panel on Climate Change, edited by: Masson-Delmotte,
V., Zhai, P., Pirani, A., Connors, S. L., Péan, C., Berger, S., Caud, N.,
Chen, Y., Goldfarb, L., Gomis, M. I., Huang, M., Leitzell, K., Lonnoy, E.,
Matthews, J., Maycock, T. K., Waterfield, T., Yelekçi, O., Yu, R., and
Zhou, B., Cambridge University Press, in press, 2022. a, b, c
Harrison, S., Bartlein, P., Brewer, S., Prentice, I., Boyd, M., Hessler, I.,
Holmgren, K., Izumi, K., and Willis, K.: Climate model benchmarking with
glacial and mid-Holocene climates, Clim. Dynam., 43, 671–688,
https://doi.org/10.1007/s00382-013-1922-6, 2014. a
Harrison, S. P., Bartlein, P., Izumi, K., Li, G., Annan, J., Hargreaves, J.,
Braconnot, P., and Kageyama, M.: Evaluation of CMIP5 palaeo-simulations to
improve climate projections, Nat. Clim. Change, 5, 735–743,
https://doi.org/10.1038/nclimate2649, 2015. a
Haywood, A. M., Tindall, J. C., Dowsett, H. J., Dolan, A. M., Foley, K. M., Hunter, S. J., Hill, D. J., Chan, W.-L., Abe-Ouchi, A., Stepanek, C., Lohmann, G., Chandan, D., Peltier, W. R., Tan, N., Contoux, C., Ramstein, G., Li, X., Zhang, Z., Guo, C., Nisancioglu, K. H., Zhang, Q., Li, Q., Kamae, Y., Chandler, M. A., Sohl, L. E., Otto-Bliesner, B. L., Feng, R., Brady, E. C., von der Heydt, A. S., Baatsen, M. L. J., and Lunt, D. J.: The Pliocene Model Intercomparison Project Phase 2: large-scale climate features and climate sensitivity, Clim. Past, 16, 2095–2123, https://doi.org/10.5194/cp-16-2095-2020, 2020. a
Hoyer, S. and Hamman, J.: xarray: N-D labeled arrays and datasets in
Python, J. Open Res. Softw., 5, 10, https://doi.org/10.5334/jors.148, 2017. a
IPCC: Annex V: Monsoons, in: Climate Change
2021: The Physical Science Basis. Contribution of Working Group I to the
Sixth Assessment Report of the Intergovernmental Panel on Climate Change,
edited by: Masson-Delmotte, V., Zhai, P., Pirani, A., Connors, S. L., Péan,
C., Berger, S., Caud, N., Chen, Y., Goldfarb, L., Gomis, M. I., Huang, M.,
Leitzell, K., Lonnoy, E., Matthews, J., Maycock, T. K., Waterfield, T.,
Yelekçi, O., Yu, R., and Zhou, B., Cambridge University Press, 2021. a, b
Iturbide, M., Gutiérrez, J. M., Alves, L. M., Bedia, J., Cerezo-Mota, R., Cimadevilla, E., Cofiño, A. S., Di Luca, A., Faria, S. H., Gorodetskaya, I. V., Hauser, M., Herrera, S., Hennessy, K., Hewitt, H. T., Jones, R. G., Krakovska, S., Manzanas, R., Martínez-Castro, D., Narisma, G. T., Nurhati, I. S., Pinto, I., Seneviratne, S. I., van den Hurk, B., and Vera, C. S.: An update of IPCC climate reference regions for subcontinental analysis of climate model data: definition and aggregated datasets, Earth Syst. Sci. Data, 12, 2959–2970, https://doi.org/10.5194/essd-12-2959-2020, 2020. a
Juckes, M., Taylor, K. E., Durack, P. J., Lawrence, B., Mizielinski, M. S., Pamment, A., Peterschmitt, J.-Y., Rixen, M., and Sénési, S.: The CMIP6 Data Request (DREQ, version 01.00.31), Geosci. Model Dev., 13, 201–224, https://doi.org/10.5194/gmd-13-201-2020, 2020. 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, Geosci. Model Dev., 11, 1033–1057, https://doi.org/10.5194/gmd-11-1033-2018, 2018. a, b, c
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
Kitoh, A., Endo, H., Krishna Kumar, K., Cavalcanti, I. F. A., Goswami, P., and
Zhou, T.: Monsoons in a changing world: A regional perspective in a global
context, J. Geophys. Res.-Atmos., 118, 3053–3065,
https://doi.org/10.1002/jgrd.50258, 2013. a
Nüst, D., Sochat, V., Marwick, B., Eglen, S. J., Head, T., Hirst, T., and
Evans, B. D.: Ten simple rules for writing Dockerfiles for reproducible data
science, PLOS Comput. Biol., 16, 1–24,
https://doi.org/10.1371/journal.pcbi.1008316, 2020. a
Otto-Bliesner, B. L., Brady, E. C., Fasullo, J., Jahn, A., Landrum, L.,
Stevenson, S., Rosenbloom, N., Mai, A., and Strand, G.: Climate variability
and change since 850 CE: An ensemble approach with the Community Earth System
Model, B. Am. Meteorol. Soc., 97, 735–754, 2016. a
Otto-Bliesner, B. L., Braconnot, P., Harrison, S. P., Lunt, D. J., Abe-Ouchi, A., Albani, S., Bartlein, P. J., Capron, E., Carlson, A. E., Dutton, A., Fischer, H., Goelzer, H., Govin, A., Haywood, A., Joos, F., LeGrande, A. N., Lipscomb, W. H., Lohmann, G., Mahowald, N., Nehrbass-Ahles, C., Pausata, F. S. R., Peterschmitt, J.-Y., Phipps, S. J., Renssen, H., and Zhang, Q.: The PMIP4 contribution to CMIP6 – Part 2: Two interglacials, scientific objective and experimental design for Holocene and Last Interglacial simulations, Geosci. Model Dev., 10, 3979–4003, https://doi.org/10.5194/gmd-10-3979-2017, 2017. a
Otto-Bliesner, B. L., Brady, E. C., Zhao, A., Brierley, C. M., Axford, Y., Capron, E., Govin, A., Hoffman, J. S., Isaacs, E., Kageyama, M., Scussolini, P., Tzedakis, P. C., Williams, C. J. R., Wolff, E., Abe-Ouchi, A., Braconnot, P., Ramos Buarque, S., Cao, J., de Vernal, A., Guarino, M. V., Guo, C., LeGrande, A. N., Lohmann, G., Meissner, K. J., Menviel, L., Morozova, P. A., Nisancioglu, K. H., O'ishi, R., Salas y Mélia, D., Shi, X., Sicard, M., Sime, L., Stepanek, C., Tomas, R., Volodin, E., Yeung, N. K. H., Zhang, Q., Zhang, Z., and Zheng, W.: Large-scale features of Last Interglacial climate: results from evaluating the lig127k simulations for the Coupled Model Intercomparison Project (CMIP6)–Paleoclimate Modeling Intercomparison Project (PMIP4), Clim. Past, 17, 63–94, https://doi.org/10.5194/cp-17-63-2021, 2021. a, b, c, d, e, f, g, h
Phillips, A. and Brierley, C.: pmip4/CVDP-ncl: Publishing revisions associated with Zhao et al. manuscript (v.5.2.pmip4), Zenodo [code], https://doi.org/10.5281/zenodo.5931098, 2022. a
Phillips, A. S., Deser, C., and Fasullo, J.: Evaluating modes of variability in
climate models, Eos, Transactions American Geophysical Union, 95, 453–455,
https://doi.org/10.1002/2014EO490002, 2014. a
Pollard, D. and Reusch, D. B.: A calendar conversion method for monthly mean
paleoclimate model output with orbital forcing, J. Geophys.
Res.-Atmos., 107, 4615–ACL3–7, https://doi.org/10.1029/2002JD002126, 2002. a
Reynolds, R. W., Rayner, N. A., Smith, T. M., Stokes, D. C., and Wang, W.: An
Improved In Situ and Satellite SST Analysis for Climate, J. Climate,
15, 1609–1625, https://doi.org/10.1175/1520-0442(2002)015<1609:AIISAS>2.0.CO;2, 2002. 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
Wang, B. and Ding, Q.: Global monsoon: Dominant mode of annual variation in the
tropics, Dynam. Atmos. Oceans, 44, 165–183,
https://doi.org/10.1016/j.dynatmoce.2007.05.002, 2008. a
Wang, B., Kim, H.-J., Kikuchi, K., and Kitoh, A.: Diagnostic metrics for
evaluation of annual and diurnal cycles, Clim. Dynam., 37, 941–955,
https://doi.org/10.1007/s00382-010-0877-0, 2011. a
Wang, P. X., Wang, B., Cheng, H., Fasullo, J., Guo, Z. T., Kiefer, T., and Liu, Z. Y.: The global monsoon across timescales: coherent variability of regional monsoons, Clim. Past, 10, 2007–2052, https://doi.org/10.5194/cp-10-2007-2014, 2014. a
Zelinka, M. D., Myers, T. A., McCoy, D. T., Po-Chedley, S., Caldwell, P. M.,
Ceppi, P., Klein, S. A., and Taylor, K. E.: Causes of higher climate
sensitivity in CMIP6 models, Geophys. Res. Lett., 47,
e2019GL085782, https://doi.org/10.1029/2019GL085782, 2020. a
Zender, C. S.: Analysis of self-describing gridded geoscience data with netCDF
Operators (NCO), Environ. Model. Softw., 23, 1338–1342, 2008. a
Zhao, A. and Brierley, C.: pmip4/pmip_p2fvar_analyzer: Incorporating revisions associated with Zhao et al. manuscript (v1.1), Zenodo [code], https://doi.org/10.5281/zenodo.5929684, 2022. a, b
Short summary
We describe the way that our group have chosen to perform our recent analyses of the Palaeoclimate Modelling Intercomparison Project ensemble simulations. We document the approach used to obtain and curate the simulations, process those outputs via the Climate Variability Diagnostics Package, and then continue through to compute ensemble-wide statistics and create figures. We also provide interim data from all steps, the codes used and the ability for users to perform their own analyses.
We describe the way that our group have chosen to perform our recent analyses of the...