Articles | Volume 15, issue 3
https://doi.org/10.5194/esd-15-689-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/esd-15-689-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
11 Jun 2024
Research article |
| 11 Jun 2024
| 11 Jun 2024
Changing effects of external forcing on Atlantic–Pacific interactions
Institute of Environmental Physics (IUP), University of Bremen, Bremen, Germany
Deutsches Zentrum für Luft- und Raumfahrt e.V. (DLR), Institut für Physik der Atmosphäre, Oberpfaffenhofen, Germany
Evgenia Galytska
Institute of Environmental Physics (IUP), University of Bremen, Bremen, Germany
Deutsches Zentrum für Luft- und Raumfahrt e.V. (DLR), Institut für Physik der Atmosphäre, Oberpfaffenhofen, Germany
Gerald A. Meehl
Climate and Global Dynamics Laboratory, National Center for Atmospheric Research (NCAR), Boulder, CO, USA
Jakob Runge
Deutsches Zentrum für Luft- und Raumfahrt e.V. (DLR), Institut für Datenwissenschaften, Jena, Germany
Fachgebiet Klimainformatik, Technische Universität Berlin, Berlin, Germany
Katja Weigel
Institute of Environmental Physics (IUP), University of Bremen, Bremen, Germany
Deutsches Zentrum für Luft- und Raumfahrt e.V. (DLR), Institut für Physik der Atmosphäre, Oberpfaffenhofen, Germany
Veronika Eyring
Deutsches Zentrum für Luft- und Raumfahrt e.V. (DLR), Institut für Physik der Atmosphäre, Oberpfaffenhofen, Germany
Institute of Environmental Physics (IUP), University of Bremen, Bremen, Germany
Related authors
Soufiane Karmouche, Evgenia Galytska, Jakob Runge, Gerald A. Meehl, Adam S. Phillips, Katja Weigel, and Veronika Eyring
Earth Syst. Dynam., 14, 309–344, https://doi.org/10.5194/esd-14-309-2023, https://doi.org/10.5194/esd-14-309-2023, 2023
Short summary
Short summary
This study uses a causal discovery method to evaluate the ability of climate models to represent the interactions between the Atlantic multidecadal variability (AMV) and the Pacific decadal variability (PDV). The approach and findings in this study present a powerful methodology that can be applied to a number of environment-related topics, offering tremendous insights to improve the understanding of the complex Earth system and the state of the art of climate modeling.
Arndt Kaps, Axel Lauer, Rémi Kazeroni, Martin Stengel, and Veronika Eyring
Earth Syst. Sci. Data, 16, 3001–3016, https://doi.org/10.5194/essd-16-3001-2024, https://doi.org/10.5194/essd-16-3001-2024, 2024
Short summary
Short summary
CCClim displays observations of clouds in terms of cloud classes that have been in use for a long time. CCClim is a machine-learning-powered product based on multiple existing observational products from different satellites. We show that the cloud classes in CCClim are physically meaningful and can be used to study cloud characteristics in more detail. The goal of this is to make real-world clouds more easily understandable to eventually improve the simulation of clouds in climate models.
Bjorn Stevens, Stefan Adami, Tariq Ali, Hartwig Anzt, Zafer Aslan, Sabine Attinger, Jaana Bäck, Johanna Baehr, Peter Bauer, Natacha Bernier, Bob Bishop, Hendryk Bockelmann, Sandrine Bony, Guy Brasseur, David N. Bresch, Sean Breyer, Gilbert Brunet, Pier Luigi Buttigieg, Junji Cao, Christelle Castet, Yafang Cheng, Ayantika Dey Choudhury, Deborah Coen, Susanne Crewell, Atish Dabholkar, Qing Dai, Francisco Doblas-Reyes, Dale Durran, Ayoub El Gaidi, Charlie Ewen, Eleftheria Exarchou, Veronika Eyring, Florencia Falkinhoff, David Farrell, Piers M. Forster, Ariane Frassoni, Claudia Frauen, Oliver Fuhrer, Shahzad Gani, Edwin Gerber, Debra Goldfarb, Jens Grieger, Nicolas Gruber, Wilco Hazeleger, Rolf Herken, Chris Hewitt, Torsten Hoefler, Huang-Hsiung Hsu, Daniela Jacob, Alexandra Jahn, Christian Jakob, Thomas Jung, Christopher Kadow, In-Sik Kang, Sarah Kang, Karthik Kashinath, Katharina Kleinen-von Königslöw, Daniel Klocke, Uta Kloenne, Milan Klöwer, Chihiro Kodama, Stefan Kollet, Tobias Kölling, Jenni Kontkanen, Steve Kopp, Michal Koran, Markku Kulmala, Hanna Lappalainen, Fakhria Latifi, Bryan Lawrence, June Yi Lee, Quentin Lejeun, Christian Lessig, Chao Li, Thomas Lippert, Jürg Luterbacher, Pekka Manninen, Jochem Marotzke, Satoshi Matsouoka, Charlotte Merchant, Peter Messmer, Gero Michel, Kristel Michielsen, Tomoki Miyakawa, Jens Müller, Ramsha Munir, Sandeep Narayanasetti, Ousmane Ndiaye, Carlos Nobre, Achim Oberg, Riko Oki, Tuba Özkan-Haller, Tim Palmer, Stan Posey, Andreas Prein, Odessa Primus, Mike Pritchard, Julie Pullen, Dian Putrasahan, Johannes Quaas, Krishnan Raghavan, Venkatachalam Ramaswamy, Markus Rapp, Florian Rauser, Markus Reichstein, Aromar Revi, Sonakshi Saluja, Masaki Satoh, Vera Schemann, Sebastian Schemm, Christina Schnadt Poberaj, Thomas Schulthess, Cath Senior, Jagadish Shukla, Manmeet Singh, Julia Slingo, Adam Sobel, Silvina Solman, Jenna Spitzer, Philip Stier, Thomas Stocker, Sarah Strock, Hang Su, Petteri Taalas, John Taylor, Susann Tegtmeier, Georg Teutsch, Adrian Tompkins, Uwe Ulbrich, Pier-Luigi Vidale, Chien-Ming Wu, Hao Xu, Najibullah Zaki, Laure Zanna, Tianjun Zhou, and Florian Ziemen
Earth Syst. Sci. Data, 16, 2113–2122, https://doi.org/10.5194/essd-16-2113-2024, https://doi.org/10.5194/essd-16-2113-2024, 2024
Short summary
Short summary
To manage Earth in the Anthropocene, new tools, new institutions, and new forms of international cooperation will be required. Earth Virtualization Engines is proposed as an international federation of centers of excellence to empower all people to respond to the immense and urgent challenges posed by climate change.
John T. Fasullo, Jean-Christophe Golaz, Julie M. Caron, Nan Rosenbloom, Gerald A. Meehl, Warren Strand, Sasha Glanville, Samantha Stevenson, Maria Molina, Christine A. Shields, Chengzhu Zhang, James Benedict, Hailong Wang, and Tony Bartoletti
Earth Syst. Dynam., 15, 367–386, https://doi.org/10.5194/esd-15-367-2024, https://doi.org/10.5194/esd-15-367-2024, 2024
Short summary
Short summary
Climate model large ensembles provide a unique and invaluable means for estimating the climate response to external forcing agents and quantify contrasts in model structure. Here, an overview of the Energy Exascale Earth System Model (E3SM) version 2 large ensemble is given along with comparisons to large ensembles from E3SM version 1 and versions 1 and 2 of the Community Earth System Model. The paper provides broad and important context for users of these ensembles.
Bettina K. Gier, Manuel Schlund, Pierre Friedlingstein, Chris D. Jones, Colin Jones, Sönke Zaehle, and Veronika Eyring
EGUsphere, https://doi.org/10.5194/egusphere-2024-277, https://doi.org/10.5194/egusphere-2024-277, 2024
Short summary
Short summary
This study investigates present day carbon cycle variables in CMIP5 and CMIP6 simulations. A significant improvement in the simulation of photosynthesis in models with nitrogen cycle is found, as well as only small differences between emission and concentration based simulations. Thus, we recommend the use of emission driven simulations in CMIP7 as default setup, and to view the nitrogen cycle as a necessary part of all future carbon cycle models.
Colin Gareth Jones, Fanny Adloff, Ben Booth, Peter Cox, Veronika Eyring, Pierre Friedlingstein, Katja Frieler, Helene Hewitt, Hazel Jeffery, Sylvie Joussaume, Torben Koenigk, Bryan N. Lawrence, Eleanor O'Rourke, Malcolm Roberts, Benjamin Sanderson, Roland Séférian, Samuel Somot, Pier-Luigi Vidale, Detlef van Vuuren, Mario Acosta, Mats Bentsen, Raffaele Bernardello, Richard Betts, Ed Blockley, Julien Boé, Tom Bracegirdle, Pascale Braconnot, Victor Brovkin, Carlo Buontempo, Francisco J. Doblas-Reyes, Markus G. Donat, Italo Epicoco, Pete Falloon, Sandro Fiore, Thomas Froelicher, Neven Fuckar, Matthew Gidden, Helge Goessling, Rune Grand Graversen, Silvio Gualdi, Jose Manuel Gutiérrez, Tatiana Ilyina, Daniela Jacob, Chris Jones, Martin Juckes, Elizabeth Kendon, Erik Kjellström, Reto Knutti, Jason A. Lowe, Matthew Mizielinski, Paola Nassisi, Michael Obersteiner, Pierre Regnier, Romain Roehrig, David Salas y Melia, Carl-Friedrich Schleussner, Michael Schulz, Enrico Scoccimarro, Laurent Terray, Hannes Thiemann, Richard Wood, Shuting Yang, and Sönke Zaehle
EGUsphere, https://doi.org/10.5194/egusphere-2024-453, https://doi.org/10.5194/egusphere-2024-453, 2024
Short summary
Short summary
We propose a number of priority areas for the international climate research community to address over the coming ~6 years (i.e. to 2030). Advances in these areas will increase our understanding of past and future Earth system change, including the societal and environmental impacts of this change, as well as deliver significantly improved scientific support to international climate policy, such as the 7th IPCC Assessment Report and the UNFCCC Global Stocktake under the Paris Climate Agreement.
Benjamin Mark Sanderson, Ben B. B. Booth, John Dunne, Veronika Eyring, Rosie A. Fisher, Pierre Friedlingstein, Matthew J. Gidden, Tomohiro Hajima, Chris D. Jones, Colin Jones, Andrew King, Charles D. Koven, David M. Lawrence, Jason Lowe, Nadine Mengis, Glen P. Peters, Joeri Rogelj, Chris Smith, Abigail C. Snyder, Isla R. Simpson, Abigail L. S. Swann, Claudia Tebaldi, Tatiana Ilyina, Carl-Friedrich Schleussner, Roland Seferian, Bjørn Hallvard Samset, Detlef van Vuuren, and Sönke Zaehle
EGUsphere, https://doi.org/10.5194/egusphere-2023-2127, https://doi.org/10.5194/egusphere-2023-2127, 2023
Short summary
Short summary
We discuss how, in order to provide more relevant guidance for climate policy, coordinated climate experiments should adopt a greater focus on simulations where Earth System Models are provided with carbon emissions from fossil fuels together with land use change instructions, rather than past approaches which have largely focussed on experiments with prescribed atmospheric carbon dioxide concentrations. We highlight the technical feasibility of achieving these simulations in coming years.
Michael Kiefer, Dale F. Hurst, Gabriele P. Stiller, Stefan Lossow, Holger Vömel, John Anderson, Faiza Azam, Jean-Loup Bertaux, Laurent Blanot, Klaus Bramstedt, John P. Burrows, Robert Damadeo, Bianca Maria Dinelli, Patrick Eriksson, Maya García-Comas, John C. Gille, Mark Hervig, Yasuko Kasai, Farahnaz Khosrawi, Donal Murtagh, Gerald E. Nedoluha, Stefan Noël, Piera Raspollini, William G. Read, Karen H. Rosenlof, Alexei Rozanov, Christopher E. Sioris, Takafumi Sugita, Thomas von Clarmann, Kaley A. Walker, and Katja Weigel
Atmos. Meas. Tech., 16, 4589–4642, https://doi.org/10.5194/amt-16-4589-2023, https://doi.org/10.5194/amt-16-4589-2023, 2023
Short summary
Short summary
We quantify biases and drifts (and their uncertainties) between the stratospheric water vapor measurement records of 15 satellite-based instruments (SATs, with 31 different retrievals) and balloon-borne frost point hygrometers (FPs) launched at 27 globally distributed stations. These comparisons of measurements during the period 2000–2016 are made using robust, consistent statistical methods. With some exceptions, the biases and drifts determined for most SAT–FP pairs are < 10 % and < 1 % yr−1.
Soufiane Karmouche, Evgenia Galytska, Jakob Runge, Gerald A. Meehl, Adam S. Phillips, Katja Weigel, and Veronika Eyring
Earth Syst. Dynam., 14, 309–344, https://doi.org/10.5194/esd-14-309-2023, https://doi.org/10.5194/esd-14-309-2023, 2023
Short summary
Short summary
This study uses a causal discovery method to evaluate the ability of climate models to represent the interactions between the Atlantic multidecadal variability (AMV) and the Pacific decadal variability (PDV). The approach and findings in this study present a powerful methodology that can be applied to a number of environment-related topics, offering tremendous insights to improve the understanding of the complex Earth system and the state of the art of climate modeling.
Manuel Schlund, Birgit Hassler, Axel Lauer, Bouwe Andela, Patrick Jöckel, Rémi Kazeroni, Saskia Loosveldt Tomas, Brian Medeiros, Valeriu Predoi, Stéphane Sénési, Jérôme Servonnat, Tobias Stacke, Javier Vegas-Regidor, Klaus Zimmermann, and Veronika Eyring
Geosci. Model Dev., 16, 315–333, https://doi.org/10.5194/gmd-16-315-2023, https://doi.org/10.5194/gmd-16-315-2023, 2023
Short summary
Short summary
The Earth System Model Evaluation Tool (ESMValTool) is a community diagnostics and performance metrics tool for routine evaluation of Earth system models. Originally, ESMValTool was designed to process reformatted output provided by large model intercomparison projects like the Coupled Model Intercomparison Project (CMIP). Here, we describe a new extension of ESMValTool that allows for reading and processing native climate model output, i.e., data that have not been reformatted before.
William G. Read, Gabriele Stiller, Stefan Lossow, Michael Kiefer, Farahnaz Khosrawi, Dale Hurst, Holger Vömel, Karen Rosenlof, Bianca M. Dinelli, Piera Raspollini, Gerald E. Nedoluha, John C. Gille, Yasuko Kasai, Patrick Eriksson, Christopher E. Sioris, Kaley A. Walker, Katja Weigel, John P. Burrows, and Alexei Rozanov
Atmos. Meas. Tech., 15, 3377–3400, https://doi.org/10.5194/amt-15-3377-2022, https://doi.org/10.5194/amt-15-3377-2022, 2022
Short summary
Short summary
This paper attempts to provide an assessment of the accuracy of 21 satellite-based instruments that remotely measure atmospheric humidity in the upper troposphere of the Earth's atmosphere. The instruments made their measurements from 1984 to the present time; however, most of these instruments began operations after 2000, and only a few are still operational. The objective of this study is to quantify the accuracy of each satellite humidity data set.
Katja Weigel, Lisa Bock, Bettina K. Gier, Axel Lauer, Mattia Righi, Manuel Schlund, Kemisola Adeniyi, Bouwe Andela, Enrico Arnone, Peter Berg, Louis-Philippe Caron, Irene Cionni, Susanna Corti, Niels Drost, Alasdair Hunter, Llorenç Lledó, Christian Wilhelm Mohr, Aytaç Paçal, Núria Pérez-Zanón, Valeriu Predoi, Marit Sandstad, Jana Sillmann, Andreas Sterl, Javier Vegas-Regidor, Jost von Hardenberg, and Veronika Eyring
Geosci. Model Dev., 14, 3159–3184, https://doi.org/10.5194/gmd-14-3159-2021, https://doi.org/10.5194/gmd-14-3159-2021, 2021
Short summary
Short summary
This work presents new diagnostics for the Earth System Model Evaluation Tool (ESMValTool) v2.0 on the hydrological cycle, extreme events, impact assessment, regional evaluations, and ensemble member selection. The ESMValTool v2.0 diagnostics are developed by a large community of scientists aiming to facilitate the evaluation and comparison of Earth system models (ESMs) with a focus on the ESMs participating in the Coupled Model Intercomparison Project (CMIP).
Michaela I. Hegglin, Susann Tegtmeier, John Anderson, Adam E. Bourassa, Samuel Brohede, Doug Degenstein, Lucien Froidevaux, Bernd Funke, John Gille, Yasuko Kasai, Erkki T. Kyrölä, Jerry Lumpe, Donal Murtagh, Jessica L. Neu, Kristell Pérot, Ellis E. Remsberg, Alexei Rozanov, Matthew Toohey, Joachim Urban, Thomas von Clarmann, Kaley A. Walker, Hsiang-Jui Wang, Carlo Arosio, Robert Damadeo, Ryan A. Fuller, Gretchen Lingenfelser, Christopher McLinden, Diane Pendlebury, Chris Roth, Niall J. Ryan, Christopher Sioris, Lesley Smith, and Katja Weigel
Earth Syst. Sci. Data, 13, 1855–1903, https://doi.org/10.5194/essd-13-1855-2021, https://doi.org/10.5194/essd-13-1855-2021, 2021
Short summary
Short summary
An overview of the SPARC Data Initiative is presented, to date the most comprehensive assessment of stratospheric composition measurements spanning 1979–2018. Measurements of 26 chemical constituents obtained from an international suite of space-based limb sounders were compiled into vertically resolved, zonal monthly mean time series. The quality and consistency of these gridded datasets are then evaluated using a climatological validation approach and a range of diagnostics.
Christopher Krich, Mirco Migliavacca, Diego G. Miralles, Guido Kraemer, Tarek S. El-Madany, Markus Reichstein, Jakob Runge, and Miguel D. Mahecha
Biogeosciences, 18, 2379–2404, https://doi.org/10.5194/bg-18-2379-2021, https://doi.org/10.5194/bg-18-2379-2021, 2021
Short summary
Short summary
Ecosystems and the atmosphere interact with each other. These interactions determine e.g. the water and carbon fluxes and thus are crucial to understand climate change effects. We analysed the interactions for many ecosystems across the globe, showing that very different ecosystems can have similar interactions with the atmosphere. Meteorological conditions seem to be the strongest interaction-shaping factor. This means that common principles can be identified to describe ecosystem behaviour.
James Keeble, Birgit Hassler, Antara Banerjee, Ramiro Checa-Garcia, Gabriel Chiodo, Sean Davis, Veronika Eyring, Paul T. Griffiths, Olaf Morgenstern, Peer Nowack, Guang Zeng, Jiankai Zhang, Greg Bodeker, Susannah Burrows, Philip Cameron-Smith, David Cugnet, Christopher Danek, Makoto Deushi, Larry W. Horowitz, Anne Kubin, Lijuan Li, Gerrit Lohmann, Martine Michou, Michael J. Mills, Pierre Nabat, Dirk Olivié, Sungsu Park, Øyvind Seland, Jens Stoll, Karl-Hermann Wieners, and Tongwen Wu
Atmos. Chem. Phys., 21, 5015–5061, https://doi.org/10.5194/acp-21-5015-2021, https://doi.org/10.5194/acp-21-5015-2021, 2021
Short summary
Short summary
Stratospheric ozone and water vapour are key components of the Earth system; changes to both have important impacts on global and regional climate. We evaluate changes to these species from 1850 to 2100 in the new generation of CMIP6 models. There is good agreement between the multi-model mean and observations, although there is substantial variation between the individual models. The future evolution of both ozone and water vapour is strongly dependent on the assumed future emissions scenario.
Claudia Tebaldi, Kevin Debeire, Veronika Eyring, Erich Fischer, John Fyfe, Pierre Friedlingstein, Reto Knutti, Jason Lowe, Brian O'Neill, Benjamin Sanderson, Detlef van Vuuren, Keywan Riahi, Malte Meinshausen, Zebedee Nicholls, Katarzyna B. Tokarska, George Hurtt, Elmar Kriegler, Jean-Francois Lamarque, Gerald Meehl, Richard Moss, Susanne E. Bauer, Olivier Boucher, Victor Brovkin, Young-Hwa Byun, Martin Dix, Silvio Gualdi, Huan Guo, Jasmin G. John, Slava Kharin, YoungHo Kim, Tsuyoshi Koshiro, Libin Ma, Dirk Olivié, Swapna Panickal, Fangli Qiao, Xinyao Rong, Nan Rosenbloom, Martin Schupfner, Roland Séférian, Alistair Sellar, Tido Semmler, Xiaoying Shi, Zhenya Song, Christian Steger, Ronald Stouffer, Neil Swart, Kaoru Tachiiri, Qi Tang, Hiroaki Tatebe, Aurore Voldoire, Evgeny Volodin, Klaus Wyser, Xiaoge Xin, Shuting Yang, Yongqiang Yu, and Tilo Ziehn
Earth Syst. Dynam., 12, 253–293, https://doi.org/10.5194/esd-12-253-2021, https://doi.org/10.5194/esd-12-253-2021, 2021
Short summary
Short summary
We present an overview of CMIP6 ScenarioMIP outcomes from up to 38 participating ESMs according to the new SSP-based scenarios. Average temperature and precipitation projections according to a wide range of forcings, spanning a wider range than the CMIP5 projections, are documented as global averages and geographic patterns. Times of crossing various warming levels are computed, together with benefits of mitigation for selected pairs of scenarios. Comparisons with CMIP5 are also discussed.
Manuel Schlund, Axel Lauer, Pierre Gentine, Steven C. Sherwood, and Veronika Eyring
Earth Syst. Dynam., 11, 1233–1258, https://doi.org/10.5194/esd-11-1233-2020, https://doi.org/10.5194/esd-11-1233-2020, 2020
Short summary
Short summary
As an important measure of climate change, the Equilibrium Climate Sensitivity (ECS) describes the change in surface temperature after a doubling of the atmospheric CO2 concentration. Climate models from the Coupled Model Intercomparison Project (CMIP) show a wide range in ECS. Emergent constraints are a technique to reduce uncertainties in ECS with observational data. Emergent constraints developed with data from CMIP phase 5 show reduced skill and higher ECS ranges when applied to CMIP6 data.
Bettina K. Gier, Michael Buchwitz, Maximilian Reuter, Peter M. Cox, Pierre Friedlingstein, and Veronika Eyring
Biogeosciences, 17, 6115–6144, https://doi.org/10.5194/bg-17-6115-2020, https://doi.org/10.5194/bg-17-6115-2020, 2020
Short summary
Short summary
Models from Coupled Model Intercomparison Project (CMIP) phases 5 and 6 are compared to a satellite data product of column-averaged CO2 mole fractions (XCO2). The previously believed discrepancy of the negative trend in seasonal cycle amplitude in the satellite product, which is not seen in in situ data nor in the models, is attributed to a sampling characteristic. Furthermore, CMIP6 models are shown to have made progress in reproducing the observed XCO2 time series compared to CMIP5.
Giorgia Di Capua, Jakob Runge, Reik V. Donner, Bart van den Hurk, Andrew G. Turner, Ramesh Vellore, Raghavan Krishnan, and Dim Coumou
Weather Clim. Dynam., 1, 519–539, https://doi.org/10.5194/wcd-1-519-2020, https://doi.org/10.5194/wcd-1-519-2020, 2020
Short summary
Short summary
We study the interactions between the tropical convective activity and the mid-latitude circulation in the Northern Hemisphere during boreal summer. We identify two circumglobal wave patterns with phase shifts corresponding to the South Asian and the western North Pacific monsoon systems at an intra-seasonal timescale. These patterns show two-way interactions in a causal framework at a weekly timescale and assess how El Niño affects these interactions.
Axel Lauer, Veronika Eyring, Omar Bellprat, Lisa Bock, Bettina K. Gier, Alasdair Hunter, Ruth Lorenz, Núria Pérez-Zanón, Mattia Righi, Manuel Schlund, Daniel Senftleben, Katja Weigel, and Sabrina Zechlau
Geosci. Model Dev., 13, 4205–4228, https://doi.org/10.5194/gmd-13-4205-2020, https://doi.org/10.5194/gmd-13-4205-2020, 2020
Short summary
Short summary
The Earth System Model Evaluation Tool is a community software tool designed for evaluation and analysis of climate models. New features of version 2.0 include analysis scripts for important large-scale features in climate models, diagnostics for extreme events, regional model and impact evaluation. In this paper, newly implemented climate metrics, emergent constraints for climate-relevant feedbacks and diagnostics for future model projections are described and illustrated with examples.
Veronika Eyring, Lisa Bock, Axel Lauer, Mattia Righi, Manuel Schlund, Bouwe Andela, Enrico Arnone, Omar Bellprat, Björn Brötz, Louis-Philippe Caron, Nuno Carvalhais, Irene Cionni, Nicola Cortesi, Bas Crezee, Edouard L. Davin, Paolo Davini, Kevin Debeire, Lee de Mora, Clara Deser, David Docquier, Paul Earnshaw, Carsten Ehbrecht, Bettina K. Gier, Nube Gonzalez-Reviriego, Paul Goodman, Stefan Hagemann, Steven Hardiman, Birgit Hassler, Alasdair Hunter, Christopher Kadow, Stephan Kindermann, Sujan Koirala, Nikolay Koldunov, Quentin Lejeune, Valerio Lembo, Tomas Lovato, Valerio Lucarini, François Massonnet, Benjamin Müller, Amarjiit Pandde, Núria Pérez-Zanón, Adam Phillips, Valeriu Predoi, Joellen Russell, Alistair Sellar, Federico Serva, Tobias Stacke, Ranjini Swaminathan, Verónica Torralba, Javier Vegas-Regidor, Jost von Hardenberg, Katja Weigel, and Klaus Zimmermann
Geosci. Model Dev., 13, 3383–3438, https://doi.org/10.5194/gmd-13-3383-2020, https://doi.org/10.5194/gmd-13-3383-2020, 2020
Short summary
Short summary
The Earth System Model Evaluation Tool (ESMValTool) is a community diagnostics and performance metrics tool designed to improve comprehensive and routine evaluation of earth system models (ESMs) participating in the Coupled Model Intercomparison Project (CMIP). It has undergone rapid development since the first release in 2016 and is now a well-tested tool that provides end-to-end provenance tracking to ensure reproducibility.
Duane Waliser, Peter J. Gleckler, Robert Ferraro, Karl E. Taylor, Sasha Ames, James Biard, Michael G. Bosilovich, Otis Brown, Helene Chepfer, Luca Cinquini, Paul J. Durack, Veronika Eyring, Pierre-Philippe Mathieu, Tsengdar Lee, Simon Pinnock, Gerald L. Potter, Michel Rixen, Roger Saunders, Jörg Schulz, Jean-Noël Thépaut, and Matthias Tuma
Geosci. Model Dev., 13, 2945–2958, https://doi.org/10.5194/gmd-13-2945-2020, https://doi.org/10.5194/gmd-13-2945-2020, 2020
Short summary
Short summary
This paper provides an update to an international research activity whose objective is to facilitate access to satellite and other types of regional and global datasets for evaluating global models used to produce 21st century climate projections.
Mattia Righi, Bouwe Andela, Veronika Eyring, Axel Lauer, Valeriu Predoi, Manuel Schlund, Javier Vegas-Regidor, Lisa Bock, Björn Brötz, Lee de Mora, Faruk Diblen, Laura Dreyer, Niels Drost, Paul Earnshaw, Birgit Hassler, Nikolay Koldunov, Bill Little, Saskia Loosveldt Tomas, and Klaus Zimmermann
Geosci. Model Dev., 13, 1179–1199, https://doi.org/10.5194/gmd-13-1179-2020, https://doi.org/10.5194/gmd-13-1179-2020, 2020
Short summary
Short summary
This paper describes the second major release of ESMValTool, a community diagnostic and performance metrics tool for the evaluation of Earth system models. This new version features a brand new design, with an improved interface and a revised preprocessor. It takes advantage of state-of-the-art computational libraries and methods to deploy efficient and user-friendly data processing, improving the performance over its predecessor by more than a factor of 30.
Christopher Krich, Jakob Runge, Diego G. Miralles, Mirco Migliavacca, Oscar Perez-Priego, Tarek El-Madany, Arnaud Carrara, and Miguel D. Mahecha
Biogeosciences, 17, 1033–1061, https://doi.org/10.5194/bg-17-1033-2020, https://doi.org/10.5194/bg-17-1033-2020, 2020
Short summary
Short summary
Causal inference promises new insight into biosphere–atmosphere interactions using time series only. To understand the behaviour of a specific method on such data, we used artificial and observation-based data. The observed structures are very interpretable and reveal certain ecosystem-specific behaviour, as only a few relevant links remain, in contrast to pure correlation techniques. Thus, causal inference allows to us gain well-constrained insights into processes and interactions.
Dan Weaver, Kimberly Strong, Kaley A. Walker, Chris Sioris, Matthias Schneider, C. Thomas McElroy, Holger Vömel, Michael Sommer, Katja Weigel, Alexei Rozanov, John P. Burrows, William G. Read, Evan Fishbein, and Gabriele Stiller
Atmos. Meas. Tech., 12, 4039–4063, https://doi.org/10.5194/amt-12-4039-2019, https://doi.org/10.5194/amt-12-4039-2019, 2019
Short summary
Short summary
This work assesses water vapour profiles acquired by Atmospheric Chemistry Experiment (ACE) satellite instruments in the upper troposphere and lower stratosphere (UTLS) using comparisons to radiosondes and ground-based Fourier transform infrared spectrometer measurements acquired at a Canadian high Arctic measurement site in Eureka, Nunavut. Additional comparisons are made between these Eureka measurements and other water vapour satellite datasets for context, including AIRS, MLS, and others.
Christoph Heinze, Veronika Eyring, Pierre Friedlingstein, Colin Jones, Yves Balkanski, William Collins, Thierry Fichefet, Shuang Gao, Alex Hall, Detelina Ivanova, Wolfgang Knorr, Reto Knutti, Alexander Löw, Michael Ponater, Martin G. Schultz, Michael Schulz, Pier Siebesma, Joao Teixeira, George Tselioudis, and Martin Vancoppenolle
Earth Syst. Dynam., 10, 379–452, https://doi.org/10.5194/esd-10-379-2019, https://doi.org/10.5194/esd-10-379-2019, 2019
Short summary
Short summary
Earth system models for producing climate projections under given forcings include additional processes and feedbacks that traditional physical climate models do not consider. We present an overview of climate feedbacks for key Earth system components and discuss the evaluation of these feedbacks. The target group for this article includes generalists with a background in natural sciences and an interest in climate change as well as experts working in interdisciplinary climate research.
Stefan Lossow, Farahnaz Khosrawi, Michael Kiefer, Kaley A. Walker, Jean-Loup Bertaux, Laurent Blanot, James M. Russell, Ellis E. Remsberg, John C. Gille, Takafumi Sugita, Christopher E. Sioris, Bianca M. Dinelli, Enzo Papandrea, Piera Raspollini, Maya García-Comas, Gabriele P. Stiller, Thomas von Clarmann, Anu Dudhia, William G. Read, Gerald E. Nedoluha, Robert P. Damadeo, Joseph M. Zawodny, Katja Weigel, Alexei Rozanov, Faiza Azam, Klaus Bramstedt, Stefan Noël, John P. Burrows, Hideo Sagawa, Yasuko Kasai, Joachim Urban, Patrick Eriksson, Donal P. Murtagh, Mark E. Hervig, Charlotta Högberg, Dale F. Hurst, and Karen H. Rosenlof
Atmos. Meas. Tech., 12, 2693–2732, https://doi.org/10.5194/amt-12-2693-2019, https://doi.org/10.5194/amt-12-2693-2019, 2019
Evgenia Galytska, Alexey Rozanov, Martyn P. Chipperfield, Sandip. S. Dhomse, Mark Weber, Carlo Arosio, Wuhu Feng, and John P. Burrows
Atmos. Chem. Phys., 19, 767–783, https://doi.org/10.5194/acp-19-767-2019, https://doi.org/10.5194/acp-19-767-2019, 2019
Short summary
Short summary
In this study we analysed ozone changes in the tropical mid-stratosphere as observed by the SCIAMACHY instrument during 2004–2012. We used simulations from TOMCAT model with different chemical and dynamical forcings to reveal primary causes of ozone changes. We also considered measured NO2 and modelled NOx, NOx, and N2O data. With modelled AoA data we identified seasonal changes in the upwelling speed and explained how those changes affect N2O chemistry which leads to observed ozone changes.
Farahnaz Khosrawi, Stefan Lossow, Gabriele P. Stiller, Karen H. Rosenlof, Joachim Urban, John P. Burrows, Robert P. Damadeo, Patrick Eriksson, Maya García-Comas, John C. Gille, Yasuko Kasai, Michael Kiefer, Gerald E. Nedoluha, Stefan Noël, Piera Raspollini, William G. Read, Alexei Rozanov, Christopher E. Sioris, Kaley A. Walker, and Katja Weigel
Atmos. Meas. Tech., 11, 4435–4463, https://doi.org/10.5194/amt-11-4435-2018, https://doi.org/10.5194/amt-11-4435-2018, 2018
Short summary
Short summary
Time series of stratospheric and lower mesospheric water vapour using 33 data sets from 15 satellite instruments were compared in the framework of the second SPARC water vapour assessment. We find that most data sets can be considered in observational and modelling studies addressing, e.g. stratospheric and lower mesospheric water vapour variability and trends if data-set-specific characteristics (e.g. a drift) and restrictions (e.g. temporal and spatial coverage) are taken into account.
Klaus-Dirk Gottschaldt, Hans Schlager, Robert Baumann, Duy Sinh Cai, Veronika Eyring, Phoebe Graf, Volker Grewe, Patrick Jöckel, Tina Jurkat-Witschas, Christiane Voigt, Andreas Zahn, and Helmut Ziereis
Atmos. Chem. Phys., 18, 5655–5675, https://doi.org/10.5194/acp-18-5655-2018, https://doi.org/10.5194/acp-18-5655-2018, 2018
Short summary
Short summary
This study places aircraft trace gas measurements from within the Asian summer monsoon anticyclone into the context of regional, intra- and interannual variability. We find that the processes reflected in the measurements are present throughout multiple simulated monsoon seasons. Dynamical instabilities, photochemical ozone production, lightning and entrainments from the lower troposphere and from the tropopause region determine the distinct composition of the anticyclone and its outflow.
Evgenia Galytska, Vassyl Danylevsky, René Hommel, and John P. Burrows
Atmos. Meas. Tech., 11, 2101–2118, https://doi.org/10.5194/amt-11-2101-2018, https://doi.org/10.5194/amt-11-2101-2018, 2018
Short summary
Short summary
This research assesses the influence of biomass burning during forest fires throughout summer 2010 on aerosol load over Ukraine, the European territory of Russia (ETR) and Eastern Europe. We apply and compare ground-based and satellite measurements to determine aerosol content, dynamics, and properties. With the application of modeling techniques (HYSPLIT), we show that the maximum AOD in August 2010 over Ukraine was caused by particle transport from the forest fires in the ETR.
Stefan Noël, Katja Weigel, Klaus Bramstedt, Alexei Rozanov, Mark Weber, Heinrich Bovensmann, and John P. Burrows
Atmos. Chem. Phys., 18, 4463–4476, https://doi.org/10.5194/acp-18-4463-2018, https://doi.org/10.5194/acp-18-4463-2018, 2018
Short summary
Short summary
The combined analysis of stratospheric methane and water vapour data derived from SCIAMACHY solar occultation measurements shows the expected anti-correlation and a clear temporal variation related to waves in equatorial zonal winds. Above about 20 km most of the additional water vapour is attributed to the oxidation of methane. The SCIAMACHY data confirm that at lower altitudes water vapour and methane are transported from the tropics to higher latitudes.
Axel Lauer, Colin Jones, Veronika Eyring, Martin Evaldsson, Stefan Hagemann, Jarmo Mäkelä, Gill Martin, Romain Roehrig, and Shiyu Wang
Earth Syst. Dynam., 9, 33–67, https://doi.org/10.5194/esd-9-33-2018, https://doi.org/10.5194/esd-9-33-2018, 2018
Klaus-D. Gottschaldt, Hans Schlager, Robert Baumann, Heiko Bozem, Veronika Eyring, Peter Hoor, Patrick Jöckel, Tina Jurkat, Christiane Voigt, Andreas Zahn, and Helmut Ziereis
Atmos. Chem. Phys., 17, 6091–6111, https://doi.org/10.5194/acp-17-6091-2017, https://doi.org/10.5194/acp-17-6091-2017, 2017
Short summary
Short summary
We present upper-tropospheric trace gas measurements in the Asian summer monsoon anticyclone, obtained with the HALO research aircraft in September 2012. The anticyclone is one of the largest atmospheric features on Earth, but many aspects of it are not well understood. With the help of model simulations we find that entrainments from the tropopause region and the lower troposphere, combined with photochemistry and dynamical instabilities, can explain the observations.
Stefan Lossow, Farahnaz Khosrawi, Gerald E. Nedoluha, Faiza Azam, Klaus Bramstedt, John. P. Burrows, Bianca M. Dinelli, Patrick Eriksson, Patrick J. Espy, Maya García-Comas, John C. Gille, Michael Kiefer, Stefan Noël, Piera Raspollini, William G. Read, Karen H. Rosenlof, Alexei Rozanov, Christopher E. Sioris, Gabriele P. Stiller, Kaley A. Walker, and Katja Weigel
Atmos. Meas. Tech., 10, 1111–1137, https://doi.org/10.5194/amt-10-1111-2017, https://doi.org/10.5194/amt-10-1111-2017, 2017
William J. Collins, Jean-François Lamarque, Michael Schulz, Olivier Boucher, Veronika Eyring, Michaela I. Hegglin, Amanda Maycock, Gunnar Myhre, Michael Prather, Drew Shindell, and Steven J. Smith
Geosci. Model Dev., 10, 585–607, https://doi.org/10.5194/gmd-10-585-2017, https://doi.org/10.5194/gmd-10-585-2017, 2017
Short summary
Short summary
We have designed a set of climate model experiments called the Aerosol Chemistry Model Intercomparison Project (AerChemMIP). These are designed to quantify the climate and air quality impacts of aerosols and chemically reactive gases in the climate models that are used to simulate past and future climate. We hope that many climate modelling centres will choose to run these experiments to help understand the contribution of aerosols and chemistry to climate change.
Veronika Eyring, Peter J. Gleckler, Christoph Heinze, Ronald J. Stouffer, Karl E. Taylor, V. Balaji, Eric Guilyardi, Sylvie Joussaume, Stephan Kindermann, Bryan N. Lawrence, Gerald A. Meehl, Mattia Righi, and Dean N. Williams
Earth Syst. Dynam., 7, 813–830, https://doi.org/10.5194/esd-7-813-2016, https://doi.org/10.5194/esd-7-813-2016, 2016
Short summary
Short summary
We argue that the CMIP community has reached a critical juncture at which many baseline aspects of model evaluation need to be performed much more efficiently to enable a systematic and rapid performance assessment of the large number of models participating in CMIP, and we announce our intention to implement such a system for CMIP6. At the same time, continuous scientific research is required to develop innovative metrics and diagnostics that help narrowing the spread in climate projections.
George J. Boer, Douglas M. Smith, Christophe Cassou, Francisco Doblas-Reyes, Gokhan Danabasoglu, Ben Kirtman, Yochanan Kushnir, Masahide Kimoto, Gerald A. Meehl, Rym Msadek, Wolfgang A. Mueller, Karl E. Taylor, Francis Zwiers, Michel Rixen, Yohan Ruprich-Robert, and Rosie Eade
Geosci. Model Dev., 9, 3751–3777, https://doi.org/10.5194/gmd-9-3751-2016, https://doi.org/10.5194/gmd-9-3751-2016, 2016
Short summary
Short summary
The Decadal Climate Prediction Project (DCPP) investigates our ability to skilfully predict climate variations from a year to a decade ahead by means of a series of retrospective forecasts. Quasi-real-time forecasts are also produced for potential users. In addition, the DCPP investigates how perturbations such as volcanoes affect forecasts and, more broadly, what new information can be learned about the mechanisms governing climate variations by means of case studies of past climate behaviour.
Brian C. O'Neill, Claudia Tebaldi, Detlef P. van Vuuren, Veronika Eyring, Pierre Friedlingstein, George Hurtt, Reto Knutti, Elmar Kriegler, Jean-Francois Lamarque, Jason Lowe, Gerald A. Meehl, Richard Moss, Keywan Riahi, and Benjamin M. Sanderson
Geosci. Model Dev., 9, 3461–3482, https://doi.org/10.5194/gmd-9-3461-2016, https://doi.org/10.5194/gmd-9-3461-2016, 2016
Short summary
Short summary
The Scenario Model Intercomparison Project (ScenarioMIP) will provide multi-model climate projections based on alternative scenarios of future emissions and land use changes produced with integrated assessment models. The design consists of eight alternative 21st century scenarios plus one large initial condition ensemble and a set of long-term extensions. Climate model projections will facilitate integrated studies of climate change as well as address targeted scientific questions.
Raquel A. Silva, J. Jason West, Jean-François Lamarque, Drew T. Shindell, William J. Collins, Stig Dalsoren, Greg Faluvegi, Gerd Folberth, Larry W. Horowitz, Tatsuya Nagashima, Vaishali Naik, Steven T. Rumbold, Kengo Sudo, Toshihiko Takemura, Daniel Bergmann, Philip Cameron-Smith, Irene Cionni, Ruth M. Doherty, Veronika Eyring, Beatrice Josse, Ian A. MacKenzie, David Plummer, Mattia Righi, David S. Stevenson, Sarah Strode, Sophie Szopa, and Guang Zengast
Atmos. Chem. Phys., 16, 9847–9862, https://doi.org/10.5194/acp-16-9847-2016, https://doi.org/10.5194/acp-16-9847-2016, 2016
Short summary
Short summary
Using ozone and PM2.5 concentrations from the ACCMIP ensemble of chemistry-climate models for the four Representative Concentration Pathway scenarios (RCPs), together with projections of future population and baseline mortality rates, we quantify the human premature mortality impacts of future ambient air pollution in 2030, 2050 and 2100, relative to 2000 concentrations. We also estimate the global mortality burden of ozone and PM2.5 in 2000 and each future period.
Veronika Eyring, Sandrine Bony, Gerald A. Meehl, Catherine A. Senior, Bjorn Stevens, Ronald J. Stouffer, and Karl E. Taylor
Geosci. Model Dev., 9, 1937–1958, https://doi.org/10.5194/gmd-9-1937-2016, https://doi.org/10.5194/gmd-9-1937-2016, 2016
Short summary
Short summary
The objective of CMIP is to better understand past, present, and future climate change in a multi-model context. CMIP's increasing importance and scope is a tremendous success story, but the need to address an ever-expanding range of scientific questions arising from more and more research communities has made it necessary to revise the organization of CMIP. In response to these challenges, we have adopted a more federated structure for the sixth phase of CMIP (i.e. CMIP6) and subsequent phases.
Veronika Eyring, Mattia Righi, Axel Lauer, Martin Evaldsson, Sabrina Wenzel, Colin Jones, Alessandro Anav, Oliver Andrews, Irene Cionni, Edouard L. Davin, Clara Deser, Carsten Ehbrecht, Pierre Friedlingstein, Peter Gleckler, Klaus-Dirk Gottschaldt, Stefan Hagemann, Martin Juckes, Stephan Kindermann, John Krasting, Dominik Kunert, Richard Levine, Alexander Loew, Jarmo Mäkelä, Gill Martin, Erik Mason, Adam S. Phillips, Simon Read, Catherine Rio, Romain Roehrig, Daniel Senftleben, Andreas Sterl, Lambertus H. van Ulft, Jeremy Walton, Shiyu Wang, and Keith D. Williams
Geosci. Model Dev., 9, 1747–1802, https://doi.org/10.5194/gmd-9-1747-2016, https://doi.org/10.5194/gmd-9-1747-2016, 2016
Short summary
Short summary
A community diagnostics and performance metrics tool for the evaluation of Earth system models (ESMs) in CMIP has been developed that allows for routine comparison of single or multiple models, either against predecessor versions or against observations.
K. Weigel, A. Rozanov, F. Azam, K. Bramstedt, R. Damadeo, K.-U. Eichmann, C. Gebhardt, D. Hurst, M. Kraemer, S. Lossow, W. Read, N. Spelten, G. P. Stiller, K. A. Walker, M. Weber, H. Bovensmann, and J. P. Burrows
Atmos. Meas. Tech., 9, 133–158, https://doi.org/10.5194/amt-9-133-2016, https://doi.org/10.5194/amt-9-133-2016, 2016
Short summary
Short summary
The SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) aboard the Envisat satellite provided measurements between 2002 and 2012 with different viewing geometries. The limb viewing geometry allows the retrieval of water vapour profiles in the UTLS (upper troposphere and lower stratosphere) from the near-infrared spectral range (1353–1410 nm). Here, we present data version 3.01 and compare it to other water vapour data.
F. Khosrawi, J. Urban, S. Lossow, G. Stiller, K. Weigel, P. Braesicke, M. C. Pitts, A. Rozanov, J. P. Burrows, and D. Murtagh
Atmos. Chem. Phys., 16, 101–121, https://doi.org/10.5194/acp-16-101-2016, https://doi.org/10.5194/acp-16-101-2016, 2016
Short summary
Short summary
Our sensitivity studies based on air parcel trajectories confirm that Polar stratospheric cloud (PSC) formation is quite sensitive to water vapour and temperature changes. Considering water vapour time series from satellite measurements we do not find a consistent, significant trend in water vapour in the lower stratosphere during the past 15 years (2000–2014). Thus, the severe dentrification observed in 2010/2011 cannot be directly related to increases in stratospheric water vapour.
N. Rahpoe, M. Weber, A. V. Rozanov, K. Weigel, H. Bovensmann, J. P. Burrows, A. Laeng, G. Stiller, T. von Clarmann, E. Kyrölä, V. F. Sofieva, J. Tamminen, K. Walker, D. Degenstein, A. E. Bourassa, R. Hargreaves, P. Bernath, J. Urban, and D. P. Murtagh
Atmos. Meas. Tech., 8, 4369–4381, https://doi.org/10.5194/amt-8-4369-2015, https://doi.org/10.5194/amt-8-4369-2015, 2015
Short summary
Short summary
The analyses among six satellite instruments measuring ozone reveals that the relative drift between the sensors is not significant in the stratosphere and we conclude that merging of data from these instruments is possible. The merged ozone profiles can then be ingested in global climate models for long-term forecasts of ozone and climate change in the atmosphere. The added drift uncertainty is estimated at about 3% per decade (1 sigma) and should be applied in the calculation of ozone trends.
M. Righi, V. Eyring, K.-D. Gottschaldt, C. Klinger, F. Frank, P. Jöckel, and I. Cionni
Geosci. Model Dev., 8, 733–768, https://doi.org/10.5194/gmd-8-733-2015, https://doi.org/10.5194/gmd-8-733-2015, 2015
C. F. Schleussner, J. Runge, J. Lehmann, and A. Levermann
Earth Syst. Dynam., 5, 103–115, https://doi.org/10.5194/esd-5-103-2014, https://doi.org/10.5194/esd-5-103-2014, 2014
V. Naik, A. Voulgarakis, A. M. Fiore, L. W. Horowitz, J.-F. Lamarque, M. Lin, M. J. Prather, P. J. Young, D. Bergmann, P. J. Cameron-Smith, I. Cionni, W. J. Collins, S. B. Dalsøren, R. Doherty, V. Eyring, G. Faluvegi, G. A. Folberth, B. Josse, Y. H. Lee, I. A. MacKenzie, T. Nagashima, T. P. C. van Noije, D. A. Plummer, M. Righi, S. T. Rumbold, R. Skeie, D. T. Shindell, D. S. Stevenson, S. Strode, K. Sudo, S. Szopa, and G. Zeng
Atmos. Chem. Phys., 13, 5277–5298, https://doi.org/10.5194/acp-13-5277-2013, https://doi.org/10.5194/acp-13-5277-2013, 2013
D. S. Stevenson, P. J. Young, V. Naik, J.-F. Lamarque, D. T. Shindell, A. Voulgarakis, R. B. Skeie, S. B. Dalsoren, G. Myhre, T. K. Berntsen, G. A. Folberth, S. T. Rumbold, W. J. Collins, I. A. MacKenzie, R. M. Doherty, G. Zeng, T. P. C. van Noije, A. Strunk, D. Bergmann, P. Cameron-Smith, D. A. Plummer, S. A. Strode, L. Horowitz, Y. H. Lee, S. Szopa, K. Sudo, T. Nagashima, B. Josse, I. Cionni, M. Righi, V. Eyring, A. Conley, K. W. Bowman, O. Wild, and A. Archibald
Atmos. Chem. Phys., 13, 3063–3085, https://doi.org/10.5194/acp-13-3063-2013, https://doi.org/10.5194/acp-13-3063-2013, 2013
A. Voulgarakis, V. Naik, J.-F. Lamarque, D. T. Shindell, P. J. Young, M. J. Prather, O. Wild, R. D. Field, D. Bergmann, P. Cameron-Smith, I. Cionni, W. J. Collins, S. B. Dalsøren, R. M. Doherty, V. Eyring, G. Faluvegi, G. A. Folberth, L. W. Horowitz, B. Josse, I. A. MacKenzie, T. Nagashima, D. A. Plummer, M. Righi, S. T. Rumbold, D. S. Stevenson, S. A. Strode, K. Sudo, S. Szopa, and G. Zeng
Atmos. Chem. Phys., 13, 2563–2587, https://doi.org/10.5194/acp-13-2563-2013, https://doi.org/10.5194/acp-13-2563-2013, 2013
P. J. Young, A. T. Archibald, K. W. Bowman, J.-F. Lamarque, V. Naik, D. S. Stevenson, S. Tilmes, A. Voulgarakis, O. Wild, D. Bergmann, P. Cameron-Smith, I. Cionni, W. J. Collins, S. B. Dalsøren, R. M. Doherty, V. Eyring, G. Faluvegi, L. W. Horowitz, B. Josse, Y. H. Lee, I. A. MacKenzie, T. Nagashima, D. A. Plummer, M. Righi, S. T. Rumbold, R. B. Skeie, D. T. Shindell, S. A. Strode, K. Sudo, S. Szopa, and G. Zeng
Atmos. Chem. Phys., 13, 2063–2090, https://doi.org/10.5194/acp-13-2063-2013, https://doi.org/10.5194/acp-13-2063-2013, 2013
J.-F. Lamarque, D. T. Shindell, B. Josse, P. J. Young, I. Cionni, V. Eyring, D. Bergmann, P. Cameron-Smith, W. J. Collins, R. Doherty, S. Dalsoren, G. Faluvegi, G. Folberth, S. J. Ghan, L. W. Horowitz, Y. H. Lee, I. A. MacKenzie, T. Nagashima, V. Naik, D. Plummer, M. Righi, S. T. Rumbold, M. Schulz, R. B. Skeie, D. S. Stevenson, S. Strode, K. Sudo, S. Szopa, A. Voulgarakis, and G. Zeng
Geosci. Model Dev., 6, 179–206, https://doi.org/10.5194/gmd-6-179-2013, https://doi.org/10.5194/gmd-6-179-2013, 2013
Related subject area
Topics: Climate dynamics and variability | Interactions: Ocean/atmosphere interactions | Methods: Earth system and climate modeling
An overview of the E3SM version 2 large ensemble and comparison to other E3SM and CESM large ensembles
Similar North Pacific variability despite suppressed El Niño variability in the warm mid-Pliocene climate
Impact of Atlantic multidecadal variability on rainfall intensity distribution and timing of the West African monsoon
A quantitative assessment of air–sea heat flux trends from ERA5 since 1950 in the North Atlantic basin
John T. Fasullo, Jean-Christophe Golaz, Julie M. Caron, Nan Rosenbloom, Gerald A. Meehl, Warren Strand, Sasha Glanville, Samantha Stevenson, Maria Molina, Christine A. Shields, Chengzhu Zhang, James Benedict, Hailong Wang, and Tony Bartoletti
Earth Syst. Dynam., 15, 367–386, https://doi.org/10.5194/esd-15-367-2024, https://doi.org/10.5194/esd-15-367-2024, 2024
Short summary
Short summary
Climate model large ensembles provide a unique and invaluable means for estimating the climate response to external forcing agents and quantify contrasts in model structure. Here, an overview of the Energy Exascale Earth System Model (E3SM) version 2 large ensemble is given along with comparisons to large ensembles from E3SM version 1 and versions 1 and 2 of the Community Earth System Model. The paper provides broad and important context for users of these ensembles.
Arthur Merlijn Oldeman, Michiel L. J. Baatsen, Anna S. von der Heydt, Frank M. Selten, and Henk A. Dijkstra
EGUsphere, https://doi.org/10.5194/egusphere-2024-766, https://doi.org/10.5194/egusphere-2024-766, 2024
Short summary
Short summary
We might be able to constrain uncertainty in future climate projections by investigating variations in the climate of the past. In this study, we investigate the interactions of climate variability between the tropical Pacific (El Niño) and the North Pacific in a warm past climate – the mid-Pliocene, a period roughly 3 million years ago. Using model simulations, we find that although the variability of El Niño was reduced, the variability in the North Pacific atmosphere was not.
Elsa Mohino, Paul-Arthur Monerie, Juliette Mignot, Moussa Diakhaté, Markus Donat, Christopher David Roberts, and Francisco Doblas-Reyes
Earth Syst. Dynam., 15, 15–40, https://doi.org/10.5194/esd-15-15-2024, https://doi.org/10.5194/esd-15-15-2024, 2024
Short summary
Short summary
The impact of the Atlantic multidecadal variability (AMV) on the rainfall distribution and timing of the West African monsoon is not well known. Analysing model output, we find that a positive AMV enhances the number of wet days, daily rainfall intensity, and extremes over the Sahel and tends to prolong the monsoon length through later demise. Heavy rainfall events increase all over the Sahel, while moderate ones only occur in the north. Model biases affect the skill in simulating AMV impact.
Johannes Mayer, Leopold Haimberger, and Michael Mayer
Earth Syst. Dynam., 14, 1085–1105, https://doi.org/10.5194/esd-14-1085-2023, https://doi.org/10.5194/esd-14-1085-2023, 2023
Short summary
Short summary
This study investigates the temporal stability and reliability of winter-month trends of air–sea heat fluxes from ERA5 forecasts over the North Atlantic basin for the period 1950–2019. Driving forces of trends and the impact of modes of climate variability and analysis increments on air–sea heat fluxes are investigated. Finally, a new and independent estimate of the Atlantic Meridional Overturning Circulation weakening is provided and associated with a decrease in air–sea heat fluxes.
Cited articles
Andela, B., Broetz, B., de Mora, L., Drost, N., Eyring, V., Koldunov, N., Lauer, A., Mueller, B., Predoi, V., Righi, M., Schlund, M., Vegas-Regidor, J., Zimmermann, K., Adeniyi, K., Arnone, E., Bellprat, O., Berg, P., Bock, L., Bodas-Salcedo, A., Caron, L.-P., Carvalhais, N., Cionni, I., Cortesi, N., Corti, S., Crezee, B., Davin, E. L., Davini, P., Deser, C., Diblen, F., Docquier, D., Dreyer, L., Ehbrecht, C., Earnshaw, P., Gier, B., Gonzalez-Reviriego, N., Goodman, P., Hagemann, S., von Hardenberg, J., Hassler, B., Heuer, H., Hunter, A., Kadow, C., Kindermann, S., Koirala, S., Kuehbacher, B., Lledó, L., Lejeune, Q., Lembo, V., Little, B., Loosveldt-Tomas, S., Lorenz, R., Lovato, T., Lucarini, V., Massonnet, F., Mohr, C. W., Amarjiit, P., Pérez-Zanón, N., Phillips, A., Russell, J., Sandstad, M., Sellar, A., Senftleben, D., Serva, F., Sillmann, J., Stacke, T., Swaminathan, R., Torralba, V., Weigel, K., Sarauer, E., Roberts, C., Kalverla, P., Alidoost, S., Verhoeven, S., Vreede, B., Smeets, S., Soares Siqueira, A., Kazeroni, R., Potter, J., Winterstein, F., Beucher, R., Kraft, J., Ruhe, L., and Bonnet, P.: ESMValTool, Zenodo [code], https://doi.org/10.5281/zenodo.10408909, 2023. a
Allen, R. J., Norris, J. R., and Kovilakam, M.: Influence of anthropogenic aerosols and the Pacific Decadal Oscillation on tropical belt width, Nat. Geosci., 7, 270–274, https://doi.org/10.1038/ngeo2091, 2014. a
An, X., Wu, B., Zhou, T., and Liu, B.: Atlantic Multidecadal Oscillation Drives Interdecadal Pacific Variability via Tropical Atmospheric Bridge, J. Climate, 34, 5543–5553, https://doi.org/10.1175/jcli-d-20-0983.1, 2021. a
Barnett, T. P.: Variations in Near-Global Sea Level Pressure, J. Atmos. Sci., 42, 478–501, https://doi.org/10.1175/1520-0469(1985)042<0478:vingsl>2.0.co;2, 1985. a
Bayr, T., Dommenget, D., Martin, T., and Power, S. B.: The eastward shift of the Walker Circulation in response to global warming and its relationship to ENSO variability, Clim. Dynam., 43, 2747–2763, https://doi.org/10.1007/s00382-014-2091-y, 2014. a
Bellucci, A., Mariotti, A., and Gualdi, S.: The Role of Forcings in the Twentieth-Century North Atlantic Multidecadal Variability: The 1940–75 North Atlantic Cooling Case Study, J. Climate, 30, 7317–7337, https://doi.org/10.1175/jcli-d-16-0301.1, 2017. a
Bjerknes, J.: A possible response of the atmospheric Hadley circulation to equatorial anomalies of ocean temperature, Tellus, 18, 820–829, https://doi.org/10.1111/j.2153-3490.1966.tb00303.x, 1966. a
Bjerknes, J.: Atmospheric Teleconnections from the Equatorial Pacific, Month. Weather Rev., 97, 163–172, https://doi.org/10.1175/1520-0493(1969)097<0163:atftep>2.3.co;2, 1969. a, b
Booth, B. B. B., Dunstone, N. J., Halloran, P. R., Andrews, T., and Bellouin, N.: Aerosols implicated as a prime driver of twentieth-century North Atlantic climate variability, Nature, 484, 228–232, https://doi.org/10.1038/nature10946, 2012. a
Borchert, L. F., Koul, V., Menary, M. B., Befort, D. J., Swingedouw, D., Sgubin, G., and Mignot, J.: Skillful decadal prediction of unforced southern European summer temperature variations, Environ. Res. Lett., 16, 104017, https://doi.org/10.1088/1748-9326/ac20f5, 2021. a, b
Brönnimann, S.: Impact of El Niño–Southern Oscillation on European climate, Rev. Geophys., 45, RG3003, https://doi.org/10.1029/2006rg000199, 2007. a, b
Brönnimann, S., Xoplaki, E., Casty, C., Pauling, A., and Luterbacher, J.: ENSO influence on Europe during the last centuries, Clim. Dynam., 28, 181–197, https://doi.org/10.1007/s00382-006-0175-z, 2006. a, b
Capotondi, A., Deser, C., Phillips, A. S., Okumura, Y., and Larson, S. M.: ENSO and Pacific Decadal Variability in the Community Earth System Model Version 2, J. Adv. Model. Earth Sy., 12, e2019MS002022, https://doi.org/10.1029/2019ms002022, 2020. a
Casselman, J. W., Taschetto, A. S., and Domeisen, D. I.: Non-linearity in the pathway of El Niño-Southern Oscillation to the tropical North Atlantic, J. Climate, 34, 7277–7296, https://doi.org/10.1175/jcli-d-20-0952.1, 2021. a, b
Cassou, C. and Terray, L.: Oceanic Forcing of the Wintertime Low-Frequency Atmospheric Variability in the North Atlantic European Sector: A Study with the ARPEGE Model, J. Climate, 14, 4266–4291, https://doi.org/10.1175/1520-0442(2001)014<4266:ofotwl>2.0.co;2, 2001. a
Chang, P., Fang, Y., Saravanan, R., Ji, L., and Seidel, H.: The cause of the fragile relationship between the Pacific El Niño and the Atlantic Niño, Nature, 443, 324–328, https://doi.org/10.1038/nature05053, 2006. a
Chen, H.-C., Jin, F.-F., Zhao, S., Wittenberg, A. T., and Xie, S.: ENSO Dynamics in the E3SM-1-0, CESM2, and GFDL-CM4 Climate Models, J. Climate, 34, 9365–9384, https://doi.org/10.1175/jcli-d-21-0355.1, 2021. a
Chiang, J. C. H. and Vimont, D. J.: Analogous Pacific and Atlantic Meridional Modes of Tropical Atmosphere–Ocean Variability*, J. Climate, 17, 4143–4158, https://doi.org/10.1175/jcli4953.1, 2004. a
Chung, E.-S., Timmermann, A., Soden, B. J., Ha, K.-J., Shi, L., and John, V. O.: Reconciling opposing Walker circulation trends in observations and model projections, Nat. Clim. Change, 9, 405–412, https://doi.org/10.1038/s41558-019-0446-4, 2019. a, b, c
Chylek, P., Folland, C., Klett, J. D., and Dubey, M. K.: CMIP5 Climate Models Overestimate Cooling by Volcanic Aerosols, Geophys. Res. Lett., 47, e2020GL087047, https://doi.org/10.1029/2020gl087047, 2020. a
Copernicus Climate Change Service: ERA5 monthly averaged data on single levels from 1979 to present, Copernicus Climate Change Service [data set], https://doi.org/10.24381/CDS.F17050D7, 2019. a
Copernicus Climate Change Service: ORAS5 global ocean reanalysis monthly data from 1958 to present, Copernicus Climate Change Service [data set], https://doi.org/10.24381/CDS.67E8EEB7, 2021. a
Czaja, A., van der Vaart, P., and Marshall, J.: A Diagnostic Study of the Role of Remote Forcing in Tropical Atlantic Variability, J. Climate, 15, 3280–3290, https://doi.org/10.1175/1520-0442(2002)015<3280:adsotr>2.0.co;2, 2002. a
Danabasoglu, G., Lamarque, J., Bacmeister, J., Bailey, D. A., DuVivier, A. K., Edwards, J., Emmons, L. K., Fasullo, J., Garcia, R., Gettelman, A., Hannay, C., Holland, M. M., Large, W. G., Lauritzen, P. H., Lawrence, D. M., Lenaerts, J. T. M., Lindsay, K., Lipscomb, W. H., Mills, M. J., Neale, R., Oleson, K. W., Otto‐Bliesner, B., Phillips, A. S., Sacks, W., Tilmes, S., van Kampenhout, L., Vertenstein, M., Bertini, A., Dennis, J., Deser, C., Fischer, C., Fox‐Kemper, B., Kay, J. E., Kinnison, D., Kushner, P. J., Larson, V. E., Long, M. C., Mickelson, S., Moore, J. K., Nienhouse, E., Polvani, L., Rasch, P. J., and Strand, W. G.: The Community Earth System Model Version 2 (CESM2), J. Adv. Model. Earth Sy., 12, e2019MS001916, https://doi.org/10.1029/2019ms001916, 2020. a, b
Debeire, K., Gerhardus, A., Runge, J., and Eyring, V.: Bootstrap aggregation and confidence measures to improve time series causal discovery, in: Proceedings of the Third Conference on Causal Learning and Reasoning, edited by: Locatello, F. and Didelez, V., PMLR, Vol. 236, 979–1007, 2024. a
Deser, C.: “Certain Uncertainty: The Role of Internal Climate Variability in Projections of Regional Climate Change and Risk Management”, Earth’s Future, 8, e2020EF001854, https://doi.org/10.1029/2020ef001854, 2020. a
Deser, C., Phillips, A., Bourdette, V., and Teng, H.: Uncertainty in climate change projections: the role of internal variability, Clim. Dynam., 38, 527–546, https://doi.org/10.1007/s00382-010-0977-x, 2010. a, b
DiNezio, P. N., Vecchi, G. A., and Clement, A. C.: Detectability of Changes in the Walker Circulation in Response to Global Warming*, J. Climate, 26, 4038–4048, https://doi.org/10.1175/jcli-d-12-00531.1, 2013. a
Dong, L. and McPhaden, M. J.: The role of external forcing and internal variability in regulating global mean surface temperatures on decadal timescales, Environ. Res. Lett., 12, 034011, https://doi.org/10.1088/1748-9326/aa5dd8, 2017. a
Dong, L., Zhou, T., and Chen, X.: Changes of Pacific decadal variability in the twentieth century driven by internal variability, greenhouse gases, and aerosols, Geophys. Res. Lett., 41, 8570–8577, https://doi.org/10.1002/2014gl062269, 2014. a, b
Enfield, D. B. and Mayer, D. A.: Tropical Atlantic sea surface temperature variability and its relation to El Niño‐Southern Oscillation, J. Geophys. Res., 102, 929–945, https://doi.org/10.1029/96JC03296, 1997. a
Enfield, D. B., Mestas‐Nuñez, A. M., Mayer, D. A., and Cid‐Serrano, L.: How ubiquitous is the dipole relationship in tropical Atlantic sea surface temperatures?, J. Geophys. Res.-Oceans, 104, 7841–7848, https://doi.org/10.1029/1998jc900109, 1999. 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
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., Hurtt, G. C., Jahn, A., Jones, C. D., Klein, S. A., Krasting, J. P., Kwiatkowski, L., Lorenz, R., Maloney, E., Meehl, G. A., Pendergrass, A. G., Pincus, R., Ruane, A. C., Russell, J. L., Sanderson, B. M., Santer, B. D., Sherwood, S. C., Simpson, I. R., Stouffer, R. J., and Williamson, M. S.: Taking climate model evaluation to the next level, Nat. Clim. Change, 9, 102–110, https://doi.org/10.1038/s41558-018-0355-y, 2019. a
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.-K., Morgenstern, O., and Sun, Y.: Human Influence on the Climate System, 423–552, Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, https://doi.org/10.1017/9781009157896.005, 2021. a
Fasullo, J. T., Phillips, A. S., 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, b, c
Fyfe, J. C., Kharin, V. V., Santer, B. D., Cole, J. N. S., and Gillett, N. P.: Significant impact of forcing uncertainty in a large ensemble of climate model simulations, P. Natl. Acad. Sci., 118, e2016549118, https://doi.org/10.1073/pnas.2016549118, 2021. a, b
Galytska, E., Weigel, K., Handorf, D., Jaiser, R., Köhler, R., Runge, J., and Eyring, V.: Evaluating Causal Arctic-Midlatitude Teleconnections in CMIP6, J. Geophys. Res.-Atmos., 128, e2022JD037978, https://doi.org/10.1029/2022JD037978, 2023. a
García-Serrano, J., Cassou, C., Douville, H., Giannini, A., and Doblas-Reyes, F. J.: Revisiting the ENSO Teleconnection to the Tropical North Atlantic, J. Climate, 30, 6945–6957, https://doi.org/10.1175/jcli-d-16-0641.1, 2017a. a
Gerhardus, A. and Runge, J.: High-recall causal discovery for autocorrelated time series with latent confounders, in: Advances in Neural Information Processing Systems, edited by: Larochelle, H., Ranzato, M., Hadsell, R., Balcan, M. F., and Lin, H., Curran Associates, Inc., Vol. 33, 12615–12625, 2020. a
Gill, A. E.: Some simple solutions for heat‐induced tropical circulation, Q. J. Roy. Meteor. Soc., 106, 447–462, https://doi.org/10.1002/qj.49710644905, 1980. a
Ham, Y., Kug, J., and Park, J.: Two distinct roles of Atlantic SSTs in ENSO variability: North Tropical Atlantic SST and Atlantic Niño, Geophys. Res. Lett., 40, 4012–4017, https://doi.org/10.1002/grl.50729, 2013a. a
Ham, Y.-G., Kug, J.-S., Park, J.-Y., and Jin, F.-F.: Sea surface temperature in the north tropical Atlantic as a trigger for El Niño/Southern Oscillation events, Nat. Geosci., 6, 112–116, https://doi.org/10.1038/ngeo1686, 2013b. a, b, c, d
Haustein, K., Otto, F. E. L., Venema, V., Jacobs, P., Cowtan, K., Hausfather, Z., Way, R. G., White, B., Subramanian, A., and Schurer, A. P.: A Limited Role for Unforced Internal Variability in Twentieth-Century Warming, J. Climate, 32, 4893–4917, https://doi.org/10.1175/jcli-d-18-0555.1, 2019. a
He, C., Clement, A. C., Kramer, S. M., Cane, M. A., Klavans, J. M., Fenske, T. M., and Murphy, L. N.: Tropical Atlantic multidecadal variability is dominated by external forcin, Nature, 622, 521–527, https://doi.org/10.1038/s41586-023-06489-4, 2023. a, b
Honda, M., Nakamura, H., Ukita, J., Kousaka, I., and Takeuchi, K.: Interannual Seesaw between the Aleutian and Icelandic Lows. Part I: Seasonal Dependence and Life Cycle, J. Climate, 14, 1029–1042, https://doi.org/10.1175/1520-0442(2001)014<1029:isbtaa>2.0.co;2, 2001. a, b, c, d
Hoskins, B. J. and Karoly, D. J.: The Steady Linear Response of a Spherical Atmosphere to Thermal and Orographic Forcing, J. Atmos. Sci., 38, 1179–1196, https://doi.org/10.1175/1520-0469(1981)038<1179:tslroa>2.0.co;2, 1981. a, b
Hurrell, J. W. and Deser, C.: North Atlantic climate variability: The role of the North Atlantic Oscillation, J. Marine Syst., 78, 28–41, https://doi.org/10.1016/j.jmarsys.2008.11.026, 2009. a
IPCC: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, https://doi.org/10.1017/CBO9781107415324, 2013. a
Jiang, L. and Li, T.: Relative roles of El Niño-induced extratropical and tropical forcing in generating Tropical North Atlantic (TNA) SST anomaly, Clim. Dynam., 53, 3791–3804, https://doi.org/10.1007/s00382-019-04748-7, 2019. a, b, c, d
Kalnay, E., Kanamitsu, M., Kistler, R., Collins, W., Deaven, D., Gandin, L., Iredell, M., Saha, S., White, G., Woollen, J., Zhu, Y., Leetmaa, A., Reynolds, R., Chelliah, M., Ebisuzaki, W., Higgins, W., Janowiak, J., Mo, K. C., Ropelewski, C., Wang, J., Jenne, R., and Joseph, D.: The NCEP/NCAR 40-Year Reanalysis Project, B. Am. Meteorol. Soc., 77, 437–471, https://doi.org/10.1175/1520-0477(1996)077<0437:tnyrp>2.0.co;2, 1996. a
Karmouche, S.: EyringMLClimateGroup/karmouche24esd_AtlanticPacificPacemaker_Causality: 1st Release, Zenodo [code], https://doi.org/10.5281/zenodo.11518925, 2024. a
Karoly, D. J.: Rossby wave propagation in a barotropic atmosphere, Dynam. Atmos. Oceans, 7, 111–125, https://doi.org/10.1016/0377-0265(83)90013-1, 1983. a, b
Kaufmann, R. K., Kauppi, H., Mann, M. L., and Stock, J. H.: Reconciling anthropogenic climate change with observed temperature 1998–2008, P. Natl. Acad. Sci. USA, 108, 11790–11793, https://doi.org/10.1073/pnas.1102467108, 2011. a
Keenlyside, N. S., Ding, H., and Latif, M.: Potential of equatorial Atlantic variability to enhance El Niño prediction, Geophys. Res. Lett., 40, 2278–2283, https://doi.org/10.1002/grl.50362, 2013. a
Klavans, J. M., Cane, M. A., Clement, A. C., and Murphy, L. N.: NAO predictability from external forcing in the late 20th century, npj Climate and Atmospheric Science, 4, 22, https://doi.org/10.1038/s41612-021-00177-8, 2021. a
Klein, S. A., Soden, B. J., and Lau, N.-C.: Remote Sea Surface Temperature Variations during ENSO: Evidence for a Tropical Atmospheric Bridge, J. Climate, 12, 917–932, https://doi.org/10.1175/1520-0442(1999)012<0917:rsstvd>2.0.co;2, 1999. a, b, c
Kociuba, G. and Power, S. B.: Inability of CMIP5 Models to Simulate Recent Strengthening of the Walker Circulation: Implications for Projections, J. Climate, 28, 20–35, https://doi.org/10.1175/jcli-d-13-00752.1, 2014. a
Kosaka, Y. and Xie, S.-P.: Recent global-warming hiatus tied to equatorial Pacific surface cooling, Nature, 501, 403–407, https://doi.org/10.1038/nature12534, 2013. a
Kucharski, F., Kang, I.-S., Farneti, R., and Feudale, L.: Tropical Pacific response to 20th century Atlantic warming: PACIFIC RESPONSE TO ATLANTIC WARMING, Geophys. Res. Lett., 38, L03702, https://doi.org/10.1029/2010gl046248, 2011. a
Kucharski, F., Ikram, F., Molteni, F., Farneti, R., Kang, I.-S., No, H.-H., King, M. P., Giuliani, G., and Mogensen, K.: Atlantic forcing of Pacific decadal variability, Clim. Dynam., 46, 2337–2351, https://doi.org/10.1007/s00382-015-2705-z, 2015. a
Kumar, A., Jha, B., and Wang, H.: Attribution of SST variability in global oceans and the role of ENSO, Clim. Dynam., 43, 209–220, https://doi.org/10.1007/s00382-013-1865-y, 2013. a
Latif, M. and Grötzner, A.: The equatorial Atlantic oscillation and its response to ENSO, Clim. Dynam., 16, 213–218, https://doi.org/10.1007/s003820050014, 2000. a, b, c
Lee, S., Enfield, D. B., and Wang, C.: Why do some El Niños have no impact on tropical North Atlantic SST?, Geophys. Res. Lett., 35, L16705, https://doi.org/10.1029/2008gl034734, 2008. a
Lengaigne, M., Boulanger, J., Menkes, C., Masson, S., Madec, G., and Delecluse, P.: Ocean response to the March 1997 Westerly Wind Event, J. Geophys. Res.-Oceans, 107, SRF 16-1–SRF 16-20, https://doi.org/10.1029/2001jc000841, 2002. a, b
Lengaigne, M., Boulanger, J.-P., Menkes, C., Madec, G., Delecluse, P., Guilyardi, E., and Slingo, J.: The March 1997 Westerly Wind Event and the Onset of the 1997/98 El Niño: Understanding the Role of the Atmospheric Response, J. Climate, 16, 3330–3343, https://doi.org/10.1175/1520-0442(2003)016<3330:tmwwea>2.0.co;2, 2003. a, b, c
Lengaigne, M., Guilyardi, E., Boulanger, J.-P., Menkes, C., Delecluse, P., Inness, P., Cole, J., and Slingo, J.: Triggering of El Niño by westerly wind events in a coupled general circulation model, Clim. Dynam., 23, 601–620, https://doi.org/10.1007/s00382-004-0457-2, 2004. a, b
Levine, A. F. Z., McPhaden, M. J., and Frierson, D. M. W.: The impact of the AMO on multidecadal ENSO variability, Geophys. Res. Lett., 44, 3877–3886, https://doi.org/10.1002/2017gl072524, 2017. a
Li, X., Xie, S.-P., Gille, S. T., and Yoo, C.: Atlantic-induced pan-tropical climate change over the past three decades, Nat. Clim. Change, 6, 275–279, https://doi.org/10.1038/nclimate2840, 2015. a, b
Lian, T. and Chen, D.: The essential role of early-spring westerly wind burst in generating the centennial extreme 1997/98 El Niño, J. Climate, 34, 8377–8388, https://doi.org/10.1175/jcli-d-21-0010.1, 2021. a
Lin, H. and Derome, J.: Nonlinearity of the Extratropical Response to Tropical Forcing, J. Climate, 17, 2597–2608, https://doi.org/10.1175/1520-0442(2004)017<2597:notert>2.0.co;2, 2004. a
Luo, J.-J., Sasaki, W., and Masumoto, Y.: Indian Ocean warming modulates Pacific climate change, P. Natl. Acad. Sci. USA, 109, 18701–18706, https://doi.org/10.1073/pnas.1210239109, 2012. a
L'Heureux, M. L., Lee, S., and Lyon, B.: Recent multidecadal strengthening of the Walker circulation across the tropical Pacific, Nat. Clim. Change, 3, 571–576, https://doi.org/10.1038/nclimate1840, 2013. a
Maher, N., McGregor, S., England, M. H., and Gupta, A. S.: Effects of volcanism on tropical variability, Geophys. Res. Lett., 42, 6024–6033, https://doi.org/10.1002/2015gl064751, 2015. a
Maher, N., Matei, D., Milinski, S., and Marotzke, J.: ENSO Change in Climate Projections: Forced Response or Internal Variability?, Geophys. Res. Lett., 45, 11390–11398, https://doi.org/10.1029/2018gl079764, 2018. a
Mann, M. E., Steinman, B. A., and Miller, S. K.: On forced temperature changes, internal variability, and the AMO: INTERNAL VARIABILITY AND THE AMO, Geophys. Res. Lett., 41, 3211–3219, https://doi.org/10.1002/2014gl059233, 2014. a, b
Mantua, N. J., Hare, S. R., Zhang, Y., Wallace, J. M., and Francis, R. C.: A Pacific Interdecadal Climate Oscillation with Impacts on Salmon Production, B. Am. Meteorol. Soc., 78, 1069–1079, https://doi.org/10.1175/1520-0477(1997)078<1069:apicow>2.0.co;2, 1997. a, b
Martín-Rey, M., Rodríguez-Fonseca, B., Polo, I., and Kucharski, F.: On the Atlantic–Pacific Niños connection: a multidecadal modulated mode, Clim. Dynam., 43, 3163–3178, https://doi.org/10.1007/s00382-014-2305-3, 2014a. a, b
Martín-Rey, M., Rodríguez-Fonseca, B., Polo, I., and Kucharski, F.: On the Atlantic–Pacific Niños connection: a multidecadal modulated mode, Clim. Dynam., 43, 3163–3178, https://doi.org/10.1007/s00382-014-2305-3, 2014b. a
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. B. R., Maycock, T. K., Waterfield, T., Yelekçi, O., Yu, R., and Zhou, B.: AR6, Annex IV: Modes of Variability, 2153–2192, Cambridge University Press, ISBN 9781009157896, https://doi.org/10.1017/9781009157896.018, 2023. a, b, c
Matsuno, T.: Quasi-Geostrophic Motions in the Equatorial Area, J. Meteorol. Soc. Jpn. Ser. II, 44, 25–43, https://doi.org/10.2151/jmsj1965.44.1_25, 1966. a
McBride, L. A., Hope, A. P., Canty, T. P., Bennett, B. F., Tribett, W. R., and Salawitch, R. J.: Comparison of CMIP6 historical climate simulations and future projected warming to an empirical model of global climate, Earth Syst. Dynam., 12, 545–579, https://doi.org/10.5194/esd-12-545-2021, 2021. a
McGregor, S., Timmermann, A., Stuecker, M. F., England, M. H., Merrifield, M., Jin, F.-F., and Chikamoto, Y.: Recent Walker circulation strengthening and Pacific cooling amplified by Atlantic warming, Nat. Clim. Change, 4, 888–892, https://doi.org/10.1038/nclimate2330, 2014. a, b, c
McPhaden, M. J.: Genesis and Evolution of the 1997–98 El Niño, Science, 283, 950–954, https://doi.org/10.1126/science.283.5404.950, 1999. a, b, c
Meehl, G. A., Hu, A., Arblaster, J. M., Fasullo, J., and Trenberth, K. E.: Externally Forced and Internally Generated Decadal Climate Variability Associated with the Interdecadal Pacific Oscillation, J. Climate, 26, 7298–7310, https://doi.org/10.1175/jcli-d-12-00548.1, 2013. a, b, c
Meehl, G. A., Chung, C. T. Y., Arblaster, J. M., Holland, M. M., and Bitz, C. M.: Tropical Decadal Variability and the Rate of Arctic Sea Ice Decrease, Geophys. Res. Lett., 45, 11326–11333, https://doi.org/10.1029/2018gl079989, 2018. a
Meehl, G. A., Hu, A., Castruccio, F., England, M. H., Bates, S. C., Danabasoglu, G., McGregor, S., Arblaster, J. M., Xie, S.-P., and Rosenbloom, N.: Atlantic and Pacific tropics connected by mutually interactive decadal-timescale processes, Nat. Geosci., 14, 36–42, https://doi.org/10.1038/s41561-020-00669-x, 2020. a, b, c, d, e, f, g, h, i, j, k, l
Menary, M. B., Robson, J., Allan, R. P., Booth, B. B. B., Cassou, C., Gastineau, G., Gregory, J., Hodson, D., Jones, C., Mignot, J., Ringer, M., Sutton, R., Wilcox, L., and Zhang, R.: Aerosol‐Forced AMOC Changes in CMIP6 Historical Simulations, Geophys. Res. Lett., 47, e2020GL088166, https://doi.org/10.1029/2020gl088166, 2020. a, b
Milinski, S., Maher, N., and Olonscheck, D.: How large does a large ensemble need to be?, Earth Syst. Dynam., 11, 885–901, https://doi.org/10.5194/esd-11-885-2020, 2020. a
Murphy, L. N., Bellomo, K., Cane, M., and Clement, A.: The role of historical forcings in simulating the observed Atlantic multidecadal oscillation, Geophys. Res. Lett., 44, 2472–2480, https://doi.org/10.1002/2016gl071337, 2017. a, b
Murtugudde, R. G., Ballabrera‐Poy, J., Beauchamp, J., and Busalacchi, A. J.: Relationship between zonal and meridional modes in the tropical Atlantic, Geophys. Res. Lett., 28, 4463–4466, https://doi.org/10.1029/2001gl013407, 2001. a
Neelin, J. D., Battisti, D. S., Hirst, A. C., Jin, F., Wakata, Y., Yamagata, T., and Zebiak, S. E.: ENSO theory, J. Geophys. Res.-Oceans, 103, 14261–14290, https://doi.org/10.1029/97jc03424, 1998. a, b
Newman, M., Alexander, M. A., Ault, T. R., Cobb, K. M., Deser, C., Di Lorenzo, E., Mantua, N. J., Miller, A. J., Minobe, S., Nakamura, H., Schneider, N., Vimont, D. J., Phillips, A. S., Scott, J. D., and Smith, C. A.: The Pacific Decadal Oscillation, Revisited, J. Climate, 29, 4399–4427, https://doi.org/10.1175/jcli-d-15-0508.1, 2016. a
O'Brien, J. P. and Deser, C.: Quantifying and Understanding Forced Changes to Unforced Modes of Atmospheric Circulation Variability over the North Pacific in a Coupled Model Large Ensemble, J. Climate, 36, 19–37, https://doi.org/10.1175/jcli-d-22-0101.1, 2023. a
Park, J.-H., Li, T., Yeh, S.-W., and Kim, H.: Effect of recent Atlantic warming in strengthening Atlantic–Pacific teleconnection on interannual timescale via enhanced connection with the pacific meridional mode, Clim. Dynam., 53, 371–387, https://doi.org/10.1007/s00382-018-4591-7, 2019. a, b
Park, J.-H., Sung, M.-K., Yang, Y.-M., Zhao, J., An, S.-I., and Kug, J.-S.: Role of the climatological intertropical convergence zone in the seasonal footprinting mechanism of the El Niño-Southern Oscillation, J. Climate, 34, 5243–5256, https://doi.org/10.1175/jcli-d-20-0809.1, 2021. a
Park, J.-H., Kug, J.-S., Yang, Y.-M., Oh, H., Zhao, J., and Wu, Y.: Role of the Climatological North Pacific High in the North Tropical Atlantic – ENSO Connection, J. Climate, 35, 3215–3226, https://doi.org/10.1175/jcli-d-21-0933.1, 2022. a, b
Park, J.-H., Kug, J.-S., Yang, Y.-M., Sung, M.-K., Kim, S., Kim, H.-J., Park, H.-J., and An, S.-I.: Distinct decadal modulation of Atlantic-Niño influence on ENSO, npj Climate and Atmospheric Science, 6, 105, https://doi.org/10.1038/s41612-023-00429-9, 2023a. a
Park, J.-H., Yeh, S.-W., Kug, J.-S., Yang, Y.-M., Jo, H.-S., Kim, H.-J., and An, S.-I.: Two regimes of inter-basin interactions between the Atlantic and Pacific Oceans on interannual timescales, npj Climate and Atmospheric Science, 6, 13, https://doi.org/10.1038/s41612-023-00332-3, 2023b. a, b, c, d, e, f, g, h, i, j, k, l
Phillips, A., Deser, C., Fasullo, J., Schneider, D. P., and Simpson, I. R.: Assessing Climate Variability and Change in Model Large Ensembles: A User's Guide to the “Climate Variability Diagnostics Package for Large Ensembles”, OpenSky, https://doi.org/10.5065/H7C7-F961, 2020. a
Pinto, J. G., Reyers, M., and Ulbrich, U.: The variable link between PNA and NAO in observations and in multi-century CGCM simulations, Climate Dynamics, 36, 337–354, https://doi.org/10.1007/s00382-010-0770-x, 2010. a, b, c
Polyakov, I. V. and Johnson, M. A.: Arctic decadal and interdecadal variability, Geophys. Res. Lett., 27, 4097–4100, https://doi.org/10.1029/2000gl011909, 2000. a
Power, S. B. and Kociuba, G.: What Caused the Observed Twentieth-Century Weakening of the Walker Circulation?, J. Climate, 24, 6501–6514, https://doi.org/10.1175/2011jcli4101.1, 2011. a
Rajagopalan, B., Kushnir, Y., and Tourre, Y. M.: Observed decadal midlatitude and tropical Atlantic climate variability, Geophys. Res. Lett., 25, 3967–3970, https://doi.org/10.1029/1998gl900065, 1998. a
Rayner, N. A., Parker, D. E., Horton, E. B., Folland, C. K., Alexander, L. V., Rowell, D. P., Kent, E. C., and Kaplan, A.: Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century, J. Geophys. Res.-Atmos., 108, 4407, https://doi.org/10.1029/2002jd002670, 2003. a
Righi, M., Andela, B., Eyring, V., Lauer, A., Predoi, V., Schlund, M., Vegas-Regidor, J., Bock, L., Brötz, B., de Mora, L., Diblen, F., Dreyer, L., Drost, N., Earnshaw, P., Hassler, B., Koldunov, N., Little, B., Loosveldt Tomas, S., and Zimmermann, K.: Earth System Model Evaluation Tool (ESMValTool) v2.0 – technical overview, Geosci. Model Dev., 13, 1179–1199, https://doi.org/10.5194/gmd-13-1179-2020, 2020. a
Rosenbloom, N., Simpson, I., and Phillips, A.: CESM2 Pacific Pacemaker Ensemble, NCAR [data set], https://doi.org/10.26024/gtrs-tf57, 2022. a
Runge, J., Nowack, P., Kretschmer, M., Flaxman, S., and Sejdinovic, D.: Detecting and quantifying causal associations in large nonlinear time series datasets, Sci. Adv., 5, eaau4996, https://doi.org/10.1126/sciadv.aau4996, 2019. a
Runge, J., Gerhardus, A., Varando, G., Eyring, V., and Camps-Valls, G.: Causal inference for time series, Nature Reviews Earth & Environment, 4, 487–505, https://doi.org/10.1038/s43017-023-00431-y, 2023a. a, b
Runge, J., Gillies, E., Strobl, E. V., and Palachy-Affek, S.: jakobrunge/tigramite: Tigramite 5.2, Zenodo [code], https://doi.org/10.5281/ZENODO.7747255, 2023b. a
Ruprich-Robert, Y., Msadek, R., Castruccio, F., Yeager, S., Delworth, T., and Danabasoglu, G.: Assessing the Climate Impacts of the Observed Atlantic Multidecadal Variability Using the GFDL CM2.1 and NCAR CESM1 Global Coupled Models, J. Climate, 30, 2785–2810, https://doi.org/10.1175/jcli-d-16-0127.1, 2017. a, b
Saravanan, R. and Chang, P.: Interaction between Tropical Atlantic Variability and El Niño–Southern Oscillation, J. Climate, 13, 2177–2194, https://doi.org/10.1175/1520-0442(2000)013<2177:ibtava>2.0.co;2, 2000. a, b
Sato, Y., Goto, D., Michibata, T., Suzuki, K., Takemura, T., Tomita, H., and Nakajima, T.: Aerosol effects on cloud water amounts were successfully simulated by a global cloud-system resolving model, Nat. Commun., 9, 985, https://doi.org/10.1038/s41467-018-03379-6, 2018. a
Scaife, A. A., Arribas, A., Blockley, E., Brookshaw, A., Clark, R. T., Dunstone, N., Eade, R., Fereday, D., Folland, C. K., Gordon, M., Hermanson, L., Knight, J. R., Lea, D. J., MacLachlan, C., Maidens, A., Martin, M., Peterson, A. K., Smith, D., Vellinga, M., Wallace, E., Waters, J., and Williams, A.: Skillful long‐range prediction of European and North American winters, Geophys. Res. Lett., 41, 2514–2519, https://doi.org/10.1002/2014gl059637, 2014. a, b
Schlund, M., Lauer, A., Gentine, P., Sherwood, S. C., and Eyring, V.: Emergent constraints on equilibrium climate sensitivity in CMIP5: do they hold for CMIP6?, Earth Syst. Dynam., 11, 1233–1258, https://doi.org/10.5194/esd-11-1233-2020, 2020. a
Smirnov, D. A. and Bezruchko, B. P.: Spurious causalities due to low temporal resolution: Towards detection of bidirectional coupling from time series, Europhys. Lett., 100, 10005, https://doi.org/10.1209/0295-5075/100/10005, 2012. a
Smith, C. J. and Forster, P. M.: Suppressed Late‐20th Century Warming in CMIP6 Models Explained by Forcing and Feedbacks, Geophys. Res. Lett., 48, e2021GL094948, https://doi.org/10.1029/2021gl094948, 2021. a, b
Smith, C. J., Harris, G. R., Palmer, M. D., Bellouin, N., Collins, W., Myhre, G., Schulz, M., Golaz, J., Ringer, M., Storelvmo, T., and Forster, P. M.: Energy Budget Constraints on the Time History of Aerosol Forcing and Climate Sensitivity, J. Geophys. Res.-Atmos., 126, e2020JD033622, https://doi.org/10.1029/2020jd033622, 2021. a
Smith, D. M., Booth, B. B. B., Dunstone, N. J., Eade, R., Hermanson, L., Jones, G. S., Scaife, A. A., Sheen, K. L., and Thompson, V.: Role of volcanic and anthropogenic aerosols in the recent global surface warming slowdown, Nat. Clim. Change, 6, 936–940, https://doi.org/10.1038/nclimate3058, 2016. a, b
Smith, D. M., Eade, R., Scaife, A. A., Caron, L.-P., Danabasoglu, G., DelSole, T. M., Delworth, T., Doblas-Reyes, F. J., Dunstone, N. J., Hermanson, L., Kharin, V., Kimoto, M., Merryfield, W. J., Mochizuki, T., Müller, W. A., Pohlmann, H., Yeager, S., and Yang, X.: Robust skill of decadal climate predictions, npj Climate and Atmospheric Science, 2, 13, https://doi.org/10.1038/s41612-019-0071-y, 2019. a
Smith, D. M., Gillett, N. P., Simpson, I. R., Athanasiadis, P. J., Baehr, J., Bethke, I., Bilge, T. A., Bonnet, R., Boucher, O., Findell, K. L., Gastineau, G., Gualdi, S., Hermanson, L., Leung, L. R., Mignot, J., Müller, W. A., Osprey, S., Otterå, O. H., Persad, G. G., Scaife, A. A., Schmidt, G. A., Shiogama, H., Sutton, R. T., Swingedouw, D., Yang, S., Zhou, T., and Ziehn, T.: Attribution of multi-annual to decadal changes in the climate system: The Large Ensemble Single Forcing Model Intercomparison Project (LESFMIP), Front. Clim., 4, 955414, https://doi.org/10.3389/fclim.2022.955414, 2022. a, b
Soulard, N. and Lin, H.: The spring relationship between the Pacific-North American pattern and the North Atlantic Oscillation, Clim. Dynam., 48, 619–629, https://doi.org/10.1007/s00382-016-3098-3, 2016. a, b, c
Sutton, R. T., Jewson, S. P., and Rowell, D. P.: The Elements of Climate Variability in the Tropical Atlantic Region, J. Climate, 13, 3261–3284, https://doi.org/10.1175/1520-0442(2000)013<3261:teocvi>2.0.co;2, 2000. a
Taschetto, A. S., Rodrigues, R. R., Meehl, G. A., McGregor, S., and England, M. H.: How sensitive are the Pacific–tropical North Atlantic teleconnections to the position and intensity of El Niño-related warming?, Clim. Dynam., 46, 1841–1860, https://doi.org/10.1007/s00382-015-2679-x, 2015. a
Tebaldi, C., Dorheim, K., Wehner, M., and Leung, R.: Extreme metrics from large ensembles: investigating the effects of ensemble size on their estimates, Earth Syst. Dynam., 12, 1427–1501, https://doi.org/10.5194/esd-12-1427-2021, 2021. a, b
Tokarska, K. B., Hegerl, G. C., Schurer, A. P., Forster, P. M., and Marvel, K.: Observational constraints on the effective climate sensitivity from the historical period, Environ. Res. Lett., 15, 034043, https://doi.org/10.1088/1748-9326/ab738f, 2020a. a, b
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, 2020b. a
Trenberth, K. E.: The Definition of El Niño, Bulletin of the American Meteorological Society, 78, 2771–2777, https://doi.org/10.1175/1520-0477(1997)078<2771:tdoeno>2.0.co;2, 1997. a, b, c, d
Trenberth, K. E. and Shea, D. J.: Atlantic hurricanes and natural variability in 2005, Geophys. Res. Lett., 33, L12704, https://doi.org/10.1029/2006gl026894, 2006. a, b
Vecchi, G. A. and Soden, B. J.: Global Warming and the Weakening of the Tropical Circulation, J. Climate, 20, 4316–4340, https://doi.org/10.1175/jcli4258.1, 2007. a
Visbeck, M., Chassignet, E. P., Curry, R. G., Delworth, T. L., Dickson, R. R., and Krahmann, G.: The ocean's response to North Atlantic Oscillation variability, Geophysical Monograph Series, American Geophysical Union, 113–145, https://doi.org/10.1029/134gm06, 2003. a
Wallace, J. M. and Gutzler, D. S.: Teleconnections in the Geopotential Height Field during the Northern Hemisphere Winter, Mon. Weather Rev., 109, 784–812, https://doi.org/10.1175/1520-0493(1981)109<0784:titghf>2.0.co;2, 1981. a, b, c, d
Wang, C.: Atlantic Climate Variability and Its Associated Atmospheric Circulation Cells, J. Climate, 15, 1516–1536, https://doi.org/10.1175/1520-0442(2002)015<1516:acvaia>2.0.co;2, 2002. a
Wang, C.: A review of ENSO theories, Nat. Sci. Rev., 5, 813–825, https://doi.org/10.1093/nsr/nwy104, 2018. a
Wang, C.: Three-ocean interactions and climate variability: a review and perspective, Clim. Dynam., 53, 5119–5136, https://doi.org/10.1007/s00382-019-04930-x, 2019. a
Wang, J., Yang, B., Ljungqvist, F. C., Luterbacher, J., Osborn, T. J., Briffa, K. R., and Zorita, E.: Internal and external forcing of multidecadal Atlantic climate variability over the past 1, 200 years, Nat. Geosci., 10, 512–517, https://doi.org/10.1038/ngeo2962, 2017. a
Wang, L., Yu, J.-Y., and Paek, H.: Enhanced biennial variability in the Pacific due to Atlantic capacitor effect, Nat. Commun., 8, 14887, https://doi.org/10.1038/ncomms14887, 2017. a, b, c
Watanabe, M. and Tatebe, H.: Reconciling roles of sulphate aerosol forcing and internal variability in Atlantic multidecadal climate changes, Clim. Dynam., 53, 4651–4665, https://doi.org/10.1007/s00382-019-04811-3, 2019. a, b
Wei, M., Shu, Q., Song, Z., Song, Y., Yang, X., Guo, Y., Li, X., and Qiao, F.: Could CMIP6 climate models reproduce the early-2000s global warming slowdown?, Sci. China Earth Sci., 64, 853–865, https://doi.org/10.1007/s11430-020-9740-3, 2021. a, b
Wu, M., Zhou, T., Li, C., Li, H., Chen, X., Wu, B., Zhang, W., and Zhang, L.: A very likely weakening of Pacific Walker Circulation in constrained near-future projections, Nat. Commun., 12, 6502, https://doi.org/10.1038/s41467-021-26693-y, 2021. a
Yang, D., Arblaster, J. M., Meehl, G. A., England, M. H., Lim, E.-P., Bates, S., and Rosenbloom, N.: Role of Tropical Variability in Driving Decadal Shifts in the Southern Hemisphere Summertime Eddy-Driven Jet, J. Climate, 33, 5445–5463, https://doi.org/10.1175/jcli-d-19-0604.1, 2020 (data available at: https://www.earthsystemgrid.org/dataset/ucar.cgd.ccsm4.ATL-PACEMAKER.html, last access: 29 April 2024). a, b
Yang, Y., Wu, L., Guo, Y., Gan, B., Cai, W., Huang, G., Li, X., Geng, T., Jing, Z., Li, S., Liang, X., and Xie, S.-P.: Greenhouse warming intensifies north tropical Atlantic climate variability, Sci. Adv., 7, eabg9690, https://doi.org/10.1126/sciadv.abg9690, 2021. a
Yang, Y.-M., An, S.-I., Wang, B., and Park, J. H.: A global-scale multidecadal variability driven by Atlantic multidecadal oscillation, Nat. Sci. Rev., 7, 1190–1197, https://doi.org/10.1093/nsr/nwz216, 2019. a
Zebiak, S. E.: Air–Sea Interaction in the Equatorial Atlantic Region, J. Climate, 6, 1567–1586, https://doi.org/10.1175/1520-0442(1993)006<1567:aiitea>2.0.co;2, 1993. a, b
Zhang, R., Sutton, R., Danabasoglu, G., Kwon, Y.-O., Marsh, R., Yeager, S. G., Amrhein, D. E., and Little, C. M.: A review of the role of the Atlantic Meridional Overturning Circulation in Atlantic Multidecadal Variability and associated climate impacts, Rev. Geophys., 57, 316–375, https://doi.org/10.1029/2019RG000644, 2019. a, b
Zhao, X. and Allen, R. J.: Strengthening of the Walker Circulation in recent decades and the role of natural sea surface temperature variability, Environmental Research Communications, 1, 021003, https://doi.org/10.1088/2515-7620/ab0dab, 2019. a
Short summary
This study explores Atlantic–Pacific interactions and their response to external factors. Causal analysis of 1950–2014 data reveals a shift from a Pacific- to an Atlantic-driven regime. Contrasting impacts between El Niño and tropical Atlantic temperatures are highlighted, along with different pathways connecting the two oceans. The findings also suggest increasing remote contributions of forced Atlantic responses in modulating local Pacific responses during the most recent analyzed decades.
This study explores Atlantic–Pacific interactions and their response to external factors. Causal...
Altmetrics
Final-revised paper
Preprint