Articles | Volume 17, issue 23
https://doi.org/10.5194/bg-17-6115-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-17-6115-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
08 Dec 2020
Research article |
| 08 Dec 2020
| 08 Dec 2020
Spatially resolved evaluation of Earth system models with satellite column-averaged CO2
University of Bremen, Institute of Environmental Physics (IUP),
Bremen, Germany
Deutsches Zentrum für Luft- und Raumfahrt (DLR), Institut für
Physik der Atmosphäre, Oberpfaffenhofen, Germany
Michael Buchwitz
University of Bremen, Institute of Environmental Physics (IUP),
Bremen, Germany
Maximilian Reuter
University of Bremen, Institute of Environmental Physics (IUP),
Bremen, Germany
Peter M. Cox
College of Engineering, Mathematics and Physical Sciences, University
of Exeter, Exeter, EX4 4QE, United Kingdom
Pierre Friedlingstein
College of Engineering, Mathematics and Physical Sciences, University
of Exeter, Exeter, EX4 4QE, United Kingdom
LMD/IPSL, ENS, PSL Université, École Polytechnique, Institut
Polytechnique de Paris, Sorbonne Université, CNRS, Paris, France
Veronika Eyring
Deutsches Zentrum für Luft- und Raumfahrt (DLR), Institut für
Physik der Atmosphäre, Oberpfaffenhofen, Germany
University of Bremen, Institute of Environmental Physics (IUP),
Bremen, Germany
Related authors
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.
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).
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.
Stefan Noël, Michael Buchwitz, Michael Hilker, Maximilian Reuter, Michael Weimer, Heinrich Bovensmann, John P. Burrows, Hartmut Bösch, and Ruediger Lang
Atmos. Meas. Tech., 17, 2317–2334, https://doi.org/10.5194/amt-17-2317-2024, https://doi.org/10.5194/amt-17-2317-2024, 2024
Short summary
Short summary
FOCAL-CO2M is one of the three operational retrieval algorithms which will be used to derive XCO2 and XCH4 from measurements of the forthcoming European CO2M mission. We present results of applications of FOCAL-CO2M to simulated spectra, from which confidence is gained that the algorithm is able to fulfil the challenging requirements on systematic errors for the CO2M mission (spatio-temporal bias ≤ 0.5 ppm for XCO2 and ≤ 5 ppb for XCH4).
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.
Yona Silvy, Thomas L. Frölicher, Jens Terhaar, Fortunat Joos, Friedrich A. Burger, Fabrice Lacroix, Myles Allen, Raffaele Bernadello, Laurent Bopp, Victor Brovkin, Jonathan R. Buzan, Patricia Cadule, Martin Dix, John Dunne, Pierre Friedlingstein, Goran Georgievski, Tomohiro Hajima, Stuart Jenkins, Michio Kawamiya, Nancy Y. Kiang, Vladimir Lapin, Donghyun Lee, Paul Lerner, Nadine Mengis, Estela A. Monteiro, David Paynter, Glen P. Peters, Anastasia Romanou, Jörg Schwinger, Sarah Sparrow, Eric Stofferahn, Jerry Tjiputra, Etienne Tourigny, and Tilo Ziehn
EGUsphere, https://doi.org/10.5194/egusphere-2024-488, https://doi.org/10.5194/egusphere-2024-488, 2024
Short summary
Short summary
We apply the Adaptive Emission Reduction Approach with Earth System Models to provide simulations in which all ESMs converge at 1.5 °C and 2 °C warming levels. These simulations provide compatible emission pathways for a given warming level, uncovering uncertainty ranges previously missing in the CMIP scenarios. This new type of target-based emission-driven simulations offers a more coherent assessment across ESMs for studying both the carbon cycle and impacts under climate stabilization.
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.
Blanca Fuentes Andrade, Michael Buchwitz, Maximilian Reuter, Heinrich Bovensmann, Andreas Richter, Hartmut Boesch, and John P. Burrows
Atmos. Meas. Tech., 17, 1145–1173, https://doi.org/10.5194/amt-17-1145-2024, https://doi.org/10.5194/amt-17-1145-2024, 2024
Short summary
Short summary
We developed a method to estimate CO2 emissions from localized sources, such as power plants, using satellite data and applied it to estimate CO2 emissions from the Bełchatów Power Station (Poland). As the detection of CO2 emission plumes from satellite data is difficult, we used observations of co-emitted NO2 to constrain the emission plume region. Our results agree with CO2 emission estimations based on the power-plant-generated power and emission factors.
Steffen Vanselow, Oliver Schneising, Michael Buchwitz, Maximilian Reuter, Heinrich Bovensmann, Hartmut Boesch, and John P. Burrows
EGUsphere, https://doi.org/10.5194/egusphere-2024-379, https://doi.org/10.5194/egusphere-2024-379, 2024
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
We developed an algorithm to automatically detect persistent methane source regions, to quantify their emissions and to determine their source types, by analyzing TROPOMI data from 2018–2021. The over 200 globally detected natural and anthropogenic source regions include small-scale point sources such as individual coal mines and larger-scale source regions such as wetlands and large oil and gas fields.
Tomohiro Hajima, Michio Kawamiya, Akihiko Ito, Kaoru Tachiiri, Chris Jones, Vivek Arora, Victor Brovkin, Roland Séférian, Spencer Liddicoat, Pierre Friedlingstein, and Elena Shevliakova
EGUsphere, https://doi.org/10.5194/egusphere-2024-188, https://doi.org/10.5194/egusphere-2024-188, 2024
Short summary
Short summary
This study analyzes atmospheric CO2 concentrations and global carbon budgets simulated by multiple Earth system models, using several types of simulations. We successfully identified problems of global carbon budget in each model. We also found urgent issues that should be solved in the latest generation of models, land use change CO2 emissions.
Oliver Schneising, Michael Buchwitz, Maximilian Reuter, Michael Weimer, Heinrich Bovensmann, John P. Burrows, and Hartmut Bösch
EGUsphere, https://doi.org/10.5194/egusphere-2023-2709, https://doi.org/10.5194/egusphere-2023-2709, 2024
Short summary
Short summary
Large quantities of CO and CO2 are emitted during conventional steel production. As satellite-based estimates of CO2 emissions at facility level are challenging, co-emitted CO can indicate the carbon footprint of steel plants. We estimate CO emissions for German steelworks and use CO2 emissions from emissions trading data to derive a sector-specific CO/CO2 emission ratio for the steel industry, which is a prerequisite to use CO as a proxy for CO2 emissions from comparable steel production sites.
Jonas Hachmeister, Oliver Schneising, Michael Buchwitz, John P. Burrows, Justus Notholt, and Matthias Buschmann
Atmos. Chem. Phys., 24, 577–595, https://doi.org/10.5194/acp-24-577-2024, https://doi.org/10.5194/acp-24-577-2024, 2024
Short summary
Short summary
We quantified changes in atmospheric methane concentrations using satellite data and a dynamic linear model approach. We calculated global annual methane increases for the years 2019–2022, which are in good agreement with other sources. For zonal methane growth rates, we identified strong inter-hemispheric differences in 2019 and 2022. For 2022, we could attribute decreases in the global growth rate to the Northern Hemisphere, possibly related to a reduction in anthropogenic emissions.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Dorothee C. E. Bakker, Judith Hauck, Peter Landschützer, Corinne Le Quéré, Ingrid T. Luijkx, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Peter Anthoni, Leticia Barbero, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Bertrand Decharme, Laurent Bopp, Ida Bagus Mandhara Brasika, Patricia Cadule, Matthew A. Chamberlain, Naveen Chandra, Thi-Tuyet-Trang Chau, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Xinyu Dou, Kazutaka Enyo, Wiley Evans, Stefanie Falk, Richard A. Feely, Liang Feng, Daniel J. Ford, Thomas Gasser, Josefine Ghattas, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Jens Heinke, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Andrew R. Jacobson, Atul Jain, Tereza Jarníková, Annika Jersild, Fei Jiang, Zhe Jin, Fortunat Joos, Etsushi Kato, Ralph F. Keeling, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Arne Körtzinger, Xin Lan, Nathalie Lefèvre, Hongmei Li, Junjie Liu, Zhiqiang Liu, Lei Ma, Greg Marland, Nicolas Mayot, Patrick C. McGuire, Galen A. McKinley, Gesa Meyer, Eric J. Morgan, David R. Munro, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin M. O'Brien, Are Olsen, Abdirahman M. Omar, Tsuneo Ono, Melf Paulsen, Denis Pierrot, Katie Pocock, Benjamin Poulter, Carter M. Powis, Gregor Rehder, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Thais M. Rosan, Jörg Schwinger, Roland Séférian, T. Luke Smallman, Stephen M. Smith, Reinel Sospedra-Alfonso, Qing Sun, Adrienne J. Sutton, Colm Sweeney, Shintaro Takao, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Hiroyuki Tsujino, Francesco Tubiello, Guido R. van der Werf, Erik van Ooijen, Rik Wanninkhof, Michio Watanabe, Cathy Wimart-Rousseau, Dongxu Yang, Xiaojuan Yang, Wenping Yuan, Xu Yue, Sönke Zaehle, Jiye Zeng, and Bo Zheng
Earth Syst. Sci. Data, 15, 5301–5369, https://doi.org/10.5194/essd-15-5301-2023, https://doi.org/10.5194/essd-15-5301-2023, 2023
Short summary
Short summary
The Global Carbon Budget 2023 describes the methodology, main results, and data sets used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, land ecosystems, and the ocean over the historical period (1750–2023). These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
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.
Rebecca M. Varney, Pierre Friedlingstein, Sarah E. Chadburn, Eleanor J. Burke, and Peter M. Cox
EGUsphere, https://doi.org/10.5194/egusphere-2023-2666, https://doi.org/10.5194/egusphere-2023-2666, 2023
Short summary
Short summary
Soil carbon is the largest store of carbon on the land surface of Earth and is known to be particularly sensitive to climate change. Understanding this future response is vital to successfully meet Paris agreement targets, which rely heavily on carbon uptake by the land surface. In this study, the individual responses of soil carbon are quantified and compared amongst CMIP6 Earth system models used within the most recent IPCC report, and the role of soils within the land response is highlighted.
Arndt Kaps, Axel Lauer, Rémi Kazeroni, Martin Stengel, and Veronika Eyring
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-424, https://doi.org/10.5194/essd-2023-424, 2023
Revised manuscript under review for ESSD
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.
Zi Huang, Jiaoyue Wang, Longfei Bing, Yijiao Qiu, Rui Guo, Ying Yu, Mingjing Ma, Le Niu, Dan Tong, Robbie M. Andrew, Pierre Friedlingstein, Josep G. Canadell, Fengming Xi, and Zhu Liu
Earth Syst. Sci. Data, 15, 4947–4958, https://doi.org/10.5194/essd-15-4947-2023, https://doi.org/10.5194/essd-15-4947-2023, 2023
Short summary
Short summary
This is about global and regional cement process carbon emissions and CO2 uptake calculations from 1930 to 2019. The global cement production is rising to 4.4 Gt, causing processing carbon emission of 1.81 Gt (95% CI: 1.75–1.88 Gt CO2) in 2021. Plus, in 2021, cement’s carbon accumulated uptake (22.9 Gt, 95% CI: 19.6–22.6 Gt CO2) has offset 55.2% of cement process CO2 emissions (41.5 Gt, 95% CI: 38.7–47.1 Gt CO2) since 1930.
Matthew J. McGrath, Ana Maria Roxana Petrescu, Philippe Peylin, Robbie M. Andrew, Bradley Matthews, Frank Dentener, Juraj Balkovič, Vladislav Bastrikov, Meike Becker, Gregoire Broquet, Philippe Ciais, Audrey Fortems-Cheiney, Raphael Ganzenmüller, Giacomo Grassi, Ian Harris, Matthew Jones, Jürgen Knauer, Matthias Kuhnert, Guillaume Monteil, Saqr Munassar, Paul I. Palmer, Glen P. Peters, Chunjing Qiu, Mart-Jan Schelhaas, Oksana Tarasova, Matteo Vizzarri, Karina Winkler, Gianpaolo Balsamo, Antoine Berchet, Peter Briggs, Patrick Brockmann, Frédéric Chevallier, Giulia Conchedda, Monica Crippa, Stijn N. C. Dellaert, Hugo A. C. Denier van der Gon, Sara Filipek, Pierre Friedlingstein, Richard Fuchs, Michael Gauss, Christoph Gerbig, Diego Guizzardi, Dirk Günther, Richard A. Houghton, Greet Janssens-Maenhout, Ronny Lauerwald, Bas Lerink, Ingrid T. Luijkx, Géraud Moulas, Marilena Muntean, Gert-Jan Nabuurs, Aurélie Paquirissamy, Lucia Perugini, Wouter Peters, Roberto Pilli, Julia Pongratz, Pierre Regnier, Marko Scholze, Yusuf Serengil, Pete Smith, Efisio Solazzo, Rona L. Thompson, Francesco N. Tubiello, Timo Vesala, and Sophia Walther
Earth Syst. Sci. Data, 15, 4295–4370, https://doi.org/10.5194/essd-15-4295-2023, https://doi.org/10.5194/essd-15-4295-2023, 2023
Short summary
Short summary
Accurate estimation of fluxes of carbon dioxide from the land surface is essential for understanding future impacts of greenhouse gas emissions on the climate system. A wide variety of methods currently exist to estimate these sources and sinks. We are continuing work to develop annual comparisons of these diverse methods in order to clarify what they all actually calculate and to resolve apparent disagreement, in addition to highlighting opportunities for increased understanding.
Soufiane Karmouche, Evgenia Galytska, Gerald A. Meehl, Jakob Runge, Katja Weigel, and Veronika Eyring
EGUsphere, https://doi.org/10.5194/egusphere-2023-1861, https://doi.org/10.5194/egusphere-2023-1861, 2023
Short summary
Short summary
This study explores Atlantic-Pacific interactions and their response to external factors. Using advanced causal analysis, we analyzed climate data from 1950–2014, revealing a shift from a Pacific- to an Atlantic-driven regime. The contrasting impacts between El Niño and Tropical North Atlantic temperatures were highlighted, along with different pathways connecting the two oceans. These findings have the potential to enhance understanding of the climate system and guide model improvements.
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, Veronique Bouchet, 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, Detlef Stammer, 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 Discuss., https://doi.org/10.5194/essd-2023-376, https://doi.org/10.5194/essd-2023-376, 2023
Revised manuscript accepted for ESSD
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 are proposed as international federation of centers of excellence to empower all people to respond to the immense and urgent challenges posed by climate change.
Rebecca M. Varney, Sarah E. Chadburn, Eleanor J. Burke, Simon Jones, Andy J. Wiltshire, and Peter M. Cox
Biogeosciences, 20, 3767–3790, https://doi.org/10.5194/bg-20-3767-2023, https://doi.org/10.5194/bg-20-3767-2023, 2023
Short summary
Short summary
This study evaluates soil carbon projections during the 21st century in CMIP6 Earth system models. In general, we find a reduced spread of changes in global soil carbon in CMIP6 compared to the previous CMIP5 generation. The reduced CMIP6 spread arises from an emergent relationship between soil carbon changes due to change in plant productivity and soil carbon changes due to changes in turnover time. We show that this relationship is consistent with false priming under transient climate change.
Nina Raoult, Tim Jupp, Ben Booth, and Peter Cox
Earth Syst. Dynam., 14, 723–731, https://doi.org/10.5194/esd-14-723-2023, https://doi.org/10.5194/esd-14-723-2023, 2023
Short summary
Short summary
Climate models are used to predict the impact of climate change. However, poorly constrained parameters used in the physics of the models mean that we simulate a large spread of possible future outcomes. We can use real-world observations to reduce the uncertainty of parameter values, but we do not have observations to reduce the spread of possible future outcomes directly. We present a method for translating the reduction in parameter uncertainty into a reduction in possible model projections.
Paul D. L. Ritchie, Hassan Alkhayuon, Peter M. Cox, and Sebastian Wieczorek
Earth Syst. Dynam., 14, 669–683, https://doi.org/10.5194/esd-14-669-2023, https://doi.org/10.5194/esd-14-669-2023, 2023
Short summary
Short summary
Complex systems can undergo abrupt changes or tipping points when external forcing crosses a critical level and are of increasing concern because of their severe impacts. However, tipping points can also occur when the external forcing changes too quickly without crossing any critical levels, which is very relevant for Earth’s systems and contemporary climate. We give an intuitive explanation of such rate-induced tipping and provide illustrative examples from natural and human systems.
Piers M. Forster, Christopher J. Smith, Tristram Walsh, William F. Lamb, Robin Lamboll, Mathias Hauser, Aurélien Ribes, Debbie Rosen, Nathan Gillett, Matthew D. Palmer, Joeri Rogelj, Karina von Schuckmann, Sonia I. Seneviratne, Blair Trewin, Xuebin Zhang, Myles Allen, Robbie Andrew, Arlene Birt, Alex Borger, Tim Boyer, Jiddu A. Broersma, Lijing Cheng, Frank Dentener, Pierre Friedlingstein, José M. Gutiérrez, Johannes Gütschow, Bradley Hall, Masayoshi Ishii, Stuart Jenkins, Xin Lan, June-Yi Lee, Colin Morice, Christopher Kadow, John Kennedy, Rachel Killick, Jan C. Minx, Vaishali Naik, Glen P. Peters, Anna Pirani, Julia Pongratz, Carl-Friedrich Schleussner, Sophie Szopa, Peter Thorne, Robert Rohde, Maisa Rojas Corradi, Dominik Schumacher, Russell Vose, Kirsten Zickfeld, Valérie Masson-Delmotte, and Panmao Zhai
Earth Syst. Sci. Data, 15, 2295–2327, https://doi.org/10.5194/essd-15-2295-2023, https://doi.org/10.5194/essd-15-2295-2023, 2023
Short summary
Short summary
This is a critical decade for climate action, but there is no annual tracking of the level of human-induced warming. We build on the Intergovernmental Panel on Climate Change assessment reports that are authoritative but published infrequently to create a set of key global climate indicators that can be tracked through time. Our hope is that this becomes an important annual publication that policymakers, media, scientists and the public can refer to.
Mark S. Williamson, Peter M. Cox, Chris Huntingford, and Femke J. M. M. Nijsse
EGUsphere, https://doi.org/10.5194/egusphere-2023-1093, https://doi.org/10.5194/egusphere-2023-1093, 2023
Short summary
Short summary
Emergent constraints on equilibrium climate sensitivity (ECS) have generally got statistically weaker in the latest set of state-of-the-art climate models (CMIP6) compared to past sets (CMIP5). We look at why this weakening happened for one particular study (Cox et al, 2018) and attribute it to an assumption made in the theory that when corrected for restores a stronger relationship between predictor and ECS.
Chris Huntingford, Peter M. Cox, Mark S. Williamson, Joseph J. Clarke, and Paul D. L. Ritchie
Earth Syst. Dynam., 14, 433–442, https://doi.org/10.5194/esd-14-433-2023, https://doi.org/10.5194/esd-14-433-2023, 2023
Short summary
Short summary
Emergent constraints (ECs) reduce the spread of projections between climate models. ECs estimate changes to climate features impacting adaptation policy, and with this high profile, the method is under scrutiny. Asking
What is an EC?, we suggest they are often the discovery of parameters that characterise hidden large-scale equations that climate models solve implicitly. We present this conceptually via two examples. Our analysis implies possible new paths to link ECs and physical processes.
Anna Agustí-Panareda, Jérôme Barré, Sébastien Massart, Antje Inness, Ilse Aben, Melanie Ades, Bianca C. Baier, Gianpaolo Balsamo, Tobias Borsdorff, Nicolas Bousserez, Souhail Boussetta, Michael Buchwitz, Luca Cantarello, Cyril Crevoisier, Richard Engelen, Henk Eskes, Johannes Flemming, Sébastien Garrigues, Otto Hasekamp, Vincent Huijnen, Luke Jones, Zak Kipling, Bavo Langerock, Joe McNorton, Nicolas Meilhac, Stefan Noël, Mark Parrington, Vincent-Henri Peuch, Michel Ramonet, Miha Razinger, Maximilian Reuter, Roberto Ribas, Martin Suttie, Colm Sweeney, Jérôme Tarniewicz, and Lianghai Wu
Atmos. Chem. Phys., 23, 3829–3859, https://doi.org/10.5194/acp-23-3829-2023, https://doi.org/10.5194/acp-23-3829-2023, 2023
Short summary
Short summary
We present a global dataset of atmospheric CO2 and CH4, the two most important human-made greenhouse gases, which covers almost 2 decades (2003–2020). It is produced by combining satellite data of CO2 and CH4 with a weather and air composition prediction model, and it has been carefully evaluated against independent observations to ensure validity and point out deficiencies to the user. This dataset can be used for scientific studies in the field of climate change and the global carbon cycle.
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.
Giacomo Grassi, Clemens Schwingshackl, Thomas Gasser, Richard A. Houghton, Stephen Sitch, Josep G. Canadell, Alessandro Cescatti, Philippe Ciais, Sandro Federici, Pierre Friedlingstein, Werner A. Kurz, Maria J. Sanz Sanchez, Raúl Abad Viñas, Ramdane Alkama, Selma Bultan, Guido Ceccherini, Stefanie Falk, Etsushi Kato, Daniel Kennedy, Jürgen Knauer, Anu Korosuo, Joana Melo, Matthew J. McGrath, Julia E. M. S. Nabel, Benjamin Poulter, Anna A. Romanovskaya, Simone Rossi, Hanqin Tian, Anthony P. Walker, Wenping Yuan, Xu Yue, and Julia Pongratz
Earth Syst. Sci. Data, 15, 1093–1114, https://doi.org/10.5194/essd-15-1093-2023, https://doi.org/10.5194/essd-15-1093-2023, 2023
Short summary
Short summary
Striking differences exist in estimates of land-use CO2 fluxes between the national greenhouse gas inventories and the IPCC assessment reports. These differences hamper an accurate assessment of the collective progress under the Paris Agreement. By implementing an approach that conceptually reconciles land-use CO2 flux from national inventories and the global models used by the IPCC, our study is an important step forward for increasing confidence in land-use CO2 flux estimates.
Oliver Schneising, Michael Buchwitz, Jonas Hachmeister, Steffen Vanselow, Maximilian Reuter, Matthias Buschmann, Heinrich Bovensmann, and John P. Burrows
Atmos. Meas. Tech., 16, 669–694, https://doi.org/10.5194/amt-16-669-2023, https://doi.org/10.5194/amt-16-669-2023, 2023
Short summary
Short summary
Methane and carbon monoxide are important constituents of the atmosphere in the context of climate change and air pollution. We present the latest advances in the TROPOMI/WFMD algorithm to simultaneously retrieve atmospheric methane and carbon monoxide abundances from space. The changes in the latest product version are described in detail, and the resulting improvements are demonstrated. An overview of the products is provided including a discussion of annual increases and validation results.
Morgan Sparey, Peter Cox, and Mark S. Williamson
Biogeosciences, 20, 451–488, https://doi.org/10.5194/bg-20-451-2023, https://doi.org/10.5194/bg-20-451-2023, 2023
Short summary
Short summary
Accurate climate models are vital for mitigating climate change; however, projections often disagree. Using Köppen–Geiger bioclimate classifications we show that CMIP6 climate models agree well on the fraction of global land surface that will change classification per degree of global warming. We find that 13 % of land will change climate per degree of warming from 1 to 3 K; thus, stabilising warming at 1.5 rather than 2 K would save over 7.5 million square kilometres from bioclimatic change.
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.
Isobel M. Parry, Paul D. L. Ritchie, and Peter M. Cox
Earth Syst. Dynam., 13, 1667–1675, https://doi.org/10.5194/esd-13-1667-2022, https://doi.org/10.5194/esd-13-1667-2022, 2022
Short summary
Short summary
Despite little evidence of regional Amazon rainforest dieback, many localised abrupt dieback events are observed in the latest state-of-the-art global climate models under anthropogenic climate change. The detected dieback events would still cause severe consequences for local communities and ecosystems. This study suggests that 7 ± 5 % of the northern South America region would experience abrupt downward shifts in vegetation carbon for every degree of global warming past 1.5 °C.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Luke Gregor, Judith Hauck, Corinne Le Quéré, Ingrid T. Luijkx, Are Olsen, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Ramdane Alkama, Almut Arneth, Vivek K. Arora, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Henry C. Bittig, Laurent Bopp, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Wiley Evans, Stefanie Falk, Richard A. Feely, Thomas Gasser, Marion Gehlen, Thanos Gkritzalis, Lucas Gloege, Giacomo Grassi, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Atul K. Jain, Annika Jersild, Koji Kadono, Etsushi Kato, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Peter Landschützer, Nathalie Lefèvre, Keith Lindsay, Junjie Liu, Zhu Liu, Gregg Marland, Nicolas Mayot, Matthew J. McGrath, Nicolas Metzl, Natalie M. Monacci, David R. Munro, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin O'Brien, Tsuneo Ono, Paul I. Palmer, Naiqing Pan, Denis Pierrot, Katie Pocock, Benjamin Poulter, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Carmen Rodriguez, Thais M. Rosan, Jörg Schwinger, Roland Séférian, Jamie D. Shutler, Ingunn Skjelvan, Tobias Steinhoff, Qing Sun, Adrienne J. Sutton, Colm Sweeney, Shintaro Takao, Toste Tanhua, Pieter P. Tans, Xiangjun Tian, Hanqin Tian, Bronte Tilbrook, Hiroyuki Tsujino, Francesco Tubiello, Guido R. van der Werf, Anthony P. Walker, Rik Wanninkhof, Chris Whitehead, Anna Willstrand Wranne, Rebecca Wright, Wenping Yuan, Chao Yue, Xu Yue, Sönke Zaehle, Jiye Zeng, and Bo Zheng
Earth Syst. Sci. Data, 14, 4811–4900, https://doi.org/10.5194/essd-14-4811-2022, https://doi.org/10.5194/essd-14-4811-2022, 2022
Short summary
Short summary
The Global Carbon Budget 2022 describes the datasets and methodology used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, the land ecosystems, and the ocean. These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Rebecca M. Varney, Sarah E. Chadburn, Eleanor J. Burke, and Peter M. Cox
Biogeosciences, 19, 4671–4704, https://doi.org/10.5194/bg-19-4671-2022, https://doi.org/10.5194/bg-19-4671-2022, 2022
Short summary
Short summary
Soil carbon is the Earth’s largest terrestrial carbon store, and the response to climate change represents one of the key uncertainties in obtaining accurate global carbon budgets required to successfully militate against climate change. The ability of climate models to simulate present-day soil carbon is therefore vital. This study assesses soil carbon simulation in the latest ensemble of models which allows key areas for future model development to be identified.
Taraka Davies-Barnard, Sönke Zaehle, and Pierre Friedlingstein
Biogeosciences, 19, 3491–3503, https://doi.org/10.5194/bg-19-3491-2022, https://doi.org/10.5194/bg-19-3491-2022, 2022
Short summary
Short summary
Biological nitrogen fixation is the largest natural input of new nitrogen onto land. Earth system models mainly represent global total terrestrial biological nitrogen fixation within observational uncertainties but overestimate tropical fixation. The model range of increase in biological nitrogen fixation in the SSP3-7.0 scenario is 3 % to 87 %. While biological nitrogen fixation is a key source of new nitrogen, its predictive power for net primary productivity in models is limited.
Jonas Hachmeister, Oliver Schneising, Michael Buchwitz, Alba Lorente, Tobias Borsdorff, John P. Burrows, Justus Notholt, and Matthias Buschmann
Atmos. Meas. Tech., 15, 4063–4074, https://doi.org/10.5194/amt-15-4063-2022, https://doi.org/10.5194/amt-15-4063-2022, 2022
Short summary
Short summary
Sentinel-5P trace gas retrievals rely on elevation data in their calculations. Outdated or inaccurate data can lead to significant errors in e.g. dry-air mole fractions of methane (XCH4). We show that the use of inadequate elevation data leads to strong XCH4 anomalies in Greenland. Similar problems can be expected for other regions with inaccurate elevation data. However, we expect these to be more localized. We show that updating elevation data used in the retrieval solves this issue.
Stefan Noël, Maximilian Reuter, Michael Buchwitz, Jakob Borchardt, Michael Hilker, Oliver Schneising, Heinrich Bovensmann, John P. Burrows, Antonio Di Noia, Robert J. Parker, Hiroshi Suto, Yukio Yoshida, Matthias Buschmann, Nicholas M. Deutscher, Dietrich G. Feist, David W. T. Griffith, Frank Hase, Rigel Kivi, Cheng Liu, Isamu Morino, Justus Notholt, Young-Suk Oh, Hirofumi Ohyama, Christof Petri, David F. Pollard, Markus Rettinger, Coleen Roehl, Constantina Rousogenous, Mahesh Kumar Sha, Kei Shiomi, Kimberly Strong, Ralf Sussmann, Yao Té, Voltaire A. Velazco, Mihalis Vrekoussis, and Thorsten Warneke
Atmos. Meas. Tech., 15, 3401–3437, https://doi.org/10.5194/amt-15-3401-2022, https://doi.org/10.5194/amt-15-3401-2022, 2022
Short summary
Short summary
We present a new version (v3) of the GOSAT and GOSAT-2 FOCAL products.
In addition to an increased number of XCO2 data, v3 also includes products for XCH4 (full-physics and proxy), XH2O and the relative ratio of HDO to H2O (δD). For GOSAT-2, we also present first XCO and XN2O results. All FOCAL data products show reasonable spatial distribution and temporal variations and agree well with TCCON. Global XN2O maps show a gradient from the tropics to higher latitudes on the order of 15 ppb.
Shakirudeen Lawal, Stephen Sitch, Danica Lombardozzi, Julia E. M. S. Nabel, Hao-Wei Wey, Pierre Friedlingstein, Hanqin Tian, and Bruce Hewitson
Hydrol. Earth Syst. Sci., 26, 2045–2071, https://doi.org/10.5194/hess-26-2045-2022, https://doi.org/10.5194/hess-26-2045-2022, 2022
Short summary
Short summary
To investigate the impacts of drought on vegetation, which few studies have done due to various limitations, we used the leaf area index as proxy and dynamic global vegetation models (DGVMs) to simulate drought impacts because the models use observationally derived climate. We found that the semi-desert biome responds strongly to drought in the summer season, while the tropical forest biome shows a weak response. This study could help target areas to improve drought monitoring and simulation.
Pierre Friedlingstein, Matthew W. Jones, Michael O'Sullivan, Robbie M. Andrew, Dorothee C. E. Bakker, Judith Hauck, Corinne Le Quéré, Glen P. Peters, Wouter Peters, Julia Pongratz, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Rob B. Jackson, Simone R. Alin, Peter Anthoni, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Laurent Bopp, Thi Tuyet Trang Chau, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Kim I. Currie, Bertrand Decharme, Laique M. Djeutchouang, Xinyu Dou, Wiley Evans, Richard A. Feely, Liang Feng, Thomas Gasser, Dennis Gilfillan, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Ingrid T. Luijkx, Atul Jain, Steve D. Jones, Etsushi Kato, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Arne Körtzinger, Peter Landschützer, Siv K. Lauvset, Nathalie Lefèvre, Sebastian Lienert, Junjie Liu, Gregg Marland, Patrick C. McGuire, Joe R. Melton, David R. Munro, Julia E. M. S. Nabel, Shin-Ichiro Nakaoka, Yosuke Niwa, Tsuneo Ono, Denis Pierrot, Benjamin Poulter, Gregor Rehder, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Thais M. Rosan, Jörg Schwinger, Clemens Schwingshackl, Roland Séférian, Adrienne J. Sutton, Colm Sweeney, Toste Tanhua, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Francesco Tubiello, Guido R. van der Werf, Nicolas Vuichard, Chisato Wada, Rik Wanninkhof, Andrew J. Watson, David Willis, Andrew J. Wiltshire, Wenping Yuan, Chao Yue, Xu Yue, Sönke Zaehle, and Jiye Zeng
Earth Syst. Sci. Data, 14, 1917–2005, https://doi.org/10.5194/essd-14-1917-2022, https://doi.org/10.5194/essd-14-1917-2022, 2022
Short summary
Short summary
The Global Carbon Budget 2021 describes the data sets and methodology used to quantify the emissions of carbon dioxide and their partitioning among the atmosphere, land, and ocean. These living data are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Carlos Alberti, Qiansi Tu, Frank Hase, Maria V. Makarova, Konstantin Gribanov, Stefani C. Foka, Vyacheslav Zakharov, Thomas Blumenstock, Michael Buchwitz, Christopher Diekmann, Benjamin Ertl, Matthias M. Frey, Hamud Kh. Imhasin, Dmitry V. Ionov, Farahnaz Khosrawi, Sergey I. Osipov, Maximilian Reuter, Matthias Schneider, and Thorsten Warneke
Atmos. Meas. Tech., 15, 2199–2229, https://doi.org/10.5194/amt-15-2199-2022, https://doi.org/10.5194/amt-15-2199-2022, 2022
Short summary
Short summary
Satellite and ground-based observations at high latitudes are much sparser than at low or mid latitudes, which makes direct coincident comparisons between remote-sensing observations more difficult. Therefore, a method of scaling continuous CAMS model data to the ground-based observations is developed and used for creating virtual COCCON observations. These adjusted CAMS data are then used for satellite inter-comparison, showing good agreement in both Peterhof and Yekaterinburg cities.
István Dunkl, Aaron Spring, Pierre Friedlingstein, and Victor Brovkin
Earth Syst. Dynam., 12, 1413–1426, https://doi.org/10.5194/esd-12-1413-2021, https://doi.org/10.5194/esd-12-1413-2021, 2021
Short summary
Short summary
The variability in atmospheric CO2 is largely controlled by terrestrial carbon fluxes. These land–atmosphere fluxes are predictable for around 2 years, but the mechanisms providing the predictability are not well understood. By decomposing the predictability of carbon fluxes into individual contributors we were able to explain the spatial and seasonal patterns and the interannual variability of CO2 flux predictability.
Alexander J. Winkler, Ranga B. Myneni, Alexis Hannart, Stephen Sitch, Vanessa Haverd, Danica Lombardozzi, Vivek K. Arora, Julia Pongratz, Julia E. M. S. Nabel, Daniel S. Goll, Etsushi Kato, Hanqin Tian, Almut Arneth, Pierre Friedlingstein, Atul K. Jain, Sönke Zaehle, and Victor Brovkin
Biogeosciences, 18, 4985–5010, https://doi.org/10.5194/bg-18-4985-2021, https://doi.org/10.5194/bg-18-4985-2021, 2021
Short summary
Short summary
Satellite observations since the early 1980s show that Earth's greening trend is slowing down and that browning clusters have been emerging, especially in the last 2 decades. A collection of model simulations in conjunction with causal theory points at climatic changes as a key driver of vegetation changes in natural ecosystems. Most models underestimate the observed vegetation browning, especially in tropical rainforests, which could be due to an excessive CO2 fertilization effect in models.
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).
Stefan Noël, Maximilian Reuter, Michael Buchwitz, Jakob Borchardt, Michael Hilker, Heinrich Bovensmann, John P. Burrows, Antonio Di Noia, Hiroshi Suto, Yukio Yoshida, Matthias Buschmann, Nicholas M. Deutscher, Dietrich G. Feist, David W. T. Griffith, Frank Hase, Rigel Kivi, Isamu Morino, Justus Notholt, Hirofumi Ohyama, Christof Petri, James R. Podolske, David F. Pollard, Mahesh Kumar Sha, Kei Shiomi, Ralf Sussmann, Yao Té, Voltaire A. Velazco, and Thorsten Warneke
Atmos. Meas. Tech., 14, 3837–3869, https://doi.org/10.5194/amt-14-3837-2021, https://doi.org/10.5194/amt-14-3837-2021, 2021
Short summary
Short summary
We present the first GOSAT and GOSAT-2 XCO2 data derived with the FOCAL retrieval algorithm. Comparisons of the GOSAT-FOCAL product with other data reveal long-term agreement within about 1 ppm over 1 decade, differences in seasonal variations of about 0.5 ppm, and a mean regional bias to ground-based TCCON data of 0.56 ppm with a mean scatter of 1.89 ppm. GOSAT-2-FOCAL data are preliminary only, but first comparisons show that they compare well with the GOSAT-FOCAL results and TCCON.
Garry D. Hayman, Edward Comyn-Platt, Chris Huntingford, Anna B. Harper, Tom Powell, Peter M. Cox, William Collins, Christopher Webber, Jason Lowe, Stephen Sitch, Joanna I. House, Jonathan C. Doelman, Detlef P. van Vuuren, Sarah E. Chadburn, Eleanor Burke, and Nicola Gedney
Earth Syst. Dynam., 12, 513–544, https://doi.org/10.5194/esd-12-513-2021, https://doi.org/10.5194/esd-12-513-2021, 2021
Short summary
Short summary
We model greenhouse gas emission scenarios consistent with limiting global warming to either 1.5 or 2 °C above pre-industrial levels. We quantify the effectiveness of methane emission control and land-based mitigation options regionally. Our results highlight the importance of reducing methane emissions for realistic emission pathways that meet the global warming targets. For land-based mitigation, growing bioenergy crops on existing agricultural land is preferable to replacing forests.
Zichong Chen, Junjie Liu, Daven K. Henze, Deborah N. Huntzinger, Kelley C. Wells, Stephen Sitch, Pierre Friedlingstein, Emilie Joetzjer, Vladislav Bastrikov, Daniel S. Goll, Vanessa Haverd, Atul K. Jain, Etsushi Kato, Sebastian Lienert, Danica L. Lombardozzi, Patrick C. McGuire, Joe R. Melton, Julia E. M. S. Nabel, Benjamin Poulter, Hanqin Tian, Andrew J. Wiltshire, Sönke Zaehle, and Scot M. Miller
Atmos. Chem. Phys., 21, 6663–6680, https://doi.org/10.5194/acp-21-6663-2021, https://doi.org/10.5194/acp-21-6663-2021, 2021
Short summary
Short summary
NASA's Orbiting Carbon Observatory 2 (OCO-2) satellite observes atmospheric CO2 globally. We use a multiple regression and inverse model to quantify the relationships between OCO-2 and environmental drivers within individual years for 2015–2018 and within seven global biomes. Our results point to limitations of current space-based observations for inferring environmental relationships but also indicate the potential to inform key relationships that are very uncertain in process-based models.
Andrew J. Wiltshire, Eleanor J. Burke, Sarah E. Chadburn, Chris D. Jones, Peter M. Cox, Taraka Davies-Barnard, Pierre Friedlingstein, Anna B. Harper, Spencer Liddicoat, Stephen Sitch, and Sönke Zaehle
Geosci. Model Dev., 14, 2161–2186, https://doi.org/10.5194/gmd-14-2161-2021, https://doi.org/10.5194/gmd-14-2161-2021, 2021
Short summary
Short summary
Limited nitrogen availbility can restrict the growth of plants and their ability to assimilate carbon. It is important to include the impact of this process on the global land carbon cycle. This paper presents a model of the coupled land carbon and nitrogen cycle, which is included within the UK Earth System model to improve projections of climate change and impacts on ecosystems.
Ashique Vellalassery, Dhanyalekshmi Pillai, Julia Marshall, Christoph Gerbig, Michael Buchwitz, Oliver Schneising, and Aparnna Ravi
Atmos. Chem. Phys., 21, 5393–5414, https://doi.org/10.5194/acp-21-5393-2021, https://doi.org/10.5194/acp-21-5393-2021, 2021
Short summary
Short summary
We investigate factors contributing to the severe and persistent air quality degradation in northern India that has worsened during every winter over the last decade. This is achieved by implementing atmospheric modelling and using recently available Sentinel-5 P satellite data for carbon monoxide. We see a minimal role of biomass burning, except for the state of Punjab. The aim is to focus on residential and industrial emission reduction strategies to tackle air pollution over northern India.
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.
Michael Buchwitz, Maximilian Reuter, Stefan Noël, Klaus Bramstedt, Oliver Schneising, Michael Hilker, Blanca Fuentes Andrade, Heinrich Bovensmann, John P. Burrows, Antonio Di Noia, Hartmut Boesch, Lianghai Wu, Jochen Landgraf, Ilse Aben, Christian Retscher, Christopher W. O'Dell, and David Crisp
Atmos. Meas. Tech., 14, 2141–2166, https://doi.org/10.5194/amt-14-2141-2021, https://doi.org/10.5194/amt-14-2141-2021, 2021
Short summary
Short summary
The COVID-19 pandemic resulted in reduced anthropogenic carbon dioxide (CO2) emissions during 2020 in large parts of the world. We have used a small ensemble of satellite retrievals of column-averaged CO2 (XCO2) to find out if a regional-scale reduction of atmospheric CO2 can be detected from space. We focus on East China and show that it is challenging to reliably detect and to accurately quantify the emission reduction, which only results in regional XCO2 reductions of about 0.1–0.2 ppm.
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.
Maximilian Reuter, Heinrich Bovensmann, Michael Buchwitz, Jakob Borchardt, Sven Krautwurst, Konstantin Gerilowski, Matthias Lindauer, Dagmar Kubistin, and John P. Burrows
Atmos. Meas. Tech., 14, 153–172, https://doi.org/10.5194/amt-14-153-2021, https://doi.org/10.5194/amt-14-153-2021, 2021
Short summary
Short summary
CO2 measurements from a small unmanned aircraft system (sUAS) can provide a cost-effective way to complement and validate satellite-based measurements of anthropogenic CO2 emissions. We introduce an sUAS which is capable of determining atmospheric CO2 mass fluxes from its own sensor data. We show results of validation flights at the ICOS atmospheric station in Steinkimmen and from demonstration flights downwind a CO2-emitting natural gas processing facility.
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.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Judith Hauck, Are Olsen, Glen P. Peters, Wouter Peters, Julia Pongratz, Stephen Sitch, Corinne Le Quéré, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone Alin, Luiz E. O. C. Aragão, Almut Arneth, Vivek Arora, Nicholas R. Bates, Meike Becker, Alice Benoit-Cattin, Henry C. Bittig, Laurent Bopp, Selma Bultan, Naveen Chandra, Frédéric Chevallier, Louise P. Chini, Wiley Evans, Liesbeth Florentie, Piers M. Forster, Thomas Gasser, Marion Gehlen, Dennis Gilfillan, Thanos Gkritzalis, Luke Gregor, Nicolas Gruber, Ian Harris, Kerstin Hartung, Vanessa Haverd, Richard A. Houghton, Tatiana Ilyina, Atul K. Jain, Emilie Joetzjer, Koji Kadono, Etsushi Kato, Vassilis Kitidis, Jan Ivar Korsbakken, Peter Landschützer, Nathalie Lefèvre, Andrew Lenton, Sebastian Lienert, Zhu Liu, Danica Lombardozzi, Gregg Marland, Nicolas Metzl, David R. Munro, Julia E. M. S. Nabel, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin O'Brien, Tsuneo Ono, Paul I. Palmer, Denis Pierrot, Benjamin Poulter, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Jörg Schwinger, Roland Séférian, Ingunn Skjelvan, Adam J. P. Smith, Adrienne J. Sutton, Toste Tanhua, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Guido van der Werf, Nicolas Vuichard, Anthony P. Walker, Rik Wanninkhof, Andrew J. Watson, David Willis, Andrew J. Wiltshire, Wenping Yuan, Xu Yue, and Sönke Zaehle
Earth Syst. Sci. Data, 12, 3269–3340, https://doi.org/10.5194/essd-12-3269-2020, https://doi.org/10.5194/essd-12-3269-2020, 2020
Short summary
Short summary
The Global Carbon Budget 2020 describes the data sets and methodology used to quantify the emissions of carbon dioxide and their partitioning among the atmosphere, land, and ocean. These living data are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Yilong Wang, Grégoire Broquet, François-Marie Bréon, Franck Lespinas, Michael Buchwitz, Maximilian Reuter, Yasjka Meijer, Armin Loescher, Greet Janssens-Maenhout, Bo Zheng, and Philippe Ciais
Geosci. Model Dev., 13, 5813–5831, https://doi.org/10.5194/gmd-13-5813-2020, https://doi.org/10.5194/gmd-13-5813-2020, 2020
Taraka Davies-Barnard, Johannes Meyerholt, Sönke Zaehle, Pierre Friedlingstein, Victor Brovkin, Yuanchao Fan, Rosie A. Fisher, Chris D. Jones, Hanna Lee, Daniele Peano, Benjamin Smith, David Wårlind, and Andy J. Wiltshire
Biogeosciences, 17, 5129–5148, https://doi.org/10.5194/bg-17-5129-2020, https://doi.org/10.5194/bg-17-5129-2020, 2020
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.
Arthur P. K. Argles, Jonathan R. Moore, Chris Huntingford, Andrew J. Wiltshire, Anna B. Harper, Chris D. Jones, and Peter M. Cox
Geosci. Model Dev., 13, 4067–4089, https://doi.org/10.5194/gmd-13-4067-2020, https://doi.org/10.5194/gmd-13-4067-2020, 2020
Short summary
Short summary
The Robust Ecosystem Demography (RED) model simulates cohorts of vegetation through mass classes. RED establishes a framework for representing demographic changes through competition, growth, and mortality across the size distribution of a forest. The steady state of the model can be solved analytically, enabling initialization. When driven by mean growth rates from a land-surface model, RED is able to fit the observed global vegetation map, giving a map of implicit mortality rates.
Vivek K. Arora, Anna Katavouta, Richard G. Williams, Chris D. Jones, Victor Brovkin, Pierre Friedlingstein, Jörg Schwinger, Laurent Bopp, Olivier Boucher, Patricia Cadule, Matthew A. Chamberlain, James R. Christian, Christine Delire, Rosie A. Fisher, Tomohiro Hajima, Tatiana Ilyina, Emilie Joetzjer, Michio Kawamiya, Charles D. Koven, John P. Krasting, Rachel M. Law, David M. Lawrence, Andrew Lenton, Keith Lindsay, Julia Pongratz, Thomas Raddatz, Roland Séférian, Kaoru Tachiiri, Jerry F. Tjiputra, Andy Wiltshire, Tongwen Wu, and Tilo Ziehn
Biogeosciences, 17, 4173–4222, https://doi.org/10.5194/bg-17-4173-2020, https://doi.org/10.5194/bg-17-4173-2020, 2020
Short summary
Short summary
Since the preindustrial period, land and ocean have taken up about half of the carbon emitted into the atmosphere by humans. Comparison of different earth system models with the carbon cycle allows us to assess how carbon uptake by land and ocean differs among models. This yields an estimate of uncertainty in our understanding of how land and ocean respond to increasing atmospheric CO2. This paper summarizes results from two such model intercomparison projects that use an idealized scenario.
Femke J. M. M. Nijsse, Peter M. Cox, and Mark S. Williamson
Earth Syst. Dynam., 11, 737–750, https://doi.org/10.5194/esd-11-737-2020, https://doi.org/10.5194/esd-11-737-2020, 2020
Short summary
Short summary
One of the key questions in climate science is how much more heating we will get for a given rise in carbon dioxide in the atmosphere. A new generation of models showed that this might be more than previously expected. Comparing the new models to observed temperature rise since 1970, we show that there is no need to revise the estimate upwards. Air pollution, whose effect on climate warming is poorly understood, stopped rising, allowing us to better constrain the greenhouse gas signal.
Oliver Schneising, Michael Buchwitz, Maximilian Reuter, Steffen Vanselow, Heinrich Bovensmann, and John P. Burrows
Atmos. Chem. Phys., 20, 9169–9182, https://doi.org/10.5194/acp-20-9169-2020, https://doi.org/10.5194/acp-20-9169-2020, 2020
Short summary
Short summary
The switch from the use of coal to natural gas or oil for energy generation potentially reduces the impact on global warming due to lower CO2 emissions with the same energy content. However, this climate benefit is offset by fugitive methane emissions during the production and distribution process. We quantify emission and leakage rates relative to production for several large production regions based on satellite observations to evaluate the climate footprint of the gas and oil industry.
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.
Simon Jones, Lucy Rowland, Peter Cox, Deborah Hemming, Andy Wiltshire, Karina Williams, Nicholas C. Parazoo, Junjie Liu, Antonio C. L. da Costa, Patrick Meir, Maurizio Mencuccini, and Anna B. Harper
Biogeosciences, 17, 3589–3612, https://doi.org/10.5194/bg-17-3589-2020, https://doi.org/10.5194/bg-17-3589-2020, 2020
Short summary
Short summary
Non-structural carbohydrates (NSCs) are an important set of molecules that help plants to grow and respire when photosynthesis is restricted by extreme climate events. In this paper we present a simple model of NSC storage and assess the effect that it has on simulations of vegetation at the ecosystem scale. Our model has the potential to significantly change predictions of plant behaviour in global vegetation models, which would have large implications for predictions of the future climate.
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.
Shufen Pan, Naiqing Pan, Hanqin Tian, Pierre Friedlingstein, Stephen Sitch, Hao Shi, Vivek K. Arora, Vanessa Haverd, Atul K. Jain, Etsushi Kato, Sebastian Lienert, Danica Lombardozzi, Julia E. M. S. Nabel, Catherine Ottlé, Benjamin Poulter, Sönke Zaehle, and Steven W. Running
Hydrol. Earth Syst. Sci., 24, 1485–1509, https://doi.org/10.5194/hess-24-1485-2020, https://doi.org/10.5194/hess-24-1485-2020, 2020
Short summary
Short summary
Evapotranspiration (ET) links global water, carbon and energy cycles. We used 4 remote sensing models, 2 machine-learning algorithms and 14 land surface models to analyze the changes in global terrestrial ET. These three categories of approaches agreed well in terms of ET intensity. For 1982–2011, all models showed that Earth greening enhanced terrestrial ET. The small interannual variability of global terrestrial ET suggests it has a potential planetary boundary of around 600 mm yr-1.
Oliver Schneising, Michael Buchwitz, Maximilian Reuter, Heinrich Bovensmann, and John P. Burrows
Atmos. Chem. Phys., 20, 3317–3332, https://doi.org/10.5194/acp-20-3317-2020, https://doi.org/10.5194/acp-20-3317-2020, 2020
Short summary
Short summary
As a consequence of climate change, droughts in California are occurring more often, providing ample fuel for destructive wildfires. The associated smoke is reducing air quality as it contains pollutants considered harmful to public health and the environment such as carbon monoxide (CO). We analyse the statewide distribution of CO during the first days of two specific wildfires using satellite measurements and assess the corresponding air quality burden in major Californian cities.
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.
Jonathan R. Moore, Arthur P. K. Argles, Kai Zhu, Chris Huntingford, and Peter M. Cox
Biogeosciences, 17, 1013–1032, https://doi.org/10.5194/bg-17-1013-2020, https://doi.org/10.5194/bg-17-1013-2020, 2020
Short summary
Short summary
The distribution of tree sizes across Amazonia can be fitted very well (for both trunk diameter and tree mass) by a simple equilibrium model assuming power law growth and size-independent mortality. We find tree growth to mirror some aspects of metabolic scaling theory and that there may be a trade-off between fast-growing, short-lived and longer-lived, slow-growing ones. Our Amazon mortality-to-growth ratio is very similar to US temperate forests, hinting at a universal property for trees.
Maximilian Reuter, Michael Buchwitz, Oliver Schneising, Stefan Noël, Heinrich Bovensmann, John P. Burrows, Hartmut Boesch, Antonio Di Noia, Jasdeep Anand, Robert J. Parker, Peter Somkuti, Lianghai Wu, Otto P. Hasekamp, Ilse Aben, Akihiko Kuze, Hiroshi Suto, Kei Shiomi, Yukio Yoshida, Isamu Morino, David Crisp, Christopher W. O'Dell, Justus Notholt, Christof Petri, Thorsten Warneke, Voltaire A. Velazco, Nicholas M. Deutscher, David W. T. Griffith, Rigel Kivi, David F. Pollard, Frank Hase, Ralf Sussmann, Yao V. Té, Kimberly Strong, Sébastien Roche, Mahesh K. Sha, Martine De Mazière, Dietrich G. Feist, Laura T. Iraci, Coleen M. Roehl, Christian Retscher, and Dinand Schepers
Atmos. Meas. Tech., 13, 789–819, https://doi.org/10.5194/amt-13-789-2020, https://doi.org/10.5194/amt-13-789-2020, 2020
Short summary
Short summary
We present new satellite-derived data sets of atmospheric carbon dioxide (CO2) and methane (CH4). The data products are column-averaged dry-air mole fractions of CO2 and CH4, denoted XCO2 and XCH4. The products cover the years 2003–2018 and are merged Level 2 (satellite footprints) and merged Level 3 (gridded at monthly time and 5° x 5° spatial resolution) products obtained from combining several individual sensor products. We present the merging algorithms and product validation results.
Oliver Schneising, Michael Buchwitz, Maximilian Reuter, Heinrich Bovensmann, John P. Burrows, Tobias Borsdorff, Nicholas M. Deutscher, Dietrich G. Feist, David W. T. Griffith, Frank Hase, Christian Hermans, Laura T. Iraci, Rigel Kivi, Jochen Landgraf, Isamu Morino, Justus Notholt, Christof Petri, David F. Pollard, Sébastien Roche, Kei Shiomi, Kimberly Strong, Ralf Sussmann, Voltaire A. Velazco, Thorsten Warneke, and Debra Wunch
Atmos. Meas. Tech., 12, 6771–6802, https://doi.org/10.5194/amt-12-6771-2019, https://doi.org/10.5194/amt-12-6771-2019, 2019
Short summary
Short summary
We introduce an algorithm that is used to simultaneously derive the abundances of the important atmospheric constituents carbon monoxide and methane from the TROPOMI instrument onboard the Sentinel-5 Precursor satellite, which enables the determination of both gases with an unprecedented level of detail on a global scale. The quality of the resulting data sets is assessed and the first results are presented.
Pierre Friedlingstein, Matthew W. Jones, Michael O'Sullivan, Robbie M. Andrew, Judith Hauck, Glen P. Peters, Wouter Peters, Julia Pongratz, Stephen Sitch, Corinne Le Quéré, Dorothee C. E. Bakker, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Peter Anthoni, Leticia Barbero, Ana Bastos, Vladislav Bastrikov, Meike Becker, Laurent Bopp, Erik Buitenhuis, Naveen Chandra, Frédéric Chevallier, Louise P. Chini, Kim I. Currie, Richard A. Feely, Marion Gehlen, Dennis Gilfillan, Thanos Gkritzalis, Daniel S. Goll, Nicolas Gruber, Sören Gutekunst, Ian Harris, Vanessa Haverd, Richard A. Houghton, George Hurtt, Tatiana Ilyina, Atul K. Jain, Emilie Joetzjer, Jed O. Kaplan, Etsushi Kato, Kees Klein Goldewijk, Jan Ivar Korsbakken, Peter Landschützer, Siv K. Lauvset, Nathalie Lefèvre, Andrew Lenton, Sebastian Lienert, Danica Lombardozzi, Gregg Marland, Patrick C. McGuire, Joe R. Melton, Nicolas Metzl, David R. Munro, Julia E. M. S. Nabel, Shin-Ichiro Nakaoka, Craig Neill, Abdirahman M. Omar, Tsuneo Ono, Anna Peregon, Denis Pierrot, Benjamin Poulter, Gregor Rehder, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Roland Séférian, Jörg Schwinger, Naomi Smith, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Francesco N. Tubiello, Guido R. van der Werf, Andrew J. Wiltshire, and Sönke Zaehle
Earth Syst. Sci. Data, 11, 1783–1838, https://doi.org/10.5194/essd-11-1783-2019, https://doi.org/10.5194/essd-11-1783-2019, 2019
Short summary
Short summary
The Global Carbon Budget 2019 describes the data sets and methodology used to quantify the emissions of carbon dioxide and their partitioning among the atmosphere, land, and ocean. These living data are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Ana Bastos, Philippe Ciais, Frédéric Chevallier, Christian Rödenbeck, Ashley P. Ballantyne, Fabienne Maignan, Yi Yin, Marcos Fernández-Martínez, Pierre Friedlingstein, Josep Peñuelas, Shilong L. Piao, Stephen Sitch, William K. Smith, Xuhui Wang, Zaichun Zhu, Vanessa Haverd, Etsushi Kato, Atul K. Jain, Sebastian Lienert, Danica Lombardozzi, Julia E. M. S. Nabel, Philippe Peylin, Benjamin Poulter, and Dan Zhu
Atmos. Chem. Phys., 19, 12361–12375, https://doi.org/10.5194/acp-19-12361-2019, https://doi.org/10.5194/acp-19-12361-2019, 2019
Short summary
Short summary
Here we show that land-surface models improved their ability to simulate the increase in the amplitude of seasonal CO2-cycle exchange (SCANBP) by ecosystems compared to estimates by two atmospheric inversions. We find a dominant role of vegetation growth over boreal Eurasia to the observed increase in SCANBP, strongly driven by CO2 fertilization, and an overall negative effect of temperature on SCANBP. Biases can be explained by the sensitivity of simulated microbial respiration to temperature.
Karina E. Williams, Anna B. Harper, Chris Huntingford, Lina M. Mercado, Camilla T. Mathison, Pete D. Falloon, Peter M. Cox, and Joon Kim
Geosci. Model Dev., 12, 3207–3240, https://doi.org/10.5194/gmd-12-3207-2019, https://doi.org/10.5194/gmd-12-3207-2019, 2019
Short summary
Short summary
Data from the First ISLSCP Field Experiment, 1987–1989, is used to assess how well the JULES land-surface model simulates water stress in tallgrass prairie vegetation. We find that JULES simulates a decrease in key carbon and water cycle variables during the dry period, as expected, but that it does not capture the shape of the diurnal cycle on these days. These results will be used to inform future model development as part of wider evaluation efforts.
Maximilian Reuter, Michael Buchwitz, Oliver Schneising, Sven Krautwurst, Christopher W. O'Dell, Andreas Richter, Heinrich Bovensmann, and John P. Burrows
Atmos. Chem. Phys., 19, 9371–9383, https://doi.org/10.5194/acp-19-9371-2019, https://doi.org/10.5194/acp-19-9371-2019, 2019
Short summary
Short summary
The quantification of anthropogenic emissions with current CO2 satellite sensors is difficult, but NO2 is co-emitted, making it a suitable tracer of recently emitted CO2. We analyze enhancements of CO2 and NO2 observed by OCO-2 and S5P and estimate the CO2 plume cross-sectional fluxes that we compare with emission databases. Our results demonstrate the usefulness of simultaneous satellite observations of CO2 and NO2 as envisaged for the European Copernicus anthropogenic CO2 monitoring mission
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.
Ye Liu, Yongkang Xue, Glen MacDonald, Peter Cox, and Zhengqiu Zhang
Earth Syst. Dynam., 10, 9–29, https://doi.org/10.5194/esd-10-9-2019, https://doi.org/10.5194/esd-10-9-2019, 2019
Short summary
Short summary
Climate regime shift during the 1980s identified by abrupt change in temperature, precipitation, etc. had a substantial impact on the ecosystem at different scales. Our paper identifies the spatial and temporal characteristics of the effects of climate variability, global warming, and eCO2 on ecosystem trends before and after the shift. We found about 15 % (20 %) of the global land area had enhanced positive trend (trend sign reversed) during the 1980s due to climate regime shift.
Michael Buchwitz, Maximilian Reuter, Oliver Schneising, Stefan Noël, Bettina Gier, Heinrich Bovensmann, John P. Burrows, Hartmut Boesch, Jasdeep Anand, Robert J. Parker, Peter Somkuti, Rob G. Detmers, Otto P. Hasekamp, Ilse Aben, André Butz, Akihiko Kuze, Hiroshi Suto, Yukio Yoshida, David Crisp, and Christopher O'Dell
Atmos. Chem. Phys., 18, 17355–17370, https://doi.org/10.5194/acp-18-17355-2018, https://doi.org/10.5194/acp-18-17355-2018, 2018
Short summary
Short summary
We present a new satellite data set of column-averaged mixing ratios of carbon dioxide (CO2), which covers the time period 2003 to 2016. We used this data set to compute annual mean atmospheric CO2 growth rates. We show that the growth rate is highest during 2015 and 2016 despite nearly constant CO2 emissions from fossil fuel burning in recent years. The high growth rates are attributed to year 2015-2016 El Nino episodes. We present correlations with fossil fuel emissions and ENSO indices.
Corinne Le Quéré, Robbie M. Andrew, Pierre Friedlingstein, Stephen Sitch, Judith Hauck, Julia Pongratz, Penelope A. Pickers, Jan Ivar Korsbakken, Glen P. Peters, Josep G. Canadell, Almut Arneth, Vivek K. Arora, Leticia Barbero, Ana Bastos, Laurent Bopp, Frédéric Chevallier, Louise P. Chini, Philippe Ciais, Scott C. Doney, Thanos Gkritzalis, Daniel S. Goll, Ian Harris, Vanessa Haverd, Forrest M. Hoffman, Mario Hoppema, Richard A. Houghton, George Hurtt, Tatiana Ilyina, Atul K. Jain, Truls Johannessen, Chris D. Jones, Etsushi Kato, Ralph F. Keeling, Kees Klein Goldewijk, Peter Landschützer, Nathalie Lefèvre, Sebastian Lienert, Zhu Liu, Danica Lombardozzi, Nicolas Metzl, David R. Munro, Julia E. M. S. Nabel, Shin-ichiro Nakaoka, Craig Neill, Are Olsen, Tsueno Ono, Prabir Patra, Anna Peregon, Wouter Peters, Philippe Peylin, Benjamin Pfeil, Denis Pierrot, Benjamin Poulter, Gregor Rehder, Laure Resplandy, Eddy Robertson, Matthias Rocher, Christian Rödenbeck, Ute Schuster, Jörg Schwinger, Roland Séférian, Ingunn Skjelvan, Tobias Steinhoff, Adrienne Sutton, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Francesco N. Tubiello, Ingrid T. van der Laan-Luijkx, Guido R. van der Werf, Nicolas Viovy, Anthony P. Walker, Andrew J. Wiltshire, Rebecca Wright, Sönke Zaehle, and Bo Zheng
Earth Syst. Sci. Data, 10, 2141–2194, https://doi.org/10.5194/essd-10-2141-2018, https://doi.org/10.5194/essd-10-2141-2018, 2018
Short summary
Short summary
The Global Carbon Budget 2018 describes the data sets and methodology used to quantify the emissions of carbon dioxide and their partitioning among the atmosphere, land, and ocean. These living data are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Qianyu Li, Xingjie Lu, Yingping Wang, Xin Huang, Peter M. Cox, and Yiqi Luo
Biogeosciences, 15, 6909–6925, https://doi.org/10.5194/bg-15-6909-2018, https://doi.org/10.5194/bg-15-6909-2018, 2018
Short summary
Short summary
Land-surface models have been widely used to predict the responses of terrestrial ecosystems to climate change. A better understanding of model mechanisms that govern terrestrial ecosystem responses to rising atmosphere [CO2] is needed. Our study for the first time shows that the expansion of leaf area under rising [CO2] is the most important response for the stimulation of land carbon accumulation by a land-surface model: CABLE. Processes related to leaf area should be better calibrated.
Jun Wang, Ning Zeng, Meirong Wang, Fei Jiang, Jingming Chen, Pierre Friedlingstein, Atul K. Jain, Ziqiang Jiang, Weimin Ju, Sebastian Lienert, Julia Nabel, Stephen Sitch, Nicolas Viovy, Hengmao Wang, and Andrew J. Wiltshire
Atmos. Chem. Phys., 18, 10333–10345, https://doi.org/10.5194/acp-18-10333-2018, https://doi.org/10.5194/acp-18-10333-2018, 2018
Short summary
Short summary
Based on the Mauna Loa CO2 records and TRENDY multi-model historical simulations, we investigate the different impacts of EP and CP El Niños on interannual carbon cycle variability. Composite analysis indicates that the evolutions of CO2 growth rate anomalies have three clear differences in terms of precursors (negative and neutral), amplitudes (strong and weak), and durations of peak (Dec–Apr and Oct–Jan) during EP and CP El Niños, respectively. We further discuss their terrestrial mechanisms.
Anna B. Harper, Andrew J. Wiltshire, Peter M. Cox, Pierre Friedlingstein, Chris D. Jones, Lina M. Mercado, Stephen Sitch, Karina Williams, and Carolina Duran-Rojas
Geosci. Model Dev., 11, 2857–2873, https://doi.org/10.5194/gmd-11-2857-2018, https://doi.org/10.5194/gmd-11-2857-2018, 2018
Short summary
Short summary
Dynamic global vegetation models are used for studying historical and future changes to vegetation and the terrestrial carbon cycle. JULES is a DGVM that represents the land surface in the UK Earth System Model. We compared simulated gross and net primary productivity of vegetation, vegetation distribution, and aspects of the transient carbon cycle to observational datasets. JULES was able to accurately reproduce many aspects of the terrestrial carbon cycle with the recent improvements.
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.
Corinne Le Quéré, Robbie M. Andrew, Pierre Friedlingstein, Stephen Sitch, Julia Pongratz, Andrew C. Manning, Jan Ivar Korsbakken, Glen P. Peters, Josep G. Canadell, Robert B. Jackson, Thomas A. Boden, Pieter P. Tans, Oliver D. Andrews, Vivek K. Arora, Dorothee C. E. Bakker, Leticia Barbero, Meike Becker, Richard A. Betts, Laurent Bopp, Frédéric Chevallier, Louise P. Chini, Philippe Ciais, Catherine E. Cosca, Jessica Cross, Kim Currie, Thomas Gasser, Ian Harris, Judith Hauck, Vanessa Haverd, Richard A. Houghton, Christopher W. Hunt, George Hurtt, Tatiana Ilyina, Atul K. Jain, Etsushi Kato, Markus Kautz, Ralph F. Keeling, Kees Klein Goldewijk, Arne Körtzinger, Peter Landschützer, Nathalie Lefèvre, Andrew Lenton, Sebastian Lienert, Ivan Lima, Danica Lombardozzi, Nicolas Metzl, Frank Millero, Pedro M. S. Monteiro, David R. Munro, Julia E. M. S. Nabel, Shin-ichiro Nakaoka, Yukihiro Nojiri, X. Antonio Padin, Anna Peregon, Benjamin Pfeil, Denis Pierrot, Benjamin Poulter, Gregor Rehder, Janet Reimer, Christian Rödenbeck, Jörg Schwinger, Roland Séférian, Ingunn Skjelvan, Benjamin D. Stocker, Hanqin Tian, Bronte Tilbrook, Francesco N. Tubiello, Ingrid T. van der Laan-Luijkx, Guido R. van der Werf, Steven van Heuven, Nicolas Viovy, Nicolas Vuichard, Anthony P. Walker, Andrew J. Watson, Andrew J. Wiltshire, Sönke Zaehle, and Dan Zhu
Earth Syst. Sci. Data, 10, 405–448, https://doi.org/10.5194/essd-10-405-2018, https://doi.org/10.5194/essd-10-405-2018, 2018
Short summary
Short summary
The Global Carbon Budget 2017 describes data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. It is the 12th annual update and the 6th published in this journal.
Mahdi Nakhavali, Pierre Friedlingstein, Ronny Lauerwald, Jing Tang, Sarah Chadburn, Marta Camino-Serrano, Bertrand Guenet, Anna Harper, David Walmsley, Matthias Peichl, and Bert Gielen
Geosci. Model Dev., 11, 593–609, https://doi.org/10.5194/gmd-11-593-2018, https://doi.org/10.5194/gmd-11-593-2018, 2018
Short summary
Short summary
In order to provide a better understanding of the Earth's carbon cycle, we need a model that represents the whole continuum from atmosphere to land and into the ocean. In this study we include in JULES a representation of dissolved organic carbon (DOC) processes. Our results show that the model is able to reproduce the DOC concentration and controlling processes, including leaching to the riverine system, which is fundamental for integrating the terrestrial and aquatic ecosystem.
Thomas Krings, Bruno Neininger, Konstantin Gerilowski, Sven Krautwurst, Michael Buchwitz, John P. Burrows, Carsten Lindemann, Thomas Ruhtz, Dirk Schüttemeyer, and Heinrich Bovensmann
Atmos. Meas. Tech., 11, 721–739, https://doi.org/10.5194/amt-11-721-2018, https://doi.org/10.5194/amt-11-721-2018, 2018
Grégoire Broquet, François-Marie Bréon, Emmanuel Renault, Michael Buchwitz, Maximilian Reuter, Heinrich Bovensmann, Frédéric Chevallier, Lin Wu, and Philippe Ciais
Atmos. Meas. Tech., 11, 681–708, https://doi.org/10.5194/amt-11-681-2018, https://doi.org/10.5194/amt-11-681-2018, 2018
Short summary
Short summary
This study assesses the potential of space-borne imagery of CO2 atmospheric concentrations for monitoring the emissions from the Paris area. Such imagery could be provided by European and American missions in the next decade. It highlights the difficulty to improve current knowledge on CO2 emissions for urban areas with CO2 observations from satellites, and calls for more technological innovations in the remote sensing of CO2 and in the models that exploit it.
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
Sven Krautwurst, Konstantin Gerilowski, Haflidi H. Jonsson, David R. Thompson, Richard W. Kolyer, Laura T. Iraci, Andrew K. Thorpe, Markus Horstjann, Michael Eastwood, Ira Leifer, Samuel A. Vigil, Thomas Krings, Jakob Borchardt, Michael Buchwitz, Matthew M. Fladeland, John P. Burrows, and Heinrich Bovensmann
Atmos. Meas. Tech., 10, 3429–3452, https://doi.org/10.5194/amt-10-3429-2017, https://doi.org/10.5194/amt-10-3429-2017, 2017
Short summary
Short summary
This study investigates a subset of data collected during the CO2 and Methane EXperiment (COMEX) in 2014. It focuses on airborne measurements to quantify the emissions from landfills in the Los Angeles Basin. Airborne remote sensing data have been used to estimate the emission rate of one particular landfill on four different days. The results have been compared to airborne in situ measurements. Airborne imaging spectroscopy has been used to identify emission hotspots across the landfill.
Christopher J. Merchant, Frank Paul, Thomas Popp, Michael Ablain, Sophie Bontemps, Pierre Defourny, Rainer Hollmann, Thomas Lavergne, Alexandra Laeng, Gerrit de Leeuw, Jonathan Mittaz, Caroline Poulsen, Adam C. Povey, Max Reuter, Shubha Sathyendranath, Stein Sandven, Viktoria F. Sofieva, and Wolfgang Wagner
Earth Syst. Sci. Data, 9, 511–527, https://doi.org/10.5194/essd-9-511-2017, https://doi.org/10.5194/essd-9-511-2017, 2017
Short summary
Short summary
Climate data records (CDRs) contain data describing Earth's climate and should address uncertainty in the data to communicate what is known about climate variability or change and what range of doubt exists. This paper discusses good practice for including uncertainty information in CDRs for the essential climate variables (ECVs) derived from satellite data. Recommendations emerge from the shared experience of diverse ECV projects within the European Space Agency Climate Change Initiative.
Marko Scholze, Michael Buchwitz, Wouter Dorigo, Luis Guanter, and Shaun Quegan
Biogeosciences, 14, 3401–3429, https://doi.org/10.5194/bg-14-3401-2017, https://doi.org/10.5194/bg-14-3401-2017, 2017
Short summary
Short summary
This paper briefly reviews data assimilation techniques in carbon cycle data assimilation and the requirements of data assimilation systems on observations. We provide a non-exhaustive overview of current observations and their uncertainties for use in terrestrial carbon cycle data assimilation, focussing on relevant space-based observations.
Chris Huntingford, Hui Yang, Anna Harper, Peter M. Cox, Nicola Gedney, Eleanor J. Burke, Jason A. Lowe, Garry Hayman, William J. Collins, Stephen M. Smith, and Edward Comyn-Platt
Earth Syst. Dynam., 8, 617–626, https://doi.org/10.5194/esd-8-617-2017, https://doi.org/10.5194/esd-8-617-2017, 2017
Short summary
Short summary
Recent UNFCCC climate meetings have placed much emphasis on constraining global warming to remain below 2 °C. The 2015 Paris meeting went further and gave an aspiration to fulfil a 1.5 °C threshold. We provide a flexible set of algebraic global temperature profiles that stabilise to either target. This will potentially allow the climate research community to estimate local climatic implications for these temperature profiles, along with emissions trajectories to fulfil them.
Eleanor J. Burke, Altug Ekici, Ye Huang, Sarah E. Chadburn, Chris Huntingford, Philippe Ciais, Pierre Friedlingstein, Shushi Peng, and Gerhard Krinner
Biogeosciences, 14, 3051–3066, https://doi.org/10.5194/bg-14-3051-2017, https://doi.org/10.5194/bg-14-3051-2017, 2017
Short summary
Short summary
There are large reserves of carbon within the permafrost which might be released to the atmosphere under global warming. Our models suggest this release may cause an additional global temperature increase of 0.005 to 0.2°C by the year 2100 and 0.01 to 0.34°C by the year 2300. Under climate mitigation scenarios this is between 1.5 and 9 % (by 2100) and between 6 and 16 % (by 2300) of the global mean temperature change. There is a large uncertainty associated with these results.
Richard J. Millar, Zebedee R. Nicholls, Pierre Friedlingstein, and Myles R. Allen
Atmos. Chem. Phys., 17, 7213–7228, https://doi.org/10.5194/acp-17-7213-2017, https://doi.org/10.5194/acp-17-7213-2017, 2017
Short summary
Short summary
Simple representations of the global coupled climate–carbon-cycle system are required for climate policy analysis. Existing models have often failed to capture important physical dependencies of the climate response to carbon dioxide emissions. In this paper we propose a simple but novel modification to impulse-response climate–carbon-cycle models to capture these physical dependencies. This simple model creates an important tool for both climate policy and climate science analysis.
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.
Michael Buchwitz, Oliver Schneising, Maximilian Reuter, Jens Heymann, Sven Krautwurst, Heinrich Bovensmann, John P. Burrows, Hartmut Boesch, Robert J. Parker, Peter Somkuti, Rob G. Detmers, Otto P. Hasekamp, Ilse Aben, André Butz, Christian Frankenberg, and Alexander J. Turner
Atmos. Chem. Phys., 17, 5751–5774, https://doi.org/10.5194/acp-17-5751-2017, https://doi.org/10.5194/acp-17-5751-2017, 2017
Short summary
Short summary
Methane is an important greenhouse gas and increasing atmospheric concentrations result in global warming. We present a simple method to derive annual methane emission estimates of methane hotspot areas from satellite data. We present results for four source areas. We found that our estimates are in good agreement with other studies/data sets for the Four Corners region in the USA and for Azerbaijan but we also found higher emissions for parts of California and Turkmenistan.
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.
Corinne Le Quéré, Robbie M. Andrew, Josep G. Canadell, Stephen Sitch, Jan Ivar Korsbakken, Glen P. Peters, Andrew C. Manning, Thomas A. Boden, Pieter P. Tans, Richard A. Houghton, Ralph F. Keeling, Simone Alin, Oliver D. Andrews, Peter Anthoni, Leticia Barbero, Laurent Bopp, Frédéric Chevallier, Louise P. Chini, Philippe Ciais, Kim Currie, Christine Delire, Scott C. Doney, Pierre Friedlingstein, Thanos Gkritzalis, Ian Harris, Judith Hauck, Vanessa Haverd, Mario Hoppema, Kees Klein Goldewijk, Atul K. Jain, Etsushi Kato, Arne Körtzinger, Peter Landschützer, Nathalie Lefèvre, Andrew Lenton, Sebastian Lienert, Danica Lombardozzi, Joe R. Melton, Nicolas Metzl, Frank Millero, Pedro M. S. Monteiro, David R. Munro, Julia E. M. S. Nabel, Shin-ichiro Nakaoka, Kevin O'Brien, Are Olsen, Abdirahman M. Omar, Tsuneo Ono, Denis Pierrot, Benjamin Poulter, Christian Rödenbeck, Joe Salisbury, Ute Schuster, Jörg Schwinger, Roland Séférian, Ingunn Skjelvan, Benjamin D. Stocker, Adrienne J. Sutton, Taro Takahashi, Hanqin Tian, Bronte Tilbrook, Ingrid T. van der Laan-Luijkx, Guido R. van der Werf, Nicolas Viovy, Anthony P. Walker, Andrew J. Wiltshire, and Sönke Zaehle
Earth Syst. Sci. Data, 8, 605–649, https://doi.org/10.5194/essd-8-605-2016, https://doi.org/10.5194/essd-8-605-2016, 2016
Short summary
Short summary
The Global Carbon Budget 2016 is the 11th annual update of emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, land, and ocean. This data synthesis brings together measurements, statistical information, and analyses of model results in order to provide an assessment of the global carbon budget and their uncertainties for years 1959 to 2015, with a projection for year 2016.
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.
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.
Fang Zhao, Ning Zeng, Ghassem Asrar, Pierre Friedlingstein, Akihiko Ito, Atul Jain, Eugenia Kalnay, Etsushi Kato, Charles D. Koven, Ben Poulter, Rashid Rafique, Stephen Sitch, Shijie Shu, Beni Stocker, Nicolas Viovy, Andy Wiltshire, and Sonke Zaehle
Biogeosciences, 13, 5121–5137, https://doi.org/10.5194/bg-13-5121-2016, https://doi.org/10.5194/bg-13-5121-2016, 2016
Short summary
Short summary
The increasing seasonality of atmospheric CO2 is strongly linked with enhanced land vegetation activities in the last 5 decades, for which the importance of increasing CO2, climate and land use/cover change was evaluated in single model studies (Zeng et al., 2014; Forkel et al., 2016). Here we examine the relative importance of these factors in multiple models. Our results highlight models can show similar results in some benchmarks with different underlying regional dynamics.
Nina M. Raoult, Tim E. Jupp, Peter M. Cox, and Catherine M. Luke
Geosci. Model Dev., 9, 2833–2852, https://doi.org/10.5194/gmd-9-2833-2016, https://doi.org/10.5194/gmd-9-2833-2016, 2016
Short summary
Short summary
We present a set of "optimal" parameter values used to describe the influence of vegetation in a numerical climate model, and the software suite that we developed to find it. Observational data from ~ 100 locations were used, and the optimal parameters improve the fit in 90 % of the locations. The new parameter values will allow the climate model to give better predictions, and our software should prove useful in future calibrations.
Chris D. Jones, Vivek Arora, Pierre Friedlingstein, Laurent Bopp, Victor Brovkin, John Dunne, Heather Graven, Forrest Hoffman, Tatiana Ilyina, Jasmin G. John, Martin Jung, Michio Kawamiya, Charlie Koven, Julia Pongratz, Thomas Raddatz, James T. Randerson, and Sönke Zaehle
Geosci. Model Dev., 9, 2853–2880, https://doi.org/10.5194/gmd-9-2853-2016, https://doi.org/10.5194/gmd-9-2853-2016, 2016
Short summary
Short summary
How the carbon cycle interacts with climate will affect future climate change and how society plans emissions reductions to achieve climate targets. The Coupled Climate Carbon Cycle Model Intercomparison Project (C4MIP) is an endorsed activity of CMIP6 and aims to quantify these interactions and feedbacks in state-of-the-art climate models. This paper lays out the experimental protocol for modelling groups to follow to contribute to C4MIP. It is a contribution to the CMIP6 GMD Special Issue.
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.
Dhanyalekshmi Pillai, Michael Buchwitz, Christoph Gerbig, Thomas Koch, Maximilian Reuter, Heinrich Bovensmann, Julia Marshall, and John P. Burrows
Atmos. Chem. Phys., 16, 9591–9610, https://doi.org/10.5194/acp-16-9591-2016, https://doi.org/10.5194/acp-16-9591-2016, 2016
Short summary
Short summary
Approximately 70 % of total CO2 emissions arise from cities; however, there exist large uncertainties in quantifying urban emissions. The present study investigates the potential of a satellite mission like CarbonSat to retrieve the city emissions via inverse modelling techniques. The study makes a valid conclusion that an instrument like CarbonSat has high potential to provide important information on city emissions when exploiting the observations using a high-resolution modelling system.
Anna B. Harper, Peter M. Cox, Pierre Friedlingstein, Andy J. Wiltshire, Chris D. Jones, Stephen Sitch, Lina M. Mercado, Margriet Groenendijk, Eddy Robertson, Jens Kattge, Gerhard Bönisch, Owen K. Atkin, Michael Bahn, Johannes Cornelissen, Ülo Niinemets, Vladimir Onipchenko, Josep Peñuelas, Lourens Poorter, Peter B. Reich, Nadjeda A. Soudzilovskaia, and Peter van Bodegom
Geosci. Model Dev., 9, 2415–2440, https://doi.org/10.5194/gmd-9-2415-2016, https://doi.org/10.5194/gmd-9-2415-2016, 2016
Short summary
Short summary
Dynamic global vegetation models (DGVMs) are used to predict the response of vegetation to climate change. We improved the representation of carbon uptake by ecosystems in a DGVM by including a wider range of trade-offs between nutrient allocation to photosynthetic capacity and leaf structure, based on observed plant traits from a worldwide data base. The improved model has higher rates of photosynthesis and net C uptake by plants, and more closely matches observations at site and global scales.
Stefan C. Dekker, Margriet Groenendijk, Ben B. B. Booth, Chris Huntingford, and Peter M. Cox
Earth Syst. Dynam., 7, 525–533, https://doi.org/10.5194/esd-7-525-2016, https://doi.org/10.5194/esd-7-525-2016, 2016
Short summary
Short summary
Our analysis allows us to infer maps of changing plant water-use efficiency (WUE) for 1901–2010, using atmospheric observations of temperature, humidity and CO2. Our estimated increase in global WUE is consistent with the tree-ring and eddy covariance data, but much larger than the historical WUE increases simulated by Earth System Models (ESMs). We therefore conclude that the effects of increasing CO2 on plant WUE are significantly underestimated in the latest climate projections.
Stijn Hantson, Almut Arneth, Sandy P. Harrison, Douglas I. Kelley, I. Colin Prentice, Sam S. Rabin, Sally Archibald, Florent Mouillot, Steve R. Arnold, Paulo Artaxo, Dominique Bachelet, Philippe Ciais, Matthew Forrest, Pierre Friedlingstein, Thomas Hickler, Jed O. Kaplan, Silvia Kloster, Wolfgang Knorr, Gitta Lasslop, Fang Li, Stephane Mangeon, Joe R. Melton, Andrea Meyn, Stephen Sitch, Allan Spessa, Guido R. van der Werf, Apostolos Voulgarakis, and Chao Yue
Biogeosciences, 13, 3359–3375, https://doi.org/10.5194/bg-13-3359-2016, https://doi.org/10.5194/bg-13-3359-2016, 2016
Short summary
Short summary
Our ability to predict the magnitude and geographic pattern of past and future fire impacts rests on our ability to model fire regimes. A large variety of models exist, and it is unclear which type of model or degree of complexity is required to model fire adequately at regional to global scales. In this paper we summarize the current state of the art in fire-regime modelling and model evaluation, and outline what lessons may be learned from the Fire Model Intercomparison Project – FireMIP.
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.
Stefan Noël, Klaus Bramstedt, Michael Hilker, Patricia Liebing, Johannes Plieninger, Max Reuter, Alexei Rozanov, Christopher E. Sioris, Heinrich Bovensmann, and John P. Burrows
Atmos. Meas. Tech., 9, 1485–1503, https://doi.org/10.5194/amt-9-1485-2016, https://doi.org/10.5194/amt-9-1485-2016, 2016
Short summary
Short summary
Stratospheric methane (CH4) and carbon dioxide (CO2) profiles have been derived from solar occultation measurements of the SCIAMACHY satellite instrument. The accuracy of these profiles is estimated to be about 5–10 % for CH4 and 2–3 % for CO2, mainly limited by unexpected vertical oscillations. Results are available for August 2002 to April 2012 and latitudes between about 50 and 70° N. From these, time series trends have been estimated, which are in reasonable agreement with total column trends.
Susan Kulawik, Debra Wunch, Christopher O'Dell, Christian Frankenberg, Maximilian Reuter, Tomohiro Oda, Frederic Chevallier, Vanessa Sherlock, Michael Buchwitz, Greg Osterman, Charles E. Miller, Paul O. Wennberg, David Griffith, Isamu Morino, Manvendra K. Dubey, Nicholas M. Deutscher, Justus Notholt, Frank Hase, Thorsten Warneke, Ralf Sussmann, John Robinson, Kimberly Strong, Matthias Schneider, Martine De Mazière, Kei Shiomi, Dietrich G. Feist, Laura T. Iraci, and Joyce Wolf
Atmos. Meas. Tech., 9, 683–709, https://doi.org/10.5194/amt-9-683-2016, https://doi.org/10.5194/amt-9-683-2016, 2016
Short summary
Short summary
To accurately estimate source and sink locations of carbon dioxide, systematic errors in satellite measurements and models must be characterized. This paper examines two satellite data sets (GOSAT, launched 2009, and SCIAMACHY, launched 2002), and two models (CarbonTracker and MACC) vs. the TCCON CO2 validation data set. We assess biases and errors by season and latitude, satellite performance under averaging, and diurnal variability. Our findings are useful for assimilation of satellite data.
Sébastien Massart, Anna Agustí-Panareda, Jens Heymann, Michael Buchwitz, Frédéric Chevallier, Maximilian Reuter, Michael Hilker, John P. Burrows, Nicholas M. Deutscher, Dietrich G. Feist, Frank Hase, Ralf Sussmann, Filip Desmet, Manvendra K. Dubey, David W. T. Griffith, Rigel Kivi, Christof Petri, Matthias Schneider, and Voltaire A. Velazco
Atmos. Chem. Phys., 16, 1653–1671, https://doi.org/10.5194/acp-16-1653-2016, https://doi.org/10.5194/acp-16-1653-2016, 2016
Short summary
Short summary
This study presents the European Centre for Medium-Range Weather Forecasts (ECMWF) monitoring of atmospheric CO2 using measurements from the Greenhouse gases Observing Satellite (GOSAT). We show that the modelled CO2 has a better precision than standard CO2 satellite products compared to ground-based measurements. We also present the CO2 forecast based on our best knowledge of the atmospheric CO2 distribution. We show that it has skill to forecast the largest scale CO2 patterns up to day 5.
G. Murray-Tortarolo, P. Friedlingstein, S. Sitch, V. J. Jaramillo, F. Murguía-Flores, A. Anav, Y. Liu, A. Arneth, A. Arvanitis, A. Harper, A. Jain, E. Kato, C. Koven, B. Poulter, B. D. Stocker, A. Wiltshire, S. Zaehle, and N. Zeng
Biogeosciences, 13, 223–238, https://doi.org/10.5194/bg-13-223-2016, https://doi.org/10.5194/bg-13-223-2016, 2016
Short summary
Short summary
We modelled the carbon (C) cycle in Mexico for three different time periods: past (20th century), present (2000-2005) and future (2006-2100). We used different available products to estimate C stocks and fluxes in the country. Contrary to other current estimates, our results showed that Mexico was a C sink and this is likely to continue in the next century (unless the most extreme climate-change scenarios are reached).
Z. A. Thomas, F. Kwasniok, C. A. Boulton, P. M. Cox, R. T. Jones, T. M. Lenton, and C. S. M. Turney
Clim. Past, 11, 1621–1633, https://doi.org/10.5194/cp-11-1621-2015, https://doi.org/10.5194/cp-11-1621-2015, 2015
Short summary
Short summary
Using a combination of speleothem records and model simulations of the East Asian Monsoon over the penultimate glacial cycle, we search for early warning signals of past tipping points. We detect a characteristic slower response to perturbations prior to an abrupt monsoon shift at the glacial termination; however, we do not detect these signals in the preceding shifts. Our results have important implications for detecting tipping points in palaeoclimate records outside glacial terminations.
C. Le Quéré, R. Moriarty, R. M. Andrew, J. G. Canadell, S. Sitch, J. I. Korsbakken, P. Friedlingstein, G. P. Peters, R. J. Andres, T. A. Boden, R. A. Houghton, J. I. House, R. F. Keeling, P. Tans, A. Arneth, D. C. E. Bakker, L. Barbero, L. Bopp, J. Chang, F. Chevallier, L. P. Chini, P. Ciais, M. Fader, R. A. Feely, T. Gkritzalis, I. Harris, J. Hauck, T. Ilyina, A. K. Jain, E. Kato, V. Kitidis, K. Klein Goldewijk, C. Koven, P. Landschützer, S. K. Lauvset, N. Lefèvre, A. Lenton, I. D. Lima, N. Metzl, F. Millero, D. R. Munro, A. Murata, J. E. M. S. Nabel, S. Nakaoka, Y. Nojiri, K. O'Brien, A. Olsen, T. Ono, F. F. Pérez, B. Pfeil, D. Pierrot, B. Poulter, G. Rehder, C. Rödenbeck, S. Saito, U. Schuster, J. Schwinger, R. Séférian, T. Steinhoff, B. D. Stocker, A. J. Sutton, T. Takahashi, B. Tilbrook, I. T. van der Laan-Luijkx, G. R. van der Werf, S. van Heuven, D. Vandemark, N. Viovy, A. Wiltshire, S. Zaehle, and N. Zeng
Earth Syst. Sci. Data, 7, 349–396, https://doi.org/10.5194/essd-7-349-2015, https://doi.org/10.5194/essd-7-349-2015, 2015
Short summary
Short summary
Accurate assessment of anthropogenic carbon dioxide emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere is important to understand the global carbon cycle, support the development of climate policies, and project future climate change. We describe data sets and a methodology to quantify all major components of the global carbon budget, including their uncertainties, based on a range of data and models and their interpretation by a broad scientific community.
C. D. Koven, J. Q. Chambers, K. Georgiou, R. Knox, R. Negron-Juarez, W. J. Riley, V. K. Arora, V. Brovkin, P. Friedlingstein, and C. D. Jones
Biogeosciences, 12, 5211–5228, https://doi.org/10.5194/bg-12-5211-2015, https://doi.org/10.5194/bg-12-5211-2015, 2015
Short summary
Short summary
Terrestrial carbon feedbacks are a large uncertainty in climate change. We separate modeled feedback responses into those governed by changed carbon inputs (productivity) and changed outputs (turnover). The disaggregated responses show that both are important in controlling inter-model uncertainty. Interactions between productivity and turnover are also important, and research must focus on these interactions for more accurate projections of carbon cycle feedbacks.
S. E. Chadburn, E. J. Burke, R. L. H. Essery, J. Boike, M. Langer, M. Heikenfeld, P. M. Cox, and P. Friedlingstein
The Cryosphere, 9, 1505–1521, https://doi.org/10.5194/tc-9-1505-2015, https://doi.org/10.5194/tc-9-1505-2015, 2015
Short summary
Short summary
In this paper we use a global land-surface model to study the dynamics of Arctic permafrost. We examine the impact of new and improved processes in the model, namely soil depth and resolution, organic soils, moss and the representation of snow. These improvements make the simulated soil temperatures and thaw depth significantly more realistic. Simulations under future climate scenarios show that permafrost thaws more slowly in the new model version, but still a large amount is lost by 2100.
J. Heymann, M. Reuter, M. Hilker, M. Buchwitz, O. Schneising, H. Bovensmann, J. P. Burrows, A. Kuze, H. Suto, N. M. Deutscher, M. K. Dubey, D. W. T. Griffith, F. Hase, S. Kawakami, R. Kivi, I. Morino, C. Petri, C. Roehl, M. Schneider, V. Sherlock, R. Sussmann, V. A. Velazco, T. Warneke, and D. Wunch
Atmos. Meas. Tech., 8, 2961–2980, https://doi.org/10.5194/amt-8-2961-2015, https://doi.org/10.5194/amt-8-2961-2015, 2015
Short summary
Short summary
Long-term data sets of global atmospheric carbon dioxide concentrations based on observations from different satellite instruments may suffer from inconsistencies originating from the use of different retrieval algorithms. This issue has been addressed by applying the Bremen Optimal Estimation DOAS retrieval algorithm to SCIAMACHY and TANSO-FTS observations. Detailed comparisons with TCCON and CarbonTracker show good consistency between the SCIAMACHY and TANSO-FTS data sets.
S. Chadburn, E. Burke, R. Essery, J. Boike, M. Langer, M. Heikenfeld, P. Cox, and P. Friedlingstein
Geosci. Model Dev., 8, 1493–1508, https://doi.org/10.5194/gmd-8-1493-2015, https://doi.org/10.5194/gmd-8-1493-2015, 2015
Short summary
Short summary
Permafrost, ground that is frozen for 2 or more years, is found extensively in the Arctic. It stores large quantities of carbon, which may be released under climate warming, so it is important to include it in climate models. Here we improve the representation of permafrost in a climate model land-surface scheme, both in the numerical representation of soil and snow, and by adding the effects of organic soils and moss. Site simulations show significantly improved soil temperature and thaw depth.
C. Le Quéré, R. Moriarty, R. M. Andrew, G. P. Peters, P. Ciais, P. Friedlingstein, S. D. Jones, S. Sitch, P. Tans, A. Arneth, T. A. Boden, L. Bopp, Y. Bozec, J. G. Canadell, L. P. Chini, F. Chevallier, C. E. Cosca, I. Harris, M. Hoppema, R. A. Houghton, J. I. House, A. K. Jain, T. Johannessen, E. Kato, R. F. Keeling, V. Kitidis, K. Klein Goldewijk, C. Koven, C. S. Landa, P. Landschützer, A. Lenton, I. D. Lima, G. Marland, J. T. Mathis, N. Metzl, Y. Nojiri, A. Olsen, T. Ono, S. Peng, W. Peters, B. Pfeil, B. Poulter, M. R. Raupach, P. Regnier, C. Rödenbeck, S. Saito, J. E. Salisbury, U. Schuster, J. Schwinger, R. Séférian, J. Segschneider, T. Steinhoff, B. D. Stocker, A. J. Sutton, T. Takahashi, B. Tilbrook, G. R. van der Werf, N. Viovy, Y.-P. Wang, R. Wanninkhof, A. Wiltshire, and N. Zeng
Earth Syst. Sci. Data, 7, 47–85, https://doi.org/10.5194/essd-7-47-2015, https://doi.org/10.5194/essd-7-47-2015, 2015
Short summary
Short summary
Carbon dioxide (CO2) emissions from human activities (burning fossil fuels and cement production, deforestation and other land-use change) are set to rise again in 2014.
This study (updated yearly) makes an accurate assessment of anthropogenic CO2 emissions and their redistribution between the atmosphere, ocean, and terrestrial biosphere in order to better understand the global carbon cycle, support the development of climate policies, and project future climate change.
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
S. Sitch, P. Friedlingstein, N. Gruber, S. D. Jones, G. Murray-Tortarolo, A. Ahlström, S. C. Doney, H. Graven, C. Heinze, C. Huntingford, S. Levis, P. E. Levy, M. Lomas, B. Poulter, N. Viovy, S. Zaehle, N. Zeng, A. Arneth, G. Bonan, L. Bopp, J. G. Canadell, F. Chevallier, P. Ciais, R. Ellis, M. Gloor, P. Peylin, S. L. Piao, C. Le Quéré, B. Smith, Z. Zhu, and R. Myneni
Biogeosciences, 12, 653–679, https://doi.org/10.5194/bg-12-653-2015, https://doi.org/10.5194/bg-12-653-2015, 2015
M. Reuter, M. Buchwitz, M. Hilker, J. Heymann, O. Schneising, D. Pillai, H. Bovensmann, J. P. Burrows, H. Bösch, R. Parker, A. Butz, O. Hasekamp, C. W. O'Dell, Y. Yoshida, C. Gerbig, T. Nehrkorn, N. M. Deutscher, T. Warneke, J. Notholt, F. Hase, R. Kivi, R. Sussmann, T. Machida, H. Matsueda, and Y. Sawa
Atmos. Chem. Phys., 14, 13739–13753, https://doi.org/10.5194/acp-14-13739-2014, https://doi.org/10.5194/acp-14-13739-2014, 2014
Short summary
Short summary
Current knowledge about the European terrestrial biospheric carbon sink relies upon bottom-up and global surface flux inverse model estimates using in situ measurements. Our analysis of five satellite data sets comprises a regional inversion designed to be insensitive to potential retrieval biases and transport errors. We show that the satellite-derived sink is larger (1.0±0.3GtC/a) than previous estimates (0.4±0.4GtC/a).
L. Kwiatkowski, A. Yool, J. I. Allen, T. R. Anderson, R. Barciela, E. T. Buitenhuis, M. Butenschön, C. Enright, P. R. Halloran, C. Le Quéré, L. de Mora, M.-F. Racault, B. Sinha, I. J. Totterdell, and P. M. Cox
Biogeosciences, 11, 7291–7304, https://doi.org/10.5194/bg-11-7291-2014, https://doi.org/10.5194/bg-11-7291-2014, 2014
G. D. Hayman, F. M. O'Connor, M. Dalvi, D. B. Clark, N. Gedney, C. Huntingford, C. Prigent, M. Buchwitz, O. Schneising, J. P. Burrows, C. Wilson, N. Richards, and M. Chipperfield
Atmos. Chem. Phys., 14, 13257–13280, https://doi.org/10.5194/acp-14-13257-2014, https://doi.org/10.5194/acp-14-13257-2014, 2014
Short summary
Short summary
Globally, wetlands are a major source of methane, which is the second most important greenhouse gas. We find the JULES wetland methane scheme to perform well in general, although there is a tendency for it to overpredict emissions in the tropics and underpredict them in northern latitudes. Our study highlights novel uses of satellite data as a major tool to constrain land-atmosphere methane flux models in a warming world.
C. Yue, P. Ciais, P. Cadule, K. Thonicke, S. Archibald, B. Poulter, W. M. Hao, S. Hantson, F. Mouillot, P. Friedlingstein, F. Maignan, and N. Viovy
Geosci. Model Dev., 7, 2747–2767, https://doi.org/10.5194/gmd-7-2747-2014, https://doi.org/10.5194/gmd-7-2747-2014, 2014
Short summary
Short summary
ORCHIDEE-SPITFIRE model could moderately capture the decadal trend and variation of burned area during the 20th century, and the spatial and temporal patterns of contemporary vegetation fires. The model has a better performance in simulating fires for regions dominated by climate-driven fires, such as boreal forests. However, it has limited capability to reproduce the infrequent but important large fires in different ecosystems, where urgent model improvement is needed in the future.
P. Ciais, A. J. Dolman, A. Bombelli, R. Duren, A. Peregon, P. J. Rayner, C. Miller, N. Gobron, G. Kinderman, G. Marland, N. Gruber, F. Chevallier, R. J. Andres, G. Balsamo, L. Bopp, F.-M. Bréon, G. Broquet, R. Dargaville, T. J. Battin, A. Borges, H. Bovensmann, M. Buchwitz, J. Butler, J. G. Canadell, R. B. Cook, R. DeFries, R. Engelen, K. R. Gurney, C. Heinze, M. Heimann, A. Held, M. Henry, B. Law, S. Luyssaert, J. Miller, T. Moriyama, C. Moulin, R. B. Myneni, C. Nussli, M. Obersteiner, D. Ojima, Y. Pan, J.-D. Paris, S. L. Piao, B. Poulter, S. Plummer, S. Quegan, P. Raymond, M. Reichstein, L. Rivier, C. Sabine, D. Schimel, O. Tarasova, R. Valentini, R. Wang, G. van der Werf, D. Wickland, M. Williams, and C. Zehner
Biogeosciences, 11, 3547–3602, https://doi.org/10.5194/bg-11-3547-2014, https://doi.org/10.5194/bg-11-3547-2014, 2014
B. Dils, M. Buchwitz, M. Reuter, O. Schneising, H. Boesch, R. Parker, S. Guerlet, I. Aben, T. Blumenstock, J. P. Burrows, A. Butz, N. M. Deutscher, C. Frankenberg, F. Hase, O. P. Hasekamp, J. Heymann, M. De Mazière, J. Notholt, R. Sussmann, T. Warneke, D. Griffith, V. Sherlock, and D. Wunch
Atmos. Meas. Tech., 7, 1723–1744, https://doi.org/10.5194/amt-7-1723-2014, https://doi.org/10.5194/amt-7-1723-2014, 2014
C. Le Quéré, G. P. Peters, R. J. Andres, R. M. Andrew, T. A. Boden, P. Ciais, P. Friedlingstein, R. A. Houghton, G. Marland, R. Moriarty, S. Sitch, P. Tans, A. Arneth, A. Arvanitis, D. C. E. Bakker, L. Bopp, J. G. Canadell, L. P. Chini, S. C. Doney, A. Harper, I. Harris, J. I. House, A. K. Jain, S. D. Jones, E. Kato, R. F. Keeling, K. Klein Goldewijk, A. Körtzinger, C. Koven, N. Lefèvre, F. Maignan, A. Omar, T. Ono, G.-H. Park, B. Pfeil, B. Poulter, M. R. Raupach, P. Regnier, C. Rödenbeck, S. Saito, J. Schwinger, J. Segschneider, B. D. Stocker, T. Takahashi, B. Tilbrook, S. van Heuven, N. Viovy, R. Wanninkhof, A. Wiltshire, and S. Zaehle
Earth Syst. Sci. Data, 6, 235–263, https://doi.org/10.5194/essd-6-235-2014, https://doi.org/10.5194/essd-6-235-2014, 2014
I. N. Fletcher, L. E. O. C. Aragão, A. Lima, Y. Shimabukuro, and P. Friedlingstein
Biogeosciences, 11, 1449–1459, https://doi.org/10.5194/bg-11-1449-2014, https://doi.org/10.5194/bg-11-1449-2014, 2014
D. Dalmonech, A. M. Foley, A. Anav, P. Friedlingstein, A. D. Friend, M. Kidston, M. Willeit, and S. Zaehle
Biogeosciences Discuss., https://doi.org/10.5194/bgd-11-2083-2014, https://doi.org/10.5194/bgd-11-2083-2014, 2014
Revised manuscript has not been submitted
O. Schneising, M. Reuter, M. Buchwitz, J. Heymann, H. Bovensmann, and J. P. Burrows
Atmos. Chem. Phys., 14, 133–141, https://doi.org/10.5194/acp-14-133-2014, https://doi.org/10.5194/acp-14-133-2014, 2014
A. M. Foley, D. Dalmonech, A. D. Friend, F. Aires, A. T. Archibald, P. Bartlein, L. Bopp, J. Chappellaz, P. Cox, N. R. Edwards, G. Feulner, P. Friedlingstein, S. P. Harrison, P. O. Hopcroft, C. D. Jones, J. Kolassa, J. G. Levine, I. C. Prentice, J. Pyle, N. Vázquez Riveiros, E. W. Wolff, and S. Zaehle
Biogeosciences, 10, 8305–8328, https://doi.org/10.5194/bg-10-8305-2013, https://doi.org/10.5194/bg-10-8305-2013, 2013
M. Buchwitz, M. Reuter, H. Bovensmann, D. Pillai, J. Heymann, O. Schneising, V. Rozanov, T. Krings, J. P. Burrows, H. Boesch, C. Gerbig, Y. Meijer, and A. Löscher
Atmos. Meas. Tech., 6, 3477–3500, https://doi.org/10.5194/amt-6-3477-2013, https://doi.org/10.5194/amt-6-3477-2013, 2013
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
C. Le Quéré, R. J. Andres, T. Boden, T. Conway, R. A. Houghton, J. I. House, G. Marland, G. P. Peters, G. R. van der Werf, A. Ahlström, R. M. Andrew, L. Bopp, J. G. Canadell, P. Ciais, S. C. Doney, C. Enright, P. Friedlingstein, C. Huntingford, A. K. Jain, C. Jourdain, E. Kato, R. F. Keeling, K. Klein Goldewijk, S. Levis, P. Levy, M. Lomas, B. Poulter, M. R. Raupach, J. Schwinger, S. Sitch, B. D. Stocker, N. Viovy, S. Zaehle, and N. Zeng
Earth Syst. Sci. Data, 5, 165–185, https://doi.org/10.5194/essd-5-165-2013, https://doi.org/10.5194/essd-5-165-2013, 2013
B. B. B. Booth, D. Bernie, D. McNeall, E. Hawkins, J. Caesar, C. Boulton, P. Friedlingstein, and D. M. H. Sexton
Earth Syst. Dynam., 4, 95–108, https://doi.org/10.5194/esd-4-95-2013, https://doi.org/10.5194/esd-4-95-2013, 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
O. Schneising, J. Heymann, M. Buchwitz, M. Reuter, H. Bovensmann, and J. P. Burrows
Atmos. Chem. Phys., 13, 2445–2454, https://doi.org/10.5194/acp-13-2445-2013, https://doi.org/10.5194/acp-13-2445-2013, 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
M. Reuter, H. Bösch, H. Bovensmann, A. Bril, M. Buchwitz, A. Butz, J. P. Burrows, C. W. O'Dell, S. Guerlet, O. Hasekamp, J. Heymann, N. Kikuchi, S. Oshchepkov, R. Parker, S. Pfeifer, O. Schneising, T. Yokota, and Y. Yoshida
Atmos. Chem. Phys., 13, 1771–1780, https://doi.org/10.5194/acp-13-1771-2013, https://doi.org/10.5194/acp-13-1771-2013, 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
T. Krings, K. Gerilowski, M. Buchwitz, J. Hartmann, T. Sachs, J. Erzinger, J. P. Burrows, and H. Bovensmann
Atmos. Meas. Tech., 6, 151–166, https://doi.org/10.5194/amt-6-151-2013, https://doi.org/10.5194/amt-6-151-2013, 2013
Related subject area
Biogeochemistry: Greenhouse Gases
Timescale dependence of airborne fraction and underlying climate–carbon-cycle feedbacks for weak perturbations in CMIP5 models
Technical note: Preventing CO2 overestimation from mercuric or copper(II) chloride preservation of dissolved greenhouse gases in freshwater samples
Exploring temporal and spatial variation of nitrous oxide flux using several years of peatland forest automatic chamber data
Diurnal versus spatial variability of greenhouse gas emissions from an anthropogenically modified lowland river in Germany
Regional assessment and uncertainty analysis of carbon and nitrogen balances at cropland scale using the ecosystem model LandscapeDNDC
Resolving heterogeneous fluxes from tundra halves the growing season carbon budget
Lawns and meadows in urban green space – a comparison from perspectives of greenhouse gases, drought resilience and plant functional types
Large contribution of soil N2O emission to the global warming potential of a large-scale oil palm plantation despite changing from conventional to reduced management practices
Identifying landscape hot and cold spots of soil greenhouse gas fluxes by combining field measurements and remote sensing data
A case study on topsoil removal and rewetting for paludiculture: effect on biogeochemistry and greenhouse gas emissions from Typha latifolia, Typha angustifolia and Azolla filiculoides
Enhanced Southern Ocean CO2 outgassing as a result of stronger and poleward shifted southern hemispheric westerlies
Modelling CO2 and N2O emissions from soils in silvopastoral systems of the West-African Sahelian band
Spatial and temporal variability of methane emissions and environmental conditions in a hyper-eutrophic fishpond
Optical and radar Earth observation data for upscaling methane emissions linked to permafrost degradation in sub-Arctic peatlands in northern Sweden
Assessing improvements in global ocean pCO2 machine learning reconstructions with Southern Ocean autonomous sampling
Herbivore–shrub interactions influence ecosystem respiration and biogenic volatile organic compound composition in the subarctic
Methane emissions due to reservoir flushing: a significant emission pathway?
Carbon dioxide and methane fluxes from mounds of African fungus-growing termites
Diel and seasonal methane dynamics in the shallow and turbulent Wadden Sea
Technical note: Skirt chamber – an open dynamic method for the rapid and minimally intrusive measurement of greenhouse gas emissions from peatlands
Seasonal variability of nitrous oxide concentrations and emissions in a temperate estuary
Reviews and syntheses: Recent advances in microwave remote sensing in support of terrestrial carbon cycle science in Arctic–boreal regions
Simulated methane emissions from Arctic ponds are highly sensitive to warming
Water-table-driven greenhouse gas emission estimates guide peatland restoration at national scale
Relationships between greenhouse gas production and landscape position during short-term permafrost thaw under anaerobic conditions in the Lena Delta
Carbon emissions and radiative forcings from tundra wildfires in the Yukon–Kuskokwim River Delta, Alaska
Carbon monoxide (CO) cycling in the Fram Strait, Arctic Ocean
Post-flooding disturbance recovery promotes carbon capture in riparian zones
Meteorological responses of carbon dioxide and methane fluxes in the terrestrial and aquatic ecosystems of a subarctic landscape
Carbon emission and export from the Ket River, western Siberia
Evaluation of wetland CH4 in the Joint UK Land Environment Simulator (JULES) land surface model using satellite observations
Greenhouse gas fluxes in mangrove forest soil in an Amazon estuary
Temporal patterns and drivers of CO2 emission from dry sediments in a groyne field of a large river
Effects of water table level and nitrogen deposition on methane and nitrous oxide emissions in an alpine peatland
Highest methane concentrations in an Arctic river linked to local terrestrial inputs
Seasonal study of the small-scale variability in dissolved methane in the western Kiel Bight (Baltic Sea) during the European heatwave in 2018
Trace gas fluxes from tidal salt marsh soils: implications for carbon–sulfur biogeochemistry
Spatial and temporal variation in δ13C values of methane emitted from a hemiboreal mire: methanogenesis, methanotrophy, and hysteresis
Intercomparison of methods to estimate gross primary production based on CO2 and COS flux measurements
Lateral carbon export has low impact on the net ecosystem carbon balance of a polygonal tundra catchment
The effect of static chamber base on N2O flux in drip irrigation
Controls on autotrophic and heterotrophic respiration in an ombrotrophic bog
Episodic N2O emissions following tillage of a legume–grass cover crop mixture
Variation in CO2 and CH4 fluxes among land cover types in heterogeneous Arctic tundra in northeastern Siberia
Response of vegetation and carbon fluxes to brown lemming herbivory in northern Alaska
Sources of nitrous oxide and the fate of mineral nitrogen in subarctic permafrost peat soils
Data-based estimates of interannual sea–air CO2 flux variations 1957–2020 and their relation to environmental drivers
Evaluating alternative ebullition models for predicting peatland methane emission and its pathways via data–model fusion
Excess soil moisture and fresh carbon input are prerequisites for methane production in podzolic soil
Low biodegradability of particulate organic carbon mobilized from thaw slumps on the Peel Plateau, NT, and possible chemosynthesis and sorption effects
Guilherme L. Torres Mendonça, Julia Pongratz, and Christian H. Reick
Biogeosciences, 21, 1923–1960, https://doi.org/10.5194/bg-21-1923-2024, https://doi.org/10.5194/bg-21-1923-2024, 2024
Short summary
Short summary
We study the timescale dependence of airborne fraction and underlying feedbacks by a theory of the climate–carbon system. Using simulations we show the predictive power of this theory and find that (1) this fraction generally decreases for increasing timescales and (2) at all timescales the total feedback is negative and the model spread in a single feedback causes the spread in the airborne fraction. Our study indicates that those are properties of the system, independently of the scenario.
François Clayer, Jan Erik Thrane, Kuria Ndungu, Andrew King, Peter Dörsch, and Thomas Rohrlack
Biogeosciences, 21, 1903–1921, https://doi.org/10.5194/bg-21-1903-2024, https://doi.org/10.5194/bg-21-1903-2024, 2024
Short summary
Short summary
Determination of dissolved greenhouse gas (GHG) in freshwater allows us to estimate GHG fluxes. Mercuric chloride (HgCl2) is used to preserve water samples prior to GHG analysis despite its environmental and health impacts and interferences with water chemistry in freshwater. Here, we tested the effects of HgCl2, two substitutes and storage time on GHG in water from two boreal lakes. Preservation with HgCl2 caused overestimation of CO2 concentration with consequences for GHG flux estimation.
Helena Rautakoski, Mika Korkiakoski, Jarmo Mäkelä, Markku Koskinen, Kari Minkkinen, Mika Aurela, Paavo Ojanen, and Annalea Lohila
Biogeosciences, 21, 1867–1886, https://doi.org/10.5194/bg-21-1867-2024, https://doi.org/10.5194/bg-21-1867-2024, 2024
Short summary
Short summary
Current and future nitrous oxide (N2O) emissions are difficult to estimate due to their high variability in space and time. Several years of N2O fluxes from drained boreal peatland forest indicate high importance of summer precipitation, winter temperature, and snow conditions in controlling annual N2O emissions. The results indicate increasing year-to-year variation in N2O emissions in changing climate with more extreme seasonal weather conditions.
Matthias Koschorreck, Norbert Kamjunke, Uta Koedel, Michael Rode, Claudia Schuetze, and Ingeborg Bussmann
Biogeosciences, 21, 1613–1628, https://doi.org/10.5194/bg-21-1613-2024, https://doi.org/10.5194/bg-21-1613-2024, 2024
Short summary
Short summary
We measured the emission of carbon dioxide (CO2) and methane (CH4) from different sites at the river Elbe in Germany over 3 days to find out what is more important for quantification: small-scale spatial variability or diurnal temporal variability. We found that CO2 emissions were very different between day and night, while CH4 emissions were more different between sites. Dried out river sediments contributed to CO2 emissions, while the side areas of the river were important CH4 sources.
Odysseas Sifounakis, Edwin Haas, Klaus Butterbach-Bahl, and Maria P. Papadopoulou
Biogeosciences, 21, 1563–1581, https://doi.org/10.5194/bg-21-1563-2024, https://doi.org/10.5194/bg-21-1563-2024, 2024
Short summary
Short summary
We performed a full assessment of the carbon and nitrogen cycles of a cropland ecosystem. An uncertainty analysis and quantification of all carbon and nitrogen fluxes were deployed. The inventory simulations include greenhouse gas emissions of N2O, NH3 volatilization and NO3 leaching from arable land cultivation in Greece. The inventory also reports changes in soil organic carbon and nitrogen stocks in arable soils.
Sarah M. Ludwig, Luke Schiferl, Jacqueline Hung, Susan M. Natali, and Roisin Commane
Biogeosciences, 21, 1301–1321, https://doi.org/10.5194/bg-21-1301-2024, https://doi.org/10.5194/bg-21-1301-2024, 2024
Short summary
Short summary
Landscapes are often assumed to be homogeneous when using eddy covariance fluxes, which can lead to biases when calculating carbon budgets. In this study we report eddy covariance carbon fluxes from heterogeneous tundra. We used the footprints of each flux observation to unmix the fluxes coming from components of the landscape. We identified and quantified hot spots of carbon emissions in the landscape. Accurately scaling with landscape heterogeneity yielded half as much regional carbon uptake.
Justine Trémeau, Beñat Olascoaga, Leif Backman, Esko Karvinen, Henriikka Vekuri, and Liisa Kulmala
Biogeosciences, 21, 949–972, https://doi.org/10.5194/bg-21-949-2024, https://doi.org/10.5194/bg-21-949-2024, 2024
Short summary
Short summary
We studied urban lawns and meadows in the Helsinki metropolitan area, Finland. We found that meadows are more resistant to drought events but that they do not increase carbon sequestration compared with lawns. Moreover, the transformation from lawns to meadows did not demonstrate any negative climate effects in terms of greenhouse gas emissions. Even though social and economic aspects also steer urban development, these results can guide planning to consider carbon-smart options.
Guantao Chen, Edzo Veldkamp, Muhammad Damris, Bambang Irawan, Aiyen Tjoa, and Marife D. Corre
Biogeosciences, 21, 513–529, https://doi.org/10.5194/bg-21-513-2024, https://doi.org/10.5194/bg-21-513-2024, 2024
Short summary
Short summary
We established an oil palm management experiment in a large-scale oil palm plantation in Jambi, Indonesia. We recorded oil palm fruit yield and measured soil CO2, N2O, and CH4 fluxes. After 4 years of treatment, compared with conventional fertilization with herbicide weeding, reduced fertilization with mechanical weeding did not reduce yield and soil greenhouse gas emissions, which highlights the legacy effects of over a decade of conventional management prior to the start of the experiment.
Elizabeth Gachibu Wangari, Ricky Mwangada Mwanake, Tobias Houska, David Kraus, Gretchen Maria Gettel, Ralf Kiese, Lutz Breuer, and Klaus Butterbach-Bahl
Biogeosciences, 20, 5029–5067, https://doi.org/10.5194/bg-20-5029-2023, https://doi.org/10.5194/bg-20-5029-2023, 2023
Short summary
Short summary
Agricultural landscapes act as sinks or sources of the greenhouse gases (GHGs) CO2, CH4, or N2O. Various physicochemical and biological processes control the fluxes of these GHGs between ecosystems and the atmosphere. Therefore, fluxes depend on environmental conditions such as soil moisture, soil temperature, or soil parameters, which result in large spatial and temporal variations of GHG fluxes. Here, we describe an example of how this variation may be studied and analyzed.
Merit van den Berg, Thomas Gremmen, Renske J. E. Vroom, Jacobus van Huissteden, Jim Boonman, Corine J. A. van Huissteden, Ype van der Velde, Alfons J. P. Smolders, and Bas P. van de Riet
EGUsphere, https://doi.org/10.5194/egusphere-2023-2826, https://doi.org/10.5194/egusphere-2023-2826, 2023
Short summary
Short summary
Drained peatlands emit 3 % of the global greenhouse gas emission. Paludiculture is a way to reduce CO2 emissions while at the same time generating an income for landowners. The side effect is the potentially high methane emission. We found very high methane emission for broadleaf cattail, compared to narrowleaf cattail and water fern. The rewetting was, however, effective to stop CO2 emission for all species. The highest potential to reduce greenhouse gas emission had narrowleaf cattail.
Laurie C. Menviel, Paul Spence, Andrew E. Kiss, Matthew A. Chamberlain, Hakase Hayashida, Matthew H. England, and Darryn Waugh
Biogeosciences, 20, 4413–4431, https://doi.org/10.5194/bg-20-4413-2023, https://doi.org/10.5194/bg-20-4413-2023, 2023
Short summary
Short summary
As the ocean absorbs 25% of the anthropogenic emissions of carbon, it is important to understand the impact of climate change on the flux of carbon between the ocean and the atmosphere. Here, we use a very high-resolution ocean, sea-ice, carbon cycle model to show that the capability of the Southern Ocean to uptake CO2 has decreased over the last 40 years due to a strengthening and poleward shift of the southern hemispheric westerlies. This trend is expected to continue over the coming century.
Yélognissè Agbohessou, Claire Delon, Manuela Grippa, Eric Mougin, Daouda Ngom, Espoir Koudjo Gaglo, Ousmane Ndiaye, Paulo Salgado, and Olivier Roupsard
EGUsphere, https://doi.org/10.5194/egusphere-2023-2452, https://doi.org/10.5194/egusphere-2023-2452, 2023
Short summary
Short summary
Emissions of greenhouse gases in the Sahel are not well represented, because considered as weak compared to the rest of the world. However, natural areas in the Sahel emit carbon dioxide and nitrous oxides which need to be assessed because of extended surfaces. We propose an assessment of such emissions in Sahelian silvopastoral systems, and how they are influenced by environmental characteristics. These results are essential to inform on climate change strategies in the region.
Petr Znachor, Jiří Nedoma, Vojtech Kolar, and Anna Matoušů
Biogeosciences, 20, 4273–4288, https://doi.org/10.5194/bg-20-4273-2023, https://doi.org/10.5194/bg-20-4273-2023, 2023
Short summary
Short summary
We conducted intensive spatial sampling of the hypertrophic fishpond to better understand the spatial dynamics of methane fluxes and environmental heterogeneity in fishponds. The diffusive fluxes of methane accounted for only a minor fraction of the total fluxes and both varied pronouncedly within the pond and over the studied summer season. This could be explained only by the water depth. Wind substantially affected temperature, oxygen and chlorophyll a distribution in the pond.
Sofie Sjögersten, Martha Ledger, Matthias Siewert, Betsabé de la Barreda-Bautista, Andrew Sowter, David Gee, Giles Foody, and Doreen S. Boyd
Biogeosciences, 20, 4221–4239, https://doi.org/10.5194/bg-20-4221-2023, https://doi.org/10.5194/bg-20-4221-2023, 2023
Short summary
Short summary
Permafrost thaw in Arctic regions is increasing methane emissions, but quantification is difficult given the large and remote areas impacted. We show that UAV data together with satellite data can be used to extrapolate emissions across the wider landscape as well as detect areas at risk of higher emissions. A transition of currently degrading areas to fen type vegetation can increase emission by several orders of magnitude, highlighting the importance of quantifying areas at risk.
Thea Hatlen Heimdal, Galen A. McKinley, Adrienne J. Sutton, Amanda R. Fay, and Lucas Gloege
Biogeosciences Discuss., https://doi.org/10.5194/bg-2023-160, https://doi.org/10.5194/bg-2023-160, 2023
Revised manuscript accepted for BG
Short summary
Short summary
Measurements of ocean carbon are limited in time and space. Machine learning algorithms are therefore used to reconstruct ocean carbon where observations do not exist. Improving these reconstructions is important in order to accurately estimate how much carbon the ocean absorbs from the atmosphere. In this study, we find that that a small addition of observations from the Southern Ocean, obtained by autonomous sampling platforms, could significantly improve the reconstructions.
Cole G. Brachmann, Tage Vowles, Riikka Rinnan, Mats P. Björkman, Anna Ekberg, and Robert G. Björk
Biogeosciences, 20, 4069–4086, https://doi.org/10.5194/bg-20-4069-2023, https://doi.org/10.5194/bg-20-4069-2023, 2023
Short summary
Short summary
Herbivores change plant communities through grazing, altering the amount of CO2 and plant-specific chemicals (termed VOCs) emitted. We tested this effect by excluding herbivores and studying the CO2 and VOC emissions. Herbivores reduced CO2 emissions from a meadow community and altered VOC composition; however, community type had the strongest effect on the amount of CO2 and VOCs released. Herbivores can mediate greenhouse gas emissions, but the effect is marginal and community dependent.
Ole Lessmann, Jorge Encinas Fernández, Karla Martínez-Cruz, and Frank Peeters
Biogeosciences, 20, 4057–4068, https://doi.org/10.5194/bg-20-4057-2023, https://doi.org/10.5194/bg-20-4057-2023, 2023
Short summary
Short summary
Based on a large dataset of seasonally resolved methane (CH4) pore water concentrations in a reservoir's sediment, we assess the significance of CH4 emissions due to reservoir flushing. In the studied reservoir, CH4 emissions caused by one flushing operation can represent 7 %–14 % of the annual CH4 emissions and depend on the timing of the flushing operation. In reservoirs with high sediment loadings, regular flushing may substantially contribute to the overall CH4 emissions.
Matti Räsänen, Risto Vesala, Petri Rönnholm, Laura Arppe, Petra Manninen, Markus Jylhä, Jouko Rikkinen, Petri Pellikka, and Janne Rinne
Biogeosciences, 20, 4029–4042, https://doi.org/10.5194/bg-20-4029-2023, https://doi.org/10.5194/bg-20-4029-2023, 2023
Short summary
Short summary
Fungus-growing termites recycle large parts of dead plant material in African savannas and are significant sources of greenhouse gases. We measured CO2 and CH4 fluxes from their mounds and surrounding soils in open and closed habitats. The fluxes scale with mound volume. The results show that emissions from mounds of fungus-growing termites are more stable than those from other termites. The soil fluxes around the mound are affected by the termite colonies at up to 2 m distance from the mound.
Tim René de Groot, Anne Margriet Mol, Katherine Mesdag, Pierre Ramond, Rachel Ndhlovu, Julia Catherine Engelmann, Thomas Röckmann, and Helge Niemann
Biogeosciences, 20, 3857–3872, https://doi.org/10.5194/bg-20-3857-2023, https://doi.org/10.5194/bg-20-3857-2023, 2023
Short summary
Short summary
This study investigates methane dynamics in the Wadden Sea. Our measurements revealed distinct variations triggered by seasonality and tidal forcing. The methane budget was higher in warmer seasons but surprisingly high in colder seasons. Methane dynamics were amplified during low tides, flushing the majority of methane into the North Sea or releasing it to the atmosphere. Methanotrophic activity was also elevated during low tide but mitigated only a small fraction of the methane efflux.
Frederic Thalasso, Brenda Riquelme, Andrés Gómez, Roy Mackenzie, Francisco Javier Aguirre, Jorge Hoyos-Santillan, Ricardo Rozzi, and Armando Sepulveda-Jauregui
Biogeosciences, 20, 3737–3749, https://doi.org/10.5194/bg-20-3737-2023, https://doi.org/10.5194/bg-20-3737-2023, 2023
Short summary
Short summary
A robust skirt-chamber design to capture and quantify greenhouse gas emissions from peatlands is presented. Compared to standard methods, this design improves the spatial resolution of field studies in remote locations while minimizing intrusion.
Gesa Schulz, Tina Sanders, Yoana G. Voynova, Hermann W. Bange, and Kirstin Dähnke
Biogeosciences, 20, 3229–3247, https://doi.org/10.5194/bg-20-3229-2023, https://doi.org/10.5194/bg-20-3229-2023, 2023
Short summary
Short summary
Nitrous oxide (N2O) is an important greenhouse gas. However, N2O emissions from estuaries underlie significant uncertainties due to limited data availability and high spatiotemporal variability. We found the Elbe Estuary (Germany) to be a year-round source of N2O, with the highest emissions in winter along with high nitrogen loads. However, in spring and summer, N2O emissions did not decrease alongside lower nitrogen loads because organic matter fueled in situ N2O production along the estuary.
Alex Mavrovic, Oliver Sonnentag, Juha Lemmetyinen, Jennifer L. Baltzer, Christophe Kinnard, and Alexandre Roy
Biogeosciences, 20, 2941–2970, https://doi.org/10.5194/bg-20-2941-2023, https://doi.org/10.5194/bg-20-2941-2023, 2023
Short summary
Short summary
This review supports the integration of microwave spaceborne information into carbon cycle science for Arctic–boreal regions. The microwave data record spans multiple decades with frequent global observations of soil moisture and temperature, surface freeze–thaw cycles, vegetation water storage, snowpack properties, and land cover. This record holds substantial unexploited potential to better understand carbon cycle processes.
Zoé Rehder, Thomas Kleinen, Lars Kutzbach, Victor Stepanenko, Moritz Langer, and Victor Brovkin
Biogeosciences, 20, 2837–2855, https://doi.org/10.5194/bg-20-2837-2023, https://doi.org/10.5194/bg-20-2837-2023, 2023
Short summary
Short summary
We use a new model to investigate how methane emissions from Arctic ponds change with warming. We find that emissions increase substantially. Under annual temperatures 5 °C above present temperatures, pond methane emissions are more than 3 times higher than now. Most of this increase is caused by an increase in plant productivity as plants provide the substrate microbes used to produce methane. We conclude that vegetation changes need to be included in predictions of pond methane emissions.
Julian Koch, Lars Elsgaard, Mogens H. Greve, Steen Gyldenkærne, Cecilie Hermansen, Gregor Levin, Shubiao Wu, and Simon Stisen
Biogeosciences, 20, 2387–2403, https://doi.org/10.5194/bg-20-2387-2023, https://doi.org/10.5194/bg-20-2387-2023, 2023
Short summary
Short summary
Utilizing peatlands for agriculture leads to large emissions of greenhouse gases worldwide. The emissions are triggered by lowering the water table, which is a necessary step in order to make peatlands arable. Many countries aim at reducing their emissions by restoring peatlands, which can be achieved by stopping agricultural activities and thereby raising the water table. We estimate a total emission of 2.6 Mt CO2-eq for organic-rich peatlands in Denmark and a potential reduction of 77 %.
Mélissa Laurent, Matthias Fuchs, Tanja Herbst, Alexandra Runge, Susanne Liebner, and Claire C. Treat
Biogeosciences, 20, 2049–2064, https://doi.org/10.5194/bg-20-2049-2023, https://doi.org/10.5194/bg-20-2049-2023, 2023
Short summary
Short summary
In this study we investigated the effect of different parameters (temperature, landscape position) on the production of greenhouse gases during a 1-year permafrost thaw experiment. For very similar carbon and nitrogen contents, our results show a strong heterogeneity in CH4 production, as well as in microbial abundance. According to our study, these differences are mainly due to the landscape position and the hydrological conditions established as a result of the topography.
Michael Moubarak, Seeta Sistla, Stefano Potter, Susan M. Natali, and Brendan M. Rogers
Biogeosciences, 20, 1537–1557, https://doi.org/10.5194/bg-20-1537-2023, https://doi.org/10.5194/bg-20-1537-2023, 2023
Short summary
Short summary
Tundra wildfires are increasing in frequency and severity with climate change. We show using a combination of field measurements and computational modeling that tundra wildfires result in a positive feedback to climate change by emitting significant amounts of long-lived greenhouse gasses. With these effects, attention to tundra fires is necessary for mitigating climate change.
Hanna I. Campen, Damian L. Arévalo-Martínez, and Hermann W. Bange
Biogeosciences, 20, 1371–1379, https://doi.org/10.5194/bg-20-1371-2023, https://doi.org/10.5194/bg-20-1371-2023, 2023
Short summary
Short summary
Carbon monoxide (CO) is a climate-relevant trace gas emitted from the ocean. However, oceanic CO cycling is understudied. Results from incubation experiments conducted in the Fram Strait (Arctic Ocean) indicated that (i) pH did not affect CO cycling and (ii) enhanced CO production and consumption were positively correlated with coloured dissolved organic matter and nitrate concentrations. This suggests microbial CO uptake to be the driving factor for CO cycling in the Arctic Ocean.
Yihong Zhu, Ruihua Liu, Huai Zhang, Shaoda Liu, Zhengfeng Zhang, Fei-Hai Yu, and Timothy G. Gregoire
Biogeosciences, 20, 1357–1370, https://doi.org/10.5194/bg-20-1357-2023, https://doi.org/10.5194/bg-20-1357-2023, 2023
Short summary
Short summary
With global warming, the risk of flooding is rising, but the response of the carbon cycle of aquatic and associated riparian systems
to flooding is still unclear. Based on the data collected in the Lijiang, we found that flooding would lead to significant carbon emissions of fluvial areas and riparian areas during flooding, but carbon capture may happen after flooding. In the riparian areas, the surviving vegetation, especially clonal plants, played a vital role in this transformation.
Lauri Heiskanen, Juha-Pekka Tuovinen, Henriikka Vekuri, Aleksi Räsänen, Tarmo Virtanen, Sari Juutinen, Annalea Lohila, Juha Mikola, and Mika Aurela
Biogeosciences, 20, 545–572, https://doi.org/10.5194/bg-20-545-2023, https://doi.org/10.5194/bg-20-545-2023, 2023
Short summary
Short summary
We measured and modelled the CO2 and CH4 fluxes of the terrestrial and aquatic ecosystems of the subarctic landscape for 2 years. The landscape was an annual CO2 sink and a CH4 source. The forest had the largest contribution to the landscape-level CO2 sink and the peatland to the CH4 emissions. The lakes released 24 % of the annual net C uptake of the landscape back to the atmosphere. The C fluxes were affected most by the rainy peak growing season of 2017 and the drought event in July 2018.
Artem G. Lim, Ivan V. Krickov, Sergey N. Vorobyev, Mikhail A. Korets, Sergey Kopysov, Liudmila S. Shirokova, Jan Karlsson, and Oleg S. Pokrovsky
Biogeosciences, 19, 5859–5877, https://doi.org/10.5194/bg-19-5859-2022, https://doi.org/10.5194/bg-19-5859-2022, 2022
Short summary
Short summary
In order to quantify C transport and emission and main environmental factors controlling the C cycle in Siberian rivers, we investigated the largest tributary of the Ob River, the Ket River basin, by measuring spatial and seasonal variations in carbon CO2 and CH4 concentrations and emissions together with hydrochemical analyses. The obtained results are useful for large-scale modeling of C emission and export fluxes from permafrost-free boreal rivers of an underrepresented region of the world.
Robert J. Parker, Chris Wilson, Edward Comyn-Platt, Garry Hayman, Toby R. Marthews, A. Anthony Bloom, Mark F. Lunt, Nicola Gedney, Simon J. Dadson, Joe McNorton, Neil Humpage, Hartmut Boesch, Martyn P. Chipperfield, Paul I. Palmer, and Dai Yamazaki
Biogeosciences, 19, 5779–5805, https://doi.org/10.5194/bg-19-5779-2022, https://doi.org/10.5194/bg-19-5779-2022, 2022
Short summary
Short summary
Wetlands are the largest natural source of methane, one of the most important climate gases. The JULES land surface model simulates these emissions. We use satellite data to evaluate how well JULES reproduces the methane seasonal cycle over different tropical wetlands. It performs well for most regions; however, it struggles for some African wetlands influenced heavily by river flooding. We explain the reasons for these deficiencies and highlight how future development will improve these areas.
Saúl Edgardo Martínez Castellón, José Henrique Cattanio, José Francisco Berrêdo, Marcelo Rollnic, Maria de Lourdes Ruivo, and Carlos Noriega
Biogeosciences, 19, 5483–5497, https://doi.org/10.5194/bg-19-5483-2022, https://doi.org/10.5194/bg-19-5483-2022, 2022
Short summary
Short summary
We seek to understand the influence of climatic seasonality and microtopography on CO2 and CH4 fluxes in an Amazonian mangrove. Topography and seasonality had a contrasting influence when comparing the two gas fluxes: CO2 fluxes were greater in high topography in the dry period, and CH4 fluxes were greater in the rainy season in low topography. Only CO2 fluxes were correlated with soil organic matter, the proportion of carbon and nitrogen, and redox potential.
Matthias Koschorreck, Klaus Holger Knorr, and Lelaina Teichert
Biogeosciences, 19, 5221–5236, https://doi.org/10.5194/bg-19-5221-2022, https://doi.org/10.5194/bg-19-5221-2022, 2022
Short summary
Short summary
At low water levels, parts of the bottom of rivers fall dry. These beaches or mudflats emit the greenhouse gas carbon dioxide (CO2) to the atmosphere. We found that those emissions are caused by microbial reactions in the sediment and that they change with time. Emissions were influenced by many factors like temperature, water level, rain, plants, and light.
Wantong Zhang, Zhengyi Hu, Joachim Audet, Thomas A. Davidson, Enze Kang, Xiaoming Kang, Yong Li, Xiaodong Zhang, and Jinzhi Wang
Biogeosciences, 19, 5187–5197, https://doi.org/10.5194/bg-19-5187-2022, https://doi.org/10.5194/bg-19-5187-2022, 2022
Short summary
Short summary
This work focused on the CH4 and N2O emissions from alpine peatlands in response to the interactive effects of altered water table levels and increased nitrogen deposition. Across the 2-year mesocosm experiment, nitrogen deposition showed nonlinear effects on CH4 emissions and linear effects on N2O emissions, and these N effects were associated with the water table levels. Our results imply the future scenario of strengthened CH4 and N2O emissions from an alpine peatland.
Karel Castro-Morales, Anna Canning, Sophie Arzberger, Will A. Overholt, Kirsten Küsel, Olaf Kolle, Mathias Göckede, Nikita Zimov, and Arne Körtzinger
Biogeosciences, 19, 5059–5077, https://doi.org/10.5194/bg-19-5059-2022, https://doi.org/10.5194/bg-19-5059-2022, 2022
Short summary
Short summary
Permafrost thaw releases methane that can be emitted into the atmosphere or transported by Arctic rivers. Methane measurements are lacking in large Arctic river regions. In the Kolyma River (northeast Siberia), we measured dissolved methane to map its distribution with great spatial detail. The river’s edge and river junctions had the highest methane concentrations compared to other river areas. Microbial communities in the river showed that the river’s methane likely is from the adjacent land.
Sonja Gindorf, Hermann W. Bange, Dennis Booge, and Annette Kock
Biogeosciences, 19, 4993–5006, https://doi.org/10.5194/bg-19-4993-2022, https://doi.org/10.5194/bg-19-4993-2022, 2022
Short summary
Short summary
Methane is a climate-relevant greenhouse gas which is emitted to the atmosphere from coastal areas such as the Baltic Sea. We measured the methane concentration in the water column of the western Kiel Bight. Methane concentrations were higher in September than in June. We found no relationship between the 2018 European heatwave and methane concentrations. Our results show that the methane distribution in the water column is strongly affected by temporal and spatial variabilities.
Margaret Capooci and Rodrigo Vargas
Biogeosciences, 19, 4655–4670, https://doi.org/10.5194/bg-19-4655-2022, https://doi.org/10.5194/bg-19-4655-2022, 2022
Short summary
Short summary
Tidal salt marsh soil emits greenhouse gases, as well as sulfur-based gases, which play roles in global climate but are not well studied as they are difficult to measure. Traditional methods of measuring these gases worked relatively well for carbon dioxide, but less so for methane, nitrous oxide, carbon disulfide, and dimethylsulfide. High variability of trace gases complicates the ability to accurately calculate gas budgets and new approaches are needed for monitoring protocols.
Janne Rinne, Patryk Łakomiec, Patrik Vestin, Joel D. White, Per Weslien, Julia Kelly, Natascha Kljun, Lena Ström, and Leif Klemedtsson
Biogeosciences, 19, 4331–4349, https://doi.org/10.5194/bg-19-4331-2022, https://doi.org/10.5194/bg-19-4331-2022, 2022
Short summary
Short summary
The study uses the stable isotope 13C of carbon in methane to investigate the origins of spatial and temporal variation in methane emitted by a temperate wetland ecosystem. The results indicate that methane production is more important for spatial variation than methane consumption by micro-organisms. Temporal variation on a seasonal timescale is most likely affected by more than one driver simultaneously.
Kukka-Maaria Kohonen, Roderick Dewar, Gianluca Tramontana, Aleksanteri Mauranen, Pasi Kolari, Linda M. J. Kooijmans, Dario Papale, Timo Vesala, and Ivan Mammarella
Biogeosciences, 19, 4067–4088, https://doi.org/10.5194/bg-19-4067-2022, https://doi.org/10.5194/bg-19-4067-2022, 2022
Short summary
Short summary
Four different methods for quantifying photosynthesis (GPP) at ecosystem scale were tested, of which two are based on carbon dioxide (CO2) and two on carbonyl sulfide (COS) flux measurements. CO2-based methods are traditional partitioning, and a new method uses machine learning. We introduce a novel method for calculating GPP from COS fluxes, with potentially better applicability than the former methods. Both COS-based methods gave on average higher GPP estimates than the CO2-based estimates.
Lutz Beckebanze, Benjamin R. K. Runkle, Josefine Walz, Christian Wille, David Holl, Manuel Helbig, Julia Boike, Torsten Sachs, and Lars Kutzbach
Biogeosciences, 19, 3863–3876, https://doi.org/10.5194/bg-19-3863-2022, https://doi.org/10.5194/bg-19-3863-2022, 2022
Short summary
Short summary
In this study, we present observations of lateral and vertical carbon fluxes from a permafrost-affected study site in the Russian Arctic. From this dataset we estimate the net ecosystem carbon balance for this study site. We show that lateral carbon export has a low impact on the net ecosystem carbon balance during the complete study period (3 months). Nevertheless, our results also show that lateral carbon export can exceed vertical carbon uptake at the beginning of the growing season.
Shahar Baram, Asher Bar-Tal, Alon Gal, Shmulik P. Friedman, and David Russo
Biogeosciences, 19, 3699–3711, https://doi.org/10.5194/bg-19-3699-2022, https://doi.org/10.5194/bg-19-3699-2022, 2022
Short summary
Short summary
Static chambers are the most common tool used to measure greenhouse gas (GHG) fluxes. We tested the impact of such chambers on nitrous oxide emissions in drip irrigation. Field measurements and 3-D simulations show that the chamber base drastically affects the water and nutrient distribution in the soil and hence the measured GHG fluxes. A nomogram is suggested to determine the optimal diameter of a cylindrical chamber that ensures minimal disturbance.
Tracy E. Rankin, Nigel T. Roulet, and Tim R. Moore
Biogeosciences, 19, 3285–3303, https://doi.org/10.5194/bg-19-3285-2022, https://doi.org/10.5194/bg-19-3285-2022, 2022
Short summary
Short summary
Peatland respiration is made up of plant and peat sources. How to separate these sources is not well known as peat respiration is not straightforward and is more influenced by vegetation dynamics than previously thought. Results of plot level measurements from shrubs and sparse grasses in a woody bog show that plants' respiration response to changes in climate is related to their different root structures, implying a difference in the mechanisms by which they obtain water resources.
Alison Bressler and Jennifer Blesh
Biogeosciences, 19, 3169–3184, https://doi.org/10.5194/bg-19-3169-2022, https://doi.org/10.5194/bg-19-3169-2022, 2022
Short summary
Short summary
Our field experiment tested if a mixture of a nitrogen-fixing legume and non-legume cover crop could reduce nitrous oxide (N2O) emissions following tillage, compared to the legume grown alone. We found higher N2O following both legume treatments, compared to those without, and lower emissions from the cover crop mixture at one of the two test sites, suggesting that interactions between cover crop types and soil quality influence N2O emissions.
Sari Juutinen, Mika Aurela, Juha-Pekka Tuovinen, Viktor Ivakhov, Maiju Linkosalmi, Aleksi Räsänen, Tarmo Virtanen, Juha Mikola, Johanna Nyman, Emmi Vähä, Marina Loskutova, Alexander Makshtas, and Tuomas Laurila
Biogeosciences, 19, 3151–3167, https://doi.org/10.5194/bg-19-3151-2022, https://doi.org/10.5194/bg-19-3151-2022, 2022
Short summary
Short summary
We measured CO2 and CH4 fluxes in heterogenous Arctic tundra in eastern Siberia. We found that tundra wetlands with sedge and grass vegetation contributed disproportionately to the landscape's ecosystem CO2 uptake and CH4 emissions to the atmosphere. Moreover, we observed high CH4 consumption in dry tundra, particularly in barren areas, offsetting part of the CH4 emissions from the wetlands.
Jessica Plein, Rulon W. Clark, Kyle A. Arndt, Walter C. Oechel, Douglas Stow, and Donatella Zona
Biogeosciences, 19, 2779–2794, https://doi.org/10.5194/bg-19-2779-2022, https://doi.org/10.5194/bg-19-2779-2022, 2022
Short summary
Short summary
Tundra vegetation and the carbon balance of Arctic ecosystems can be substantially impacted by herbivory. We tested how herbivory by brown lemmings in individual enclosure plots have impacted carbon exchange of tundra ecosystems via altering carbon dioxide (CO2) and methane (CH4) fluxes. Lemmings significantly decreased net CO2 uptake while not affecting CH4 emissions. There was no significant difference in the subsequent growing season due to recovery of the vegetation.
Jenie Gil, Maija E. Marushchak, Tobias Rütting, Elizabeth M. Baggs, Tibisay Pérez, Alexander Novakovskiy, Tatiana Trubnikova, Dmitry Kaverin, Pertti J. Martikainen, and Christina Biasi
Biogeosciences, 19, 2683–2698, https://doi.org/10.5194/bg-19-2683-2022, https://doi.org/10.5194/bg-19-2683-2022, 2022
Short summary
Short summary
N2O emissions from permafrost soils represent up to 11.6 % of total N2O emissions from natural soils, and their contribution to the global N2O budget will likely increase due to climate change. A better understanding of N2O production from permafrost soil is needed to evaluate the role of arctic ecosystems in the global N2O budget. By studying microbial N2O production processes in N2O hotspots in permafrost peatlands, we identified denitrification as the dominant source of N2O in these surfaces.
Christian Rödenbeck, Tim DeVries, Judith Hauck, Corinne Le Quéré, and Ralph F. Keeling
Biogeosciences, 19, 2627–2652, https://doi.org/10.5194/bg-19-2627-2022, https://doi.org/10.5194/bg-19-2627-2022, 2022
Short summary
Short summary
The ocean is an important part of the global carbon cycle, taking up about a quarter of the anthropogenic CO2 emitted by burning of fossil fuels and thus slowing down climate change. However, the CO2 uptake by the ocean is, in turn, affected by variability and trends in climate. Here we use carbon measurements in the surface ocean to quantify the response of the oceanic CO2 exchange to environmental conditions and discuss possible mechanisms underlying this response.
Shuang Ma, Lifen Jiang, Rachel M. Wilson, Jeff P. Chanton, Scott Bridgham, Shuli Niu, Colleen M. Iversen, Avni Malhotra, Jiang Jiang, Xingjie Lu, Yuanyuan Huang, Jason Keller, Xiaofeng Xu, Daniel M. Ricciuto, Paul J. Hanson, and Yiqi Luo
Biogeosciences, 19, 2245–2262, https://doi.org/10.5194/bg-19-2245-2022, https://doi.org/10.5194/bg-19-2245-2022, 2022
Short summary
Short summary
The relative ratio of wetland methane (CH4) emission pathways determines how much CH4 is oxidized before leaving the soil. We found an ebullition modeling approach that has a better performance in deep layer pore water CH4 concentration. We suggest using this approach in land surface models to accurately represent CH4 emission dynamics and response to climate change. Our results also highlight that both CH4 flux and belowground concentration data are important to constrain model parameters.
Mika Korkiakoski, Tiia Määttä, Krista Peltoniemi, Timo Penttilä, and Annalea Lohila
Biogeosciences, 19, 2025–2041, https://doi.org/10.5194/bg-19-2025-2022, https://doi.org/10.5194/bg-19-2025-2022, 2022
Short summary
Short summary
We measured CH4 fluxes and production and oxidation potentials from irrigated and non-irrigated podzolic soil in a boreal forest. CH4 sink was smaller at the irrigated site but did not cause CH4 emission, with one exception. We also showed that under laboratory conditions, not only wet conditions, but also fresh carbon, are needed to make podzolic soil into a CH4 source. Our study provides important data for improving the process models describing the upland soil CH4 dynamics.
Sarah Shakil, Suzanne E. Tank, Jorien E. Vonk, and Scott Zolkos
Biogeosciences, 19, 1871–1890, https://doi.org/10.5194/bg-19-1871-2022, https://doi.org/10.5194/bg-19-1871-2022, 2022
Short summary
Short summary
Permafrost thaw-driven landslides in the western Arctic are increasing organic carbon delivered to headwaters of drainage networks in the western Canadian Arctic by orders of magnitude. Through a series of laboratory experiments, we show that less than 10 % of this organic carbon is likely to be mineralized to greenhouse gases during transport in these networks. Rather most of the organic carbon is likely destined for burial and sequestration for centuries to millennia.
Cited articles
Adachi, Y., Yukimoto, S., Deushi, M., Obata, A., Nakano, H., Tanaka, T. Y.,
Hosaka, M., Sakami, T., Yoshimura, H., Hirabara, M., Shindo, E., Tsujino,
H., Mizuta, R., Yabu, S., Koshiro, T., Ose, T., and Kitoh, A.: Basic
performance of a new earth system model of the Meteorological Research
Institute (MRI-ESM1), Pap. Meteorol. Geophys., 64, 1–19,
https://doi.org/10.2467/mripapers.64.1, 2013.
Anav, A., Friedlingstein, P., Kidston, M., Bopp, L., Ciais, P., Cox, P.,
Jones, C., Jung, M., Myneni, R., and Zhu, Z.: Evaluating the Land and Ocean
Components of the Global Carbon Cycle in the CMIP5 Earth System Models, J.
Climate, 26, 6801–6843, https://doi.org/10.1175/Jcli-D-12-00417.1, 2013.
Andela, B., Broetz, B., de Mora, L., Drost, N., Eyring, V., Koldunov, N., Lauer, A., Predoi, V., Righi, M., Schlund, M., Vegas-Regidor, J., Zimmermann, K., Bock, L., Diblen, F., Dreyer, L., Earnshaw, P., Hassler, B., Little, B., Loosveldt-Tomas, S., Smeets, S., Camphuijsen, J., Gier, B.K., Weigel, K., Hauser, M., Kalverla, P., Galytska, E., Cos-Espuña, P., Pelupessy, I., Koirala, S., Stacke, T., Alidoost, S., and Jury, M.: ESMValCore, https://doi.org/10.5281/zenodo.3387139, 2020b.
Arora, V. K., Scinocca, J. F., Boer, G. J., Christian, J. R., Denman, K. L.,
Flato, G. M., Kharin, V. V., Lee, W. G., and Merryfield, W. J.: Carbon
emission limits required to satisfy future representative concentration
pathways of greenhouse gases, Geophys. Res. Lett., 38, L05805,
https://doi.org/10.1029/2010gl046270, 2011.
Arora, V. K., Boer, G. J., Friedlingstein, P., Eby, M., Jones, C. D.,
Christian, J. R., Bonan, G., Bopp, L., Brovkin, V., Cadule, P., Hajima, T.,
Ilyina, T., Lindsay, K., Tjiputra, J. F., and Wu, T.: Carbon-Concentration
and Carbon-Climate Feedbacks in CMIP5 Earth System Models, J. Climate, 26,
5289–5314, https://doi.org/10.1175/Jcli-D-12-00494.1, 2013.
Arora, V. K., Katavouta, A., Williams, R. G., Jones, C. D., Brovkin, V., Friedlingstein, P., Schwinger, J., Bopp, L., Boucher, O., Cadule, P., Chamberlain, M. A., Christian, J. R., Delire, C., Fisher, R. A., Hajima, T., Ilyina, T., Joetzjer, E., Kawamiya, M., Koven, C. D., Krasting, J. P., Law, R. M., Lawrence, D. M., Lenton, A., Lindsay, K., Pongratz, J., Raddatz, T., Séférian, R., Tachiiri, K., Tjiputra, J. F., Wiltshire, A., Wu, T., and Ziehn, T.: Carbon–concentration and carbon–climate feedbacks in CMIP6 models and their comparison to CMIP5 models, Biogeosciences, 17, 4173–4222, https://doi.org/10.5194/bg-17-4173-2020, 2020.
Bao, Y., Qiao, F., and Song, Z.: The historical global carbon cycle simulation of FIO-ESM, Geo-phys. Res. Abstr., EGU2012-6834, EGU General Assembly 2012, Vienna, Austria, 2012.
Barnes, E. A., Parazoo, N., Orbe, C., and Denning, A. S.: Isentropic
transport and the seasonal cycle amplitude of CO2, J. Geophys. Res.-Atmos., 121,
8106–8124, https://doi.org/10.1002/2016jd025109, 2016.
Bastos, A., Ciais, P., Chevallier, F., Rödenbeck, C., Ballantyne, A. P., Maignan, F., Yin, Y., Fernández-Martínez, M., Friedlingstein, P., Peñuelas, J., Piao, S. L., Sitch, S., Smith, W. K., Wang, X., Zhu, Z., Haverd, V., Kato, E., Jain, A. K., Lienert, S., Lombardozzi, D., Nabel, J. E. M. S., Peylin, P., Poulter, B., and Zhu, D.: Contrasting effects of CO2 fertilization, land-use change and warming on seasonal amplitude of Northern Hemisphere CO2 exchange, Atmos. Chem. Phys., 19, 12361–12375, https://doi.org/10.5194/acp-19-12361-2019, 2019.
Basu, S., Guerlet, S., Butz, A., Houweling, S., Hasekamp, O., Aben, I., Krummel, P., Steele, P., Langenfelds, R., Torn, M., Biraud, S., Stephens, B., Andrews, A., and Worthy, D.: Global CO2 fluxes estimated from GOSAT retrievals of total column CO2, Atmos. Chem. Phys., 13, 8695–8717, https://doi.org/10.5194/acp-13-8695-2013, 2013.
Bovensmann, H., Burrows, J. P., Buchwitz, M., Frerick, J., Noel, S.,
Rozanov, V. V., Chance, K. V., and Goede, A. P. H.: SCIAMACHY: Mission
objectives and measurement modes, J. Atmos. Sci., 56, 127–150, https://doi.org/10.1175/1520-0469(1999)056<0127:Smoamm>2.0.Co;2, 1999.
Bronselaer, B., Winton, M., Russell, J., Sabine, C. L., and Khatiwala, S.:
Agreement of CMIP5 Simulated and Observed Ocean Anthropogenic CO2 Uptake,
Geophys. Res. Lett., 44, 298–305, https://doi.org/10.1002/2017gl074435, 2017.
Buchwitz, M. and Reuter, M.: Merged SCIAMACHY/ENVISAT and TANSO-FTS/GOSAT atmospheric column-average dry-air mole fraction of CO2 (XCO2 ) (XCO2_CRDP3_001) – Technical Document, 2016, available at: http://134.102.186.42/?q=webfm_send/330, last access: 30 November 2020.
Buchwitz, M., Reuter, M., Schneising-Weigel, O., Aben, I., Detmers, R. G.,
Hasekamp, O. P., Boesch, H., Anand, J., Crevoisier, C., and Armante, R.:
Product User Guide and Specification (PUGS) – Main document, Technical
Report Copernicus Climate Change Service (C3S), Reading, UK, 91 pp., 2017a.
Buchwitz, M., Reuter, M., Schneising-Weigel, O., Aben, I., Detmers, R. G.,
Hasekamp, O. P., Boesch, H., Anand, J., Crevoisier, C., and Armante, R.:
Product Quality Assessment Report (PQAR) – Main document, Technical Report
Copernicus Climate Change Service (C3S), Reading, UK, 103 pp., 2017b.
Buchwitz, M., Reuter, M., Schneising, O., Noël, S., Gier, B., Bovensmann, H., Burrows, J. P., Boesch, H., Anand, J., Parker, R. J., Somkuti, P., Detmers, R. G., Hasekamp, O. P., Aben, I., Butz, A., Kuze, A., Suto, H., Yoshida, Y., Crisp, D., and O'Dell, C.: Computation and analysis of atmospheric carbon dioxide annual mean growth rates from satellite observations during 2003–2016, Atmos. Chem. Phys., 18, 17355–17370, https://doi.org/10.5194/acp-18-17355-2018, 2018.
Burrows, J. P., Holzle, E., Goede, A. P. H., Visser, H., and Fricke, W.:
Sciamachy – Scanning Imaging Absorption Spectrometer for Atmospheric
Chartography, Acta Astronaut., 35, 445–451, https://doi.org/10.1016/0094-5765(94)00278-T,
1995.
Calle, L., Poulter, B., and Patra, P. K.: A segmentation algorithm for characterizing rise and fall segments in seasonal cycles: an application to XCO2 to estimate benchmarks and assess model bias, Atmos. Meas. Tech., 12, 2611–2629, https://doi.org/10.5194/amt-12-2611-2019, 2019.
Chevallier, F., Palmer, P. I., Feng, L., Boesch, H., O'Dell, C. W., and
Bousquet, P.: Toward robust and consistent regional CO2 flux estimates from
in situ and spaceborne measurements of atmospheric CO2, Geophys. Res. Lett.,
41, 1065–1070, https://doi.org/10.1002/2013gl058772, 2014.
Ciais, P., Sabine, C., Bala, G., Bopp, L., Brovkin, V., Canadell, J.,
Chhabra, A., DeFries, R., Galloway, J., Heimann, M., Jones, C., Le Quéré,
C., Myneni, R. B., Piao, S., and Thornton, P.: Carbon and Other
Biogeochemical Cycles, 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. F., Qin, D., Plattner, G.-K., Tignor, M., Allen, S. K., Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley, P. M., Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 465–570,
https://doi.org/10.1017/CBO9781107415324.015, 2013.
Cox, P. M., Pearson, D., Booth, B. B., Friedlingstein, P., Huntingford, C.,
Jones, C. D., and Luke, C. M.: Sensitivity of tropical carbon to climate
change constrained by carbon dioxide variability, Nature, 494, 341–344,
https://doi.org/10.1038/nature11882, 2013.
Dlugokencky, E. J., Lang, P. M., Mund, J. W., Crotwell, A. M., Crotwell, M.
J., and Thoning, K. W.: Atmospheric Carbon Dioxide Dry Air Mole Fractions
from the NOAA ESRL Carbon Cycle Cooperative Global Air Sampling Network,
available at: ftp://aftp.cmdl.noaa.gov/data/trace_gases/co2/flask/surface/ (last access: 31 July 2018), 2018.
Dlugokencky, E. J., Mund, J. W., Crotwell, A. M., Crotwell, M. J., and
Thoning, K. W.: Atmospheric Carbon Dioxide Dry Air Mole Fractions from the
NOAA GML Carbon Cycle Cooperative Global Air Sampling Network, 1968–2019, 2020.
Dunne, J. P., John, J. G., Adcroft, A. J., Griffies, S. M., Hallberg, R. W.,
Shevliakova, E., Stouffer, R. J., Cooke, W., Dunne, K. A., Harrison, M. J.,
Krasting, J. P., Malyshev, S. L., Milly, P. C. D., Phillipps, P. J.,
Sentman, L. T., Samuels, B. L., Spelman, M. J., Winton, M., Wittenberg, A.
T., and Zadeh, N.: GFDL's ESM2 Global Coupled Climate-Carbon Earth System
Models. Part I: Physical Formulation and Baseline Simulation
Characteristics, J. Climate, 25, 6646–6665, https://doi.org/10.1175/Jcli-D-11-00560.1, 2012.
Dunne, J. P., John, J. G., Shevliakova, E., Stouffer, R. J., Krasting, J.
P., Malyshev, S. L., Milly, P. C. D., Sentman, L. T., Adcroft, A. J., Cooke,
W., Dunne, K. A., Griffies, S. M., Hallberg, R. W., Harrison, M. J., Levy,
H., Wittenberg, A. T., Phillips, P. J., and Zadeh, N.: GFDL's ESM2 Global
Coupled Climate-Carbon Earth System Models. Part II: Carbon System
Formulation and Baseline Simulation Characteristics, J. Climate, 26,
2247–2267, https://doi.org/10.1175/Jcli-D-12-00150.1, 2013.
Dunne, J. P., Horowitz, L. W., Adcroft, A. J., Ginoux, P., Held, I. M.,
John, J. G., Krasting, J. P., Malyshev, S., Naik, V., Paulot, F.,
Shevliakova, E., Stock, C. A., Zadeh, N., Balaji, V., Blanton, C., Dunne, K.
A., Dupuis, C., Durachta, J., Dussin, R., Gauthier, P. P. G., Griffies, S.
M., Guo, H., Hallberg, R. W., Harrison, M., He, J., Hurlin, W., McHugh, C.,
Menzel, R., Milly, P. C. D., Nikonov, S., Paynter, D. J., Ploshay, J.,
Radhakrishnan, A., Rand, K., Reichl, B. G., Robinson, T., Schwarzkopf, D.
M., Sentman, L. T., Underwood, S., Vahlenkamp, H., Winton, M., Wittenberg,
A. T., Wyman, B., Zeng, Y., and Zhao, M.: The GFDL Earth System Model
version 4.1 (GFDL-ESM 4.1): Overall coupled model description and simulation
characteristics, J. Adv. Model. Earth. Sy., 12, e2019MS002015,
https://doi.org/10.1029/2019ms002015, 2020.
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, 2016a.
Eyring, V., Righi, M., Lauer, A., Evaldsson, M., Wenzel, S., Jones, C., Anav, A., Andrews, O., Cionni, I., Davin, E. L., Deser, C., Ehbrecht, C., Friedlingstein, P., Gleckler, P., Gottschaldt, K.-D., Hagemann, S., Juckes, M., Kindermann, S., Krasting, J., Kunert, D., Levine, R., Loew, A., Mäkelä, J., Martin, G., Mason, E., Phillips, A. S., Read, S., Rio, C., Roehrig, R., Senftleben, D., Sterl, A., van Ulft, L. H., Walton, J., Wang, S., and Williams, K. D.: ESMValTool (v1.0) – a community diagnostic and performance metrics tool for routine evaluation of Earth system models in CMIP, Geosci. Model Dev., 9, 1747–1802, https://doi.org/10.5194/gmd-9-1747-2016, 2016b.
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.
Eyring, V., Bock, L., Lauer, A., Righi, M., Schlund, M., Andela, B., Arnone, E., Bellprat, O., Brötz, B., Caron, L.-P., Carvalhais, N., Cionni, I., Cortesi, N., Crezee, B., Davin, E. L., Davini, P., Debeire, K., de Mora, L., Deser, C., Docquier, D., Earnshaw, P., Ehbrecht, C., Gier, B. K., Gonzalez-Reviriego, N., Goodman, P., Hagemann, S., Hardiman, S., Hassler, B., Hunter, A., Kadow, C., Kindermann, S., Koirala, S., Koldunov, N., Lejeune, Q., Lembo, V., Lovato, T., Lucarini, V., Massonnet, F., Müller, B., Pandde, A., Pérez-Zanón, N., Phillips, A., Predoi, V., Russell, J., Sellar, A., Serva, F., Stacke, T., Swaminathan, R., Torralba, V., Vegas-Regidor, J., von Hardenberg, J., Weigel, K., and Zimmermann, K.: Earth System Model Evaluation Tool (ESMValTool) v2.0 – an extended set of large-scale diagnostics for quasi-operational and comprehensive evaluation of Earth system models in CMIP, Geosci. Model Dev., 13, 3383–3438, https://doi.org/10.5194/gmd-13-3383-2020, 2020.
Fernández-Martínez, M., Sardans, J., Chevallier, F., Ciais, P.,
Obersteiner, M., Vicca, S., Canadell, J. G., Bastos, A., Friedlingstein, P.,
Sitch, S., Piao, S. L., Janssens, I. A., and Peñuelas, J.: Global trends
in carbon sinks and their relationships with CO2 and temperature, Nat. Clim, Change, 9, 73—9, https://doi.org/10.1038/s41558-018-0367-7, 2019.
Ferraro, R., Waliser, D. E., Gleckler, P., Taylor, K. E., and Eyring, V.:
Evolving Obs4MIPs to Support Phase 6 of the Coupled Model Intercomparison
Project (CMIP6), B. Am. Meteorol. Soc., 96,
131–133, https://doi.org/10.1175/bams-d-14-00216.1, 2015.
Friedl, M. A., Sulla-Menashe, D., Tan, B., Schneider, A., Ramankutty, N.,
Sibley, A., and Huang, X. M.: MODIS Collection 5 global land cover:
Algorithm refinements and characterization of new datasets, Remote Sens.
Environ., 114, 168–182, https://doi.org/10.1016/j.rse.2009.08.016, 2010a.
Friedl, M. A., Strahler, A. H., Hodges, J., Hall, F. G., Collatz, G. J., Meeson, B. W., Los, S. O., Brown De Colstoun, E., and Landis, D. R.: ISLSCP II MODIS (Collection 4) IGBP Land Cover, 2000–2001, ORNL DAAC, Oak Ridge, Tennessee, USA, https://doi.org/doi.org/10.3334/ORNLDAAC/968 (last access: 3 January 2018), 2010b.
Friedlingstein, P., Cox, P., Betts, R., Bopp, L., von Bloh, W., Brovkin, V.,
Cadule, P., Doney, S., Eby, M., Fung, I., Bala, G., John, J., Jones, C.,
Joos, F., Kato, T., Kawamiya, M., Knorr, W., Lindsay, K., Matthews, H. D.,
Raddatz, T., Rayner, P., Reick, C., Roeckner, E., Schnitzler, K. G., Schnur,
R., Strassmann, K., Weaver, A. J., Yoshikawa, C., and Zeng, N.:
Climate-Carbon Cycle Feedback Analysis: Results from the C4MIP Model
Intercomparison, J. Climate, 19, 3337–3353, https://doi.org/10.1175/jcli3800.1, 2006.
Friedlingstein, P., Meinshausen, M., Arora, V. K., Jones, C. D., Anav, A.,
Liddicoat, S. K., and Knutti, R.: Uncertainties in CMIP5 Climate Projections
due to Carbon Cycle Feedbacks, J. Climate, 27, 511–526,
https://doi.org/10.1175/Jcli-D-12-00579.1, 2014.
Gent, P. R., Danabasoglu, G., Donner, L. J., Holland, M. M., Hunke, E. C.,
Jayne, S. R., Lawrence, D. M., Neale, R. B., Rasch, P. J., Vertenstein, M.,
Worley, P. H., Yang, Z. L., and Zhang, M. H.: The Community Climate System
Model Version 4, J. Climate, 24, 4973–4991, https://doi.org/10.1175/2011jcli4083.1, 2011.
GISTEMP Team: GISS Surface Temperature Analysis (GISTEMP), version 4, NASA Goddard Institute for Space Studies, available at: https://data.giss.nasa.gov/gistemp/, last access: 13 February 2020.
Giorgetta, M. A., Jungclaus, J., Reick, C. H., Legutke, S., Bader, J.,
Bottinger, M., Brovkin, V., Crueger, T., Esch, M., Fieg, K., Glushak, K.,
Gayler, V., Haak, H., Hollweg, H. D., Ilyina, T., Kinne, S., Kornblueh, L.,
Matei, D., Mauritsen, T., Mikolajewicz, U., Mueller, W., Notz, D., Pithan,
F., Raddatz, T., Rast, S., Redler, R., Roeckner, E., Schmidt, H., Schnur,
R., Segschneider, J., Six, K. D., Stockhause, M., Timmreck, C., Wegner, J.,
Widmann, H., Wieners, K. H., Claussen, M., Marotzke, J., and Stevens, B.:
Climate and carbon cycle changes from 1850 to 2100 in MPI-ESM simulations
for the Coupled Model Intercomparison Project phase 5, J. Adv. Model. Earth Sy.,
5, 572–597, https://doi.org/10.1002/jame.20038, 2013.
Graven, H. D., Keeling, R. F., Piper, S. C., Patra, P. K., Stephens, B. B.,
Wofsy, S. C., Welp, L. R., Sweeney, C., Tans, P. P., Kelley, J. J., Daube,
B. C., Kort, E. A., Santoni, G. W., and Bent, J. D.: Enhanced seasonal
exchange of CO2 by northern ecosystems since 1960, Science, 341, 1085–1089,
https://doi.org/10.1126/science.1239207, 2013.
Hajima, T., Tachiiri, K., Ito, A., and Kawamiya, M.: Uncertainty of
Concentration-Terrestrial Carbon Feedback in Earth System Models, J. Climate,
27, 3425–3445, https://doi.org/10.1175/Jcli-D-13-00177.1, 2014.
Hajima, T., Abe, M., Arakawa, O., Suzuki, T., Komuro, Y., Ogochi, K.,
Watanabe, M., Yamamoto, A., Tatebe, H., Noguchi, M. A., Ohgaito, R., Ito,
A., Yamazaki, D., Ito, A., Takata, K., Watanabe, S., Kawamiya, M., and
Tachiiri, K.: MIROC MIROC-ES2L model output prepared for CMIP6 CMIP esm-hist
v20200318, Earth System Grid Federation, https://doi.org/10.22033/ESGF/CMIP6.5496, 2020a.
Hajima, T., Watanabe, M., Yamamoto, A., Tatebe, H., Noguchi, M. A., Abe, M., Ohgaito, R., Ito, A., Yamazaki, D., Okajima, H., Ito, A., Takata, K., Ogochi, K., Watanabe, S., and Kawamiya, M.: Development of the MIROC-ES2L Earth system model and the evaluation of biogeochemical processes and feedbacks, Geosci. Model Dev., 13, 2197–2244, https://doi.org/10.5194/gmd-13-2197-2020, 2020b.
Hansen, J., Ruedy, R., Sato, M., and Lo, K.: Global Surface Temperature
Change, Rev. Geophys., 48, 4004, https://doi.org/10.1029/2010rg000345, 2010.
Hayman, G. D., O'Connor, F. M., Dalvi, M., Clark, D. B., Gedney, N., Huntingford, C., Prigent, C., Buchwitz, M., Schneising, O., Burrows, J. P., Wilson, C., Richards, N., and Chipperfield, M.: Comparison of the HadGEM2 climate-chemistry model against in situ and SCIAMACHY atmospheric methane data, Atmos. Chem. Phys., 14, 13257–13280, https://doi.org/10.5194/acp-14-13257-2014, 2014.
Hoffman, F. M., Randerson, J. T., Arora, V. K., Bao, Q., Cadule, P., Ji, D.,
Jones, C. D., Kawamiya, M., Khatiwala, S., Lindsay, K., Obata, A.,
Shevliakova, E., Six, K. D., Tjiputra, J. F., Volodin, E. M., and Wu, T.:
Causes and implications of persistent atmospheric carbon dioxide biases in
Earth System Models, J. Geophys. Res.-Biogeo., 119, 141–162,
https://doi.org/10.1002/2013jg002381, 2014.
Houweling, S., Baker, D., Basu, S., Boesch, H., Butz, A., Chevallier, F.,
Deng, F., Dlugokencky, E. J., Feng, L., Ganshin, A., Hasekamp, O., Jones,
D., Maksyutov, S., Marshall, J., Oda, T., O'Dell, C. W., Oshchepkov, S.,
Palmer, P. I., Peylin, P., Poussi, Z., Reum, F., Takagi, H., Yoshida, Y.,
and Zhuravlev, R.: An intercomparison of inverse models for estimating
sources and sinks of CO2 using GOSAT measurements, J. Geophys.
Res.-Atmos., 120, 5253–5266, https://doi.org/10.1002/2014jd022962, 2015.
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, UK,
https://doi.org/10.1017/CBO9781107415324, 2013.
Ji, D., Wang, L., Feng, J., Wu, Q., Cheng, H., Zhang, Q., Yang, J., Dong, W., Dai, Y., Gong, D., Zhang, R.-H., Wang, X., Liu, J., Moore, J. C., Chen, D., and Zhou, M.: Description and basic evaluation of Beijing Normal University Earth System Model (BNU-ESM) version 1, Geosci. Model Dev., 7, 2039–2064, https://doi.org/10.5194/gmd-7-2039-2014, 2014.
Kaminski, T., Knorr, W., Schurmann, G., Scholze, M., Rayner, P. J., Zaehle,
S., Blessing, S., Dorigo, W., Gayler, V., Giering, R., Gobron, N., Grant, J.
P., Heimann, M., Hooker-Stroud, A., Houweling, S., Kato, T., Kattge, J.,
Kelley, D., Kemp, S., Koffi, E. N., Kostler, C., Mathieu, P. P., Pinty, B.,
Reick, C. H., Rodenbeck, C., Schnur, R., Scipal, K., Sebald, C., Stacke, T.,
van Scheltinga, A. T., Vossbeck, M., Widmann, H., and Ziehn, T.: The
BETHY/JSBACH Carbon Cycle Data Assimilation System: experiences and
challenges, J. Geophys. Res.-Biogeo., 118, 1414–1426, https://doi.org/10.1002/jgrg.20118, 2013.
Keeling, C. D., Bacastow, R. B., Bainbridge, A. E., Ekdahl, C. A., Guenther,
P. R., Waterman, L. S., and Chin, J. F. S.: Atmospheric Carbon-Dioxide
Variations at Mauna-Loa Observatory, Hawaii, Tellus, 28, 538–551,
https://doi.org/10.1111/j.2153-3490.1976.tb00701.x, 1976.
Keeling, C. D., Bacastow, R. B., Carter, A. F., Piper, S. C., Whorf, T. P.,
Heimann, M., Mook, W. G., and Roeloffzen, H.: A three-dimensional model of
atmospheric CO2 transport based on observed winds: 1. Analysis of
observational data, in: Aspects of Climate Variability in the Pacific and
the Western Americas, edited by: Peterson, D. H., American Geophysical Union, Washington, DC, 165–236, 1989.
Keeling, C. D., Whorf, T. P., Wahlen, M., and Vanderplicht, J.: Interannual
Extremes in the Rate of Rise of Atmospheric Carbon-Dioxide since 1980,
Nature, 375, 666–670, https://doi.org/10.1038/375666a0, 1995.
Keeling, C. D., Chin, J. F. S., and Whorf, T. P.: Increased activity of
northern vegetation inferred from atmospheric CO2 measurements, Nature, 382,
146–149, https://doi.org/10.1038/382146a0, 1996.
Krasting, J. P., John, J. G., Blanton, C., McHugh, C., Nikonov, S.,
Radhakrishnan, A., Rand, K., Zadeh, N. T., Balaji, V., Durachta, J., Dupuis,
C., Menzel, R., Robinson, T., Underwood, S., Vahlenkamp, H., Dunne, K. A.,
Gauthier, P. P. G., Ginoux, P., Griffies, S. M., Hallberg, R., Harrison, M.,
Hurlin, W., Malyshev, S., Naik, V., Paulot, F., Paynter, D. J., Ploshay, J.,
Schwarzkopf, D. M., Seman, C. J., Silvers, L., Wyman, B., Zeng, Y., Adcroft,
A., Dunne, J. P., Dussin, R., Guo, H., He, J., Held, I. M., Horowitz, L. W.,
Lin, P., Milly, P. C. D., Shevliakova, E., Stock, C., Winton, M., Xie, Y.,
and Zhao, M.: NOAA-GFDL GFDL-ESM4 model output prepared for CMIP6 CMIP
esm-hist v20190829, Earth System Grid Federation, https://doi.org/10.22033/ESGF/CMIP6.8522,
2018.
Kuze, A., Suto, H., Nakajima, M., and Hamazaki, T.: Thermal and near
infrared sensor for carbon observation Fourier-transform spectrometer on the
Greenhouse Gases Observing Satellite for greenhouse gases monitoring, Appl.
Opt., 48, 6716–6733, https://doi.org/10.1364/AO.48.006716, 2009.
Lauer, A., Eyring, V., Bellprat, O., Bock, L., Gier, B. K., Hunter, A., Lorenz, R., Pérez-Zanón, N., Righi, M., Schlund, M., Senftleben, D., Weigel, K., and Zechlau, S.: Earth System Model Evaluation Tool (ESMValTool) v2.0 – diagnostics for emergent constraints and future projections from Earth system models in CMIP, Geosci. Model Dev., 13, 4205–4228, https://doi.org/10.5194/gmd-13-4205-2020, 2020.
Law, R. M., Ziehn, T., Matear, R. J., Lenton, A., Chamberlain, M. A., Stevens, L. E., Wang, Y.-P., Srbinovsky, J., Bi, D., Yan, H., and Vohralik, P. F.: The carbon cycle in the Australian Community Climate and Earth System Simulator (ACCESS-ESM1) – Part 1: Model description and pre-industrial simulation, Geosci. Model Dev., 10, 2567–2590, https://doi.org/10.5194/gmd-10-2567-2017, 2017.
Lenssen, N. J. L., Schmidt, G. A., Hansen, J. E., Menne, M. J., Persin, A.,
Ruedy, R., and Zyss, D.: Improvements in the GISTEMP Uncertainty Model,
J. Geophys. Res.-Atmos., 124, 6307–6326,
https://doi.org/10.1029/2018jd029522, 2019.
Lindsay, K., Bonan, G. B., Doney, S. C., Hoffman, F. M., Lawrence, D. M.,
Long, M. C., Mahowald, N. M., Moore, J. K., Randerson, J. T., and Thornton,
P. E.: Preindustrial-Control and Twentieth-Century Carbon Cycle Experiments
with the Earth System Model CESM1 (BGC), J. Climate, 27, 8981–9005,
https://doi.org/10.1175/Jcli-D-12-00565.1, 2014.
Mauritsen, T., Bader, J., Becker, T., Behrens, J., Bittner, M., Brokopf, R.,
Brovkin, V., Claussen, M., Crueger, T., Esch, M., Fast, I., Fiedler, S.,
Fläschner, D., Gayler, V., Giorgetta, M., Goll, D. S., Haak, H.,
Hagemann, S., Hedemann, C., Hohenegger, C., Ilyina, T., Jahns, T.,
Jimenéz-de-la-Cuesta, D., Jungclaus, J., Kleinen, T., Kloster, S.,
Kracher, D., Kinne, S., Kleberg, D., Lasslop, G., Kornblueh, L., Marotzke,
J., Matei, D., Meraner, K., Mikolajewicz, U., Modali, K., Möbis, B.,
Müller, W. A., Nabel, J. E. M. S., Nam, C. C. W., Notz, D., Nyawira,
S.-S., Paulsen, H., Peters, K., Pincus, R., Pohlmann, H., Pongratz, J.,
Popp, M., Raddatz, T. J., Rast, S., Redler, R., Reick, C. H., Rohrschneider,
T., Schemann, V., Schmidt, H., Schnur, R., Schulzweida, U., Six, K. D.,
Stein, L., Stemmler, I., Stevens, B., von Storch, J.-S., Tian, F., Voigt,
A., Vrese, P., Wieners, K.-H., Wilkenskjeld, S., Winkler, A., and Roeckner,
E.: Developments in the MPI-M Earth System Model version 1.2 (MPI-ESM1.2)
and Its Response to Increasing CO2, J. Adv. Model. Earth. Sy., 11, 998–1038,
https://doi.org/10.1029/2018ms001400, 2019.
Myneni, R. B., Keeling, C. D., Tucker, C. J., Asrar, G., and Nemani, R. R.:
Increased plant growth in the northern high latitudes from 1981 to 1991,
Nature, 386, 698–702, https://doi.org/10.1038/386698a0, 1997.
Piao, S., Liu, Z., Wang, Y., Ciais, P., Yao, Y., Peng, S., Chevallier, F.,
Friedlingstein, P., Janssens, I. A., Peñuelas, J., Sitch, S., and Wang,
T.: On the causes of trends in the seasonal amplitude of atmospheric CO2,
Glob. Change Biol., 24, 608–616, https://doi.org/10.1111/gcb.13909, 2018.
Qiao, F. L., Song, Z. Y., Bao, Y., Song, Y. J., Shu, Q., Huang, C. J., and
Zhao, W.: Development and evaluation of an Earth System Model with surface
gravity waves, J. Geophys. Res.-Ocean., 118, 4514–4524, https://doi.org/10.1002/jgrc.20327,
2013.
Reich, P. B., Hobbie, S. E., Lee, T., Ellsworth, D. S., West, J. B., Tilman,
D., Knops, J. M. H., Naeem, S., and Trost, J.: Nitrogen limitation
constrains sustainability of ecosystem response to CO2, Nature, 440,
922–925, https://doi.org/10.1038/nature04486, 2006.
Reuter, M., Bösch, H., Bovensmann, H., Bril, A., Buchwitz, M., Butz, A., Burrows, J. P., O'Dell, C. W., Guerlet, S., Hasekamp, O., Heymann, J., Kikuchi, N., Oshchepkov, S., Parker, R., Pfeifer, S., Schneising, O., Yokota, T., and Yoshida, Y.: A joint effort to deliver satellite retrieved atmospheric CO2 concentrations for surface flux inversions: the ensemble median algorithm EMMA, Atmos. Chem. Phys., 13, 1771–1780, https://doi.org/10.5194/acp-13-1771-2013, 2013.
Reuter, M., Buchwitz, M., Hilker, M., Heymann, J., Schneising, O., Pillai, D., Bovensmann, H., Burrows, J. P., Bösch, H., Parker, R., Butz, A., Hasekamp, O., O'Dell, C. W., Yoshida, Y., Gerbig, C., Nehrkorn, T., Deutscher, N. M., Warneke, T., Notholt, J., Hase, F., Kivi, R., Sussmann, R., Machida, T., Matsueda, H., and Sawa, Y.: Satellite-inferred European carbon sink larger than expected, Atmos. Chem. Phys., 14, 13739–13753, https://doi.org/10.5194/acp-14-13739-2014, 2014.
Reuter, M., Buchwitz, M., and Schneising-Weigel, O.: Product User Guide and
Specification (PUGS) – ANNEX D for products XCO2_EMMA and
XCH4_EMMA, 1–19, available at: https://www.iup.uni-bremen.de/carbon_ghg/docs/C3S/CDR1_2003-2016/PUGS/C3S_D312a_Lot6.3.1.5-v1_PUGS_ANNEX-D_v1.3.pdf (last access: 30 November 2020), 2017.
Reuter, M.: O4Mv3 XCO2 data product version 3, available at: https://cds.climate.copernicus.eu/cdsapp#!/dataset/satellite-carbon-dioxide?tab=form, last access: 1 August 2018.
Reuter, M., Buchwitz, M., Schneising, O., Noël, S., Bovensmann, H., Burrows, J. P., Boesch, H., Di Noia, A., Anand, J., Parker, R. J., Somkuti, P., Wu, L., Hasekamp, O. P., Aben, I., Kuze, A., Suto, H., Shiomi, K., Yoshida, Y., Morino, I., Crisp, D., O'Dell, C. W., Notholt, J., Petri, C., Warneke, T., Velazco, V. A., Deutscher, N. M., Griffith, D. W. T., Kivi, R., Pollard, D. F., Hase, F., Sussmann, R., Té, Y. V., Strong, K., Roche, S., Sha, M. K., De Mazière, M., Feist, D. G., Iraci, L. T., Roehl, C. M., Retscher, C., and Schepers, D.: Ensemble-based satellite-derived carbon dioxide and methane column-averaged dry-air mole fraction data sets (2003–2018) for carbon and climate applications, Atmos. Meas. Tech., 13, 789–819, https://doi.org/10.5194/amt-13-789-2020, 2020.
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.
Ryu, Y., Berry, J. A., and Baldocchi, D. D.: What is global photosynthesis?
History, uncertainties and opportunities, Remote Sens. Environ., 223, 95–114, https://doi.org/10.1016/j.rse.2019.01.016, 2019.
Schneising, O., Reuter, M., Buchwitz, M., Heymann, J., Bovensmann, H., and Burrows, J. P.: Terrestrial carbon sink observed from space: variation of growth rates and seasonal cycle amplitudes in response to interannual surface temperature variability, Atmos. Chem. Phys., 14, 133–141, https://doi.org/10.5194/acp-14-133-2014, 2014.
Seferian, R.: CNRM-CERFACS CNRM-ESM2-1 model output prepared for CMIP6 CMIP
esm-hist v20200715, Earth System Grid Federation, https://doi.org/10.22033/ESGF/CMIP6.4003,
2019.
Séférian, R., Nabat, P., Michou, M., Saint-Martin, D., Voldoire, A.,
Colin, J., Decharme, B., Delire, C., Berthet, S., Chevallier, M.,
Sénési, S., Franchisteguy, L., Vial, J., Mallet, M., Joetzjer, E.,
Geoffroy, O., Guérémy, J.-F., Moine, M.-P., Msadek, R., Ribes, A.,
Rocher, M., Roehrig, R., Salas-y-Mélia, D., Sanchez, E., Terray, L.,
Valcke, S., Waldman, R., Aumont, O., Bopp, L., Deshayes, J., Éthé,
C., and Madec, G.: Evaluation of CNRM Earth System Model, CNRM-ESM2-1: Role
of Earth System Processes in Present-Day and Future Climate, J. Adv. Model.
Earth Sy., 11, 4182–4227, https://doi.org/10.1029/2019ms001791, 2019.
Seland, Ø., Bentsen, M., Oliviè, D. J. L., Toniazzo, T., Gjermundsen,
A., Graff, L. S., Debernard, J. B., Gupta, A. K., He, Y., Kirkevåg, A.,
Schwinger, J., Tjiputra, J., Aas, K. S., Bethke, I., Fan, Y., Griesfeller,
J., Grini, A., Guo, C., Ilicak, M., Karset, I. H. H., Landgren, O. A.,
Liakka, J., Moseid, K. O., Nummelin, A., Spensberger, C., Tang, H., Zhang,
Z., Heinze, C., Iversen, T., and Schulz, M.: NCC NorESM2-LM model output
prepared for CMIP6 CMIP esm-hist v20190920, Earth System Grid Federation,
https://doi.org/10.22033/ESGF/CMIP6.7924, 2019.
Seland, Ø., Bentsen, M., Seland Graff, L., Olivié, D., Toniazzo, T., Gjermundsen, A., Debernard, J. B., Gupta, A. K., He, Y., Kirkevåg, A., Schwinger, J., Tjiputra, J., Schancke Aas, K., Bethke, I., Fan, Y., Griesfeller, J., Grini, A., Guo, C., Ilicak, M., Hafsahl Karset, I. H., Landgren, O., Liakka, J., Onsum Moseid, K., Nummelin, A., Spensberger, C., Tang, H., Zhang, Z., Heinze, C., Iverson, T., and Schulz, M.: The Norwegian Earth System Model, NorESM2 – Evaluation of theCMIP6 DECK and historical simulations, Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2019-378, in review, 2020.
Sellar, A. A., Jones, C. G., Mulcahy, J. P., Tang, Y., Yool, A., Wiltshire,
A., O'Connor, F. M., Stringer, M., Hill, R., Palmieri, J., Woodward, S., de
Mora, L., Kuhlbrodt, T., Rumbold, S. T., Kelley, D. I., Ellis, R., Johnson,
C. E., Walton, J., Abraham, N. L., Andrews, M. B., Andrews, T., Archibald,
A. T., Berthou, S., Burke, E., Blockley, E., Carslaw, K., Dalvi, M.,
Edwards, J., Folberth, G. A., Gedney, N., Griffiths, P. T., Harper, A. B.,
Hendry, M. A., Hewitt, A. J., Johnson, B., Jones, A., Jones, C. D., Keeble,
J., Liddicoat, S., Morgenstern, O., Parker, R. J., Predoi, V., Robertson,
E., Siahaan, A., Smith, R. S., Swaminathan, R., Woodhouse, M. T., Zeng, G.,
and Zerroukat, M.: UKESM1: Description and Evaluation of the U.K. Earth
System Model, J. Adv. Model. Earth. Sy., 11, 4513–4558, https://doi.org/10.1029/2019MS001739,
2019.
Shindell, D. T., Lamarque, J.-F., Schulz, M., Flanner, M., Jiao, C., Chin, M., Young, P. J., Lee, Y. H., Rotstayn, L., Mahowald, N., Milly, G., Faluvegi, G., Balkanski, Y., Collins, W. J., Conley, A. J., Dalsoren, S., Easter, R., Ghan, S., Horowitz, L., Liu, X., Myhre, G., Nagashima, T., Naik, V., Rumbold, S. T., Skeie, R., Sudo, K., Szopa, S., Takemura, T., Voulgarakis, A., Yoon, J.-H., and Lo, F.: Radiative forcing in the ACCMIP historical and future climate simulations, Atmos. Chem. Phys., 13, 2939–2974, https://doi.org/10.5194/acp-13-2939-2013, 2013.
Still, C. J., Riley, W. J., Biraud, S. C., Noone, D. C., Buenning, N. H.,
Randerson, J. T., Torn, M. S., Welker, J., White, J. W. C., Vachon, R.,
Farquhar, G. D., and Berry, J. A.: Influence of clouds and diffuse radiation
on ecosystem-atmosphere CO2 and CO18O exchanges, J. Geophys.
Res.-Biogeo., 114, G01018, 10.1029/2007jg000675, 2009.
Swart, N. C., Cole, J. N. S., Kharin, V. V., Lazare, M., Scinocca, J. F., Gillett, N. P., Anstey, J., Arora, V., Christian, J. R., Hanna, S., Jiao, Y., Lee, W. G., Majaess, F., Saenko, O. A., Seiler, C., Seinen, C., Shao, A., Sigmond, M., Solheim, L., von Salzen, K., Yang, D., and Winter, B.: The Canadian Earth System Model version 5 (CanESM5.0.3), Geosci. Model Dev., 12, 4823–4873, https://doi.org/10.5194/gmd-12-4823-2019, 2019a.
Swart, N. C., Cole, J. N. S., Kharin, V. V., Lazare, M., Scinocca, J. F.,
Gillett, N. P., Anstey, J., Arora, V., Christian, J. R., Jiao, Y., Lee, W.
G., Majaess, F., Saenko, O. A., Seiler, C., Seinen, C., Shao, A., Solheim,
L., von Salzen, K., Yang, D., Winter, B., and Sigmond, M.: CCCma
CanESM5-CanOE model output prepared for CMIP6 CMIP esm-hist v20190429, Earth
System Grid Federation, https://doi.org/10.22033/ESGF/CMIP6.10232, 2019b.
Swart, N. C., Cole, J. N. S., Kharin, V. V., Lazare, M., Scinocca, J. F.,
Gillett, N. P., Anstey, J., Arora, V., Christian, J. R., Jiao, Y., Lee, W.
G., Majaess, F., Saenko, O. A., Seiler, C., Seinen, C., Shao, A., Solheim,
L., von Salzen, K., Yang, D., Winter, B., and Sigmond, M.: CCCma CanESM5
model output prepared for CMIP6 CMIP esm-hist v20190429, Earth System Grid
Federation, https://doi.org/10.22033/ESGF/CMIP6.3583, 2019c.
Tang, Y., Rumbold, S., Ellis, R., Kelley, D., Mulcahy, J., Sellar, A.,
Walton, J., and Jones, C.: MOHC UKESM1.0-LL model output prepared for CMIP6
CMIP esm-hist v20190723, Earth System Grid Federation,
https://doi.org/10.22033/ESGF/CMIP6.5929, 2019.
Taylor, K. E., Stouffer, R. J., and Meehl, G. A.: An Overview of CMIP5 and
the Experiment Design, B. Am. Meteorol. Soc., 93,
485–498, https://doi.org/10.1175/bams-d-11-00094.1, 2012.
Teixeira, J., Waliser, D., Ferraro, R., Gleckler, P., Lee, T., and Potter,
G.: Satellite Observations for CMIP5: The Genesis of Obs4MIPs, B. Am. Meteorol. Soc., 95, 1329–1334,
https://doi.org/10.1175/bams-d-12-00204.1, 2014.
Tjiputra, J. F., Roelandt, C., Bentsen, M., Lawrence, D. M., Lorentzen, T., Schwinger, J., Seland, Ø., and Heinze, C.: Evaluation of the carbon cycle components in the Norwegian Earth System Model (NorESM), Geosci. Model Dev., 6, 301–325, https://doi.org/10.5194/gmd-6-301-2013, 2013.
Waliser, D., Gleckler, P. J., Ferraro, R., Taylor, K. E., Ames, S., Biard, J., Bosilovich, M. G., Brown, O., Chepfer, H., Cinquini, L., Durack, P. J., Eyring, V., Mathieu, P.-P., Lee, T., Pinnock, S., Potter, G. L., Rixen, M., Saunders, R., Schulz, J., Thépaut, J.-N., and Tuma, M.: Observations for Model Intercomparison Project (Obs4MIPs): status for CMIP6, Geosci. Model Dev., 13, 2945–2958, https://doi.org/10.5194/gmd-13-2945-2020, 2020.
Watanabe, S., Hajima, T., Sudo, K., Nagashima, T., Takemura, T., Okajima, H., Nozawa, T., Kawase, H., Abe, M., Yokohata, T., Ise, T., Sato, H., Kato, E., Takata, K., Emori, S., and Kawamiya, M.: MIROC-ESM 2010: model description and basic results of CMIP5-20c3m experiments, Geosci. Model Dev., 4, 845–872, https://doi.org/10.5194/gmd-4-845-2011, 2011.
Weigel, K., Bock, L., Gier, B. K., Lauer, A., Righi, M., Schlund, M., Adeniyi, K., Andela, B., Arnone, E., Berg, P., Caron, L.-P., Cionni, I., Corti, S., Drost, N., Hunter, A., Lledó, L., Mohr, C. W., Paçal, A., Pérez-Zanón, N., Predoi, V., Sandstad, M., Sillmann, J., Sterl, A., Vegas-Regidor, J., von Hardenberg, J., and Eyring, V.: Earth System Model Evaluation Tool (ESMValTool) v2.0 – diagnostics for extreme events, regional and impact evaluation and analysis of Earth system models in CMIP, Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-244, in review, 2020.
Wenzel, S., Cox, P. M., Eyring, V., and Friedlingstein, P.: Emergent
constraints on climate-carbon cycle feedbacks in the CMIP5 Earth system
models, J. Geophys. Res.-Biogeo., 119, 794–807, https://doi.org/10.1002/2013jg002591, 2014.
Wenzel, S., Cox, P. M., Eyring, V., and Friedlingstein, P.: Projected land
photosynthesis constrained by changes in the seasonal cycle of atmospheric
CO2, Nature, 538, 499–501, https://doi.org/10.1038/nature19772, 2016.
Wieder, W. R., Lawrence, D. M., Fisher, R. A., Bonan, G. B., Cheng, S. J.,
Goodale, C. L., Grandy, A. S., Koven, C. D., Lombardozzi, D. L., Oleson, K.
W., and Thomas, R. Q.: Beyond Static Benchmarking: Using Experimental
Manipulations to Evaluate Land Model Assumptions, Global Biogeochem.
Cy., 33, 1289–1309, https://doi.org/10.1029/2018gb006141, 2019.
Wieners, K.-H., Giorgetta, M., Jungclaus, J., Reick, C., Esch, M., Bittner,
M., Legutke, S., Schupfner, M., Wachsmann, F., Gayler, V., Haak, H., de
Vrese, P., Raddatz, T., Mauritsen, T., von Storch, J.-S., Behrens, J.,
Brovkin, V., Claussen, M., Crueger, T., Fast, I., Fiedler, S., Hagemann, S.,
Hohenegger, C., Jahns, T., Kloster, S., Kinne, S., Lasslop, G., Kornblueh,
L., Marotzke, J., Matei, D., Meraner, K., Mikolajewicz, U., Modali, K.,
Müller, W., Nabel, J., Notz, D., Peters, K., Pincus, R., Pohlmann, H.,
Pongratz, J., Rast, S., Schmidt, H., Schnur, R., Schulzweida, U., Six, K.,
Stevens, B., Voigt, A., and Roeckner, E.: MPI-M MPI-ESM1.2-LR model output
prepared for CMIP6 CMIP esm-hist v20190710, Earth System Grid Federation,
https://doi.org/10.22033/ESGF/CMIP6.6545, 2019.
Williams, D. N., Ananthakrishnan, R., Bernholdt, D. E., Bharathi, S., Brown,
D., Chen, M., Chervenak, A. L., Cinquini, L., Drach, R., Foster, I. T., Fox,
P., Fraser, D., Garcia, J., Hankin, S., Jones, P., Middleton, D. E.,
Schwidder, J., Schweitzer, R., Schuler, R., Shoshani, A., Siebenlist, F.,
Sim, A., Strand, W. G., Su, M., and Wilhelmi, N.: The Earth System Grid:
Enabling Access to Multimodel Climate Simulation Data, B.
Am. Meteorol. Soc., 90, 195–206, https://doi.org/10.1175/2008bams2459.1, 2009.
Wunch, D., Toon, G. C., Blavier, J. F., Washenfelder, R. A., Notholt, J.,
Connor, B. J., Griffith, D. W., Sherlock, V., and Wennberg, P. O.: The total
carbon column observing network, Philos. Trans. A Math. Phys. Eng. Sci., 369,
2087–2112, https://doi.org/10.1098/rsta.2010.0240, 2011.
Yin, Y., Ciais, P., Chevallier, F., Li, W., Bastos, A., Piao, S. L., Wang,
T., and Liu, H. Y.: Changes in the Response of the Northern Hemisphere
Carbon Uptake to Temperature Over the Last Three Decades, Geophys. Res. Lett.,
45, 4371–4380, https://doi.org/10.1029/2018gl077316, 2018.
Yukimoto, S., Yoshimura, H., Hosaka, M., Sakami, T., Tsujino, H., Hirabara,
M., Tanaka, T. Y., Deushi, M., Obata, A., Nakano, H., Adachi, Y., Shindo,
E., Yabu, S., Ose, T., and Kitoh, A.: Meteorological Research
Institute-Earth System Model Version 1 ( MRI-ESM1 ), Technical Reports,
available at: https://www.mri-jma.go.jp/Publish/Technical/DATA/VOL_64/index_en.html (last access: 30 November 2020), 2011.
Yukimoto, S., Adachi, Y., Hosaka, M., Sakami, T., Yoshimura, H., Hirabara,
M., Tanaka, T. Y., Shindo, E., Tsujino, H., Deushi, M., Mizuta, R., Yabu,
S., Obata, A., Nakano, H., Koshiro, T., Ose, T., and Kitoh, A.: A New Global
Climate Model of the Meteorological Research Institute: MRI-CGCM3 – Model
Description and Basic Performance, J. Meteorol. Soc.
Jpn., 90, 23–64, https://doi.org/10.2151/jmsj.2012-A02, 2012.
Yukimoto, S., Kawai, H., Koshiro, T., Oshima, N., Yoshida, K., Urakawa, S.,
Tsujino, H., Deushi, M., Tanaka, T., Hosaka, M., Yabu, S., Yoshimura, H.,
Shindo, E., Mizuta, R., Obata, A., Adachi, Y., and Ishii, M.: The
Meteorological Research Institute Earth System Model Version 2.0,
MRI-ESM2.0: Description and Basic Evaluation of the Physical Component,
J. Meteorol. Soc. Jpn., 97, 931–965,
https://doi.org/10.2151/jmsj.2019-051, 2019a.
Yukimoto, S., Koshiro, T., Kawai, H., Oshima, N., Yoshida, K., Urakawa, S.,
Tsujino, H., Deushi, M., Tanaka, T., Hosaka, M., Yoshimura, H., Shindo, E.,
Mizuta, R., Ishii, M., Obata, A., and Adachi, Y.: MRI MRI-ESM2.0 model
output prepared for CMIP6 CMIP esm-hist v20191205, Earth System Grid
Federation, https://doi.org/10.22033/ESGF/CMIP6.6807, 2019b.
Zhao, F., Zeng, N., Asrar, G., Friedlingstein, P., Ito, A., Jain, A., Kalnay, E., Kato, E., Koven, C. D., Poulter, B., Rafique, R., Sitch, S., Shu, S., Stocker, B., Viovy, N., Wiltshire, A., and Zaehle, S.: Role of CO2, climate and land use in regulating the seasonal amplitude increase of carbon fluxes in terrestrial ecosystems: a multimodel analysis, Biogeosciences, 13, 5121–5137, https://doi.org/10.5194/bg-13-5121-2016, 2016.
Ziehn, T., Lenton, A., Law, R. M., Matear, R. J., and Chamberlain, M. A.: The carbon cycle in the Australian Community Climate and Earth System Simulator (ACCESS-ESM1) – Part 2: Historical simulations, Geosci. Model Dev., 10, 2591–2614, https://doi.org/10.5194/gmd-10-2591-2017, 2017.
Ziehn, T., Chamberlain, M., Lenton, A., Law, R., Bodman, R., Dix, M., Wang,
Y., Dobrohotoff, P., Srbinovsky, J., Stevens, L., Vohralik, P., Mackallah,
C., Sullivan, A., O'Farrell, S., and Druken, K.: CSIRO ACCESS-ESM1.5 model
output prepared for CMIP6 CMIP esm-hist v20191203, Earth System Grid
Federation, https://doi.org/10.22033/ESGF/CMIP6.4242, 2019.
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.
Models from Coupled Model Intercomparison Project (CMIP) phases 5 and 6 are compared to a...
Altmetrics
Final-revised paper
Preprint