Articles | Volume 16, issue 12
https://doi.org/10.5194/gmd-16-3501-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-16-3501-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
27 Jun 2023
Model description paper |
| 27 Jun 2023
| 27 Jun 2023
The Earth system model CLIMBER-X v1.0 – Part 2: The global carbon cycle
Potsdam Institute for Climate Impact Research (PIK), Member of the Leibniz Association, P.O. Box 60 12 03, 14412 Potsdam, Germany
Tatiana Ilyina
Max Planck Institute for Meteorology, Hamburg, Germany
Max Planck Institute for Meteorology, Hamburg, Germany
Christoph Heinze
Geophysical Institute, University of Bergen, and Bjerknes Centre for Climate Research, Bergen, Norway
Mahé Perrette
Potsdam Institute for Climate Impact Research (PIK), Member of the Leibniz Association, P.O. Box 60 12 03, 14412 Potsdam, Germany
Malte Heinemann
Institute of Geosciences, Kiel University, Kiel, Germany
Daniela Dalmonech
Forest Modelling Laboratory, Institute for Agriculture and Forestry Systems in the Mediterranean, National Research Council of Italy (CNR-ISAFOM), Via Madonna Alta 128, 06128 Perugia, Italy
Victor Brovkin
Max Planck Institute for Meteorology, Hamburg, Germany
CEN, University of Hamburg, Hamburg, Germany
visiting scientist at: Potsdam Institute for Climate Impact Research (PIK), Member of the Leibniz Association, P.O. Box 60 12 03, 14412 Potsdam, Germany
Guy Munhoven
Dépt. d’Astrophysique, Géophysique et Océanographie, Université de Liège, Liège, Belgium
Janine Börker
Institute for Geology, Center for Earth System Research and Sustainability, Universität Hamburg, Bundesstrasse 55, 20146 Hamburg, Germany
Jens Hartmann
Institute for Geology, Center for Earth System Research and Sustainability, Universität Hamburg, Bundesstrasse 55, 20146 Hamburg, Germany
Gibran Romero-Mujalli
Institute for Geology, Center for Earth System Research and Sustainability, Universität Hamburg, Bundesstrasse 55, 20146 Hamburg, Germany
Andrey Ganopolski
Potsdam Institute for Climate Impact Research (PIK), Member of the Leibniz Association, P.O. Box 60 12 03, 14412 Potsdam, Germany
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Earth Syst. Dynam., 15, 1417–1434, https://doi.org/10.5194/esd-15-1417-2024, https://doi.org/10.5194/esd-15-1417-2024, 2024
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Niels Suitner, Giulia Faucher, Carl Lim, Julieta Schneider, Charly A. Moras, Ulf Riebesell, and Jens Hartmann
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Recent studies described the precipitation of carbonates as a result of alkalinity enhancement in seawater, which could adversely affect the carbon sequestration potential of ocean alkalinity enhancement (OAE) approaches. By conducting experiments in natural seawater, this study observed uniform patterns during the triggered runaway carbonate precipitation, which allow the prediction of safe and efficient local application levels of OAE scenarios.
Colin G. Jones, Fanny Adloff, Ben B. B. Booth, Peter M. Cox, Veronika Eyring, Pierre Friedlingstein, Katja Frieler, Helene T. Hewitt, Hazel A. Jeffery, Sylvie Joussaume, Torben Koenigk, Bryan N. Lawrence, Eleanor O'Rourke, Malcolm J. Roberts, Benjamin M. 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 Doblas-Reyes, Markus Donat, Italo Epicoco, Pete Falloon, Sandro Fiore, Thomas Frölicher, Neven S. Fučkar, Matthew J. Gidden, Helge F. Goessling, Rune Grand Graversen, Silvio Gualdi, José M. Gutiérrez, Tatiana Ilyina, Daniela Jacob, Chris D. Jones, Martin Juckes, Elizabeth Kendon, Erik Kjellström, Reto Knutti, Jason Lowe, Matthew Mizielinski, Paola Nassisi, Michael Obersteiner, Pierre Regnier, Romain Roehrig, David Salas y Mélia, Carl-Friedrich Schleussner, Michael Schulz, Enrico Scoccimarro, Laurent Terray, Hannes Thiemann, Richard A. Wood, Shuting Yang, and Sönke Zaehle
Earth Syst. Dynam., 15, 1319–1351, https://doi.org/10.5194/esd-15-1319-2024, https://doi.org/10.5194/esd-15-1319-2024, 2024
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We propose a number of priority areas for the international climate research community to address over the coming decade. Advances in these areas will both increase our understanding of past and future Earth system change, including the societal and environmental impacts of this change, and deliver significantly improved scientific support to international climate policy, such as future IPCC assessments and the UNFCCC Global Stocktake.
Christine Kaufhold, Matteo Willeit, Bo Liu, and Andrey Ganopolski
EGUsphere, https://doi.org/10.5194/egusphere-2024-2976, https://doi.org/10.5194/egusphere-2024-2976, 2024
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This study simulates long-term future climate scenarios to examine how long CO2 emissions will persist in the atmosphere. It shows that the effectiveness of carbon removal processes varies with the amount emitted. The removal of CO2 through silicate weathering is faster than previously thought, leading to a quicker reduction over time. The combined behaviour of different carbon cycle processes emphasizes the need to include all of them in models, as to better predict long-term atmospheric CO2.
Nathaelle Bouttes, Lester Kwiatkowski, Manon Berger, Victor Brovkin, and Guy Munhoven
Geosci. Model Dev., 17, 6513–6528, https://doi.org/10.5194/gmd-17-6513-2024, https://doi.org/10.5194/gmd-17-6513-2024, 2024
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Coral reefs are crucial for biodiversity, but they also play a role in the carbon cycle on long time scales of a few thousand years. To better simulate the future and past evolution of coral reefs and their effect on the global carbon cycle, hence on atmospheric CO2 concentration, it is necessary to include coral reefs within a climate model. Here we describe the inclusion of coral reef carbonate production in a carbon–climate model and its validation in comparison to existing modern data.
Amali A. Amali, Clemens Schwingshackl, Akihiko Ito, Alina Barbu, Christine Delire, Daniele Peano, David M. Lawrence, David Wårlind, Eddy Robertson, Edouard L. Davin, Elena Shevliakova, Ian N. Harman, Nicolas Vuichard, Paul A. Miller, Peter J. Lawrence, Tilo Ziehn, Tomohiro Hajima, Victor Brovkin, Yanwu Zhang, Vivek K. Arora, and Julia Pongratz
EGUsphere, https://doi.org/10.5194/egusphere-2024-2460, https://doi.org/10.5194/egusphere-2024-2460, 2024
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Our study explored the impact of anthropogenic land-use change (LUC) on climate dynamics, focusing on biogeophysical (BGP) and biogeochemical (BGC) effects using data from the CMIP6-LUMIP project. We found that LUC-induced carbon emissions contribute to a BGC warming of 0.20 °C, with BGC effects dominating globally over BGP effects, which show regional variability. Our findings highlight discrepancies in model simulations and emphasise the need for improved representations of LUC processes.
Chenzhi Li, Anne Dallmeyer, Jian Ni, Manuel Chevalier, Matteo Willeit, Andrei A. Andreev, Xianyong Cao, Laura Schild, Birgit Heim, and Ulrike Herzschuh
EGUsphere, https://doi.org/10.5194/egusphere-2024-1862, https://doi.org/10.5194/egusphere-2024-1862, 2024
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We present a global megabiome dynamics and distributions derived from pollen-based reconstructions over the last 21,000 years, which are suitable for the evaluation of Earth System Model-based paleo-megabiome simulations. We identified strong deviations between pollen- and model-derived megabiome distributions in the circum-Arctic areas and Tibetan Plateau during the Last Glacial Maximum and early deglaciation, as well as in North Africa and the Mediterranean regions during the Holocene.
Stefanie Talento, Matteo Willeit, and Andrey Ganopolski
Clim. Past, 20, 1349–1364, https://doi.org/10.5194/cp-20-1349-2024, https://doi.org/10.5194/cp-20-1349-2024, 2024
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To trigger glacial inception, the summer maximum insolation at high latitudes in the Northern Hemisphere must be lower than a critical value. This value is not constant but depends on the atmospheric CO2 concentration. Paleoclimatic data do not give enough information to derive the relationship between the critical threshold and CO2. However, knowledge of such a relation is important for predicting future glaciations and the impact anthropogenic CO2 emissions might have on them.
Malte Meinshausen, Carl-Friedrich Schleussner, Kathleen Beyer, Greg Bodeker, Olivier Boucher, Josep G. Canadell, John S. Daniel, Aïda Diongue-Niang, Fatima Driouech, Erich Fischer, Piers Forster, Michael Grose, Gerrit Hansen, Zeke Hausfather, Tatiana Ilyina, Jarmo S. Kikstra, Joyce Kimutai, Andrew D. King, June-Yi Lee, Chris Lennard, Tabea Lissner, Alexander Nauels, Glen P. Peters, Anna Pirani, Gian-Kasper Plattner, Hans Pörtner, Joeri Rogelj, Maisa Rojas, Joyashree Roy, Bjørn H. Samset, Benjamin M. Sanderson, Roland Séférian, Sonia Seneviratne, Christopher J. Smith, Sophie Szopa, Adelle Thomas, Diana Urge-Vorsatz, Guus J. M. Velders, Tokuta Yokohata, Tilo Ziehn, and Zebedee Nicholls
Geosci. Model Dev., 17, 4533–4559, https://doi.org/10.5194/gmd-17-4533-2024, https://doi.org/10.5194/gmd-17-4533-2024, 2024
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The scientific community is considering new scenarios to succeed RCPs and SSPs for the next generation of Earth system model runs to project future climate change. To contribute to that effort, we reflect on relevant policy and scientific research questions and suggest categories for representative emission pathways. These categories are tailored to the Paris Agreement long-term temperature goal, high-risk outcomes in the absence of further climate policy and worlds “that could have been”.
Matteo Willeit, Reinhard Calov, Stefanie Talento, Ralf Greve, Jorjo Bernales, Volker Klemann, Meike Bagge, and Andrey Ganopolski
Clim. Past, 20, 597–623, https://doi.org/10.5194/cp-20-597-2024, https://doi.org/10.5194/cp-20-597-2024, 2024
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We present transient simulations of the last glacial inception with the coupled climate–ice sheet model CLIMBER-X showing a rapid increase in Northern Hemisphere ice sheet area and a sea level drop by ~ 35 m, with the vegetation feedback playing a key role. Overall, our simulations confirm and refine previous results showing that climate-vegetation–cryosphere–carbon cycle feedbacks play a fundamental role in the transition from interglacial to glacial states.
Annika Nolte, Ezra Haaf, Benedikt Heudorfer, Steffen Bender, and Jens Hartmann
Hydrol. Earth Syst. Sci., 28, 1215–1249, https://doi.org/10.5194/hess-28-1215-2024, https://doi.org/10.5194/hess-28-1215-2024, 2024
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This study examines about 8000 groundwater level (GWL) time series from five continents to explore similarities in groundwater systems at different scales. Statistical metrics and machine learning techniques are applied to identify common GWL dynamics patterns and analyze their controlling factors. The study also highlights the potential and limitations of this data-driven approach to improve our understanding of groundwater recharge and discharge processes.
Allanah Joy Paul, Mathias Haunost, Silvan Urs Goldenberg, Jens Hartmann, Nicolás Sánchez, Julieta Schneider, Niels Suitner, and Ulf Riebesell
EGUsphere, https://doi.org/10.5194/egusphere-2024-417, https://doi.org/10.5194/egusphere-2024-417, 2024
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Ocean alkalinity enhancement (OAE) is being assessed for its potential to absorb atmospheric CO2 and store it for a long time. OAE still needs comprehensive assessment of its safety and effectiveness. We studied an idealised OAE application in a natural low nutrient ecosystem over one month. Our results showed that biogeochemical functioning remained mostly stable, but that the long-term capability for storing carbon may be limited at high alkalinity concentration.
Nico Wunderling, Anna S. von der Heydt, Yevgeny Aksenov, Stephen Barker, Robbin Bastiaansen, Victor Brovkin, Maura Brunetti, Victor Couplet, Thomas Kleinen, Caroline H. Lear, Johannes Lohmann, Rosa Maria Roman-Cuesta, Sacha Sinet, Didier Swingedouw, Ricarda Winkelmann, Pallavi Anand, Jonathan Barichivich, Sebastian Bathiany, Mara Baudena, John T. Bruun, Cristiano M. Chiessi, Helen K. Coxall, David Docquier, Jonathan F. Donges, Swinda K. J. Falkena, Ann Kristin Klose, David Obura, Juan Rocha, Stefanie Rynders, Norman Julius Steinert, and Matteo Willeit
Earth Syst. Dynam., 15, 41–74, https://doi.org/10.5194/esd-15-41-2024, https://doi.org/10.5194/esd-15-41-2024, 2024
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This paper maps out the state-of-the-art literature on interactions between tipping elements relevant for current global warming pathways. We find indications that many of the interactions between tipping elements are destabilizing. This means that tipping cascades cannot be ruled out on centennial to millennial timescales at global warming levels between 1.5 and 2.0 °C or on shorter timescales if global warming surpasses 2.0 °C.
Andrey Ganopolski
Clim. Past, 20, 151–185, https://doi.org/10.5194/cp-20-151-2024, https://doi.org/10.5194/cp-20-151-2024, 2024
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Despite significant progress in modelling Quaternary climate dynamics, a comprehensive theory of glacial cycles is still lacking. Here, using the results of model simulations and data analysis, I present a framework of the generalized Milankovitch theory (GMT), which further advances the concept proposed by Milutin Milankovitch over a century ago. The theory explains a number of facts which were not known during Milankovitch time's, such as the 100 kyr periodicity of the late Quaternary.
Takahito Mitsui, Matteo Willeit, and Niklas Boers
Earth Syst. Dynam., 14, 1277–1294, https://doi.org/10.5194/esd-14-1277-2023, https://doi.org/10.5194/esd-14-1277-2023, 2023
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The glacial–interglacial cycles of the Quaternary exhibit 41 kyr periodicity before the Mid-Pleistocene Transition (MPT) around 1.2–0.8 Myr ago and ~100 kyr periodicity after that. The mechanism generating these periodicities remains elusive. Through an analysis of an Earth system model of intermediate complexity, CLIMBER-2, we show that the dominant periodicities of glacial cycles can be explained from the viewpoint of synchronization theory.
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
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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.
Kyung-Sook Yun, Axel Timmermann, Sun-Seon Lee, Matteo Willeit, Andrey Ganopolski, and Jyoti Jadhav
Clim. Past, 19, 1951–1974, https://doi.org/10.5194/cp-19-1951-2023, https://doi.org/10.5194/cp-19-1951-2023, 2023
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To quantify the sensitivity of the earth system to orbital-scale forcings, we conducted an unprecedented quasi-continuous coupled general climate model simulation with the Community Earth System Model, which covers the climatic history of the past 3 million years. This study could stimulate future transient paleo-climate model simulations and perspectives to further highlight and document the effect of anthropogenic CO2 emissions in the broader paleo-climatic context.
Christoph Heinze, Thorsten Blenckner, Peter Brown, Friederike Fröb, Anne Morée, Adrian L. New, Cara Nissen, Stefanie Rynders, Isabel Seguro, Yevgeny Aksenov, Yuri Artioli, Timothée Bourgeois, Friedrich Burger, Jonathan Buzan, B. B. Cael, Veli Çağlar Yumruktepe, Melissa Chierici, Christopher Danek, Ulf Dieckmann, Agneta Fransson, Thomas Frölicher, Giovanni Galli, Marion Gehlen, Aridane G. González, Melchor Gonzalez-Davila, Nicolas Gruber, Örjan Gustafsson, Judith Hauck, Mikko Heino, Stephanie Henson, Jenny Hieronymus, I. Emma Huertas, Fatma Jebri, Aurich Jeltsch-Thömmes, Fortunat Joos, Jaideep Joshi, Stephen Kelly, Nandini Menon, Precious Mongwe, Laurent Oziel, Sólveig Ólafsdottir, Julien Palmieri, Fiz F. Pérez, Rajamohanan Pillai Ranith, Juliano Ramanantsoa, Tilla Roy, Dagmara Rusiecka, J. Magdalena Santana Casiano, Yeray Santana-Falcón, Jörg Schwinger, Roland Séférian, Miriam Seifert, Anna Shchiptsova, Bablu Sinha, Christopher Somes, Reiner Steinfeldt, Dandan Tao, Jerry Tjiputra, Adam Ulfsbo, Christoph Völker, Tsuyoshi Wakamatsu, and Ying Ye
Biogeosciences Discuss., https://doi.org/10.5194/bg-2023-182, https://doi.org/10.5194/bg-2023-182, 2023
Revised manuscript under review for BG
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For assessing the consequences of human-induced climate change for the marine realm, it is necessary to not only look at gradual changes but also at abrupt changes of environmental conditions. We summarise abrupt changes in ocean warming, acidification, and oxygen concentration as the key environmental factors for ecosystems. Taking these abrupt changes into account requires greenhouse gas emissions to be reduced to a larger extent than previously thought to limit respective damage.
Christine Kaufhold and Andrey Ganopolski
Saf. Nucl. Waste Disposal, 2, 89–90, https://doi.org/10.5194/sand-2-89-2023, https://doi.org/10.5194/sand-2-89-2023, 2023
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A repository in Germany must be secure for a period of at least 1 million years. We argue that the deep-future climate should be considered in the site selection process. A suite of possible future climates will be provided, using different emission scenarios. In low-emission scenarios, glacial cycles will quickly resume, changing subterranean stress and permafrost. In high-emission scenarios, the sea level will rise. Both regimes should be of interest to those working on nuclear waste disposal.
István Dunkl, Nicole Lovenduski, Alessio Collalti, Vivek K. Arora, Tatiana Ilyina, and Victor Brovkin
Biogeosciences, 20, 3523–3538, https://doi.org/10.5194/bg-20-3523-2023, https://doi.org/10.5194/bg-20-3523-2023, 2023
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Despite differences in the reproduction of gross primary productivity (GPP) by Earth system models (ESMs), ESMs have similar predictability of the global carbon cycle. We found that, although GPP variability originates from different regions and is driven by different climatic variables across the ESMs, the ESMs rely on the same mechanisms to predict their own GPP. This shows that the predictability of the carbon cycle is limited by our understanding of variability rather than predictability.
Nele Lehmann, Hugues Lantuit, Michael Ernst Böttcher, Jens Hartmann, Antje Eulenburg, and Helmuth Thomas
Biogeosciences, 20, 3459–3479, https://doi.org/10.5194/bg-20-3459-2023, https://doi.org/10.5194/bg-20-3459-2023, 2023
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Riverine alkalinity in the silicate-dominated headwater catchment at subarctic Iskorasfjellet, northern Norway, was almost entirely derived from weathering of minor carbonate occurrences in the riparian zone. The uphill catchment appeared limited by insufficient contact time of weathering agents and weatherable material. Further, alkalinity increased with decreasing permafrost extent. Thus, with climate change, alkalinity generation is expected to increase in this permafrost-degrading landscape.
Mingyang Tian, Jens Hartmann, Gibran Romero-Mujalli, Thorben Amann, Lishan Ran, and Ji-Hyung Park
Biogeosciences Discuss., https://doi.org/10.5194/bg-2023-131, https://doi.org/10.5194/bg-2023-131, 2023
Manuscript not accepted for further review
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Effective water quality management in the Elbe River from 1984 to 2018 significantly reduced CO2 emissions, particularly after Germany's reunification. Key factors in the reduction include organic carbon removal and nutrient management, with nitrogen control being more critical than phosphorus for the restoration of ecosystem capacity. Unpredictable influxes of organic carbon and the relocation of emissions from wastewater treatment can cause uncertainties for CO2 removals.
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
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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.
Thomas Kleinen, Sergey Gromov, Benedikt Steil, and Victor Brovkin
Clim. Past, 19, 1081–1099, https://doi.org/10.5194/cp-19-1081-2023, https://doi.org/10.5194/cp-19-1081-2023, 2023
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We modelled atmospheric methane continuously from the last glacial maximum to the present using a state-of-the-art Earth system model. Our model results compare well with reconstructions from ice cores and improve our understanding of a very intriguing period of Earth system history, the deglaciation, when atmospheric methane changed quickly and strongly. Deglacial methane changes are driven by emissions from tropical wetlands, with wetlands in high northern latitudes being secondary.
Philipp de Vrese, Goran Georgievski, Jesus Fidel Gonzalez Rouco, Dirk Notz, Tobias Stacke, Norman Julius Steinert, Stiig Wilkenskjeld, and Victor Brovkin
The Cryosphere, 17, 2095–2118, https://doi.org/10.5194/tc-17-2095-2023, https://doi.org/10.5194/tc-17-2095-2023, 2023
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The current generation of Earth system models exhibits large inter-model differences in the simulated climate of the Arctic and subarctic zone. We used an adapted version of the Max Planck Institute (MPI) Earth System Model to show that differences in the representation of the soil hydrology in permafrost-affected regions could help explain a large part of this inter-model spread and have pronounced impacts on important elements of Earth systems as far to the south as the tropics.
Alban Planchat, Lester Kwiatkowski, Laurent Bopp, Olivier Torres, James R. Christian, Momme Butenschön, Tomas Lovato, Roland Séférian, Matthew A. Chamberlain, Olivier Aumont, Michio Watanabe, Akitomo Yamamoto, Andrew Yool, Tatiana Ilyina, Hiroyuki Tsujino, Kristen M. Krumhardt, Jörg Schwinger, Jerry Tjiputra, John P. Dunne, and Charles Stock
Biogeosciences, 20, 1195–1257, https://doi.org/10.5194/bg-20-1195-2023, https://doi.org/10.5194/bg-20-1195-2023, 2023
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Ocean alkalinity is critical to the uptake of atmospheric carbon and acidification in surface waters. We review the representation of alkalinity and the associated calcium carbonate cycle in Earth system models. While many parameterizations remain present in the latest generation of models, there is a general improvement in the simulated alkalinity distribution. This improvement is related to an increase in the export of biotic calcium carbonate, which closer resembles observations.
Jens Hartmann, Niels Suitner, Carl Lim, Julieta Schneider, Laura Marín-Samper, Javier Arístegui, Phil Renforth, Jan Taucher, and Ulf Riebesell
Biogeosciences, 20, 781–802, https://doi.org/10.5194/bg-20-781-2023, https://doi.org/10.5194/bg-20-781-2023, 2023
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CO2 can be stored in the ocean via increasing alkalinity of ocean water. Alkalinity can be created via dissolution of alkaline materials, like limestone or soda. Presented research studies boundaries for increasing alkalinity in seawater. The best way to increase alkalinity was found using an equilibrated solution, for example as produced from reactors. Adding particles for dissolution into seawater on the other hand produces the risk of losing alkalinity and degassing of CO2 to the atmosphere.
Hongmei Li, Tatiana Ilyina, Tammas Loughran, Aaron Spring, and Julia Pongratz
Earth Syst. Dynam., 14, 101–119, https://doi.org/10.5194/esd-14-101-2023, https://doi.org/10.5194/esd-14-101-2023, 2023
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For the first time, our decadal prediction system based on Max Planck Institute Earth System Model enables prognostic atmospheric CO2 with an interactive carbon cycle. The evolution of CO2 fluxes and atmospheric CO2 growth is reconstructed well by assimilating data products; retrospective predictions show high confidence in predicting changes in the next year. The Earth system predictions provide valuable inputs for understanding the global carbon cycle and informing climate-relevant policy.
Cathy Hohenegger, Peter Korn, Leonidas Linardakis, René Redler, Reiner Schnur, Panagiotis Adamidis, Jiawei Bao, Swantje Bastin, Milad Behravesh, Martin Bergemann, Joachim Biercamp, Hendryk Bockelmann, Renate Brokopf, Nils Brüggemann, Lucas Casaroli, Fatemeh Chegini, George Datseris, Monika Esch, Geet George, Marco Giorgetta, Oliver Gutjahr, Helmuth Haak, Moritz Hanke, Tatiana Ilyina, Thomas Jahns, Johann Jungclaus, Marcel Kern, Daniel Klocke, Lukas Kluft, Tobias Kölling, Luis Kornblueh, Sergey Kosukhin, Clarissa Kroll, Junhong Lee, Thorsten Mauritsen, Carolin Mehlmann, Theresa Mieslinger, Ann Kristin Naumann, Laura Paccini, Angel Peinado, Divya Sri Praturi, Dian Putrasahan, Sebastian Rast, Thomas Riddick, Niklas Roeber, Hauke Schmidt, Uwe Schulzweida, Florian Schütte, Hans Segura, Radomyra Shevchenko, Vikram Singh, Mia Specht, Claudia Christine Stephan, Jin-Song von Storch, Raphaela Vogel, Christian Wengel, Marius Winkler, Florian Ziemen, Jochem Marotzke, and Bjorn Stevens
Geosci. Model Dev., 16, 779–811, https://doi.org/10.5194/gmd-16-779-2023, https://doi.org/10.5194/gmd-16-779-2023, 2023
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Models of the Earth system used to understand climate and predict its change typically employ a grid spacing of about 100 km. Yet, many atmospheric and oceanic processes occur on much smaller scales. In this study, we present a new model configuration designed for the simulation of the components of the Earth system and their interactions at kilometer and smaller scales, allowing an explicit representation of the main drivers of the flow of energy and matter by solving the underlying equations.
Shuang Gao, Jörg Schwinger, Jerry Tjiputra, Ingo Bethke, Jens Hartmann, Emilio Mayorga, and Christoph Heinze
Biogeosciences, 20, 93–119, https://doi.org/10.5194/bg-20-93-2023, https://doi.org/10.5194/bg-20-93-2023, 2023
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We assess the impact of riverine nutrients and carbon (C) on projected marine primary production (PP) and C uptake using a fully coupled Earth system model. Riverine inputs alleviate nutrient limitation and thus lessen the projected PP decline by up to 0.7 Pg C yr−1 globally. The effect of increased riverine C may be larger than the effect of nutrient inputs in the future on the projected ocean C uptake, while in the historical period increased nutrient inputs are considered the largest driver.
Leonidas Linardakis, Irene Stemmler, Moritz Hanke, Lennart Ramme, Fatemeh Chegini, Tatiana Ilyina, and Peter Korn
Geosci. Model Dev., 15, 9157–9176, https://doi.org/10.5194/gmd-15-9157-2022, https://doi.org/10.5194/gmd-15-9157-2022, 2022
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In Earth system modelling, we are facing the challenge of making efficient use of very large machines, with millions of cores. To meet this challenge we will need to employ multi-level and multi-dimensional parallelism. Component concurrency, being a function parallel technique, offers an additional dimension to the traditional data-parallel approaches. In this paper we examine the behaviour of component concurrency and identify the conditions for its optimal application.
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
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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.
Mateo Duque-Villegas, Martin Claussen, Victor Brovkin, and Thomas Kleinen
Clim. Past, 18, 1897–1914, https://doi.org/10.5194/cp-18-1897-2022, https://doi.org/10.5194/cp-18-1897-2022, 2022
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Using an Earth system model of intermediate complexity, we quantify contributions of the Earth's orbit, greenhouse gases (GHGs) and ice sheets to the strength of Saharan greening during late Quaternary African humid periods (AHPs). Orbital forcing is found as the dominant factor, having a critical threshold and accounting for most of the changes in the vegetation response. However, results suggest that GHGs may influence the orbital threshold and thus may play a pivotal role for future AHPs.
Matteo Willeit, Andrey Ganopolski, Alexander Robinson, and Neil R. Edwards
Geosci. Model Dev., 15, 5905–5948, https://doi.org/10.5194/gmd-15-5905-2022, https://doi.org/10.5194/gmd-15-5905-2022, 2022
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In this paper we present the climate component of the newly developed fast Earth system model CLIMBER-X. It has a horizontal resolution of 5°x5° and is designed to simulate the evolution of the Earth system on temporal scales ranging from decades to >100 000 years. CLIMBER-X is available as open-source code and is expected to be a useful tool for studying past climate changes and for the investigation of the long-term future evolution of the climate.
Pradeebane Vaittinada Ayar, Laurent Bopp, Jim R. Christian, Tatiana Ilyina, John P. Krasting, Roland Séférian, Hiroyuki Tsujino, Michio Watanabe, Andrew Yool, and Jerry Tjiputra
Earth Syst. Dynam., 13, 1097–1118, https://doi.org/10.5194/esd-13-1097-2022, https://doi.org/10.5194/esd-13-1097-2022, 2022
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The El Niño–Southern Oscillation is the main driver for the natural variability of global atmospheric CO2. It modulates the CO2 fluxes in the tropical Pacific with anomalous CO2 influx during El Niño and outflux during La Niña. This relationship is projected to reverse by half of Earth system models studied here under the business-as-usual scenario. This study shows models that simulate a positive bias in surface carbonate concentrations simulate a shift in the ENSO–CO2 flux relationship.
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
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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.
Stiig Wilkenskjeld, Frederieke Miesner, Paul P. Overduin, Matteo Puglini, and Victor Brovkin
The Cryosphere, 16, 1057–1069, https://doi.org/10.5194/tc-16-1057-2022, https://doi.org/10.5194/tc-16-1057-2022, 2022
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Thawing permafrost releases carbon to the atmosphere, enhancing global warming. Part of the permafrost soils have been flooded by rising sea levels since the last ice age, becoming subsea permafrost (SSPF). The SSPF is less studied than the part on land. In this study we use a global model to obtain rates of thawing of SSPF under different future climate scenarios until the year 3000. After the year 2100 the scenarios strongly diverge, closely connected to the eventual disappearance of sea ice.
Thomas Extier, Katharina D. Six, Bo Liu, Hanna Paulsen, and Tatiana Ilyina
Clim. Past, 18, 273–292, https://doi.org/10.5194/cp-18-273-2022, https://doi.org/10.5194/cp-18-273-2022, 2022
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The role of land–sea fluxes during deglacial flooding in ocean biogeochemistry and CO2 exchange remains poorly constrained due to the lack of climate models that consider such fluxes. We implement the terrestrial organic matter fluxes into the ocean at a transiently changing land–sea interface in MPI-ESM and investigate their effect during the last deglaciation. Most of the terrestrial carbon goes to the ocean during flooding events of Meltwater Pulse 1a, which leads to regional CO2 outgassing.
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
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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.
Stefanie Talento and Andrey Ganopolski
Earth Syst. Dynam., 12, 1275–1293, https://doi.org/10.5194/esd-12-1275-2021, https://doi.org/10.5194/esd-12-1275-2021, 2021
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We propose a model for glacial cycles and produce an assessment of possible trajectories for the next 1 million years. Under natural conditions, the next glacial inception would most likely occur ∼50 kyr after present. We show that fossil-fuel CO2 releases can have an extremely long-term effect. Potentially achievable CO2 anthropogenic emissions during the next centuries will most likely provoke ice-free conditions in the Northern Hemisphere landmasses throughout the next half a million years.
Aaron Spring, István Dunkl, Hongmei Li, Victor Brovkin, and Tatiana Ilyina
Earth Syst. Dynam., 12, 1139–1167, https://doi.org/10.5194/esd-12-1139-2021, https://doi.org/10.5194/esd-12-1139-2021, 2021
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Numerical carbon cycle prediction models usually do not start from observed carbon states due to sparse observations. Instead, only physical climate is reconstructed, assuming that the carbon cycle follows indirectly. Here, we test in an idealized framework how well this indirect and direct reconstruction with perfect observations works. We find that indirect reconstruction works quite well and that improvements from the direct method are limited, strengthening the current indirect use.
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
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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.
Bo Liu, Katharina D. Six, and Tatiana Ilyina
Biogeosciences, 18, 4389–4429, https://doi.org/10.5194/bg-18-4389-2021, https://doi.org/10.5194/bg-18-4389-2021, 2021
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We incorporate a new representation of the stable carbon isotope 13C in a global ocean biogeochemistry model. The model well reproduces the present-day 13C observations. We find a recent observation-based estimate of the oceanic 13C Suess effect (the decrease in 13C/12C ratio due to uptake of anthropogenic CO2; 13CSE) possibly underestimates 13CSE by 0.1–0.26 per mil. The new model will aid in better understanding the past ocean state via comparison to 13C/12C measurements from sediment cores.
Guy Munhoven
Geosci. Model Dev., 14, 4225–4240, https://doi.org/10.5194/gmd-14-4225-2021, https://doi.org/10.5194/gmd-14-4225-2021, 2021
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SolveSAPHE (Munhoven, 2013) was the first package to calculate pH reliably from any physically sensible pair of total alkalinity (AlkT) and dissolved inorganic carbon (CT) data and to do so in an autonomous and efficient way. Here, we extend it to use CO2, HCO3 or CO3 instead of CT. For each one of these pairs, the new SolveSAPHE calculates all of the possible pH values (0, 1, or 2), again without any prior knowledge of the solutions.
Guy Munhoven
Geosci. Model Dev., 14, 3603–3631, https://doi.org/10.5194/gmd-14-3603-2021, https://doi.org/10.5194/gmd-14-3603-2021, 2021
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Sea-floor sediments play an important role in biogeochemical cycling of elements (e.g. carbon, silicon, nutrients) in the ocean. Realistic sediment modules are, however, not yet commonly used in global ocean biogeochemical models. Here we present MEDUSA, a model of the processes taking place in the surface sea-floor sediments which control the interaction between the sediments and the ocean. MEDUSA can be configured to meet the exact needs of any given ocean biogeochemical model.
Anne L. Morée, Jörg Schwinger, Ulysses S. Ninnemann, Aurich Jeltsch-Thömmes, Ingo Bethke, and Christoph Heinze
Clim. Past, 17, 753–774, https://doi.org/10.5194/cp-17-753-2021, https://doi.org/10.5194/cp-17-753-2021, 2021
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This modeling study of the Last Glacial Maximum (LGM, ~ 21 000 years ago) ocean explores the biological and physical changes in the ocean needed to satisfy marine proxy records, with a focus on the carbon isotope 13C. We estimate that the LGM ocean may have been up to twice as efficient at sequestering carbon and nutrients at depth as compared to preindustrial times. Our work shows that both circulation and biogeochemical changes must have occurred between the LGM and preindustrial times.
Philipp de Vrese, Tobias Stacke, Thomas Kleinen, and Victor Brovkin
The Cryosphere, 15, 1097–1130, https://doi.org/10.5194/tc-15-1097-2021, https://doi.org/10.5194/tc-15-1097-2021, 2021
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With large amounts of carbon stored in frozen soils and a highly energy-limited vegetation the Arctic is very sensitive to changes in climate. Here our simulations with the land surface model JSBACH reveal a number of offsetting factors moderating the Arctic's net response to global warming. More importantly we find that the effects of climate change may not be fully reversible on decadal timescales, leading to substantially different CH4 emissions depending on whether the Arctic warms or cools.
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
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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.
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
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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.
Øyvind Seland, Mats Bentsen, Dirk Olivié, Thomas Toniazzo, Ada Gjermundsen, Lise Seland Graff, Jens Boldingh Debernard, Alok Kumar Gupta, Yan-Chun He, Alf Kirkevåg, Jörg Schwinger, Jerry Tjiputra, Kjetil Schanke Aas, Ingo Bethke, Yuanchao Fan, Jan Griesfeller, Alf Grini, Chuncheng Guo, Mehmet Ilicak, Inger Helene Hafsahl Karset, Oskar Landgren, Johan Liakka, Kine Onsum Moseid, Aleksi Nummelin, Clemens Spensberger, Hui Tang, Zhongshi Zhang, Christoph Heinze, Trond Iversen, and Michael Schulz
Geosci. Model Dev., 13, 6165–6200, https://doi.org/10.5194/gmd-13-6165-2020, https://doi.org/10.5194/gmd-13-6165-2020, 2020
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The second version of the coupled Norwegian Earth System Model (NorESM2) is presented and evaluated. The temperature and precipitation patterns has improved compared to NorESM1. The model reaches present-day warming levels to within 0.2 °C of observed temperature but with a delayed warming during the late 20th century. Under the four scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5), the warming in the period of 2090–2099 compared to 1850–1879 reaches 1.3, 2.2, 3.1, and 3.9 K.
Lena R. Boysen, Victor Brovkin, Julia Pongratz, David M. Lawrence, Peter Lawrence, Nicolas Vuichard, Philippe Peylin, Spencer Liddicoat, Tomohiro Hajima, Yanwu Zhang, Matthias Rocher, Christine Delire, Roland Séférian, Vivek K. Arora, Lars Nieradzik, Peter Anthoni, Wim Thiery, Marysa M. Laguë, Deborah Lawrence, and Min-Hui Lo
Biogeosciences, 17, 5615–5638, https://doi.org/10.5194/bg-17-5615-2020, https://doi.org/10.5194/bg-17-5615-2020, 2020
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We find a biogeophysically induced global cooling with strong carbon losses in a 20 million square kilometre idealized deforestation experiment performed by nine CMIP6 Earth system models. It takes many decades for the temperature signal to emerge, with non-local effects playing an important role. Despite a consistent experimental setup, models diverge substantially in their climate responses. This study offers unprecedented insights for understanding land use change effects in CMIP6 models.
Dipayan Choudhury, Axel Timmermann, Fabian Schloesser, Malte Heinemann, and David Pollard
Clim. Past, 16, 2183–2201, https://doi.org/10.5194/cp-16-2183-2020, https://doi.org/10.5194/cp-16-2183-2020, 2020
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Our study is the first study to conduct transient simulations over MIS 7, using a 3-D coupled climate–ice sheet model with interactive ice sheets in both hemispheres. We find glacial inceptions to be more sensitive to orbital variations, whereas glacial terminations need the concerted action of both orbital and CO2 forcings. We highlight the issue of multiple equilibria and an instability due to stationary-wave–topography feedback that can trigger unrealistic North American ice sheet growth.
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
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
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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.
Lester Kwiatkowski, Olivier Torres, Laurent Bopp, Olivier Aumont, Matthew Chamberlain, James R. Christian, John P. Dunne, Marion Gehlen, Tatiana Ilyina, Jasmin G. John, Andrew Lenton, Hongmei Li, Nicole S. Lovenduski, James C. Orr, Julien Palmieri, Yeray Santana-Falcón, Jörg Schwinger, Roland Séférian, Charles A. Stock, Alessandro Tagliabue, Yohei Takano, Jerry Tjiputra, Katsuya Toyama, Hiroyuki Tsujino, Michio Watanabe, Akitomo Yamamoto, Andrew Yool, and Tilo Ziehn
Biogeosciences, 17, 3439–3470, https://doi.org/10.5194/bg-17-3439-2020, https://doi.org/10.5194/bg-17-3439-2020, 2020
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We assess 21st century projections of marine biogeochemistry in the CMIP6 Earth system models. These models represent the most up-to-date understanding of climate change. The models generally project greater surface ocean warming, acidification, subsurface deoxygenation, and euphotic nitrate reductions but lesser primary production declines than the previous generation of models. This has major implications for the impact of anthropogenic climate change on marine ecosystems.
Matteo Puglini, Victor Brovkin, Pierre Regnier, and Sandra Arndt
Biogeosciences, 17, 3247–3275, https://doi.org/10.5194/bg-17-3247-2020, https://doi.org/10.5194/bg-17-3247-2020, 2020
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A reaction-transport model to assess the potential non-turbulent methane flux from the East Siberian Arctic sediments to water columns is applied here. We show that anaerobic oxidation of methane (AOM) is an efficient filter except for high values of sedimentation rate and advective flow, which enable considerable non-turbulent steady-state methane fluxes. Significant transient methane fluxes can also occur during the building-up phase of the AOM-performing biomass microbial community.
Andrew H. MacDougall, Thomas L. Frölicher, Chris D. Jones, Joeri Rogelj, H. Damon Matthews, Kirsten Zickfeld, Vivek K. Arora, Noah J. Barrett, Victor Brovkin, Friedrich A. Burger, Micheal Eby, Alexey V. Eliseev, Tomohiro Hajima, Philip B. Holden, Aurich Jeltsch-Thömmes, Charles Koven, Nadine Mengis, Laurie Menviel, Martine Michou, Igor I. Mokhov, Akira Oka, Jörg Schwinger, Roland Séférian, Gary Shaffer, Andrei Sokolov, Kaoru Tachiiri, Jerry Tjiputra, Andrew Wiltshire, and Tilo Ziehn
Biogeosciences, 17, 2987–3016, https://doi.org/10.5194/bg-17-2987-2020, https://doi.org/10.5194/bg-17-2987-2020, 2020
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The Zero Emissions Commitment (ZEC) is the change in global temperature expected to occur following the complete cessation of CO2 emissions. Here we use 18 climate models to assess the value of ZEC. For our experiment we find that ZEC 50 years after emissions cease is between −0.36 to +0.29 °C. The most likely value of ZEC is assessed to be close to zero. However, substantial continued warming for decades or centuries following cessation of CO2 emission cannot be ruled out.
Jerry F. Tjiputra, Jörg Schwinger, Mats Bentsen, Anne L. Morée, Shuang Gao, Ingo Bethke, Christoph Heinze, Nadine Goris, Alok Gupta, Yan-Chun He, Dirk Olivié, Øyvind Seland, and Michael Schulz
Geosci. Model Dev., 13, 2393–2431, https://doi.org/10.5194/gmd-13-2393-2020, https://doi.org/10.5194/gmd-13-2393-2020, 2020
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Ocean biogeochemistry plays an important role in determining the atmospheric carbon dioxide concentration. Earth system models, which are regularly used to study and project future climate change, generally include an ocean biogeochemistry component. Prior to their application, such models are rigorously validated against real-world observations. In this study, we evaluate the ability of the ocean biogeochemistry in the Norwegian Earth System Model version 2 to simulate various datasets.
Wagner de Oliveira Garcia, Thorben Amann, Jens Hartmann, Kristine Karstens, Alexander Popp, Lena R. Boysen, Pete Smith, and Daniel Goll
Biogeosciences, 17, 2107–2133, https://doi.org/10.5194/bg-17-2107-2020, https://doi.org/10.5194/bg-17-2107-2020, 2020
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Biomass-based terrestrial negative emission technologies (tNETS) have high potential to sequester CO2. Many CO2 uptake estimates do not include the effect of nutrient deficiencies in soils on biomass production. We show that nutrients can be partly resupplied by enhanced weathering (EW) rock powder application, increasing the effectiveness of tNETs. Depending on the deployed amounts of rock powder, EW could also improve soil hydrology, adding a new dimension to the coupling of tNETs with EW.
Joeran Maerz, Katharina D. Six, Irene Stemmler, Soeren Ahmerkamp, and Tatiana Ilyina
Biogeosciences, 17, 1765–1803, https://doi.org/10.5194/bg-17-1765-2020, https://doi.org/10.5194/bg-17-1765-2020, 2020
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Marine micro-algae bind carbon dioxide, CO2. During their decay, snowflake-like aggregates form that sink, remineralize and transport organically bound CO2 to depth; this is referred to as the biological carbon pump. In our model study, we elucidate how variable aggregate composition impacts the global pattern of vertical carbon fluxes. Our mechanistic model approach advances the representation of the global biological carbon pump and promotes a more realistic projection under climate change.
Thomas Kleinen, Uwe Mikolajewicz, and Victor Brovkin
Clim. Past, 16, 575–595, https://doi.org/10.5194/cp-16-575-2020, https://doi.org/10.5194/cp-16-575-2020, 2020
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We investigate the changes in natural methane emissions between the Last Glacial Maximum and preindustrial periods with a methane-enabled version of MPI-ESM. We consider all natural sources of methane except for emissions from wild animals and geological sources. Changes are dominated by changes in tropical wetland emissions, high-latitude wetlands play a secondary role, and all other natural sources are of minor importance. We explain the changes in ice core methane by methane emissions only.
Takasumi Kurahashi-Nakamura, André Paul, Guy Munhoven, Ute Merkel, and Michael Schulz
Geosci. Model Dev., 13, 825–840, https://doi.org/10.5194/gmd-13-825-2020, https://doi.org/10.5194/gmd-13-825-2020, 2020
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Chemical processes in ocean-floor sediments have a large influence on the marine carbon cycle, hence the global climate, at long timescales. We developed a new coupling scheme for a chemical sediment model and a comprehensive climate model. The new coupled model outperformed the original uncoupled climate model in reproducing the global distribution of sediment properties. The sediment model will also act as a
bridgebetween the ocean model and paleoceanographic data.
Thorben Amann, Jens Hartmann, Eric Struyf, Wagner de Oliveira Garcia, Elke K. Fischer, Ivan Janssens, Patrick Meire, and Jonas Schoelynck
Biogeosciences, 17, 103–119, https://doi.org/10.5194/bg-17-103-2020, https://doi.org/10.5194/bg-17-103-2020, 2020
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Weathering is a major control on atmospheric CO2 at geologic timescales. Enhancement of this process can be used to actively remove CO2 from the atmosphere. Field results are still scarce and with this experiment we try to add some near-natural insights into dissolution processes. Results show CO2 sequestration potentials but also highlight the strong variability of outcomes that can be expected in natural environments. Such experiments are of the utmost importance to identify key processes.
Fabrice Lacroix, Tatiana Ilyina, and Jens Hartmann
Biogeosciences, 17, 55–88, https://doi.org/10.5194/bg-17-55-2020, https://doi.org/10.5194/bg-17-55-2020, 2020
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Contributions of rivers to the oceanic cycling of carbon have been poorly represented in global models until now. Here, we assess the long–term implications of preindustrial riverine loads in the ocean in a novel framework which estimates the loads through a hierarchy of weathering and land–ocean export models. We investigate their impacts for the oceanic biological production and air–sea carbon flux. Finally, we assess the potential incorporation of the framework in an Earth system model.
Georgii A. Alexandrov, Victor A. Brovkin, Thomas Kleinen, and Zicheng Yu
Biogeosciences, 17, 47–54, https://doi.org/10.5194/bg-17-47-2020, https://doi.org/10.5194/bg-17-47-2020, 2020
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
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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.
Chris D. Jones, Thomas L. Frölicher, Charles Koven, Andrew H. MacDougall, H. Damon Matthews, Kirsten Zickfeld, Joeri Rogelj, Katarzyna B. Tokarska, Nathan P. Gillett, Tatiana Ilyina, Malte Meinshausen, Nadine Mengis, Roland Séférian, Michael Eby, and Friedrich A. Burger
Geosci. Model Dev., 12, 4375–4385, https://doi.org/10.5194/gmd-12-4375-2019, https://doi.org/10.5194/gmd-12-4375-2019, 2019
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Global warming is simply related to the total emission of CO2 allowing us to define a carbon budget. However, information on the Zero Emissions Commitment is a key missing link to assess remaining carbon budgets to achieve the climate targets of the Paris Agreement. It was therefore decided that a small targeted MIP activity to fill this knowledge gap would be extremely valuable. This article formalises the experimental design alongside the other CMIP6 documentation papers.
Michelle Tigchelaar, Axel Timmermann, Tobias Friedrich, Malte Heinemann, and David Pollard
The Cryosphere, 13, 2615–2631, https://doi.org/10.5194/tc-13-2615-2019, https://doi.org/10.5194/tc-13-2615-2019, 2019
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The Antarctic Ice Sheet has expanded and retracted often in the past, but, so far, studies have not identified which environmental driver is most important: air temperature, snowfall, ocean conditions or global sea level. In a modeling study of 400 000 years of Antarctic Ice Sheet variability we isolated different drivers and found that no single driver dominates. Air temperature and sea level are most important and combine in a synergistic way, with important implications for future change.
Johanna Beckmann, Mahé Perrette, Sebastian Beyer, Reinhard Calov, Matteo Willeit, and Andrey Ganopolski
The Cryosphere, 13, 2281–2301, https://doi.org/10.5194/tc-13-2281-2019, https://doi.org/10.5194/tc-13-2281-2019, 2019
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Submarine melting (SM) has been discussed as potentially triggering the recently observed retreat at outlet glaciers in Greenland. How much it may contribute in terms of future sea level rise (SLR) has not been quantified yet. When accounting for SM in our experiments, SLR contribution of 12 outlet glaciers increases by over 3-fold until the year 2100 under RCP8.5. Scaling up from 12 to all of Greenland's outlet glaciers increases future SLR contribution of Greenland by 50 %.
Alexander J. Winkler, Ranga B. Myneni, and Victor Brovkin
Earth Syst. Dynam., 10, 501–523, https://doi.org/10.5194/esd-10-501-2019, https://doi.org/10.5194/esd-10-501-2019, 2019
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The concept of
emergent constraintsis a key method to reduce uncertainty in multi-model climate projections using historical simulations and observations. Here, we present an in-depth analysis of the applicability of the method and uncover possible limitations. Key limitations are a lack of comparability (temporal, spatial, and conceptual) between models and observations and the disagreement between models on system dynamics throughout different levels of atmospheric CO2 concentration.
Thorben Amann and Jens Hartmann
Biogeosciences, 16, 2949–2960, https://doi.org/10.5194/bg-16-2949-2019, https://doi.org/10.5194/bg-16-2949-2019, 2019
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With the recent publication of the IPCC special report on the 1.5 °C target and increased attention on carbon dioxide removal (CDR) technologies, we think it is time to advance from the current way of looking at specific strategies to a more holistic CDR perspective, since multiple "side effects" may lead to additional CO2 uptake into different carbon pools. This paper explores potential co-benefits between terrestrial CDR strategies to facilitate a maximum CO2 sequestration effect.
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
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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.
Victor Brovkin, Stephan Lorenz, Thomas Raddatz, Tatiana Ilyina, Irene Stemmler, Matthew Toohey, and Martin Claussen
Biogeosciences, 16, 2543–2555, https://doi.org/10.5194/bg-16-2543-2019, https://doi.org/10.5194/bg-16-2543-2019, 2019
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Mechanisms of atmospheric CO2 growth by 20 ppm from 6000 BCE to the pre-industrial period are still uncertain. We apply the Earth system model MPI-ESM-LR for two transient simulations of the climate–carbon cycle. An additional process, e.g. carbonate accumulation on shelves, is required for consistency with ice-core CO2 data. Our simulations support the hypothesis that the ocean was a source of CO2 until the late Holocene when anthropogenic CO2 sources started to affect atmospheric CO2.
Malte Heinemann, Joachim Segschneider, and Birgit Schneider
Geosci. Model Dev., 12, 1869–1883, https://doi.org/10.5194/gmd-12-1869-2019, https://doi.org/10.5194/gmd-12-1869-2019, 2019
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Ocean CO2 uptake played a crucial role for the global cooling during ice ages. Dust formation, e.g. by ice scraping over bedrock, potentially contributed to this CO2 uptake because (1) the iron in the dust is a fertilizer and (2) the heavy dust particles can accelerate sinking organic matter (ballasting hypothesis). This study tests the glacial dust ballasting hypothesis for the first time, using an ocean model. It turns out, however, that the ballasting effect probably played a minor role.
Anne Dallmeyer, Martin Claussen, and Victor Brovkin
Clim. Past, 15, 335–366, https://doi.org/10.5194/cp-15-335-2019, https://doi.org/10.5194/cp-15-335-2019, 2019
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A simple but powerful method for the biomisation of plant functional type distributions is introduced and tested for six different dynamic global vegetation models based on pre-industrial and palaeo-simulations. The method facilitates the direct comparison between vegetation distributions simulated by different Earth system models and between model results and the pollen-based biome reconstructions. It is therefore a powerful tool for the evaluation of Earth system models.
Christoph Heinze and Klaus Hasselmann
Biogeosciences, 16, 751–753, https://doi.org/10.5194/bg-16-751-2019, https://doi.org/10.5194/bg-16-751-2019, 2019
Janine Börker, Jens Hartmann, Gibran Romero-Mujalli, and Gaojun Li
Earth Surf. Dynam., 7, 191–197, https://doi.org/10.5194/esurf-7-191-2019, https://doi.org/10.5194/esurf-7-191-2019, 2019
Thomas Schneider von Deimling, Thomas Kleinen, Gustaf Hugelius, Christian Knoblauch, Christian Beer, and Victor Brovkin
Clim. Past, 14, 2011–2036, https://doi.org/10.5194/cp-14-2011-2018, https://doi.org/10.5194/cp-14-2011-2018, 2018
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Past cold ice age temperatures and the subsequent warming towards the Holocene had large consequences for soil organic carbon (SOC) stored in perennially frozen grounds. Using an Earth system model we show how the spread in areas affected by permafrost have changed under deglacial warming, along with changes in SOC accumulation. Our model simulations suggest phases of circum-Arctic permafrost SOC gain and losses, with a net increase in SOC between the last glacial maximum and the pre-industrial.
Hanna Paulsen, Tatiana Ilyina, Johann H. Jungclaus, Katharina D. Six, and Irene Stemmler
Earth Syst. Dynam., 9, 1283–1300, https://doi.org/10.5194/esd-9-1283-2018, https://doi.org/10.5194/esd-9-1283-2018, 2018
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We use an Earth system model to study the effects of light absorption by marine cyanobacteria on climate. We find that cyanobacteria have a considerable cooling effect on tropical SST with implications for ocean and atmosphere circulation patterns as well as for climate variability. The results indicate the importance of considering phytoplankton light absorption in climate models, and specifically highlight the role of cyanobacteria due to their regulative effect on tropical SST and climate.
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
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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.
Anne L. Morée, Jörg Schwinger, and Christoph Heinze
Biogeosciences, 15, 7205–7223, https://doi.org/10.5194/bg-15-7205-2018, https://doi.org/10.5194/bg-15-7205-2018, 2018
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Changes in the distribution of the carbon isotope 13C can be used to study the climate system if the governing processes (ocean circulation and biogeochemistry) are understood. We show the Southern Ocean importance for the global 13C distribution and that changes in 13C can be strongly influenced by biogeochemistry. Interpretation of 13C as a proxy for climate signals needs to take into account the effects of changes in biogeochemistry in addition to changes in ocean circulation.
Thomas Riddick, Victor Brovkin, Stefan Hagemann, and Uwe Mikolajewicz
Geosci. Model Dev., 11, 4291–4316, https://doi.org/10.5194/gmd-11-4291-2018, https://doi.org/10.5194/gmd-11-4291-2018, 2018
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During the Last Glacial Maximum, many rivers were blocked by the presence of large ice sheets and thus found new routes to the sea. This resulted in changes in the pattern of freshwater discharge into the oceans and thus would have significantly affected ocean circulation. Also, rivers found routes across the vast exposed continental shelves to the lower coastlines of that time. We propose a model for such changes in river routing suitable for use in wider models of the last glacial cycle.
Reinhard Calov, Sebastian Beyer, Ralf Greve, Johanna Beckmann, Matteo Willeit, Thomas Kleiner, Martin Rückamp, Angelika Humbert, and Andrey Ganopolski
The Cryosphere, 12, 3097–3121, https://doi.org/10.5194/tc-12-3097-2018, https://doi.org/10.5194/tc-12-3097-2018, 2018
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We present RCP 4.5 and 8.5 projections for the Greenland glacial system with the new glacial system model IGLOO 1.0, which incorporates the ice sheet model SICOPOLIS 3.3, a model of basal hydrology and a parameterization of submarine melt of outlet glaciers. Surface temperature and mass balance anomalies from the MAR climate model serve as forcing delivering projections for the contribution of the Greenland ice sheet to sea level rise and submarine melt of Helheim and Store outlet glaciers.
Yilong Wang, Philippe Ciais, Daniel Goll, Yuanyuan Huang, Yiqi Luo, Ying-Ping Wang, A. Anthony Bloom, Grégoire Broquet, Jens Hartmann, Shushi Peng, Josep Penuelas, Shilong Piao, Jordi Sardans, Benjamin D. Stocker, Rong Wang, Sönke Zaehle, and Sophie Zechmeister-Boltenstern
Geosci. Model Dev., 11, 3903–3928, https://doi.org/10.5194/gmd-11-3903-2018, https://doi.org/10.5194/gmd-11-3903-2018, 2018
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We present a new modeling framework called Global Observation-based Land-ecosystems Utilization Model of Carbon, Nitrogen and Phosphorus (GOLUM-CNP) that combines a data-constrained C-cycle analysis with data-driven estimates of N and P inputs and losses and with observed stoichiometric ratios. GOLUM-CNP provides a traceable tool, where a consistency between different datasets of global C, N, and P cycles has been achieved.
Christoph Heinze, Tatiana Ilyina, and Marion Gehlen
Biogeosciences, 15, 3521–3539, https://doi.org/10.5194/bg-15-3521-2018, https://doi.org/10.5194/bg-15-3521-2018, 2018
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The ocean becomes increasingly acidified through uptake of additional man-made CO2 from the atmosphere. This is impacting ecosystems. In order to find out whether reduced biological production of calcium carbonate shell material of biota is occurring at a large scale, we carried out a model study simulating the changes in oceanic 230Th concentrations with reduced availability of calcium carbonate particles in the water. 230Th can serve as a useful magnifying glass for acidification impacts.
Matteo Willeit and Andrey Ganopolski
Clim. Past, 14, 697–707, https://doi.org/10.5194/cp-14-697-2018, https://doi.org/10.5194/cp-14-697-2018, 2018
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The surface energy and mass balance of ice sheets strongly depends on surface albedo. Here, using an Earth system model of intermediate complexity, we explore the role played by surface albedo for the simulation of glacial cycles. We show that the evolution of the Northern Hemisphere ice sheets over the last glacial cycle is very sensitive to the parameterization of snow grain size and the effect of dust deposition on snow albedo.
Sandy P. Harrison, Patrick J. Bartlein, Victor Brovkin, Sander Houweling, Silvia Kloster, and I. Colin Prentice
Earth Syst. Dynam., 9, 663–677, https://doi.org/10.5194/esd-9-663-2018, https://doi.org/10.5194/esd-9-663-2018, 2018
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Temperature affects fire occurrence and severity. Warming will increase fire-related carbon emissions and thus atmospheric CO2. The size of this feedback is not known. We use charcoal records to estimate pre-industrial fire emissions and a simple land–biosphere model to quantify the feedback. We infer a feedback strength of 5.6 3.2 ppm CO2 per degree of warming and a gain of 0.09 ± 0.05 for a climate sensitivity of 2.8 K. Thus, fire feedback is a large part of the climate–carbon-cycle feedback.
Ji-Hyung Park, Omme K. Nayna, Most S. Begum, Eliyan Chea, Jens Hartmann, Richard G. Keil, Sanjeev Kumar, Xixi Lu, Lishan Ran, Jeffrey E. Richey, Vedula V. S. S. Sarma, Shafi M. Tareq, Do Thi Xuan, and Ruihong Yu
Biogeosciences, 15, 3049–3069, https://doi.org/10.5194/bg-15-3049-2018, https://doi.org/10.5194/bg-15-3049-2018, 2018
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Human activities are drastically altering water and material flows in river systems across Asia. This review provides a conceptual framework for assessing the human impacts on Asian river C fluxes and an update on anthropogenic alterations of riverine C fluxes, focusing on the impacts of water pollution and river impoundments on CO2 outgassing from the rivers draining South, Southeast, and East Asian regions that account for the largest fraction of river discharge and C exports from Asia.
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
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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.
Johanna Beckmann, Mahé Perrette, and Andrey Ganopolski
The Cryosphere, 12, 301–323, https://doi.org/10.5194/tc-12-301-2018, https://doi.org/10.5194/tc-12-301-2018, 2018
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Greenland's glaciers that are in contact with the ocean undergo a special ice–ocean melting. To project numerically Greenland's centennial contribution to sea level rise, it is crucial to incorporate this special melting. We demonstrate that a numerically cheap model shows the qualitative same behavior as numerical expensive 2–3-dimensional models and calculates the same melting as empirical data show. Our analytical solution gives some insight in the yet poorly understood melting behavior.
Maarit Raivonen, Sampo Smolander, Leif Backman, Jouni Susiluoto, Tuula Aalto, Tiina Markkanen, Jarmo Mäkelä, Janne Rinne, Olli Peltola, Mika Aurela, Annalea Lohila, Marin Tomasic, Xuefei Li, Tuula Larmola, Sari Juutinen, Eeva-Stiina Tuittila, Martin Heimann, Sanna Sevanto, Thomas Kleinen, Victor Brovkin, and Timo Vesala
Geosci. Model Dev., 10, 4665–4691, https://doi.org/10.5194/gmd-10-4665-2017, https://doi.org/10.5194/gmd-10-4665-2017, 2017
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Wetlands are one of the most significant natural sources of the strong greenhouse gas methane. We developed a model that can be used within a larger wetland carbon model to simulate the methane emissions. In this study, we present the model and results of its testing. We found that the model works well with different settings and that the results depend primarily on the rate of input anoxic soil respiration and also on factors that affect the simulated oxygen concentrations in the wetland soil.
Andrey Ganopolski and Victor Brovkin
Clim. Past, 13, 1695–1716, https://doi.org/10.5194/cp-13-1695-2017, https://doi.org/10.5194/cp-13-1695-2017, 2017
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Ice cores reveal that atmospheric CO2 concentration varied synchronously with the global ice volume. Explaining the mechanism of glacial–interglacial variations of atmospheric CO2 concentrations and the link between CO2 and ice sheets evolution still remains a challenge. Here using the Earth system model of intermediate complexity we performed for the first time simulations of co-evolution of climate, ice sheets and carbon cycle using the astronomical forcing as the only external forcing.
Jakob Zscheischler, Miguel D. Mahecha, Valerio Avitabile, Leonardo Calle, Nuno Carvalhais, Philippe Ciais, Fabian Gans, Nicolas Gruber, Jens Hartmann, Martin Herold, Kazuhito Ichii, Martin Jung, Peter Landschützer, Goulven G. Laruelle, Ronny Lauerwald, Dario Papale, Philippe Peylin, Benjamin Poulter, Deepak Ray, Pierre Regnier, Christian Rödenbeck, Rosa M. Roman-Cuesta, Christopher Schwalm, Gianluca Tramontana, Alexandra Tyukavina, Riccardo Valentini, Guido van der Werf, Tristram O. West, Julie E. Wolf, and Markus Reichstein
Biogeosciences, 14, 3685–3703, https://doi.org/10.5194/bg-14-3685-2017, https://doi.org/10.5194/bg-14-3685-2017, 2017
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Here we synthesize a wide range of global spatiotemporal observational data on carbon exchanges between the Earth surface and the atmosphere. A key challenge was to consistently combining observational products of terrestrial and aquatic surfaces. Our primary goal is to identify today’s key uncertainties and observational shortcomings that would need to be addressed in future measurement campaigns or expansions of in situ observatories.
Jörg Schwinger, Jerry Tjiputra, Nadine Goris, Katharina D. Six, Alf Kirkevåg, Øyvind Seland, Christoph Heinze, and Tatiana Ilyina
Biogeosciences, 14, 3633–3648, https://doi.org/10.5194/bg-14-3633-2017, https://doi.org/10.5194/bg-14-3633-2017, 2017
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Transient global warming under the high emission scenario RCP8.5 is amplified by up to 6 % if a pH dependency of marine DMS production is assumed. Importantly, this additional warming is not spatially homogeneous but shows a pronounced north–south gradient. Over the Antarctic continent, the additional warming is almost twice the global average. In the Southern Ocean we find a small DMS–climate feedback that counteracts the original reduction of DMS production due to ocean acidification.
Eva Bauer and Andrey Ganopolski
Clim. Past, 13, 819–832, https://doi.org/10.5194/cp-13-819-2017, https://doi.org/10.5194/cp-13-819-2017, 2017
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Transient glacial cycle simulations with an EMIC and the PDD method require smaller melt factors for inception than for termination and larger factors for American than European ice sheets. The PDD online method with standard values simulates a sea level drop of 250 m at the LGM. The PDD online run reproducing the LGM ice volume has deficient ablation for reversing from glacial to interglacial climate, so termination is delayed. The SEB method with dust impact on snow albedo is seen as superior.
Mario Krapp, Alexander Robinson, and Andrey Ganopolski
The Cryosphere, 11, 1519–1535, https://doi.org/10.5194/tc-11-1519-2017, https://doi.org/10.5194/tc-11-1519-2017, 2017
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We present the snowpack model SEMIC. It calculates snow height, surface temperature, surface albedo, and the surface mass balance of snow- and ice-covered surfaces while using meteorological data as input. In this paper we describe how SEMIC works and how well it compares with snowpack data of a more sophisticated regional climate model applied to the Greenland ice sheet. Because of its simplicity and efficiency, SEMIC can be used as a coupling interface between atmospheric and ice sheet models.
Daniel S. Goll, Alexander J. Winkler, Thomas Raddatz, Ning Dong, Ian Colin Prentice, Philippe Ciais, and Victor Brovkin
Geosci. Model Dev., 10, 2009–2030, https://doi.org/10.5194/gmd-10-2009-2017, https://doi.org/10.5194/gmd-10-2009-2017, 2017
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The response of soil organic carbon decomposition to warming and the interactions between nitrogen and carbon cycling affect the feedbacks between the land carbon cycle and the climate. In the model JSBACH carbon–nitrogen interactions have only a small effect on the feedbacks, whereas modifications of soil organic carbon decomposition have a large effect. The carbon cycle in the improved model is more resilient to climatic changes than in previous version of the model.
Teresa Beaty, Christoph Heinze, Taylor Hughlett, and Arne M. E. Winguth
Biogeosciences, 14, 781–797, https://doi.org/10.5194/bg-14-781-2017, https://doi.org/10.5194/bg-14-781-2017, 2017
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In this study HAMOCC2.0 is used to address how mechanisms of oxygen minimum zone (OMZ) expansion respond to changes in CO2 radiative forcing within the model. Atmospheric pCO2 is increased at a rate of 1 % annually until stabilized. Our study suggests that expansion in the Pacific Ocean within the model is controlled largely by changes in particulate organic carbon export (POC). The vertical expansion of the OMZs in the Atlantic and Indian oceans is linked to reduced oxygen solubility.
Beniamino Abis and Victor Brovkin
Biogeosciences, 14, 511–527, https://doi.org/10.5194/bg-14-511-2017, https://doi.org/10.5194/bg-14-511-2017, 2017
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We study the link between the boreal tree-cover fraction distribution and eight globally observed environmental factors. We find that they exert a strong control over the tree-cover distribution, generally uniquely determining its state. Furthermore, we show the location of areas with potentially alternative tree-cover states under the same environmental conditions. These areas represent transition zones with reduced resilience, where the forest can shift between different vegetation states.
Marielle Saunois, Philippe Bousquet, Ben Poulter, Anna Peregon, Philippe Ciais, Josep G. Canadell, Edward J. Dlugokencky, Giuseppe Etiope, David Bastviken, Sander Houweling, Greet Janssens-Maenhout, Francesco N. Tubiello, Simona Castaldi, Robert B. Jackson, Mihai Alexe, Vivek K. Arora, David J. Beerling, Peter Bergamaschi, Donald R. Blake, Gordon Brailsford, Victor Brovkin, Lori Bruhwiler, Cyril Crevoisier, Patrick Crill, Kristofer Covey, Charles Curry, Christian Frankenberg, Nicola Gedney, Lena Höglund-Isaksson, Misa Ishizawa, Akihiko Ito, Fortunat Joos, Heon-Sook Kim, Thomas Kleinen, Paul Krummel, Jean-François Lamarque, Ray Langenfelds, Robin Locatelli, Toshinobu Machida, Shamil Maksyutov, Kyle C. McDonald, Julia Marshall, Joe R. Melton, Isamu Morino, Vaishali Naik, Simon O'Doherty, Frans-Jan W. Parmentier, Prabir K. Patra, Changhui Peng, Shushi Peng, Glen P. Peters, Isabelle Pison, Catherine Prigent, Ronald Prinn, Michel Ramonet, William J. Riley, Makoto Saito, Monia Santini, Ronny Schroeder, Isobel J. Simpson, Renato Spahni, Paul Steele, Atsushi Takizawa, Brett F. Thornton, Hanqin Tian, Yasunori Tohjima, Nicolas Viovy, Apostolos Voulgarakis, Michiel van Weele, Guido R. van der Werf, Ray Weiss, Christine Wiedinmyer, David J. Wilton, Andy Wiltshire, Doug Worthy, Debra Wunch, Xiyan Xu, Yukio Yoshida, Bowen Zhang, Zhen Zhang, and Qiuan Zhu
Earth Syst. Sci. Data, 8, 697–751, https://doi.org/10.5194/essd-8-697-2016, https://doi.org/10.5194/essd-8-697-2016, 2016
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An accurate assessment of the methane budget is important to understand the atmospheric methane concentrations and trends and to provide realistic pathways for climate change mitigation. The various and diffuse sources of methane as well and its oxidation by a very short lifetime radical challenge this assessment. We quantify the methane sources and sinks as well as their uncertainties based on both bottom-up and top-down approaches provided by a broad international scientific community.
Thomas Kleinen, Victor Brovkin, and Guy Munhoven
Clim. Past, 12, 2145–2160, https://doi.org/10.5194/cp-12-2145-2016, https://doi.org/10.5194/cp-12-2145-2016, 2016
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We investigate trends in atmospheric CO2 during three recent interglacials – the Holocene, the Eemian and MIS 11 – using an earth system model of intermediate complexity. Our model experiments show a considerable improvement in the modelled CO2 trends for all three interglacials if peat accumulation and shallow water CaCO3 sedimentation are included, forcing the model only with orbital and sea level changes. The Holocene CO2 trend requires anthropogenic emissions of CO2 only after 3 ka BP.
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
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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.
Matteo Willeit and Andrey Ganopolski
Geosci. Model Dev., 9, 3817–3857, https://doi.org/10.5194/gmd-9-3817-2016, https://doi.org/10.5194/gmd-9-3817-2016, 2016
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PALADYN is presented; it is a new comprehensive and computationally efficient land surface–vegetation–carbon cycle model designed to be used in Earth system models of intermediate complexity for long-term simulations and paleoclimate studies.
Sylvia S. Nyawira, Julia E. M. S. Nabel, Axel Don, Victor Brovkin, and Julia Pongratz
Biogeosciences, 13, 5661–5675, https://doi.org/10.5194/bg-13-5661-2016, https://doi.org/10.5194/bg-13-5661-2016, 2016
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We introduce an approach applicable to dynamic global vegetation models for evaluating simulated soil carbon changes from land-use changes against meta-analyses. The approach makes use of the large spatial coverage of the observations, and accounts for different ages of the sampled land-use transitions. The evaluation offers an opportunity for identifying causes of model–data discrepancies. Applied to the model JSBACH, we find that introducing crop harvest substantially improves the results.
Christoph Heinze, Babette A. A. Hoogakker, and Arne Winguth
Clim. Past, 12, 1949–1978, https://doi.org/10.5194/cp-12-1949-2016, https://doi.org/10.5194/cp-12-1949-2016, 2016
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Sensitivities of sediment tracers to changes in carbon cycle parameters were determined with a global ocean model. The sensitivities were combined with sediment and ice core data. The results suggest a drawdown of the sea surface temperature by 5 °C, an outgassing of the land biosphere by 430 Pg C, and a strengthening of the vertical carbon transfer by biological processes at the Last Glacial Maximum. A glacial change in marine calcium carbonate production can neither be proven nor rejected.
Stephen M. Griffies, Gokhan Danabasoglu, Paul J. Durack, Alistair J. Adcroft, V. Balaji, Claus W. Böning, Eric P. Chassignet, Enrique Curchitser, Julie Deshayes, Helge Drange, Baylor Fox-Kemper, Peter J. Gleckler, Jonathan M. Gregory, Helmuth Haak, Robert W. Hallberg, Patrick Heimbach, Helene T. Hewitt, David M. Holland, Tatiana Ilyina, Johann H. Jungclaus, Yoshiki Komuro, John P. Krasting, William G. Large, Simon J. Marsland, Simona Masina, Trevor J. McDougall, A. J. George Nurser, James C. Orr, Anna Pirani, Fangli Qiao, Ronald J. Stouffer, Karl E. Taylor, Anne Marie Treguier, Hiroyuki Tsujino, Petteri Uotila, Maria Valdivieso, Qiang Wang, Michael Winton, and Stephen G. Yeager
Geosci. Model Dev., 9, 3231–3296, https://doi.org/10.5194/gmd-9-3231-2016, https://doi.org/10.5194/gmd-9-3231-2016, 2016
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The Ocean Model Intercomparison Project (OMIP) aims to provide a framework for evaluating, understanding, and improving the ocean and sea-ice components of global climate and earth system models contributing to the Coupled Model Intercomparison Project Phase 6 (CMIP6). This document defines OMIP and details a protocol both for simulating global ocean/sea-ice models and for analysing their output.
Ana Bastos, Philippe Ciais, Jonathan Barichivich, Laurent Bopp, Victor Brovkin, Thomas Gasser, Shushi Peng, Julia Pongratz, Nicolas Viovy, and Cathy M. Trudinger
Biogeosciences, 13, 4877–4897, https://doi.org/10.5194/bg-13-4877-2016, https://doi.org/10.5194/bg-13-4877-2016, 2016
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The ice-core record shows a stabilisation of atmospheric CO2 in the 1940s, despite continued emissions from fossil fuel burning and land-use change (LUC). We use up-to-date reconstructions of the CO2 sources and sinks over the 20th century to evaluate whether these capture the CO2 plateau and to test the previously proposed hypothesis. Both strong terrestrial sink, possibly due to LUC not fully accounted for in the records, and enhanced oceanic uptake are necessary to explain this stall.
David M. Lawrence, George C. Hurtt, Almut Arneth, Victor Brovkin, Kate V. Calvin, Andrew D. Jones, Chris D. Jones, Peter J. Lawrence, Nathalie de Noblet-Ducoudré, Julia Pongratz, Sonia I. Seneviratne, and Elena Shevliakova
Geosci. Model Dev., 9, 2973–2998, https://doi.org/10.5194/gmd-9-2973-2016, https://doi.org/10.5194/gmd-9-2973-2016, 2016
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Human land-use activities have resulted in large changes to the Earth's surface, with resulting implications for climate. In the future, land-use activities are likely to expand and intensify further to meet growing demands for food, fiber, and energy. The goal of LUMIP is to take the next steps in land-use change science, and enable, coordinate, and ultimately address the most important land-use science questions in more depth and sophistication than possible in a multi-model context to date.
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
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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.
Jörg Schwinger, Nadine Goris, Jerry F. Tjiputra, Iris Kriest, Mats Bentsen, Ingo Bethke, Mehmet Ilicak, Karen M. Assmann, and Christoph Heinze
Geosci. Model Dev., 9, 2589–2622, https://doi.org/10.5194/gmd-9-2589-2016, https://doi.org/10.5194/gmd-9-2589-2016, 2016
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We present an evaluation of the ocean carbon cycle stand-alone configuration of the Norwegian Earth System Model. A re-tuning of the ecosystem parameterisation improves surface tracer fields between versions 1 and 1.2 of the model. Focus is placed on the evaluation of newly implemented parameterisations of the biological carbon pump (i.e. the sinking of particular organic carbon). We find that the model previously underestimated the carbon transport into the deep ocean below 2000 m depth.
Ulrike Port, Martin Claussen, and Victor Brovkin
Earth Syst. Dynam., 7, 535–547, https://doi.org/10.5194/esd-7-535-2016, https://doi.org/10.5194/esd-7-535-2016, 2016
Roland Séférian, Marion Gehlen, Laurent Bopp, Laure Resplandy, James C. Orr, Olivier Marti, John P. Dunne, James R. Christian, Scott C. Doney, Tatiana Ilyina, Keith Lindsay, Paul R. Halloran, Christoph Heinze, Joachim Segschneider, Jerry Tjiputra, Olivier Aumont, and Anastasia Romanou
Geosci. Model Dev., 9, 1827–1851, https://doi.org/10.5194/gmd-9-1827-2016, https://doi.org/10.5194/gmd-9-1827-2016, 2016
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This paper explores how the large diversity in spin-up protocols used for ocean biogeochemistry in CMIP5 models contributed to inter-model differences in modeled fields. We show that a link between spin-up duration and skill-score metrics emerges from both individual IPSL-CM5A-LR's results and an ensemble of CMIP5 models. Our study suggests that differences in spin-up protocols constitute a source of inter-model uncertainty which would require more attention in future intercomparison exercises.
Fabio Cresto Aleina, Benjamin R. K. Runkle, Tim Brücher, Thomas Kleinen, and Victor Brovkin
Geosci. Model Dev., 9, 915–926, https://doi.org/10.5194/gmd-9-915-2016, https://doi.org/10.5194/gmd-9-915-2016, 2016
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This study presents the hotspot parameterization, a novel approach to upscaling methane emissions in a boreal peatland from the micro-topographic scale to the landscape scale. We based this new parameterization on the analysis of water table patterns generated by the Hummock–Hollow (HH) model. We show how the hotspot parameterization successfully upscales the micro-topographic controls on methane emissions for both present-day conditions and for the next century under three different scenarios.
Matthew J. Carmichael, Daniel J. Lunt, Matthew Huber, Malte Heinemann, Jeffrey Kiehl, Allegra LeGrande, Claire A. Loptson, Chris D. Roberts, Navjit Sagoo, Christine Shields, Paul J. Valdes, Arne Winguth, Cornelia Winguth, and Richard D. Pancost
Clim. Past, 12, 455–481, https://doi.org/10.5194/cp-12-455-2016, https://doi.org/10.5194/cp-12-455-2016, 2016
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In this paper, we assess how well model-simulated precipitation rates compare to those indicated by geological data for the early Eocene, a warm interval 56–49 million years ago. Our results show that a number of models struggle to produce sufficient precipitation at high latitudes, which likely relates to cool simulated temperatures in these regions. However, calculating precipitation rates from plant fossils is highly uncertain, and further data are now required.
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
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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.
F. Cresto Aleina, B. R. K. Runkle, T. Kleinen, L. Kutzbach, J. Schneider, and V. Brovkin
Biogeosciences, 12, 5689–5704, https://doi.org/10.5194/bg-12-5689-2015, https://doi.org/10.5194/bg-12-5689-2015, 2015
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We developed a process-based model for peatland micro-topography and hydrology, the Hummock-Hollow (HH) model, which explicitly represents small-scale surface elevation changes. By coupling the HH model with a model for soil methane processes, we are able to model the effects of micro-topography on hydrology and methane emissions in a typical boreal peatland. We also identify potential biases that models without a micro-topographic representation can introduce in large-scale models.
M. Willeit and A. Ganopolski
Clim. Past, 11, 1165–1180, https://doi.org/10.5194/cp-11-1165-2015, https://doi.org/10.5194/cp-11-1165-2015, 2015
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In this paper we explore the permafrost–ice-sheet interaction using the fully coupled climate–ice-sheet model CLIMBER-2 with the addition of a newly developed permafrost module. We find that permafrost has a moderate but significant effect on ice sheet dynamics during the last glacial cycle. In particular at the Last Glacial Maximum the inclusion of permafrost leads to a 15m sea level equivalent increase in Northern Hemisphere ice volume when permafrost is included.
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
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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.
A. Robinson and M. Perrette
Geosci. Model Dev., 8, 1877–1883, https://doi.org/10.5194/gmd-8-1877-2015, https://doi.org/10.5194/gmd-8-1877-2015, 2015
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Here we present a concise interface to the NetCDF library designed to simplify reading and writing tasks of up to 6-D arrays in Fortran programs.
C. Heinze, S. Meyer, N. Goris, L. Anderson, R. Steinfeldt, N. Chang, C. Le Quéré, and D. C. E. Bakker
Earth Syst. Dynam., 6, 327–358, https://doi.org/10.5194/esd-6-327-2015, https://doi.org/10.5194/esd-6-327-2015, 2015
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Rapidly rising atmospheric CO2 concentrations caused by human actions over the past 250 years have raised cause for concern that changes in Earth’s climate system may progress at a much faster pace and larger extent than during the past 20,000 years. Questions that yet need to be answered are what the carbon uptake kinetics of the oceans will be in the future and how the increase in oceanic carbon inventory will affect its ecosystems. Major future ocean carbon research challenges are discussed.
T. J. Bohn, J. R. Melton, A. Ito, T. Kleinen, R. Spahni, B. D. Stocker, B. Zhang, X. Zhu, R. Schroeder, M. V. Glagolev, S. Maksyutov, V. Brovkin, G. Chen, S. N. Denisov, A. V. Eliseev, A. Gallego-Sala, K. C. McDonald, M.A. Rawlins, W. J. Riley, Z. M. Subin, H. Tian, Q. Zhuang, and J. O. Kaplan
Biogeosciences, 12, 3321–3349, https://doi.org/10.5194/bg-12-3321-2015, https://doi.org/10.5194/bg-12-3321-2015, 2015
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We evaluated 21 forward models and 5 inversions over western Siberia in terms of CH4 emissions and simulated wetland areas and compared these results to an intensive in situ CH4 flux data set, several wetland maps, and two satellite inundation products. In addition to assembling a definitive collection of methane emissions estimates for the region, we were able to identify the types of wetland maps and model features necessary for accurate simulations of high-latitude wetlands.
S. Kloster, T. Brücher, V. Brovkin, and S. Wilkenskjeld
Clim. Past, 11, 781–788, https://doi.org/10.5194/cp-11-781-2015, https://doi.org/10.5194/cp-11-781-2015, 2015
U. Port, M. Claussen, and V. Brovkin
Clim. Past Discuss., https://doi.org/10.5194/cpd-11-997-2015, https://doi.org/10.5194/cpd-11-997-2015, 2015
Revised manuscript not accepted
G. G. Laruelle, R. Lauerwald, J. Rotschi, P. A. Raymond, J. Hartmann, and P. Regnier
Biogeosciences, 12, 1447–1458, https://doi.org/10.5194/bg-12-1447-2015, https://doi.org/10.5194/bg-12-1447-2015, 2015
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This study quantifies the exchange of carbon dioxide (CO2) between the atmosphere and the land-ocean aquatic continuum (LOAC) of the northeast North American coast, which consists of rivers, estuaries, and the coastal ocean. Our analysis reveals significant variations of the flux intensity both in time and space across the study area. Ice cover, snowmelt, and the intensity of the estuarine filter are identified as important control factors of the CO2 exchange along the LOAC.
R. Calov, A. Robinson, M. Perrette, and A. Ganopolski
The Cryosphere, 9, 179–196, https://doi.org/10.5194/tc-9-179-2015, https://doi.org/10.5194/tc-9-179-2015, 2015
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Ice discharge into the ocean from outlet glaciers is an important
component of mass loss of the Greenland ice sheet. Here, we present a
simple parameterization of ice discharge for coarse resolution ice
sheet models, suitable for large ensembles or long-term palaeo
simulations. This parameterization reproduces in a good approximation
the present-day ice discharge compared with estimates, and the
simulation of the present-day ice sheet elevation is considerably
improved.
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. Heinze and T. Ilyina
Clim. Past, 11, 63–79, https://doi.org/10.5194/cp-11-63-2015, https://doi.org/10.5194/cp-11-63-2015, 2015
C. D. Nevison, M. Manizza, R. F. Keeling, M. Kahru, L. Bopp, J. Dunne, J. Tiputra, T. Ilyina, and B. G. Mitchell
Biogeosciences, 12, 193–208, https://doi.org/10.5194/bg-12-193-2015, https://doi.org/10.5194/bg-12-193-2015, 2015
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The observed seasonal cycles in atmospheric potential oxygen (APO) at five surface monitoring sites are compared to those inferred from the air-sea O2 fluxes of six ocean biogeochemistry models. The simulated air-sea fluxes are translated into APO seasonal cycles using a matrix method that takes into account atmospheric transport model (ATM) uncertainty among 13 different ATMs. Net primary production (NPP), estimated from satellite ocean color data, is also compared to model output.
M. Gehlen, R. Séférian, D. O. B. Jones, T. Roy, R. Roth, J. Barry, L. Bopp, S. C. Doney, J. P. Dunne, C. Heinze, F. Joos, J. C. Orr, L. Resplandy, J. Segschneider, and J. Tjiputra
Biogeosciences, 11, 6955–6967, https://doi.org/10.5194/bg-11-6955-2014, https://doi.org/10.5194/bg-11-6955-2014, 2014
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This study evaluates potential impacts of pH reductions on North Atlantic deep-sea ecosystems in response to latest IPCC scenarios.Multi-model projections of pH changes over the seafloor are analysed with reference to a critical threshold based on palaeo-oceanographic studies, contemporary observations and model results. By 2100 under the most severe IPCC CO2 scenario, pH reductions occur over ~23% of deep-sea canyons and ~8% of seamounts – including seamounts proposed as marine protected areas.
M. Heinemann, A. Timmermann, O. Elison Timm, F. Saito, and A. Abe-Ouchi
Clim. Past, 10, 1567–1579, https://doi.org/10.5194/cp-10-1567-2014, https://doi.org/10.5194/cp-10-1567-2014, 2014
E. Bauer and A. Ganopolski
Clim. Past, 10, 1333–1348, https://doi.org/10.5194/cp-10-1333-2014, https://doi.org/10.5194/cp-10-1333-2014, 2014
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
F. S. E. Vamborg, V. Brovkin, and M. Claussen
Earth Syst. Dynam., 5, 89–101, https://doi.org/10.5194/esd-5-89-2014, https://doi.org/10.5194/esd-5-89-2014, 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
R. Valentini, A. Arneth, A. Bombelli, S. Castaldi, R. Cazzolla Gatti, F. Chevallier, P. Ciais, E. Grieco, J. Hartmann, M. Henry, R. A. Houghton, M. Jung, W. L. Kutsch, Y. Malhi, E. Mayorga, L. Merbold, G. Murray-Tortarolo, D. Papale, P. Peylin, B. Poulter, P. A. Raymond, M. Santini, S. Sitch, G. Vaglio Laurin, G. R. van der Werf, C. A. Williams, and R. J. Scholes
Biogeosciences, 11, 381–407, https://doi.org/10.5194/bg-11-381-2014, https://doi.org/10.5194/bg-11-381-2014, 2014
M. Willeit, A. Ganopolski, and G. Feulner
Biogeosciences, 11, 17–32, https://doi.org/10.5194/bg-11-17-2014, https://doi.org/10.5194/bg-11-17-2014, 2014
P. Dass, C. Müller, V. Brovkin, and W. Cramer
Earth Syst. Dynam., 4, 409–424, https://doi.org/10.5194/esd-4-409-2013, https://doi.org/10.5194/esd-4-409-2013, 2013
L. Bopp, L. Resplandy, J. C. Orr, S. C. Doney, J. P. Dunne, M. Gehlen, P. Halloran, C. Heinze, T. Ilyina, R. Séférian, J. Tjiputra, and M. Vichi
Biogeosciences, 10, 6225–6245, https://doi.org/10.5194/bg-10-6225-2013, https://doi.org/10.5194/bg-10-6225-2013, 2013
G. Munhoven
Geosci. Model Dev., 6, 1367–1388, https://doi.org/10.5194/gmd-6-1367-2013, https://doi.org/10.5194/gmd-6-1367-2013, 2013
L. M. Verheijen, V. Brovkin, R. Aerts, G. Bönisch, J. H. C. Cornelissen, J. Kattge, P. B. Reich, I. J. Wright, and P. M. van Bodegom
Biogeosciences, 10, 5497–5515, https://doi.org/10.5194/bg-10-5497-2013, https://doi.org/10.5194/bg-10-5497-2013, 2013
M. Willeit, A. Ganopolski, and G. Feulner
Clim. Past, 9, 1749–1759, https://doi.org/10.5194/cp-9-1749-2013, https://doi.org/10.5194/cp-9-1749-2013, 2013
M. Claussen, K. Selent, V. Brovkin, T. Raddatz, and V. Gayler
Biogeosciences, 10, 3593–3604, https://doi.org/10.5194/bg-10-3593-2013, https://doi.org/10.5194/bg-10-3593-2013, 2013
G. G. Laruelle, H. H. Dürr, R. Lauerwald, J. Hartmann, C. P. Slomp, N. Goossens, and P. A. G. Regnier
Hydrol. Earth Syst. Sci., 17, 2029–2051, https://doi.org/10.5194/hess-17-2029-2013, https://doi.org/10.5194/hess-17-2029-2013, 2013
J. A. Collins, A. Govin, S. Mulitza, D. Heslop, M. Zabel, J. Hartmann, U. Röhl, and G. Wefer
Clim. Past, 9, 1181–1191, https://doi.org/10.5194/cp-9-1181-2013, https://doi.org/10.5194/cp-9-1181-2013, 2013
M. Eby, A. J. Weaver, K. Alexander, K. Zickfeld, A. Abe-Ouchi, A. A. Cimatoribus, E. Crespin, S. S. Drijfhout, N. R. Edwards, A. V. Eliseev, G. Feulner, T. Fichefet, C. E. Forest, H. Goosse, P. B. Holden, F. Joos, M. Kawamiya, D. Kicklighter, H. Kienert, K. Matsumoto, I. I. Mokhov, E. Monier, S. M. Olsen, J. O. P. Pedersen, M. Perrette, G. Philippon-Berthier, A. Ridgwell, A. Schlosser, T. Schneider von Deimling, G. Shaffer, R. S. Smith, R. Spahni, A. P. Sokolov, M. Steinacher, K. Tachiiri, K. Tokos, M. Yoshimori, N. Zeng, and F. Zhao
Clim. Past, 9, 1111–1140, https://doi.org/10.5194/cp-9-1111-2013, https://doi.org/10.5194/cp-9-1111-2013, 2013
R. Wania, J. R. Melton, E. L. Hodson, B. Poulter, B. Ringeval, R. Spahni, T. Bohn, C. A. Avis, G. Chen, A. V. Eliseev, P. O. Hopcroft, W. J. Riley, Z. M. Subin, H. Tian, P. M. van Bodegom, T. Kleinen, Z. C. Yu, J. S. Singarayer, S. Zürcher, D. P. Lettenmaier, D. J. Beerling, S. N. Denisov, C. Prigent, F. Papa, and J. O. Kaplan
Geosci. Model Dev., 6, 617–641, https://doi.org/10.5194/gmd-6-617-2013, https://doi.org/10.5194/gmd-6-617-2013, 2013
R. Wanninkhof, G. -H. Park, T. Takahashi, C. Sweeney, R. Feely, Y. Nojiri, N. Gruber, S. C. Doney, G. A. McKinley, A. Lenton, C. Le Quéré, C. Heinze, J. Schwinger, H. Graven, and S. Khatiwala
Biogeosciences, 10, 1983–2000, https://doi.org/10.5194/bg-10-1983-2013, https://doi.org/10.5194/bg-10-1983-2013, 2013
V. Cocco, F. Joos, M. Steinacher, T. L. Frölicher, L. Bopp, J. Dunne, M. Gehlen, C. Heinze, J. Orr, A. Oschlies, B. Schneider, J. Segschneider, and J. Tjiputra
Biogeosciences, 10, 1849–1868, https://doi.org/10.5194/bg-10-1849-2013, https://doi.org/10.5194/bg-10-1849-2013, 2013
O. D. Andrews, N. L. Bindoff, P. R. Halloran, T. Ilyina, and C. Le Quéré
Biogeosciences, 10, 1799–1813, https://doi.org/10.5194/bg-10-1799-2013, https://doi.org/10.5194/bg-10-1799-2013, 2013
F. Joos, R. Roth, J. S. Fuglestvedt, G. P. Peters, I. G. Enting, W. von Bloh, V. Brovkin, E. J. Burke, M. Eby, N. R. Edwards, T. Friedrich, T. L. Frölicher, P. R. Halloran, P. B. Holden, C. Jones, T. Kleinen, F. T. Mackenzie, K. Matsumoto, M. Meinshausen, G.-K. Plattner, A. Reisinger, J. Segschneider, G. Shaffer, M. Steinacher, K. Strassmann, K. Tanaka, A. Timmermann, and A. J. Weaver
Atmos. Chem. Phys., 13, 2793–2825, https://doi.org/10.5194/acp-13-2793-2013, https://doi.org/10.5194/acp-13-2793-2013, 2013
J. F. Tjiputra, C. Roelandt, M. Bentsen, D. M. Lawrence, T. Lorentzen, J. Schwinger, Ø. Seland, and C. Heinze
Geosci. Model Dev., 6, 301–325, https://doi.org/10.5194/gmd-6-301-2013, https://doi.org/10.5194/gmd-6-301-2013, 2013
J. R. Melton, R. Wania, E. L. Hodson, B. Poulter, B. Ringeval, R. Spahni, T. Bohn, C. A. Avis, D. J. Beerling, G. Chen, A. V. Eliseev, S. N. Denisov, P. O. Hopcroft, D. P. Lettenmaier, W. J. Riley, J. S. Singarayer, Z. M. Subin, H. Tian, S. Zürcher, V. Brovkin, P. M. van Bodegom, T. Kleinen, Z. C. Yu, and J. O. Kaplan
Biogeosciences, 10, 753–788, https://doi.org/10.5194/bg-10-753-2013, https://doi.org/10.5194/bg-10-753-2013, 2013
J. Segschneider, A. Beitsch, C. Timmreck, V. Brovkin, T. Ilyina, J. Jungclaus, S. J. Lorenz, K. D. Six, and D. Zanchettin
Biogeosciences, 10, 669–687, https://doi.org/10.5194/bg-10-669-2013, https://doi.org/10.5194/bg-10-669-2013, 2013
P. K. Patra, J. G. Canadell, R. A. Houghton, S. L. Piao, N.-H. Oh, P. Ciais, K. R. Manjunath, A. Chhabra, T. Wang, T. Bhattacharya, P. Bousquet, J. Hartman, A. Ito, E. Mayorga, Y. Niwa, P. A. Raymond, V. V. S. S. Sarma, and R. Lasco
Biogeosciences, 10, 513–527, https://doi.org/10.5194/bg-10-513-2013, https://doi.org/10.5194/bg-10-513-2013, 2013
M. Perrette, F. Landerer, R. Riva, K. Frieler, and M. Meinshausen
Earth Syst. Dynam., 4, 11–29, https://doi.org/10.5194/esd-4-11-2013, https://doi.org/10.5194/esd-4-11-2013, 2013
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Geosci. Model Dev., 18, 3003–3016, https://doi.org/10.5194/gmd-18-3003-2025, https://doi.org/10.5194/gmd-18-3003-2025, 2025
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We present, analyze, and validate a methodology for quantifying uncertainty in gridded meteorological data products produced by spatial interpolation. In a validation case study using daily maximum near-surface air temperature (Tmax), the method works well and produces predictive distributions with closely matching theoretical versus actual coverage levels. Application of the method reveals that the magnitude of uncertainty in interpolated Tmax varies significantly in both space and time.
Martin Juckes, Karl E. Taylor, Fabrizio Antonio, David Brayshaw, Carlo Buontempo, Jian Cao, Paul J. Durack, Michio Kawamiya, Hyungjun Kim, Tomas Lovato, Chloe Mackallah, Matthew Mizielinski, Alessandra Nuzzo, Martina Stockhause, Daniele Visioni, Jeremy Walton, Briony Turner, Eleanor O'Rourke, and Beth Dingley
Geosci. Model Dev., 18, 2639–2663, https://doi.org/10.5194/gmd-18-2639-2025, https://doi.org/10.5194/gmd-18-2639-2025, 2025
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The Baseline Climate Variables for Earth System Modelling (ESM-BCVs) are defined as a list of 135 variables which have high utility for the evaluation and exploitation of climate simulations. The list reflects the most frequently used variables from Earth system models based on an assessment of data publication and download records from the largest archive of global climate projects.
Yucheng Lin, Robert E. Kopp, Alexander Reedy, Matteo Turilli, Shantenu Jha, and Erica L. Ashe
Geosci. Model Dev., 18, 2609–2637, https://doi.org/10.5194/gmd-18-2609-2025, https://doi.org/10.5194/gmd-18-2609-2025, 2025
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Ingo Richter, Ping Chang, Ping-Gin Chiu, Gokhan Danabasoglu, Takeshi Doi, Dietmar Dommenget, Guillaume Gastineau, Zoe E. Gillett, Aixue Hu, Takahito Kataoka, Noel S. Keenlyside, Fred Kucharski, Yuko M. Okumura, Wonsun Park, Malte F. Stuecker, Andréa S. Taschetto, Chunzai Wang, Stephen G. Yeager, and Sang-Wook Yeh
Geosci. Model Dev., 18, 2587–2608, https://doi.org/10.5194/gmd-18-2587-2025, https://doi.org/10.5194/gmd-18-2587-2025, 2025
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Daniel F. J. Gunning, Kerim H. Nisancioglu, Emilie Capron, and Roderik S. W. van de Wal
Geosci. Model Dev., 18, 2479–2508, https://doi.org/10.5194/gmd-18-2479-2025, https://doi.org/10.5194/gmd-18-2479-2025, 2025
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Pengfei Shi, L. Ruby Leung, and Bin Wang
Geosci. Model Dev., 18, 2443–2460, https://doi.org/10.5194/gmd-18-2443-2025, https://doi.org/10.5194/gmd-18-2443-2025, 2025
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Liwen Wang, Qian Li, Qi Lv, Xuan Peng, and Wei You
Geosci. Model Dev., 18, 2427–2442, https://doi.org/10.5194/gmd-18-2427-2025, https://doi.org/10.5194/gmd-18-2427-2025, 2025
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Teo Price-Broncucia, Allison Baker, Dorit Hammerling, Michael Duda, and Rebecca Morrison
Geosci. Model Dev., 18, 2349–2372, https://doi.org/10.5194/gmd-18-2349-2025, https://doi.org/10.5194/gmd-18-2349-2025, 2025
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Esteban Fernández Villanueva and Gary Shaffer
Geosci. Model Dev., 18, 2161–2192, https://doi.org/10.5194/gmd-18-2161-2025, https://doi.org/10.5194/gmd-18-2161-2025, 2025
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Gang Tang, Zebedee Nicholls, Alexander Norton, Sönke Zaehle, and Malte Meinshausen
Geosci. Model Dev., 18, 2193–2230, https://doi.org/10.5194/gmd-18-2193-2025, https://doi.org/10.5194/gmd-18-2193-2025, 2025
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Ngoc Thi Nhu Do, Kengo Sudo, Akihiko Ito, Louisa K. Emmons, Vaishali Naik, Kostas Tsigaridis, Øyvind Seland, Gerd A. Folberth, and Douglas I. Kelley
Geosci. Model Dev., 18, 2079–2109, https://doi.org/10.5194/gmd-18-2079-2025, https://doi.org/10.5194/gmd-18-2079-2025, 2025
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Understanding historical isoprene emission changes is important for predicting future climate, but trends and their controlling factors remain uncertain. This study shows that long-term isoprene trends vary among Earth system models mainly due to partially incorporating CO2 effects and land cover changes rather than to climate. Future models that refine these factors’ effects on isoprene emissions, along with long-term observations, are essential for better understanding plant–climate interactions.
Gang Tang, Zebedee Nicholls, Chris Jones, Thomas Gasser, Alexander Norton, Tilo Ziehn, Alejandro Romero-Prieto, and Malte Meinshausen
Geosci. Model Dev., 18, 2111–2136, https://doi.org/10.5194/gmd-18-2111-2025, https://doi.org/10.5194/gmd-18-2111-2025, 2025
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We analyzed carbon and nitrogen mass conservation in data from various Earth system models. Our findings reveal significant discrepancies between flux and pool size data, where cumulative imbalances can reach hundreds of gigatons of carbon or nitrogen. These imbalances appear primarily due to missing or inconsistently reported fluxes – especially for land-use and fire emissions. To enhance data quality, we recommend that future climate data protocols address this issue at the reporting stage.
Florian Börgel, Sven Karsten, Karoline Rummel, and Ulf Gräwe
Geosci. Model Dev., 18, 2005–2019, https://doi.org/10.5194/gmd-18-2005-2025, https://doi.org/10.5194/gmd-18-2005-2025, 2025
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Forecasting river runoff, which is crucial for managing water resources and understanding climate impacts, can be challenging. This study introduces a new method using convolutional long short-term memory (ConvLSTM) networks, a machine learning model that processes spatial and temporal data. Focusing on the Baltic Sea region, our model uses weather data as input to predict daily river runoff for 97 rivers.
Tao Zhang, Cyril Morcrette, Meng Zhang, Wuyin Lin, Shaocheng Xie, Ye Liu, Kwinten Van Weverberg, and Joana Rodrigues
Geosci. Model Dev., 18, 1917–1928, https://doi.org/10.5194/gmd-18-1917-2025, https://doi.org/10.5194/gmd-18-1917-2025, 2025
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Earth system models (ESMs) struggle with the uncertainties associated with parameterizing subgrid physics. Machine learning (ML) algorithms offer a solution by learning the important relationships and features from high-resolution models. To incorporate ML parameterizations into ESMs, we develop a Fortran–Python interface that allows for calling Python functions within Fortran-based ESMs. Through two case studies, this interface demonstrates its feasibility, modularity, and effectiveness.
Camilla Mathison, Eleanor J. Burke, Gregory Munday, Chris D. Jones, Chris J. Smith, Norman J. Steinert, Andy J. Wiltshire, Chris Huntingford, Eszter Kovacs, Laila K. Gohar, Rebecca M. Varney, and Douglas McNeall
Geosci. Model Dev., 18, 1785–1808, https://doi.org/10.5194/gmd-18-1785-2025, https://doi.org/10.5194/gmd-18-1785-2025, 2025
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We present PRIME (Probabilistic Regional Impacts from Model patterns and Emissions), which is designed to take new emissions scenarios and rapidly provide regional impact information. PRIME allows large ensembles to be run on multi-centennial timescales, including the analysis of many important variables for impact assessments. Our evaluation shows that PRIME reproduces the climate response for known scenarios, providing confidence in using PRIME for novel scenarios.
Katherine M. Smith, Alice M. Barthel, LeAnn M. Conlon, Luke P. Van Roekel, Anthony Bartoletti, Jean-Christophe Golaz, Chengzhu Zhang, Carolyn Branecky Begeman, James J. Benedict, Gautam Bisht, Yan Feng, Walter Hannah, Bryce E. Harrop, Nicole Jeffery, Wuyin Lin, Po-Lun Ma, Mathew E. Maltrud, Mark R. Petersen, Balwinder Singh, Qi Tang, Teklu Tesfa, Jonathan D. Wolfe, Shaocheng Xie, Xue Zheng, Karthik Balaguru, Oluwayemi Garuba, Peter Gleckler, Aixue Hu, Jiwoo Lee, Ben Moore-Maley, and Ana C. Ordoñez
Geosci. Model Dev., 18, 1613–1633, https://doi.org/10.5194/gmd-18-1613-2025, https://doi.org/10.5194/gmd-18-1613-2025, 2025
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Version 2.1 of the U.S. Department of Energy's Energy Exascale Earth System Model (E3SM) adds the Fox-Kemper et al. (2011) mixed-layer eddy parameterization, which restratifies the ocean surface layer through an overturning streamfunction. Results include surface layer bias reduction in temperature, salinity, and sea ice extent in the North Atlantic; a small strengthening of the Atlantic meridional overturning circulation; and improvements to many atmospheric climatological variables.
Huilin Huang, Yun Qian, Gautam Bisht, Jiali Wang, Tirthankar Chakraborty, Dalei Hao, Jianfeng Li, Travis Thurber, Balwinder Singh, Zhao Yang, Ye Liu, Pengfei Xue, William J. Sacks, Ethan Coon, and Robert Hetland
Geosci. Model Dev., 18, 1427–1443, https://doi.org/10.5194/gmd-18-1427-2025, https://doi.org/10.5194/gmd-18-1427-2025, 2025
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We integrate the E3SM Land Model (ELM) with the WRF model through the Lightweight Infrastructure for Land Atmosphere Coupling (LILAC) Earth System Modeling Framework (ESMF). This framework includes a top-level driver, LILAC, for variable communication between WRF and ELM and ESMF caps for ELM initialization, execution, and finalization. The LILAC–ESMF framework maintains the integrity of the ELM's source code structure and facilitates the transfer of future ELM model developments to WRF-ELM.
Michael Nole, Jonah Bartrand, Fawz Naim, and Glenn Hammond
Geosci. Model Dev., 18, 1413–1425, https://doi.org/10.5194/gmd-18-1413-2025, https://doi.org/10.5194/gmd-18-1413-2025, 2025
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Safe carbon dioxide (CO2) storage is likely to be critical for mitigating some of the most severe effects of climate change. We present a simulation framework for modeling CO2 storage beneath the seafloor, where CO2 can form a solid. This can aid in permanent CO2 storage for long periods of time. Our models show what a commercial-scale CO2 injection would look like in a marine environment. We discuss what would need to be considered when designing a subsea CO2 injection.
Reyk Börner, Jan O. Haerter, and Romain Fiévet
Geosci. Model Dev., 18, 1333–1356, https://doi.org/10.5194/gmd-18-1333-2025, https://doi.org/10.5194/gmd-18-1333-2025, 2025
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The daily cycle of sea surface temperature (SST) impacts clouds above the ocean and could influence the clustering of thunderstorms linked to extreme rainfall and hurricanes. However, daily SST variability is often poorly represented in modeling studies of how clouds cluster. We present a simple, wind-responsive model of upper-ocean temperature for use in atmospheric simulations. Evaluating the model against observations, we show that it performs significantly better than common slab models.
Malcolm J. Roberts, Kevin A. Reed, Qing Bao, Joseph J. Barsugli, Suzana J. Camargo, Louis-Philippe Caron, Ping Chang, Cheng-Ta Chen, Hannah M. Christensen, Gokhan Danabasoglu, Ivy Frenger, Neven S. Fučkar, Shabeh ul Hasson, Helene T. Hewitt, Huanping Huang, Daehyun Kim, Chihiro Kodama, Michael Lai, Lai-Yung Ruby Leung, Ryo Mizuta, Paulo Nobre, Pablo Ortega, Dominique Paquin, Christopher D. Roberts, Enrico Scoccimarro, Jon Seddon, Anne Marie Treguier, Chia-Ying Tu, Paul A. Ullrich, Pier Luigi Vidale, Michael F. Wehner, Colin M. Zarzycki, Bosong Zhang, Wei Zhang, and Ming Zhao
Geosci. Model Dev., 18, 1307–1332, https://doi.org/10.5194/gmd-18-1307-2025, https://doi.org/10.5194/gmd-18-1307-2025, 2025
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HighResMIP2 is a model intercomparison project focusing on high-resolution global climate models, that is, those with grid spacings of 25 km or less in the atmosphere and ocean, using simulations of decades to a century in length. We are proposing an update of our simulation protocol to make the models more applicable to key questions for climate variability and hazard in present-day and future projections and to build links with other communities to provide more robust climate information.
Jordi Buckley Paules, Simone Fatichi, Bonnie Warring, and Athanasios Paschalis
Geosci. Model Dev., 18, 1287–1305, https://doi.org/10.5194/gmd-18-1287-2025, https://doi.org/10.5194/gmd-18-1287-2025, 2025
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We present and validate enhancements to the process-based T&C model aimed at improving its representation of crop growth and management practices. The updated model, T&C-CROP, enables applications such as analysing the hydrological and carbon storage impacts of land use transitions (e.g. conversions between crops, forests, and pastures) and optimizing irrigation and fertilization strategies in response to climate change.
Sébastien Masson, Swen Jullien, Eric Maisonnave, David Gill, Guillaume Samson, Mathieu Le Corre, and Lionel Renault
Geosci. Model Dev., 18, 1241–1263, https://doi.org/10.5194/gmd-18-1241-2025, https://doi.org/10.5194/gmd-18-1241-2025, 2025
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This article details a new feature we implemented in the popular regional atmospheric model WRF. This feature allows for data exchange between WRF and any other model (e.g. an ocean model) using the coupling library Ocean–Atmosphere–Sea–Ice–Soil Model Coupling Toolkit (OASIS3-MCT). This coupling interface is designed to be non-intrusive, flexible and modular. It also offers the possibility of taking into account the nested zooms used in WRF or in the models with which it is coupled.
Axel Lauer, Lisa Bock, Birgit Hassler, Patrick Jöckel, Lukas Ruhe, and Manuel Schlund
Geosci. Model Dev., 18, 1169–1188, https://doi.org/10.5194/gmd-18-1169-2025, https://doi.org/10.5194/gmd-18-1169-2025, 2025
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Earth system models are important tools to improve our understanding of current climate and to project climate change. Thus, it is crucial to understand possible shortcomings in the models. New features of the ESMValTool software package allow one to compare and visualize a model's performance with respect to reproducing observations in the context of other climate models in an easy and user-friendly way. We aim to help model developers assess and monitor climate simulations more efficiently.
Ulrich G. Wortmann, Tina Tsan, Mahrukh Niazi, Irene A. Ma, Ruben Navasardyan, Magnus-Roland Marun, Bernardo S. Chede, Jingwen Zhong, and Morgan Wolfe
Geosci. Model Dev., 18, 1155–1167, https://doi.org/10.5194/gmd-18-1155-2025, https://doi.org/10.5194/gmd-18-1155-2025, 2025
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The Earth Science Box Modeling Toolkit (ESBMTK) is a user-friendly Python library that simplifies the creation of models to study earth system processes, such as the carbon cycle and ocean chemistry. It enhances learning by emphasizing concepts over programming and is accessible to students and researchers alike. By automating complex calculations and promoting code clarity, ESBMTK accelerates model development while improving reproducibility and the usability of scientific research.
Florian Zabel, Matthias Knüttel, and Benjamin Poschlod
Geosci. Model Dev., 18, 1067–1087, https://doi.org/10.5194/gmd-18-1067-2025, https://doi.org/10.5194/gmd-18-1067-2025, 2025
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CropSuite is a new open-source crop suitability model. It provides a GUI and a wide range of options, including a spatial downscaling of climate data. We apply CropSuite to 48 staple and opportunity crops at a 1 km spatial resolution in Africa. We find that climate variability significantly impacts suitable areas but also affects optimal sowing dates and multiple cropping potential. The results provide valuable information for climate impact assessments, adaptation, and land-use planning.
Kerstin Hartung, Bastian Kern, Nils-Arne Dreier, Jörn Geisbüsch, Mahnoosh Haghighatnasab, Patrick Jöckel, Astrid Kerkweg, Wilton Jaciel Loch, Florian Prill, and Daniel Rieger
Geosci. Model Dev., 18, 1001–1015, https://doi.org/10.5194/gmd-18-1001-2025, https://doi.org/10.5194/gmd-18-1001-2025, 2025
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The ICOsahedral Non-hydrostatic (ICON) model system Community Interface (ComIn) library supports connecting third-party modules to the ICON model. Third-party modules can range from simple diagnostic Python scripts to full chemistry models. ComIn offers a low barrier for code extensions to ICON, provides multi-language support (Fortran, C/C++, and Python), and reduces the migration effort in response to new ICON releases. This paper presents the ComIn design principles and a range of use cases.
Daniel Ries, Katherine Goode, Kellie McClernon, and Benjamin Hillman
Geosci. Model Dev., 18, 1041–1065, https://doi.org/10.5194/gmd-18-1041-2025, https://doi.org/10.5194/gmd-18-1041-2025, 2025
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Machine learning has advanced research in the climate science domain, but its models are difficult to understand. In order to understand the impacts and consequences of climate interventions such as stratospheric aerosol injection, complex models are often necessary. We use a case study to illustrate how we can understand the inner workings of a complex model. We present this technique as an exploratory tool that can be used to quickly discover and assess relationships in complex climate data.
Bo Dong, Paul Ullrich, Jiwoo Lee, Peter Gleckler, Kristin Chang, and Travis A. O'Brien
Geosci. Model Dev., 18, 961–976, https://doi.org/10.5194/gmd-18-961-2025, https://doi.org/10.5194/gmd-18-961-2025, 2025
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A metrics package designed for easy analysis of atmospheric river (AR) characteristics and statistics is presented. The tool is efficient for diagnosing systematic AR bias in climate models and useful for evaluating new AR characteristics in model simulations. In climate models, landfalling AR precipitation shows dry biases globally, and AR tracks are farther poleward (equatorward) in the North and South Atlantic (South Pacific and Indian Ocean).
Panagiotis Adamidis, Erik Pfister, Hendryk Bockelmann, Dominik Zobel, Jens-Olaf Beismann, and Marek Jacob
Geosci. Model Dev., 18, 905–919, https://doi.org/10.5194/gmd-18-905-2025, https://doi.org/10.5194/gmd-18-905-2025, 2025
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In this paper, we investigated performance indicators of the climate model ICON (ICOsahedral Nonhydrostatic) on different compute architectures to answer the question of how to generate high-resolution climate simulations. Evidently, it is not enough to use more computing units of the conventionally used architectures; higher memory throughput is the most promising approach. More potential can be gained from single-node optimization rather than simply increasing the number of compute nodes.
Kangari Narender Reddy, Somnath Baidya Roy, Sam S. Rabin, Danica L. Lombardozzi, Gudimetla Venkateswara Varma, Ruchira Biswas, and Devavat Chiru Naik
Geosci. Model Dev., 18, 763–785, https://doi.org/10.5194/gmd-18-763-2025, https://doi.org/10.5194/gmd-18-763-2025, 2025
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The study aimed to improve the representation of wheat and rice in a land model for the Indian region. The modified model performed significantly better than the default model in simulating crop phenology, yield, and carbon, water, and energy fluxes compared to observations. The study highlights the need for global land models to use region-specific crop parameters for accurately simulating vegetation processes and land surface processes.
Giovanni Di Virgilio, Fei Ji, Eugene Tam, Jason P. Evans, Jatin Kala, Julia Andrys, Christopher Thomas, Dipayan Choudhury, Carlos Rocha, Yue Li, and Matthew L. Riley
Geosci. Model Dev., 18, 703–724, https://doi.org/10.5194/gmd-18-703-2025, https://doi.org/10.5194/gmd-18-703-2025, 2025
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We evaluate the skill in simulating the Australian climate of some of the latest generation of regional climate models. We show when and where the models simulate this climate with high skill versus model limitations. We show how new models perform relative to the previous-generation models, assessing how model design features may underlie key performance improvements. This work is of national and international relevance as it can help guide the use and interpretation of climate projections.
Giovanni Di Virgilio, Jason P. Evans, Fei Ji, Eugene Tam, Jatin Kala, Julia Andrys, Christopher Thomas, Dipayan Choudhury, Carlos Rocha, Stephen White, Yue Li, Moutassem El Rafei, Rishav Goyal, Matthew L. Riley, and Jyothi Lingala
Geosci. Model Dev., 18, 671–702, https://doi.org/10.5194/gmd-18-671-2025, https://doi.org/10.5194/gmd-18-671-2025, 2025
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We introduce new climate models that simulate Australia’s future climate at regional scales, including at an unprecedented resolution of 4 km for 1950–2100. We describe the model design process used to create these new climate models. We show how the new models perform relative to previous-generation models and compare their climate projections. This work is of national and international relevance as it can help guide climate model design and the use and interpretation of climate projections.
Nathan P. Gillett, Isla R. Simpson, Gabi Hegerl, Reto Knutti, Dann Mitchell, Aurélien Ribes, Hideo Shiogama, Dáithí Stone, Claudia Tebaldi, Piotr Wolski, Wenxia Zhang, and Vivek K. Arora
EGUsphere, https://doi.org/10.5194/egusphere-2024-4086, https://doi.org/10.5194/egusphere-2024-4086, 2025
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Climate model simulations of the response to human and natural influences together, natural climate influences alone, and greenhouse gases alone, among others, are key to quantifying human influence on the climate. The last set of such coordinated simulations underpinned key findings in the last Intergovernmental Panel on Climate Change (IPCC) report. Here we propose a new set of such simulations to be used in the next generation of attribution studies, and to underpin the next IPCC report.
Jiawang Feng, Chun Zhao, Qiuyan Du, Zining Yang, and Chen Jin
Geosci. Model Dev., 18, 585–603, https://doi.org/10.5194/gmd-18-585-2025, https://doi.org/10.5194/gmd-18-585-2025, 2025
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In this study, we improved the calculation of how aerosols in the air interact with radiation in WRF-Chem. The original model used a simplified method, but we developed a more accurate approach. We found that this method significantly changes the properties of the estimated aerosols and their effects on radiation, especially for dust aerosols. It also impacts the simulated weather conditions. Our work highlights the importance of correctly representing aerosol–radiation interactions in models.
Eduardo Moreno-Chamarro, Thomas Arsouze, Mario Acosta, Pierre-Antoine Bretonnière, Miguel Castrillo, Eric Ferrer, Amanda Frigola, Daria Kuznetsova, Eneko Martin-Martinez, Pablo Ortega, and Sergi Palomas
Geosci. Model Dev., 18, 461–482, https://doi.org/10.5194/gmd-18-461-2025, https://doi.org/10.5194/gmd-18-461-2025, 2025
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We present the high-resolution model version of the EC-Earth global climate model to contribute to HighResMIP. The combined model resolution is about 10–15 km in both the ocean and atmosphere, which makes it one of the finest ever used to complete historical and scenario simulations. This model is compared with two lower-resolution versions, with a 100 km and a 25 km grid. The three models are compared with observations to study the improvements thanks to the increased resolution.
Catherine Guiavarc'h, David Storkey, Adam T. Blaker, Ed Blockley, Alex Megann, Helene Hewitt, Michael J. Bell, Daley Calvert, Dan Copsey, Bablu Sinha, Sophia Moreton, Pierre Mathiot, and Bo An
Geosci. Model Dev., 18, 377–403, https://doi.org/10.5194/gmd-18-377-2025, https://doi.org/10.5194/gmd-18-377-2025, 2025
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The Global Ocean and Sea Ice configuration version 9 (GOSI9) is the new UK hierarchy of model configurations based on the Nucleus for European Modelling of the Ocean (NEMO) and available at three resolutions. It will be used for various applications, e.g. weather forecasting and climate prediction. It improves upon the previous version by reducing global temperature and salinity biases and enhancing the representation of Arctic sea ice and the Antarctic Circumpolar Current.
Andy Richling, Jens Grieger, and Henning W. Rust
Geosci. Model Dev., 18, 361–375, https://doi.org/10.5194/gmd-18-361-2025, https://doi.org/10.5194/gmd-18-361-2025, 2025
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The performance of weather and climate prediction systems is variable in time and space. It is of interest how this performance varies in different situations. We provide a decomposition of a skill score (a measure of forecast performance) as a tool for detailed assessment of performance variability to support model development or forecast improvement. The framework is exemplified with decadal forecasts to assess the impact of different ocean states in the North Atlantic on temperature forecast.
Maria R. Russo, Sadie L. Bartholomew, David Hassell, Alex M. Mason, Erica Neininger, A. James Perman, David A. J. Sproson, Duncan Watson-Parris, and Nathan Luke Abraham
Geosci. Model Dev., 18, 181–191, https://doi.org/10.5194/gmd-18-181-2025, https://doi.org/10.5194/gmd-18-181-2025, 2025
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Observational data and modelling capabilities have expanded in recent years, but there are still barriers preventing these two data sources from being used in synergy. Proper comparison requires generating, storing, and handling a large amount of data. This work describes the first step in the development of a new set of software tools, the VISION toolkit, which can enable the easy and efficient integration of observational and model data required for model evaluation.
Bijan Fallah, Masoud Rostami, Emmanuele Russo, Paula Harder, Christoph Menz, Peter Hoffmann, Iulii Didovets, and Fred F. Hattermann
Geosci. Model Dev., 18, 161–180, https://doi.org/10.5194/gmd-18-161-2025, https://doi.org/10.5194/gmd-18-161-2025, 2025
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We tried to contribute to a local climate change impact study in central Asia, a region that is water-scarce and vulnerable to global climate change. We use regional models and machine learning to produce reliable local data from global climate models. We find that regional models show more realistic and detailed changes in heavy precipitation than global climate models. Our work can help assess the future risks of extreme events and plan adaptation strategies in central Asia.
Manuel Schlund, Bouwe Andela, Jörg Benke, Ruth Comer, Birgit Hassler, Emma Hogan, Peter Kalverla, Axel Lauer, Bill Little, Saskia Loosveldt Tomas, Francesco Nattino, Patrick Peglar, Valeriu Predoi, Stef Smeets, Stephen Worsley, Martin Yeo, and Klaus Zimmermann
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-236, https://doi.org/10.5194/gmd-2024-236, 2025
Revised manuscript accepted for GMD
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The Earth System Model Evaluation Tool (ESMValTool) is a community diagnostics and performance metrics tool for the evaluation of Earth system models. Here, we describe recent significant improvements of ESMValTool’s computational efficiency including parallel, out-of-core, and distributed computing. Evaluations with the enhanced version of ESMValTool are faster, use less computational resources, and can handle input data larger than the available memory.
Thomas Rackow, Xabier Pedruzo-Bagazgoitia, Tobias Becker, Sebastian Milinski, Irina Sandu, Razvan Aguridan, Peter Bechtold, Sebastian Beyer, Jean Bidlot, Souhail Boussetta, Willem Deconinck, Michail Diamantakis, Peter Dueben, Emanuel Dutra, Richard Forbes, Rohit Ghosh, Helge F. Goessling, Ioan Hadade, Jan Hegewald, Thomas Jung, Sarah Keeley, Lukas Kluft, Nikolay Koldunov, Aleksei Koldunov, Tobias Kölling, Josh Kousal, Christian Kühnlein, Pedro Maciel, Kristian Mogensen, Tiago Quintino, Inna Polichtchouk, Balthasar Reuter, Domokos Sármány, Patrick Scholz, Dmitry Sidorenko, Jan Streffing, Birgit Sützl, Daisuke Takasuka, Steffen Tietsche, Mirco Valentini, Benoît Vannière, Nils Wedi, Lorenzo Zampieri, and Florian Ziemen
Geosci. Model Dev., 18, 33–69, https://doi.org/10.5194/gmd-18-33-2025, https://doi.org/10.5194/gmd-18-33-2025, 2025
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Detailed global climate model simulations have been created based on a numerical weather prediction model, offering more accurate spatial detail down to the scale of individual cities ("kilometre-scale") and a better understanding of climate phenomena such as atmospheric storms, whirls in the ocean, and cracks in sea ice. The new model aims to provide globally consistent information on local climate change with greater precision, benefiting environmental planning and local impact modelling.
Yilin Fang, Hoang Viet Tran, and L. Ruby Leung
Geosci. Model Dev., 18, 19–32, https://doi.org/10.5194/gmd-18-19-2025, https://doi.org/10.5194/gmd-18-19-2025, 2025
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Hurricanes may worsen water quality in the lower Mississippi River basin (LMRB) by increasing nutrient runoff. We found that runoff parameterizations greatly affect nitrate–nitrogen runoff simulated using an Earth system land model. Our simulations predicted increased nitrogen runoff in the LMRB during Hurricane Ida in 2021, albeit less pronounced than the observations, indicating areas for model improvement to better understand and manage nutrient runoff loss during hurricanes in the region.
Giovanni Seijo-Ellis, Donata Giglio, Gustavo Marques, and Frank Bryan
Geosci. Model Dev., 17, 8989–9021, https://doi.org/10.5194/gmd-17-8989-2024, https://doi.org/10.5194/gmd-17-8989-2024, 2024
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A CESM–MOM6 regional configuration of the Caribbean Sea was developed in response to the rising need for high-resolution models for climate impact studies. The configuration is validated for the period 2000–2020 and improves significant errors in a low-resolution model. Oceanic properties are well represented. Patterns of freshwater associated with the Amazon River are well captured, and the mean flows of ocean waters across multiple passages in the Caribbean Sea agree with observations.
Yan Bo, Hao Liang, Tao Li, and Feng Zhou
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-212, https://doi.org/10.5194/gmd-2024-212, 2024
Revised manuscript accepted for GMD
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This study proposed an advancing framework for modeling regional rice production, water use, and greenhouse gas emissions. The framework integrated a process-based soil-crop model with key physiological effects, a novel model upscaling method, and the NSGA-II multi-objective optimization algorithm at a parallel computing platform. The framework provides a valuable tool for irrigation optimization to deliver co-benefits of ensuring food production, reducing water use and greenhouse gas emissions.
Elizabeth J. Drenkard, Charles A. Stock, Andrew C. Ross, Yi-Cheng Teng, Theresa Morrison, Wei Cheng, Alistair Adcroft, Enrique Curchitser, Raphael Dussin, Robert Hallberg, Claudine Hauri, Katherine Hedstrom, Albert Hermann, Michael G. Jacox, Kelly A. Kearney, Remi Pages, Darren J. Pilcher, Mercedes Pozo Buil, Vivek Seelanki, and Niki Zadeh
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-195, https://doi.org/10.5194/gmd-2024-195, 2024
Preprint under review for GMD
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We made a new regional ocean model to assist fisheries and ecosystem managers make decisions in the Northeast Pacific Ocean (NEP). We found that the model did well simulating past ocean conditions like temperature, and nutrient and oxygen levels, and can even reproduce metrics used by and important to ecosystem managers.
Deifilia To, Julian Quinting, Gholam Ali Hoshyaripour, Markus Götz, Achim Streit, and Charlotte Debus
Geosci. Model Dev., 17, 8873–8884, https://doi.org/10.5194/gmd-17-8873-2024, https://doi.org/10.5194/gmd-17-8873-2024, 2024
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Pangu-Weather is a breakthrough machine learning model in medium-range weather forecasting that considers 3D atmospheric information. We show that using a simpler 2D framework improves robustness, speeds up training, and reduces computational needs by 20 %–30 %. We introduce a training procedure that varies the importance of atmospheric variables over time to speed up training convergence. Decreasing computational demand increases the accessibility of training and working with the model.
Fang Li, Xiang Song, Sandy P. Harrison, Jennifer R. Marlon, Zhongda Lin, L. Ruby Leung, Jörg Schwinger, Virginie Marécal, Shiyu Wang, Daniel S. Ward, Xiao Dong, Hanna Lee, Lars Nieradzik, Sam S. Rabin, and Roland Séférian
Geosci. Model Dev., 17, 8751–8771, https://doi.org/10.5194/gmd-17-8751-2024, https://doi.org/10.5194/gmd-17-8751-2024, 2024
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This study provides the first comprehensive assessment of historical fire simulations from 19 Earth system models in phase 6 of the Coupled Model Intercomparison Project (CMIP6). Most models reproduce global totals, spatial patterns, seasonality, and regional historical changes well but fail to simulate the recent decline in global burned area and underestimate the fire response to climate variability. CMIP6 simulations address three critical issues of phase-5 models.
Seung H. Baek, Paul A. Ullrich, Bo Dong, and Jiwoo Lee
Geosci. Model Dev., 17, 8665–8681, https://doi.org/10.5194/gmd-17-8665-2024, https://doi.org/10.5194/gmd-17-8665-2024, 2024
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We evaluate downscaled products by examining locally relevant co-variances during precipitation events. Common statistical downscaling techniques preserve expected co-variances during convective precipitation (a stationary phenomenon). However, they dampen future intensification of frontal precipitation (a non-stationary phenomenon) captured in global climate models and dynamical downscaling. Our study quantifies a ramification of the stationarity assumption underlying statistical downscaling.
Emmanuel Nyenah, Petra Döll, Daniel S. Katz, and Robert Reinecke
Geosci. Model Dev., 17, 8593–8611, https://doi.org/10.5194/gmd-17-8593-2024, https://doi.org/10.5194/gmd-17-8593-2024, 2024
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Research software is vital for scientific progress but is often developed by scientists with limited skills, time, and funding, leading to challenges in usability and maintenance. Our study across 10 sectors shows strengths in version control, open-source licensing, and documentation while emphasizing the need for containerization and code quality. We recommend workshops; code quality metrics; funding; and following the findable, accessible, interoperable, and reusable (FAIR) standards.
Chris Smith, Donald P. Cummins, Hege-Beate Fredriksen, Zebedee Nicholls, Malte Meinshausen, Myles Allen, Stuart Jenkins, Nicholas Leach, Camilla Mathison, and Antti-Ilari Partanen
Geosci. Model Dev., 17, 8569–8592, https://doi.org/10.5194/gmd-17-8569-2024, https://doi.org/10.5194/gmd-17-8569-2024, 2024
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Climate projections are only useful if the underlying models that produce them are well calibrated and can reproduce observed climate change. We formalise a software package that calibrates the open-source FaIR simple climate model to full-complexity Earth system models. Observations, including historical warming, and assessments of key climate variables such as that of climate sensitivity are used to constrain the model output.
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Short summary
In this paper we present the carbon cycle component of the newly developed fast Earth system model CLIMBER-X. The model can be run with interactive atmospheric CO2 to investigate the feedbacks between climate and the carbon cycle on temporal scales ranging from decades to > 100 000 years. CLIMBER-X is expected to be a useful tool for studying past climate–carbon cycle changes and for the investigation of the long-term future evolution of the Earth system.
In this paper we present the carbon cycle component of the newly developed fast Earth system...
