Articles | Volume 13, issue 11
https://doi.org/10.5194/gmd-13-5425-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-13-5425-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
10 Nov 2020
Model description paper |
| 10 Nov 2020
| 10 Nov 2020
Harmonization of global land use change and management for the period 850–2100 (LUH2) for CMIP6
Department of Geographical Sciences, University of Maryland, College Park, MD 20742, USA
Louise Chini
Department of Geographical Sciences, University of Maryland, College Park, MD 20742, USA
Ritvik Sahajpal
Department of Geographical Sciences, University of Maryland, College Park, MD 20742, USA
Steve Frolking
Institute for the Study of Earth, Oceans, and Space, University of New Hampshire, Durham, NH 03824, USA
Benjamin L. Bodirsky
Potsdam Institute for Climate Impact Research, Potsdam, Germany
Katherine Calvin
Joint Global Change Research Institute, Pacific Northwest National
Laboratory, Richland, WA 99354, USA
Jonathan C. Doelman
PBL Netherlands Environmental Assessment Agency, 2594 AV Den Haag, the Netherlands
Justin Fisk
Department of Geographical Sciences, University of Maryland, College Park, MD 20742, USA
Dagan Inc., Durham, NH 03824, USA
Shinichiro Fujimori
National Institute for Environmental Studies, Tsukuba, Ibaraki 305-0053, Japan
Kees Klein Goldewijk
PBL Netherlands Environmental Assessment Agency, 2594 AV Den Haag, the Netherlands
Copernicus Institute of Sustainable Development, University of
Utrecht, Utrecht, the Netherlands
Tomoko Hasegawa
National Institute for Environmental Studies, Tsukuba, Ibaraki 305-0053, Japan
Peter Havlik
International Institute for Applied Systems Analysis, Laxenburg, Austria
Andreas Heinimann
Institute of Geography and Centre for Development and Environment,
University of Bern, Bern, Switzerland
Florian Humpenöder
Potsdam Institute for Climate Impact Research, Potsdam, Germany
Johan Jungclaus
Max Planck Institute for Meterology, Hamburg, Germany
Jed O. Kaplan
Department of Earth Sciences, The University of Hong Kong, Hong Kong
Jennifer Kennedy
Department of Geographical Sciences, University of Maryland, College Park, MD 20742, USA
Tamás Krisztin
International Institute for Applied Systems Analysis, Laxenburg, Austria
David Lawrence
National Center for Atmospheric Research, Boulder, CO 80305, USA
Peter Lawrence
National Center for Atmospheric Research, Boulder, CO 80305, USA
Lei Ma
Department of Geographical Sciences, University of Maryland, College Park, MD 20742, USA
Ole Mertz
Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark
Julia Pongratz
Max Planck Institute for Meterology, Hamburg, Germany
Department of Geography, Ludwig-Maximilians Universität Munich, Munich,
Germany
Alexander Popp
Potsdam Institute for Climate Impact Research, Potsdam, Germany
Benjamin Poulter
NASA Goddard Space Flight Center, Biospheric Sciences Lab, Greenbelt, MD 20771, USA
Keywan Riahi
International Institute for Applied Systems Analysis, Laxenburg, Austria
Elena Shevliakova
Geophysical Fluid Dynamics Lab, Princeton, NJ 08540-6649, USA
Elke Stehfest
PBL Netherlands Environmental Assessment Agency, 2594 AV Den Haag, the Netherlands
Peter Thornton
Oak Ridge National Laboratory, Oak Ridge, TN 37830, USA
Francesco N. Tubiello
Statistics Division, Food and Agriculture Organization of the United Nations, Rome 00153, Italy
Detlef P. van Vuuren
PBL Netherlands Environmental Assessment Agency, 2594 AV Den Haag, the Netherlands
Copernicus Institute of Sustainable Development, University of
Utrecht, Utrecht, the Netherlands
Xin Zhang
Appalachian Laboratory, University of Maryland Center for Environmental Science, Frostburg, MD 21532, USA
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HyeJin Kim, Isabel M. D. Rosa, Rob Alkemade, Paul Leadley, George Hurtt, Alexander Popp, Detlef P. van Vuuren, Peter Anthoni, Almut Arneth, Daniele Baisero, Emma Caton, Rebecca Chaplin-Kramer, Louise Chini, Adriana De Palma, Fulvio Di Fulvio, Moreno Di Marco, Felipe Espinoza, Simon Ferrier, Shinichiro Fujimori, Ricardo E. Gonzalez, Maya Gueguen, Carlos Guerra, Mike Harfoot, Thomas D. Harwood, Tomoko Hasegawa, Vanessa Haverd, Petr Havlík, Stefanie Hellweg, Samantha L. L. Hill, Akiko Hirata, Andrew J. Hoskins, Jan H. Janse, Walter Jetz, Justin A. Johnson, Andreas Krause, David Leclère, Ines S. Martins, Tetsuya Matsui, Cory Merow, Michael Obersteiner, Haruka Ohashi, Benjamin Poulter, Andy Purvis, Benjamin Quesada, Carlo Rondinini, Aafke M. Schipper, Richard Sharp, Kiyoshi Takahashi, Wilfried Thuiller, Nicolas Titeux, Piero Visconti, Christopher Ware, Florian Wolf, and Henrique M. Pereira
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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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Yannick Le Page, Douglas Morton, Corinne Hartin, Ben Bond-Lamberty, José Miguel Cardoso Pereira, George Hurtt, and Ghassem Asrar
Earth Syst. Dynam., 8, 1237–1246, https://doi.org/10.5194/esd-8-1237-2017, https://doi.org/10.5194/esd-8-1237-2017, 2017
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Katja Frieler, Stefan Lange, Franziska Piontek, Christopher P. O. Reyer, Jacob Schewe, Lila Warszawski, Fang Zhao, Louise Chini, Sebastien Denvil, Kerry Emanuel, Tobias Geiger, Kate Halladay, George Hurtt, Matthias Mengel, Daisuke Murakami, Sebastian Ostberg, Alexander Popp, Riccardo Riva, Miodrag Stevanovic, Tatsuo Suzuki, Jan Volkholz, Eleanor Burke, Philippe Ciais, Kristie Ebi, Tyler D. Eddy, Joshua Elliott, Eric Galbraith, Simon N. Gosling, Fred Hattermann, Thomas Hickler, Jochen Hinkel, Christian Hof, Veronika Huber, Jonas Jägermeyr, Valentina Krysanova, Rafael Marcé, Hannes Müller Schmied, Ioanna Mouratiadou, Don Pierson, Derek P. Tittensor, Robert Vautard, Michelle van Vliet, Matthias F. Biber, Richard A. Betts, Benjamin Leon Bodirsky, Delphine Deryng, Steve Frolking, Chris D. Jones, Heike K. Lotze, Hermann Lotze-Campen, Ritvik Sahajpal, Kirsten Thonicke, Hanqin Tian, and Yoshiki Yamagata
Geosci. Model Dev., 10, 4321–4345, https://doi.org/10.5194/gmd-10-4321-2017, https://doi.org/10.5194/gmd-10-4321-2017, 2017
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This paper describes the simulation scenario design for the next phase of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP), which is designed to facilitate a contribution to the scientific basis for the IPCC Special Report on the impacts of 1.5 °C global warming. ISIMIP brings together over 80 climate-impact models, covering impacts on hydrology, biomes, forests, heat-related mortality, permafrost, tropical cyclones, fisheries, agiculture, energy, and coastal infrastructure.
Johann H. Jungclaus, Edouard Bard, Mélanie Baroni, Pascale Braconnot, Jian Cao, Louise P. Chini, Tania Egorova, Michael Evans, J. Fidel González-Rouco, Hugues Goosse, George C. Hurtt, Fortunat Joos, Jed O. Kaplan, Myriam Khodri, Kees Klein Goldewijk, Natalie Krivova, Allegra N. LeGrande, Stephan J. Lorenz, Jürg Luterbacher, Wenmin Man, Amanda C. Maycock, Malte Meinshausen, Anders Moberg, Raimund Muscheler, Christoph Nehrbass-Ahles, Bette I. Otto-Bliesner, Steven J. Phipps, Julia Pongratz, Eugene Rozanov, Gavin A. Schmidt, Hauke Schmidt, Werner Schmutz, Andrew Schurer, Alexander I. Shapiro, Michael Sigl, Jason E. Smerdon, Sami K. Solanki, Claudia Timmreck, Matthew Toohey, Ilya G. Usoskin, Sebastian Wagner, Chi-Ju Wu, Kok Leng Yeo, Davide Zanchettin, Qiong Zhang, and Eduardo Zorita
Geosci. Model Dev., 10, 4005–4033, https://doi.org/10.5194/gmd-10-4005-2017, https://doi.org/10.5194/gmd-10-4005-2017, 2017
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Climate model simulations covering the last millennium provide context for the evolution of the modern climate and for the expected changes during the coming centuries. They can help identify plausible mechanisms underlying palaeoclimatic reconstructions. Here, we describe the forcing boundary conditions and the experimental protocol for simulations covering the pre-industrial millennium. We describe the PMIP4 past1000 simulations as contributions to CMIP6 and additional sensitivity experiments.
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.
Hanqin Tian, Naiqing Pan, Rona L. Thompson, Josep G. Canadell, Parvadha Suntharalingam, Pierre Regnier, Eric A. Davidson, Michael Prather, Philippe Ciais, Marilena Muntean, Shufen Pan, Wilfried Winiwarter, Sönke Zaehle, Feng Zhou, Robert B. Jackson, Hermann W. Bange, Sarah Berthet, Zihao Bian, Daniele Bianchi, Alexander F. Bouwman, Erik T. Buitenhuis, Geoffrey Dutton, Minpeng Hu, Akihiko Ito, Atul K. Jain, Aurich Jeltsch-Thömmes, Fortunat Joos, Sian Kou-Giesbrecht, Paul B. Krummel, Xin Lan, Angela Landolfi, Ronny Lauerwald, Ya Li, Chaoqun Lu, Taylor Maavara, Manfredi Manizza, Dylan B. Millet, Jens Mühle, Prabir K. Patra, Glen P. Peters, Xiaoyu Qin, Peter Raymond, Laure Resplandy, Judith A. Rosentreter, Hao Shi, Qing Sun, Daniele Tonina, Francesco N. Tubiello, Guido R. van der Werf, Nicolas Vuichard, Junjie Wang, Kelley C. Wells, Luke M. Western, Chris Wilson, Jia Yang, Yuanzhi Yao, Yongfa You, and Qing Zhu
Earth Syst. Sci. Data, 16, 2543–2604, https://doi.org/10.5194/essd-16-2543-2024, https://doi.org/10.5194/essd-16-2543-2024, 2024
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Atmospheric concentrations of nitrous oxide (N2O), a greenhouse gas 273 times more potent than carbon dioxide, have increased by 25 % since the preindustrial period, with the highest observed growth rate in 2020 and 2021. This rapid growth rate has primarily been due to a 40 % increase in anthropogenic emissions since 1980. Observed atmospheric N2O concentrations in recent years have exceeded the worst-case climate scenario, underscoring the importance of reducing anthropogenic N2O emissions.
Zhen Zhang, Benjamin Poulter, Joe R. Melton, William J. Riley, George H. Allen, David J. Beerling, Philippe Bousquet, Josep G. Canadell, Etienne Fluet-Chouinard, Philippe Ciais, Nicola Gedney, Peter O. Hopcroft, Akihiko Ito, Robert B. Jackson, Atul K. Jain, Katherine Jensen, Fortunat Joos, Thomas Kleinen, Sara Knox, Tingting Li, Xin Li, Xiangyu Liu, Kyle McDonald, Gavin McNicol, Paul A. Miller, Jurek Müller, Prabir K. Patra, Changhui Peng, Shushi Peng, Zhangcai Qin, Ryan M. Riggs, Marielle Saunois, Qing Sun, Hanqin Tian, Xiaoming Xu, Yuanzhi Yao, Xi Yi, Wenxin Zhang, Qing Zhu, Qiuan Zhu, and Qianlai Zhuang
EGUsphere, https://doi.org/10.5194/egusphere-2024-1584, https://doi.org/10.5194/egusphere-2024-1584, 2024
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This study assesses global methane emissions from wetlands between 2000 and 2020 using multiple models. We found that wetland emissions increased by 6–7 Tg CH4 per year in the 2010s compared to the 2000s. Rising temperatures primarily drove this increase, while changes in precipitation and CO2 levels also played roles. Our findings highlight the importance of wetlands in the global methane budget and the need for continuous monitoring to understand their impact on climate change.
Marielle Saunois, Adrien Martinez, Benjamin Poulter, Zhen Zhang, Peter Raymond, Pierre Regnier, Joseph G. Canadell, Robert B. Jackson, Prabir K. Patra, Philippe Bousquet, Philippe Ciais, Edward J. Dlugokencky, Xin Lan, George H. Allen, David Bastviken, David J. Beerling, Dmitry A. Belikov, Donald R. Blake, Simona Castaldi, Monica Crippa, Bridget R. Deemer, Fraser Dennison, Giuseppe Etiope, Nicola Gedney, Lena Höglund-Isaksson, Meredith A. Holgerson, Peter O. Hopcroft, Gustaf Hugelius, Akihito Ito, Atul K. Jain, Rajesh Janardanan, Matthew S. Johnson, Thomas Kleinen, Paul Krummel, Ronny Lauerwald, Tingting Li, Xiangyu Liu, Kyle C. McDonald, Joe R. Melton, Jens Mühle, Jurek Müller, Fabiola Murguia-Flores, Yosuke Niwa, Sergio Noce, Shufen Pan, Robert J. Parker, Changhui Peng, Michel Ramonet, William J. Riley, Gerard Rocher-Ros, Judith A. Rosentreter, Motoki Sasakawa, Arjo Segers, Steven J. Smith, Emily H. Stanley, Joel Thanwerdas, Hanquin Tian, Aki Tsuruta, Francesco N. Tubiello, Thomas S. Weber, Guido van der Werf, Doug E. Worthy, Yi Xi, Yukio Yoshida, Wenxin Zhang, Bo Zheng, Qing Zhu, Qiuan Zhu, and Qianlai Zhuang
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-115, https://doi.org/10.5194/essd-2024-115, 2024
Preprint under review for ESSD
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Methane (CH4) is the second most important human-influenced greenhouse gas in terms of climate forcing after carbon dioxide (CO2). A consortium of multi-disciplinary scientists synthesize and update the budget of the sources and sinks of CH4. This edition benefits from important progresses in estimating emissions from lakes and ponds, reservoirs, and streams and rivers. For the 2010s decade, global CH4 emissions are estimated at 575 Tg CH4 yr-1, including ~65 % from anthropogenic sources.
Enrico Zorzetto, Paul Ginoux, Sergey Malyshev, and Elena Shevliakova
EGUsphere, https://doi.org/10.5194/egusphere-2024-1258, https://doi.org/10.5194/egusphere-2024-1258, 2024
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Light-absorbing particles (LAPs) deposition on snow leads to a darkening of the snow surface and can thus accelerate snow melt. Understanding to what extent different types of LAPs contribute to snow melt is important both to predict changes in water availability and for improving global climate model predictions. Here we extend a recently developed snow model to account for the deposition of LAPs in the snowpack and evaluate the effect of snow darkening on accelerating snow melt.
Félix García-Pereira, Jesús Fidel González-Rouco, Camilo Melo-Aguilar, Norman Julius Steinert, Elena García-Bustamante, Philip de Vrese, Johann Jungclaus, Stephan Lorenz, Stefan Hagemann, Francisco José Cuesta-Valero, Almudena García-García, and Hugo Beltrami
Earth Syst. Dynam., 15, 547–564, https://doi.org/10.5194/esd-15-547-2024, https://doi.org/10.5194/esd-15-547-2024, 2024
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According to climate model estimates, the land stored 2 % of the system's heat excess in the last decades, while observational studies show it was around 6 %. This difference stems from these models using land components that are too shallow to constrain land heat uptake. Deepening the land component does not affect the surface temperature. This result can be used to derive land heat uptake estimates from different sources, which are much closer to previous observational reports.
Danny M. Leung, Jasper F. Kok, Longlei Li, David M. Lawrence, Natalie M. Mahowald, Simone Tilmes, and Erik Kluzek
EGUsphere, https://doi.org/10.5194/egusphere-2024-1124, https://doi.org/10.5194/egusphere-2024-1124, 2024
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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This study derives a desert dust emission dataset for 1841–2000, by employing a combination of observed dust records from sedimentary cores as well as reanalyzed global dust cycle constraints. We evaluate the ability of global models to replicate the observed historical dust variability by using the emission dataset to force a historical simulation in an Earth system model. We show that prescribing our emissions forces the model to match better against observations than other mechanistic models.
Sabin I. Taranu, David M. Lawrence, Yoshihide Wada, Ting Tang, Erik Kluzek, Sam Rabin, Yi Yao, Steven J. De Hertog, Inne Vanderkelen, and Wim Thiery
EGUsphere, https://doi.org/10.5194/egusphere-2024-362, https://doi.org/10.5194/egusphere-2024-362, 2024
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In this study, we improve an existing climate model to account for human water usage across domestic, industrial, and agriculture purposes. With the new capabilities, the model is now better equipped for studying questions related to water scarcity in both present and future conditions under climate change. Despite the advancements, there remains important limitations in our modelling framework which requires further work.
Qing Ying, Benjamin Poulter, Jennifer D. Watts, Kyle A. Arndt, Anna-Maria Virkkala, Lori Bruhwiler, Youmi Oh, Brendan M. Rogers, Susan M. Natali, Hilary Sullivan, Luke D. Schiferl, Clayton Elder, Olli Peltola, Annett Bartsch, Amanda Armstrong, Ankur R. Desai, Eugénie Euskirchen, Mathias Göckede, Bernhard Lehner, Mats B. Nilsson, Matthias Peichl, Oliver Sonnentag, Eeva-Stiina Tuittila, Torsten Sachs, Aram Kalhori, Masahito Ueyama, and Zhen Zhang
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-84, https://doi.org/10.5194/essd-2024-84, 2024
Preprint under review for ESSD
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We present daily methane fluxes of northern wetlands at 10-km resolution during 2016–2022 (WetCH4) derived from a novel machine-learning framework with improved accuracy. We estimated an average annual CH4 emissions of 20.8 ±2.1 Tg CH4 yr-1. Emissions were intensified in 2016, 2020, and 2022, with the largest interannual variations coming from West Siberia. Continued, all-season tower observations and improved soil moisture products are needed for future improvement of CH4 upscaling.
Lingbo Li, Hong-Yi Li, Guta Abeshu, Jinyun Tang, L. Ruby Leung, Chang Liao, Zeli Tan, Hanqin Tian, Peter Thornton, and Xiaojuan Yang
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-43, https://doi.org/10.5194/essd-2024-43, 2024
Preprint under review for ESSD
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We have developed a new map that reveals how organic carbon from soil leaches into headwater streams over the contiguous United States. We use advanced artificial intelligence techniques and a massive amount of data, including observations at over 2,500 gauges and a wealth of climate and environmental information. The map is a critical step in understanding and predicting how carbon moves through our environment, hence a useful tool for tackling climate challenges.
Muhammad Awais, Adriano Vinca, Edward Byers, Stefan Frank, Oliver Fricko, Esther Boere, Peter Burek, Miguel Poblete Cazenave, Paul Natsuo Kishimoto, Alessio Mastrucci, Yusuke Satoh, Amanda Palazzo, Madeleine McPherson, Keywan Riahi, and Volker Krey
Geosci. Model Dev., 17, 2447–2469, https://doi.org/10.5194/gmd-17-2447-2024, https://doi.org/10.5194/gmd-17-2447-2024, 2024
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Climate change, population growth, and depletion of natural resources all pose complex and interconnected challenges. Our research offers a novel model that can help in understanding the interplay of these aspects, providing policymakers with a more robust tool for making informed future decisions. The study highlights the significance of incorporating climate impacts within large-scale global integrated assessments, which can help us in generating more climate-resilient scenarios.
James A. King, James Weber, Peter Lawrence, Stephanie Roe, Abigail L. S. Swann, and Maria Val Martin
EGUsphere, https://doi.org/10.5194/egusphere-2024-710, https://doi.org/10.5194/egusphere-2024-710, 2024
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Tackling climate change by adding, restoring, or enhancing forests is gaining global support. However, it’s important to investigate the broader implications of this. We used a computer model of the Earth to investigate a future where tree cover expanded as much as possible. We found that some tropical areas were cooler because of trees pumping water into the atmosphere, but this also led to soil and rivers drying. This is important because it might be harder to maintain the forests as a result.
Enrico Zorzetto, Sergey Malyshev, Paul Ginoux, and Elena Shevliakova
EGUsphere, https://doi.org/10.5194/egusphere-2024-506, https://doi.org/10.5194/egusphere-2024-506, 2024
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We describe a new snow scheme developed for use in global climate models, which simulates the interactions of snowpack with vegetation, atmosphere, and soil. We test the new snow model over a set of sites where in-situ observations are available. We find that, when compared to a simpler snow model, this model improves predictions of seasonal snow and of soil temperature under the snowpack, important variables for simulating both the hydrological cycle and the global climate system.
Kirsten L. Findell, Zun Yin, Eunkyo Seo, Paul A. Dirmeyer, Nathan P. Arnold, Nathaniel Chaney, Megan D. Fowler, Meng Huang, David M. Lawrence, Po-Lun Ma, and Joseph A. Santanello Jr.
Geosci. Model Dev., 17, 1869–1883, https://doi.org/10.5194/gmd-17-1869-2024, https://doi.org/10.5194/gmd-17-1869-2024, 2024
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We outline a request for sub-daily data to accurately capture the process-level connections between land states, surface fluxes, and the boundary layer response. This high-frequency model output will allow for more direct comparison with observational field campaigns on process-relevant timescales, enable demonstration of inter-model spread in land–atmosphere coupling processes, and aid in targeted identification of sources of deficiencies and opportunities for improvement of the models.
Danny M. Leung, Jasper F. Kok, Longlei Li, Natalie M. Mahowald, David M. Lawrence, Simone Tilmes, Erik Kluzek, Martina Klose, and Carlos Pérez García-Pando
Atmos. Chem. Phys., 24, 2287–2318, https://doi.org/10.5194/acp-24-2287-2024, https://doi.org/10.5194/acp-24-2287-2024, 2024
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This study uses a premier Earth system model to evaluate a new desert dust emission scheme proposed in our companion paper. We show that our scheme accounts for more dust emission physics, hence matching better against observations than other existing dust emission schemes do. Our scheme's dust emissions also couple tightly with meteorology, hence likely improving the modeled dust sensitivity to climate change. We believe this work is vital for improving dust representation in climate models.
Marika M. Holland, Cecile Hannay, John Fasullo, Alexandra Jahn, Jennifer E. Kay, Michael Mills, Isla R. Simpson, William Wieder, Peter Lawrence, Erik Kluzek, and David Bailey
Geosci. Model Dev., 17, 1585–1602, https://doi.org/10.5194/gmd-17-1585-2024, https://doi.org/10.5194/gmd-17-1585-2024, 2024
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Climate evolves in response to changing forcings, as prescribed in simulations. Models and forcings are updated over time to reflect new understanding. This makes it difficult to attribute simulation differences to either model or forcing changes. Here we present new simulations which enable the separation of model structure and forcing influence between two widely used simulation sets. Results indicate a strong influence of aerosol emission uncertainty on historical climate.
Colin Gareth Jones, Fanny Adloff, Ben Booth, Peter Cox, Veronika Eyring, Pierre Friedlingstein, Katja Frieler, Helene Hewitt, Hazel Jeffery, Sylvie Joussaume, Torben Koenigk, Bryan N. Lawrence, Eleanor O'Rourke, Malcolm Roberts, Benjamin Sanderson, Roland Séférian, Samuel Somot, Pier-Luigi Vidale, Detlef van Vuuren, Mario Acosta, Mats Bentsen, Raffaele Bernardello, Richard Betts, Ed Blockley, Julien Boé, Tom Bracegirdle, Pascale Braconnot, Victor Brovkin, Carlo Buontempo, Francisco J. Doblas-Reyes, Markus G. Donat, Italo Epicoco, Pete Falloon, Sandro Fiore, Thomas Froelicher, Neven Fuckar, Matthew Gidden, Helge Goessling, Rune Grand Graversen, Silvio Gualdi, Jose Manuel Gutiérrez, Tatiana Ilyina, Daniela Jacob, Chris Jones, Martin Juckes, Elizabeth Kendon, Erik Kjellström, Reto Knutti, Jason A. Lowe, Matthew Mizielinski, Paola Nassisi, Michael Obersteiner, Pierre Regnier, Romain Roehrig, David Salas y Melia, Carl-Friedrich Schleussner, Michael Schulz, Enrico Scoccimarro, Laurent Terray, Hannes Thiemann, Richard Wood, Shuting Yang, and Sönke Zaehle
EGUsphere, https://doi.org/10.5194/egusphere-2024-453, https://doi.org/10.5194/egusphere-2024-453, 2024
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We propose a number of priority areas for the international climate research community to address over the coming ~6 years (i.e. to 2030). Advances in these areas will increase our understanding of past and future Earth system change, including the societal and environmental impacts of this change, as well as deliver significantly improved scientific support to international climate policy, such as the 7th IPCC Assessment Report and the UNFCCC Global Stocktake under the Paris Climate Agreement.
Tomohiro Hajima, Michio Kawamiya, Akihiko Ito, Kaoru Tachiiri, Chris Jones, Vivek Arora, Victor Brovkin, Roland Séférian, Spencer Liddicoat, Pierre Friedlingstein, and Elena Shevliakova
EGUsphere, https://doi.org/10.5194/egusphere-2024-188, https://doi.org/10.5194/egusphere-2024-188, 2024
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This study analyzes atmospheric CO2 concentrations and global carbon budgets simulated by multiple Earth system models, using several types of simulations. We successfully identified problems of global carbon budget in each model. We also found urgent issues that should be solved in the latest generation of models, land use change CO2 emissions.
Wolfgang Alexander Obermeier, Clemens Schwingshackl, Ana Bastos, Giulia Conchedda, Thomas Gasser, Giacomo Grassi, Richard A. Houghton, Francesco Nicola Tubiello, Stephen Sitch, and Julia Pongratz
Earth Syst. Sci. Data, 16, 605–645, https://doi.org/10.5194/essd-16-605-2024, https://doi.org/10.5194/essd-16-605-2024, 2024
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We provide and compare country-level estimates of land-use CO2 fluxes from a variety and large number of models, bottom-up estimates, and country reports for the period 1950–2021. Although net fluxes are small in many countries, they are often composed of large compensating emissions and removals. In many countries, the estimates agree well once their individual characteristics are accounted for, but in other countries, including some of the largest emitters, substantial uncertainties exist.
Cameron I. Ludemann, Nathan Wanner, Pauline Chivenge, Achim Dobermann, Rasmus Einarsson, Patricio Grassini, Armelle Gruere, Kevin Jackson, Luis Lassaletta, Federico Maggi, Griffiths Obli-Laryea, Martin K. van Ittersum, Srishti Vishwakarma, Xin Zhang, and Francesco N. Tubiello
Earth Syst. Sci. Data, 16, 525–541, https://doi.org/10.5194/essd-16-525-2024, https://doi.org/10.5194/essd-16-525-2024, 2024
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Nutrient budgets help identify the excess or insufficient use of fertilizers and other nutrient sources in agriculture. They allow the calculation of indicators, such as the nutrient balance (surplus or deficit) and nutrient use efficiency, that help to monitor agricultural productivity and sustainability. This article describes a global cropland nutrient budget that provides data on 205 countries and territories from 1961 to 2020 (data available at https://www.fao.org/faostat/en/#data/ESB).
Felix Jäger, Jonas Schwaab, Yann Quilcaille, Michael Windisch, Jonathan Doelman, Stefan Frank, Mykola Gusti, Petr Havlik, Florian Humpenöder, Andrey Lessa Derci Augustynczik, Christoph Müller, Kanishka B. Narayan, Ryan S. Padrón, Alexander Popp, Detlef van Vuuren, Michael Wögerer, and Sonia I. Seneviratne
EGUsphere, https://doi.org/10.5194/egusphere-2024-15, https://doi.org/10.5194/egusphere-2024-15, 2024
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Climate change mitigation strategies developed with socio-economic models rely on the wide-spread (re)planting of trees to limit global warming below 2 degrees. However, most of these models neglect climate-driven shifts in forest damages like fires. By assessing existing mitigation scenarios, we show the exposure of projected forestation areas to fire-promoting weather conditions. Our study highlights the problem of ignoring climate-driven shifts in forest damages and ways to address it.
Gab Abramowitz, Anna Ukkola, Sanaa Hobeichi, Jon Cranko Page, Mathew Lipson, Martin De Kauwe, Sam Green, Claire Brenner, Jonathan Frame, Grey Nearing, Martyn Clark, Martin Best, Peter Anthoni, Gabriele Arduini, Souhail Boussetta, Silvia Caldararu, Kyeungwoo Cho, Matthias Cuntz, David Fairbairn, Craig Ferguson, Hyungjun Kim, Yeonjoo Kim, Jürgen Knauer, David Lawrence, Xiangzhong Luo, Sergey Malyshev, Tomoko Nitta, Jerome Ogee, Keith Oleson, Catherine Ottlé, Phillipe Peylin, Patricia de Rosnay, Heather Rumbold, Bob Su, Nicolas Vuichard, Anthony Walker, Xiaoni Wang-Faivre, Yunfei Wang, and Yijian Zeng
EGUsphere, https://doi.org/10.5194/egusphere-2023-3084, https://doi.org/10.5194/egusphere-2023-3084, 2024
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This paper evaluates land models – computer based models that simulate ecosystem dynamics, the land carbon, water and energy cycles and the role of land in the climate system. It uses machine learning / AI approaches to show that despite the complexity of land models, they do not perform nearly as well as they could, given the amount of information they are provided with about the prediction problem.
Tuula Aalto, Aki Tsuruta, Jarmo Mäkelä, Jurek Mueller, Maria Tenkanen, Eleanor Burke, Sarah Chadburn, Yao Gao, Vilma Mannisenaho, Thomas Kleinen, Hanna Lee, Antti Leppänen, Tiina Markkanen, Stefano Materia, Paul Miller, Daniele Peano, Olli Peltola, Benjamin Poulter, Maarit Raivonen, Marielle Saunois, David Wårlind, and Sönke Zaehle
EGUsphere, https://doi.org/10.5194/egusphere-2023-2873, https://doi.org/10.5194/egusphere-2023-2873, 2024
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Wetland methane responses to temperature and precipitation were studied in a boreal wetland-rich region in Northern Europe using ecosystem models, atmospheric inversions and up-scaled flux observations. The ecosystem models differed in their responses to temperature and precipitation and in their seasonality. However, multi-model means, inversions and up-scaled fluxes had similar seasonality, and they suggested co-limitation by temperature and precipitation.
Cecile B. Menard, Sirpa Rasmus, Ioanna Merkouriadi, Gianpaolo Balsamo, Annett Bartsch, Chris Derksen, Florent Domine, Marie Dumont, Dorothee Ehrich, Richard Essery, Bruce C. Forbes, Gerhard Krinner, David Lawrence, Glen Liston, Heidrun Matthes, Nick Rutter, Melody Sandells, Martin Schneebeli, and Sari Stark
EGUsphere, https://doi.org/10.5194/egusphere-2023-2926, https://doi.org/10.5194/egusphere-2023-2926, 2024
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Computer models, like those used in climate change studies, are written by modelers who have to decide how best to construct the models in order to satisfy the purpose they serve. Using snow modeling as an example, we examine the process behind the decisions to understand what motivates or limits modelers in their decision-making. We found that the context in which research is undertaken is often more crucial than scientific limitations. We argue for more transparency into our research practice.
Ana Maria Roxana Petrescu, Glen P. Peters, Richard Engelen, Sander Houweling, Dominik Brunner, Aki Tsuruta, Bradley Matthews, Prabir K. Patra, Dmitry Belikov, Rona L. Thompson, Lena Höglund-Isaksson, Wenxin Zhang, Arjo J. Segers, Giuseppe Etiope, Giancarlo Ciotoli, Philippe Peylin, Frédéric Chevallier, Tuula Aalto, Robbie M. Andrew, David Bastviken, Antoine Berchet, Grégoire Broquet, Giulia Conchedda, Johannes Gütschow, Jean-Matthieu Haussaire, Ronny Lauerwald, Tiina Markkanen, Jacob C. A. van Peet, Isabelle Pison, Pierre Regnier, Espen Solum, Marko Scholze, Maria Tenkanen, Francesco N. Tubiello, Guido R. van der Werf, and John R. Worden
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-516, https://doi.org/10.5194/essd-2023-516, 2024
Revised manuscript under review for ESSD
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This study provides an overview of data availability from observation and inventory-based CH4 emissions estimates. It systematically compares them and provides recommendations for robust comparisons, aiming to steadily engage more Parties in using observational methods to complement their UNFCCC submissions. Anticipating improvements in atmospheric modelling and observations, future developments need to resolve knowledge gaps in both approaches and to better quantify remaining uncertainty.
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.
Benjamin Mark Sanderson, Ben B. B. Booth, John Dunne, Veronika Eyring, Rosie A. Fisher, Pierre Friedlingstein, Matthew J. Gidden, Tomohiro Hajima, Chris D. Jones, Colin Jones, Andrew King, Charles D. Koven, David M. Lawrence, Jason Lowe, Nadine Mengis, Glen P. Peters, Joeri Rogelj, Chris Smith, Abigail C. Snyder, Isla R. Simpson, Abigail L. S. Swann, Claudia Tebaldi, Tatiana Ilyina, Carl-Friedrich Schleussner, Roland Seferian, Bjørn Hallvard Samset, Detlef van Vuuren, and Sönke Zaehle
EGUsphere, https://doi.org/10.5194/egusphere-2023-2127, https://doi.org/10.5194/egusphere-2023-2127, 2023
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We discuss how, in order to provide more relevant guidance for climate policy, coordinated climate experiments should adopt a greater focus on simulations where Earth System Models are provided with carbon emissions from fossil fuels together with land use change instructions, rather than past approaches which have largely focussed on experiments with prescribed atmospheric carbon dioxide concentrations. We highlight the technical feasibility of achieving these simulations in coming years.
Francesco N. Tubiello, Giulia Conchedda, Leon Casse, Pengyu Hao, Giorgia De Santis, and Zhongxin Chen
Earth Syst. Sci. Data, 15, 4997–5015, https://doi.org/10.5194/essd-15-4997-2023, https://doi.org/10.5194/essd-15-4997-2023, 2023
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We describe a new dataset of cropland area circa the year 2020, with global coverage and country detail. Data are generated from geospatial information on the agreement characteristics of six high-resolution cropland maps. By helping to highlight features of cropland characteristics and underlying causes for agreement across land cover products, the dataset can be used as a tool to help guide future mapping efforts towards improved agricultural monitoring.
Gudeta Sileshi, Edmundo Barrios, Johannes Lehmann, and Francesco N. Tubiello
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-288, https://doi.org/10.5194/essd-2023-288, 2023
Revised manuscript under review for ESSD
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Agricultural, fisheries, forestry and agro-processing activities produce large quantities of residues, by-products and waste materials every year. Here, we present a global organic matter database (OMD, the first of its kind, consolidating estimates of residues and by-products potentially available for use in a circular bio-economy. It also provides definitions, typologies and methods to aid consistent classification, estimation and reporting of the various residues and by-products.
Matthew J. McGrath, Ana Maria Roxana Petrescu, Philippe Peylin, Robbie M. Andrew, Bradley Matthews, Frank Dentener, Juraj Balkovič, Vladislav Bastrikov, Meike Becker, Gregoire Broquet, Philippe Ciais, Audrey Fortems-Cheiney, Raphael Ganzenmüller, Giacomo Grassi, Ian Harris, Matthew Jones, Jürgen Knauer, Matthias Kuhnert, Guillaume Monteil, Saqr Munassar, Paul I. Palmer, Glen P. Peters, Chunjing Qiu, Mart-Jan Schelhaas, Oksana Tarasova, Matteo Vizzarri, Karina Winkler, Gianpaolo Balsamo, Antoine Berchet, Peter Briggs, Patrick Brockmann, Frédéric Chevallier, Giulia Conchedda, Monica Crippa, Stijn N. C. Dellaert, Hugo A. C. Denier van der Gon, Sara Filipek, Pierre Friedlingstein, Richard Fuchs, Michael Gauss, Christoph Gerbig, Diego Guizzardi, Dirk Günther, Richard A. Houghton, Greet Janssens-Maenhout, Ronny Lauerwald, Bas Lerink, Ingrid T. Luijkx, Géraud Moulas, Marilena Muntean, Gert-Jan Nabuurs, Aurélie Paquirissamy, Lucia Perugini, Wouter Peters, Roberto Pilli, Julia Pongratz, Pierre Regnier, Marko Scholze, Yusuf Serengil, Pete Smith, Efisio Solazzo, Rona L. Thompson, Francesco N. Tubiello, Timo Vesala, and Sophia Walther
Earth Syst. Sci. Data, 15, 4295–4370, https://doi.org/10.5194/essd-15-4295-2023, https://doi.org/10.5194/essd-15-4295-2023, 2023
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Accurate estimation of fluxes of carbon dioxide from the land surface is essential for understanding future impacts of greenhouse gas emissions on the climate system. A wide variety of methods currently exist to estimate these sources and sinks. We are continuing work to develop annual comparisons of these diverse methods in order to clarify what they all actually calculate and to resolve apparent disagreement, in addition to highlighting opportunities for increased understanding.
Shruti Nath, Lukas Gudmundsson, Jonas Schwaab, Gregory Duveiller, Steven J. De Hertog, Suqi Guo, Felix Havermann, Fei Luo, Iris Manola, Julia Pongratz, Sonia I. Seneviratne, Carl F. Schleussner, Wim Thiery, and Quentin Lejeune
Geosci. Model Dev., 16, 4283–4313, https://doi.org/10.5194/gmd-16-4283-2023, https://doi.org/10.5194/gmd-16-4283-2023, 2023
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Tree cover changes play a significant role in climate mitigation and adaptation. Their regional impacts are key in informing national-level decisions and prioritising areas for conservation efforts. We present a first step towards exploring these regional impacts using a simple statistical device, i.e. emulator. The emulator only needs to train on climate model outputs representing the maximal impacts of aff-, re-, and deforestation, from which it explores plausible in-between outcomes itself.
Xiaojuan Yang, Peter Thornton, Daniel Ricciuto, Yilong Wang, and Forrest Hoffman
Biogeosciences, 20, 2813–2836, https://doi.org/10.5194/bg-20-2813-2023, https://doi.org/10.5194/bg-20-2813-2023, 2023
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We evaluated the performance of a land surface model (ELMv1-CNP) that includes both nitrogen (N) and phosphorus (P) limitation on carbon cycle processes. We show that ELMv1-CNP produces realistic estimates of present-day carbon pools and fluxes. We show that global C sources and sinks are significantly affected by P limitation. Our study suggests that introduction of P limitation in land surface models is likely to have substantial consequences for projections of future carbon uptake.
Danny M. Leung, Jasper F. Kok, Longlei Li, Gregory S. Okin, Catherine Prigent, Martina Klose, Carlos Pérez García-Pando, Laurent Menut, Natalie M. Mahowald, David M. Lawrence, and Marcelo Chamecki
Atmos. Chem. Phys., 23, 6487–6523, https://doi.org/10.5194/acp-23-6487-2023, https://doi.org/10.5194/acp-23-6487-2023, 2023
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Desert dust modeling is important for understanding climate change, as dust regulates the atmosphere's greenhouse effect and radiation. This study formulates and proposes a more physical and realistic desert dust emission scheme for global and regional climate models. By considering more aeolian processes in our emission scheme, our simulations match better against dust observations than existing schemes. We believe this work is vital in improving dust representation in climate models.
Alessandro Flammini, Hanif Adzmir, Kevin Karl, and Francesco Nicola Tubiello
Earth Syst. Sci. Data, 15, 2179–2187, https://doi.org/10.5194/essd-15-2179-2023, https://doi.org/10.5194/essd-15-2179-2023, 2023
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This paper estimates the share of greenhouse gas (GHG) emissions attributable to non-renewable wood fuel harvesting for use in residential food-related activities. It adds to a growing research base estimating GHG emissions from across the entire agri-food value chain and contributes to the development of the FAOSTAT climate change domain.
Wenfu Tang, Simone Tilmes, David M. Lawrence, Fang Li, Cenlin He, Louisa K. Emmons, Rebecca R. Buchholz, and Lili Xia
Atmos. Chem. Phys., 23, 5467–5486, https://doi.org/10.5194/acp-23-5467-2023, https://doi.org/10.5194/acp-23-5467-2023, 2023
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Globally, total wildfire burned area is projected to increase over the 21st century under scenarios without geoengineering and decrease under the two geoengineering scenarios. Geoengineering reduces fire by decreasing surface temperature and wind speed and increasing relative humidity and soil water. However, geoengineering also yields reductions in precipitation, which offset some of the fire reduction.
Fiona H. M. Tang, Thu Ha Nguyen, Giulia Conchedda, Leon Casse, Francesco N. Tubiello, and Federico Maggi
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-130, https://doi.org/10.5194/essd-2023-130, 2023
Preprint withdrawn
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CROPGRIDS is a comprehensive global, geo-referenced dataset that provides information on harvested and crop areas of 173 crops circa the year 2020. This new product provides more recent crop type information for 80 crops, covering about 1.2 billion hectares of crop area globally. CROPGRIDS will facilitate global-scale assessments in various disciplines, including agriculture and resource management, food systems, environmental impact and sustainability analyses, and agroeconomics.
Enrico Zorzetto, Sergey Malyshev, Nathaniel Chaney, David Paynter, Raymond Menzel, and Elena Shevliakova
Geosci. Model Dev., 16, 1937–1960, https://doi.org/10.5194/gmd-16-1937-2023, https://doi.org/10.5194/gmd-16-1937-2023, 2023
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In this paper we develop a methodology to model the spatial distribution of solar radiation received by land over mountainous terrain. The approach is designed to be used in Earth system models, where coarse grid cells hinder the description of fine-scale land–atmosphere interactions. We adopt a clustering algorithm to partition the land domain into a set of homogeneous sub-grid
tiles, and for each tile we evaluate solar radiation received by land based on terrain properties.
Laura C. Jackson, Eduardo Alastrué de Asenjo, Katinka Bellomo, Gokhan Danabasoglu, Helmuth Haak, Aixue Hu, Johann Jungclaus, Warren Lee, Virna L. Meccia, Oleg Saenko, Andrew Shao, and Didier Swingedouw
Geosci. Model Dev., 16, 1975–1995, https://doi.org/10.5194/gmd-16-1975-2023, https://doi.org/10.5194/gmd-16-1975-2023, 2023
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The Atlantic meridional overturning circulation (AMOC) has an important impact on the climate. There are theories that freshening of the ocean might cause the AMOC to cross a tipping point (TP) beyond which recovery is difficult; however, it is unclear whether TPs exist in global climate models. Here, we outline a set of experiments designed to explore AMOC tipping points and sensitivity to additional freshwater input as part of the North Atlantic Hosing Model Intercomparison Project (NAHosMIP).
Ana Maria Roxana Petrescu, Chunjing Qiu, Matthew J. McGrath, Philippe Peylin, Glen P. Peters, Philippe Ciais, Rona L. Thompson, Aki Tsuruta, Dominik Brunner, Matthias Kuhnert, Bradley Matthews, Paul I. Palmer, Oksana Tarasova, Pierre Regnier, Ronny Lauerwald, David Bastviken, Lena Höglund-Isaksson, Wilfried Winiwarter, Giuseppe Etiope, Tuula Aalto, Gianpaolo Balsamo, Vladislav Bastrikov, Antoine Berchet, Patrick Brockmann, Giancarlo Ciotoli, Giulia Conchedda, Monica Crippa, Frank Dentener, Christine D. Groot Zwaaftink, Diego Guizzardi, Dirk Günther, Jean-Matthieu Haussaire, Sander Houweling, Greet Janssens-Maenhout, Massaer Kouyate, Adrian Leip, Antti Leppänen, Emanuele Lugato, Manon Maisonnier, Alistair J. Manning, Tiina Markkanen, Joe McNorton, Marilena Muntean, Gabriel D. Oreggioni, Prabir K. Patra, Lucia Perugini, Isabelle Pison, Maarit T. Raivonen, Marielle Saunois, Arjo J. Segers, Pete Smith, Efisio Solazzo, Hanqin Tian, Francesco N. Tubiello, Timo Vesala, Guido R. van der Werf, Chris Wilson, and Sönke Zaehle
Earth Syst. Sci. Data, 15, 1197–1268, https://doi.org/10.5194/essd-15-1197-2023, https://doi.org/10.5194/essd-15-1197-2023, 2023
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This study updates the state-of-the-art scientific overview of CH4 and N2O emissions in the EU27 and UK in Petrescu et al. (2021a). Yearly updates are needed to improve the different respective approaches and to inform on the development of formal verification systems. It integrates the most recent emission inventories, process-based model and regional/global inversions, comparing them with UNFCCC national GHG inventories, in support to policy to facilitate real-time verification procedures.
Giacomo Grassi, Clemens Schwingshackl, Thomas Gasser, Richard A. Houghton, Stephen Sitch, Josep G. Canadell, Alessandro Cescatti, Philippe Ciais, Sandro Federici, Pierre Friedlingstein, Werner A. Kurz, Maria J. Sanz Sanchez, Raúl Abad Viñas, Ramdane Alkama, Selma Bultan, Guido Ceccherini, Stefanie Falk, Etsushi Kato, Daniel Kennedy, Jürgen Knauer, Anu Korosuo, Joana Melo, Matthew J. McGrath, Julia E. M. S. Nabel, Benjamin Poulter, Anna A. Romanovskaya, Simone Rossi, Hanqin Tian, Anthony P. Walker, Wenping Yuan, Xu Yue, and Julia Pongratz
Earth Syst. Sci. Data, 15, 1093–1114, https://doi.org/10.5194/essd-15-1093-2023, https://doi.org/10.5194/essd-15-1093-2023, 2023
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Striking differences exist in estimates of land-use CO2 fluxes between the national greenhouse gas inventories and the IPCC assessment reports. These differences hamper an accurate assessment of the collective progress under the Paris Agreement. By implementing an approach that conceptually reconciles land-use CO2 flux from national inventories and the global models used by the IPCC, our study is an important step forward for increasing confidence in land-use CO2 flux estimates.
Brendan Byrne, David F. Baker, Sourish Basu, Michael Bertolacci, Kevin W. Bowman, Dustin Carroll, Abhishek Chatterjee, Frédéric Chevallier, Philippe Ciais, Noel Cressie, David Crisp, Sean Crowell, Feng Deng, Zhu Deng, Nicholas M. Deutscher, Manvendra K. Dubey, Sha Feng, Omaira E. García, David W. T. Griffith, Benedikt Herkommer, Lei Hu, Andrew R. Jacobson, Rajesh Janardanan, Sujong Jeong, Matthew S. Johnson, Dylan B. A. Jones, Rigel Kivi, Junjie Liu, Zhiqiang Liu, Shamil Maksyutov, John B. Miller, Scot M. Miller, Isamu Morino, Justus Notholt, Tomohiro Oda, Christopher W. O'Dell, Young-Suk Oh, Hirofumi Ohyama, Prabir K. Patra, Hélène Peiro, Christof Petri, Sajeev Philip, David F. Pollard, Benjamin Poulter, Marine Remaud, Andrew Schuh, Mahesh K. Sha, Kei Shiomi, Kimberly Strong, Colm Sweeney, Yao Té, Hanqin Tian, Voltaire A. Velazco, Mihalis Vrekoussis, Thorsten Warneke, John R. Worden, Debra Wunch, Yuanzhi Yao, Jeongmin Yun, Andrew Zammit-Mangion, and Ning Zeng
Earth Syst. Sci. Data, 15, 963–1004, https://doi.org/10.5194/essd-15-963-2023, https://doi.org/10.5194/essd-15-963-2023, 2023
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Changes in the carbon stocks of terrestrial ecosystems result in emissions and removals of CO2. These can be driven by anthropogenic activities (e.g., deforestation), natural processes (e.g., fires) or in response to rising CO2 (e.g., CO2 fertilization). This paper describes a dataset of CO2 emissions and removals derived from atmospheric CO2 observations. This pilot dataset informs current capabilities and future developments towards top-down monitoring and verification systems.
Zun Yin, Kirsten L. Findell, Paul Dirmeyer, Elena Shevliakova, Sergey Malyshev, Khaled Ghannam, Nina Raoult, and Zhihong Tan
Hydrol. Earth Syst. Sci., 27, 861–872, https://doi.org/10.5194/hess-27-861-2023, https://doi.org/10.5194/hess-27-861-2023, 2023
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Land–atmosphere (L–A) interactions typically focus on daytime processes connecting the land state with the overlying atmospheric boundary layer. However, much prior L–A work used monthly or daily means due to the lack of daytime-only data products. Here we show that monthly smoothing can significantly obscure the L–A coupling signal, and including nighttime information can mute or mask the daytime processes of interest. We propose diagnosing L–A coupling within models or archiving subdaily data.
Aolin Jia, Shunlin Liang, Dongdong Wang, Lei Ma, Zhihao Wang, and Shuo Xu
Earth Syst. Sci. Data, 15, 869–895, https://doi.org/10.5194/essd-15-869-2023, https://doi.org/10.5194/essd-15-869-2023, 2023
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Satellites are now producing multiple global land surface temperature (LST) products; however, they suffer from data gaps caused by cloud cover, seriously restricting the applications, and few products provide gap-free global hourly LST. We produced global hourly, 5 km, all-sky LST data from 2011 to 2021 using geostationary and polar-orbiting satellite data. Based on the assessment, it has high accuracy and can be used to estimate evapotranspiration, drought, etc.
Evelien van Dijk, Ingar Mørkestøl Gundersen, Anna de Bode, Helge Høeg, Kjetil Loftsgarden, Frode Iversen, Claudia Timmreck, Johann Jungclaus, and Kirstin Krüger
Clim. Past, 19, 357–398, https://doi.org/10.5194/cp-19-357-2023, https://doi.org/10.5194/cp-19-357-2023, 2023
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The mid-6th century was one of the coldest periods of the last 2000 years as characterized by great societal changes. Here, we study the effect of the volcanic double event in 536 CE and 540 CE on climate and society in southern Norway. The combined climate and growing degree day models and high-resolution pollen and archaeological records reveal that the northern and western sites are vulnerable to crop failure with possible abandonment of farms, whereas the southeastern site is more resilient.
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.
Andrew F. Feldman, Zhen Zhang, Yasuko Yoshida, Abhishek Chatterjee, and Benjamin Poulter
Atmos. Chem. Phys., 23, 1545–1563, https://doi.org/10.5194/acp-23-1545-2023, https://doi.org/10.5194/acp-23-1545-2023, 2023
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We investigate the conditions under which satellite-retrieved column carbon dioxide concentrations directly hold information about surface carbon dioxide fluxes, without the use of inversion models. We show that OCO-2 column carbon dioxide retrievals, available at 1–3 month latency, can be used to directly detect and roughly estimate extreme biospheric CO2 fluxes. As such, these OCO-2 retrievals have value for rapidly monitoring extreme conditions in the terrestrial biosphere.
Minjin Lee, Charles A. Stock, John P. Dunne, and Elena Shevliakova
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-236, https://doi.org/10.5194/gmd-2022-236, 2023
Revised manuscript accepted for GMD
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Modeling global freshwater solid and nutrient loads, in both magnitude and form, is imperative for understanding emerging eutrophication problems. Such efforts, however, have been challenged by the difficulty of balancing details of freshwater biogeochemical processes with limited knowledge, input and validation datasets. Here we develop a global freshwater model that resolves intertwined algae, solid, and nutrient dynamics and provide performance assessment against measurement-based estimates.
Jed O. Kaplan and Katie Hong-Kiu Lau
Earth Syst. Sci. Data, 14, 5665–5670, https://doi.org/10.5194/essd-14-5665-2022, https://doi.org/10.5194/essd-14-5665-2022, 2022
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Global lightning strokes are recorded continuously by a network of ground-based stations. We consolidated these point observations into a map form and provide these as electronic datasets for research purposes. Here we extend our dataset to include lightning observations from 2021.
Jarmo S. Kikstra, Zebedee R. J. Nicholls, Christopher J. Smith, Jared Lewis, Robin D. Lamboll, Edward Byers, Marit Sandstad, Malte Meinshausen, Matthew J. Gidden, Joeri Rogelj, Elmar Kriegler, Glen P. Peters, Jan S. Fuglestvedt, Ragnhild B. Skeie, Bjørn H. Samset, Laura Wienpahl, Detlef P. van Vuuren, Kaj-Ivar van der Wijst, Alaa Al Khourdajie, Piers M. Forster, Andy Reisinger, Roberto Schaeffer, and Keywan Riahi
Geosci. Model Dev., 15, 9075–9109, https://doi.org/10.5194/gmd-15-9075-2022, https://doi.org/10.5194/gmd-15-9075-2022, 2022
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Assessing hundreds or thousands of emission scenarios in terms of their global mean temperature implications requires standardised procedures of infilling, harmonisation, and probabilistic temperature assessments. We here present the open-source
climate-assessmentworkflow that was used in the IPCC AR6 Working Group III report. The paper provides key insight for anyone wishing to understand the assessment of climate outcomes of mitigation pathways in the context of the Paris Agreement.
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.
Kristine Karstens, Benjamin Leon Bodirsky, Jan Philipp Dietrich, Marta Dondini, Jens Heinke, Matthias Kuhnert, Christoph Müller, Susanne Rolinski, Pete Smith, Isabelle Weindl, Hermann Lotze-Campen, and Alexander Popp
Biogeosciences, 19, 5125–5149, https://doi.org/10.5194/bg-19-5125-2022, https://doi.org/10.5194/bg-19-5125-2022, 2022
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Soil organic carbon (SOC) has been depleted by anthropogenic land cover change and agricultural management. While SOC models often simulate detailed biochemical processes, the management decisions are still little investigated at the global scale. We estimate that soils have lost around 26 GtC relative to a counterfactual natural state in 1975. Yet, since 1975, SOC has been increasing again by 4 GtC due to a higher productivity, recycling of crop residues and manure, and no-tillage practices.
Shih-Wei Fang, Claudia Timmreck, Johann Jungclaus, Kirstin Krüger, and Hauke Schmidt
Earth Syst. Dynam., 13, 1535–1555, https://doi.org/10.5194/esd-13-1535-2022, https://doi.org/10.5194/esd-13-1535-2022, 2022
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The early 19th century was the coldest period over the past 500 years, when strong tropical volcanic events and a solar minimum coincided. This study quantifies potential surface cooling from the solar and volcanic forcing in the early 19th century with large ensemble simulations, and identifies the regions that their impacts cannot be simply additive. The cooling perspective of Arctic amplification exists in both solar and post-volcano period with the albedo feedback as the main contribution.
Giacomo Grassi, Giulia Conchedda, Sandro Federici, Raul Abad Viñas, Anu Korosuo, Joana Melo, Simone Rossi, Marieke Sandker, Zoltan Somogyi, Matteo Vizzarri, and Francesco N. Tubiello
Earth Syst. Sci. Data, 14, 4643–4666, https://doi.org/10.5194/essd-14-4643-2022, https://doi.org/10.5194/essd-14-4643-2022, 2022
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Despite increasing attention on the role of land use CO2 fluxes in climate change mitigation, there are large differences in available databases. Here we present the most updated and complete compilation of land use CO2 data based on country submissions to United Nations Framework Convention on Climate Change and explain differences with other datasets. Our dataset brings clarity of land use CO2 fluxes and helps track country progress under the Paris Agreement.
Hanqin Tian, Zihao Bian, Hao Shi, Xiaoyu Qin, Naiqing Pan, Chaoqun Lu, Shufen Pan, Francesco N. Tubiello, Jinfeng Chang, Giulia Conchedda, Junguo Liu, Nathaniel Mueller, Kazuya Nishina, Rongting Xu, Jia Yang, Liangzhi You, and Bowen Zhang
Earth Syst. Sci. Data, 14, 4551–4568, https://doi.org/10.5194/essd-14-4551-2022, https://doi.org/10.5194/essd-14-4551-2022, 2022
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Nitrogen is one of the critical nutrients for growth. Evaluating the change in nitrogen inputs due to human activity is necessary for nutrient management and pollution control. In this study, we generated a historical dataset of nitrogen input to land at the global scale. This dataset consists of nitrogen fertilizer, manure, and atmospheric deposition inputs to cropland, pasture, and rangeland at high resolution from 1860 to 2019.
Basil Andrew Stansfield Davis, Marc Fasel, Jed O. Kaplan, Emmanuele Russo, and Ariane Burke
Clim. Past Discuss., https://doi.org/10.5194/cp-2022-59, https://doi.org/10.5194/cp-2022-59, 2022
Revised manuscript accepted for CP
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During the last Ice Age 21 k BP, Northern Europe was covered in ice and steppe, and forests were restricted to sheltered regions to the south. However, the composition and extent of forest and its associated climate remains unclear, with models indicating more forest north of the Alps than suggested by the data. A new compilation of pollen records with improved dating suggests greater agreement with model climate, but still suggests models over estimate forest cover especially in the west.
Daniel J. Jacob, Daniel J. Varon, Daniel H. Cusworth, Philip E. Dennison, Christian Frankenberg, Ritesh Gautam, Luis Guanter, John Kelley, Jason McKeever, Lesley E. Ott, Benjamin Poulter, Zhen Qu, Andrew K. Thorpe, John R. Worden, and Riley M. Duren
Atmos. Chem. Phys., 22, 9617–9646, https://doi.org/10.5194/acp-22-9617-2022, https://doi.org/10.5194/acp-22-9617-2022, 2022
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We review the capability of satellite observations of atmospheric methane to quantify methane emissions on all scales. We cover retrieval methods, precision requirements, inverse methods for inferring emissions, source detection thresholds, and observations of system completeness. We show that current instruments already enable quantification of regional and national emissions including contributions from large point sources. Coverage and resolution will increase significantly in coming years.
Evelien van Dijk, Johann Jungclaus, Stephan Lorenz, Claudia Timmreck, and Kirstin Krüger
Clim. Past, 18, 1601–1623, https://doi.org/10.5194/cp-18-1601-2022, https://doi.org/10.5194/cp-18-1601-2022, 2022
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A double volcanic eruption in 536 and 540 CE caused one of the coldest decades during the last 2000 years. We analyzed new climate model simulations from that period and found a cooling of up to 2°C and a sea-ice extent up to 200 km further south. Complex interactions between sea ice and ocean circulation lead to a reduction in the northward ocean heat transport, which makes the sea ice extend further south; this in turn leads to a surface cooling up to 20 years after the eruptions.
Inne Vanderkelen, Shervan Gharari, Naoki Mizukami, Martyn P. Clark, David M. Lawrence, Sean Swenson, Yadu Pokhrel, Naota Hanasaki, Ann van Griensven, and Wim Thiery
Geosci. Model Dev., 15, 4163–4192, https://doi.org/10.5194/gmd-15-4163-2022, https://doi.org/10.5194/gmd-15-4163-2022, 2022
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Human-controlled reservoirs have a large influence on the global water cycle. However, dam operations are rarely represented in Earth system models. We implement and evaluate a widely used reservoir parametrization in a global river-routing model. Using observations of individual reservoirs, the reservoir scheme outperforms the natural lake scheme. However, both schemes show a similar performance due to biases in runoff timing and magnitude when using simulated runoff.
Colm Sweeney, Abhishek Chatterjee, Sonja Wolter, Kathryn McKain, Robert Bogue, Stephen Conley, Tim Newberger, Lei Hu, Lesley Ott, Benjamin Poulter, Luke Schiferl, Brad Weir, Zhen Zhang, and Charles E. Miller
Atmos. Chem. Phys., 22, 6347–6364, https://doi.org/10.5194/acp-22-6347-2022, https://doi.org/10.5194/acp-22-6347-2022, 2022
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The Arctic Carbon Atmospheric Profiles (Arctic-CAP) project demonstrates the utility of aircraft profiles for independent evaluation of model-derived emissions and uptake of atmospheric CO2, CH4, and CO from land and ocean. Comparison with the Goddard Earth Observing System (GEOS) modeling system suggests that fluxes of CO2 are very consistent with observations, while those of CH4 have some regional and seasonal biases, and that CO comparison is complicated by transport errors.
M. Hosseini, I. Becker-Reshef, R. Sahajpal, P. Lafluf, G. Leale, E. Puricelli, S. Skakun, and H. McNairn
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2022, 405–410, https://doi.org/10.5194/isprs-annals-V-3-2022-405-2022, https://doi.org/10.5194/isprs-annals-V-3-2022-405-2022, 2022
Charles D. Koven, Vivek K. Arora, Patricia Cadule, Rosie A. Fisher, Chris D. Jones, David M. Lawrence, Jared Lewis, Keith Lindsay, Sabine Mathesius, Malte Meinshausen, Michael Mills, Zebedee Nicholls, Benjamin M. Sanderson, Roland Séférian, Neil C. Swart, William R. Wieder, and Kirsten Zickfeld
Earth Syst. Dynam., 13, 885–909, https://doi.org/10.5194/esd-13-885-2022, https://doi.org/10.5194/esd-13-885-2022, 2022
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We explore the long-term dynamics of Earth's climate and carbon cycles under a pair of contrasting scenarios to the year 2300 using six models that include both climate and carbon cycle dynamics. One scenario assumes very high emissions, while the second assumes a peak in emissions, followed by rapid declines to net negative emissions. We show that the models generally agree that warming is roughly proportional to carbon emissions but that many other aspects of the model projections differ.
Xiaoxu Shi, Martin Werner, Carolin Krug, Chris M. Brierley, Anni Zhao, Endurance Igbinosa, Pascale Braconnot, Esther Brady, Jian Cao, Roberta D'Agostino, Johann Jungclaus, Xingxing Liu, Bette Otto-Bliesner, Dmitry Sidorenko, Robert Tomas, Evgeny M. Volodin, Hu Yang, Qiong Zhang, Weipeng Zheng, and Gerrit Lohmann
Clim. Past, 18, 1047–1070, https://doi.org/10.5194/cp-18-1047-2022, https://doi.org/10.5194/cp-18-1047-2022, 2022
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Since the orbital parameters of the past are different from today, applying the modern calendar to the past climate can lead to an artificial bias in seasonal cycles. With the use of multiple model outputs, we found that such a bias is non-ignorable and should be corrected to ensure an accurate comparison between modeled results and observational records, as well as between simulated past and modern climates, especially for the Last Interglacial.
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.
Francesco N. Tubiello, Kevin Karl, Alessandro Flammini, Johannes Gütschow, Griffiths Obli-Laryea, Giulia Conchedda, Xueyao Pan, Sally Yue Qi, Hörn Halldórudóttir Heiðarsdóttir, Nathan Wanner, Roberta Quadrelli, Leonardo Rocha Souza, Philippe Benoit, Matthew Hayek, David Sandalow, Erik Mencos Contreras, Cynthia Rosenzweig, Jose Rosero Moncayo, Piero Conforti, and Maximo Torero
Earth Syst. Sci. Data, 14, 1795–1809, https://doi.org/10.5194/essd-14-1795-2022, https://doi.org/10.5194/essd-14-1795-2022, 2022
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The paper presents results from the new FAOSTAT database on food system emissions, covering all countries over the time series 1990–2019. Results indicate and further clarify – updated to 2019 – the relevance of emissions from crop and livestock production processes within the farm gate; from conversion of natural ecosystems to agriculture, such as deforestation and peat degradation; and from use of fossil fuels for energy and other industrial processes along food supply chains.
Zhu Deng, Philippe Ciais, Zitely A. Tzompa-Sosa, Marielle Saunois, Chunjing Qiu, Chang Tan, Taochun Sun, Piyu Ke, Yanan Cui, Katsumasa Tanaka, Xin Lin, Rona L. Thompson, Hanqin Tian, Yuanzhi Yao, Yuanyuan Huang, Ronny Lauerwald, Atul K. Jain, Xiaoming Xu, Ana Bastos, Stephen Sitch, Paul I. Palmer, Thomas Lauvaux, Alexandre d'Aspremont, Clément Giron, Antoine Benoit, Benjamin Poulter, Jinfeng Chang, Ana Maria Roxana Petrescu, Steven J. Davis, Zhu Liu, Giacomo Grassi, Clément Albergel, Francesco N. Tubiello, Lucia Perugini, Wouter Peters, and Frédéric Chevallier
Earth Syst. Sci. Data, 14, 1639–1675, https://doi.org/10.5194/essd-14-1639-2022, https://doi.org/10.5194/essd-14-1639-2022, 2022
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In support of the global stocktake of the Paris Agreement on climate change, we proposed a method for reconciling the results of global atmospheric inversions with data from UNFCCC national greenhouse gas inventories (NGHGIs). Here, based on a new global harmonized database that we compiled from the UNFCCC NGHGIs and a comprehensive framework presented in this study to process the results of inversions, we compared their results of carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O).
Matthew Binsted, Gokul Iyer, Pralit Patel, Neal T. Graham, Yang Ou, Zarrar Khan, Nazar Kholod, Kanishka Narayan, Mohamad Hejazi, Son Kim, Katherine Calvin, and Marshall Wise
Geosci. Model Dev., 15, 2533–2559, https://doi.org/10.5194/gmd-15-2533-2022, https://doi.org/10.5194/gmd-15-2533-2022, 2022
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GCAM-USA v5.3_water_dispatch is an open-source model that represents key interactions across economic, energy, water, and land systems in a global framework, with subnational detail in the United States. GCAM-USA can be used to explore future changes in demand for (and production of) energy, water, and crops at the state and regional level in the US. This paper describes GCAM-USA and provides four illustrative scenarios to demonstrate the model's capabilities and potential applications.
Ronny Meier, Edouard L. Davin, Gordon B. Bonan, David M. Lawrence, Xiaolong Hu, Gregory Duveiller, Catherine Prigent, and Sonia I. Seneviratne
Geosci. Model Dev., 15, 2365–2393, https://doi.org/10.5194/gmd-15-2365-2022, https://doi.org/10.5194/gmd-15-2365-2022, 2022
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We revise the roughness of the land surface in the CESM climate model. Guided by observational data, we increase the surface roughness of forests and decrease that of bare soil, snow, ice, and crops. These modifications alter simulated temperatures and wind speeds at and above the land surface considerably, in particular over desert regions. The revised model represents the diurnal variability of the land surface temperature better compared to satellite observations over most regions.
Dóra Hidy, Zoltán Barcza, Roland Hollós, Laura Dobor, Tamás Ács, Dóra Zacháry, Tibor Filep, László Pásztor, Dóra Incze, Márton Dencső, Eszter Tóth, Katarína Merganičová, Peter Thornton, Steven Running, and Nándor Fodor
Geosci. Model Dev., 15, 2157–2181, https://doi.org/10.5194/gmd-15-2157-2022, https://doi.org/10.5194/gmd-15-2157-2022, 2022
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Biogeochemical models used by the scientific community can support society in the quantification of the expected environmental impacts caused by global climate change. The Biome-BGCMuSo v6.2 biogeochemical model has been created by implementing a lot of developments related to soil hydrology as well as the soil carbon and nitrogen cycle and by integrating crop model components. Detailed descriptions of developments with case studies are presented in this paper.
Lei Ma, George Hurtt, Lesley Ott, Ritvik Sahajpal, Justin Fisk, Rachel Lamb, Hao Tang, Steve Flanagan, Louise Chini, Abhishek Chatterjee, and Joseph Sullivan
Geosci. Model Dev., 15, 1971–1994, https://doi.org/10.5194/gmd-15-1971-2022, https://doi.org/10.5194/gmd-15-1971-2022, 2022
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We present a global version of the Ecosystem Demography (ED) model which can track vegetation 3-D structure and scale up ecological processes from individual vegetation to ecosystem scale. Model evaluation against multiple benchmarking datasets demonstrated the model’s capability to simulate global vegetation dynamics across a range of temporal and spatial scales. With this version, ED has the potential to be linked with remote sensing observations to address key scientific questions.
Alessandro Flammini, Xueyao Pan, Francesco Nicola Tubiello, Sally Yue Qiu, Leonardo Rocha Souza, Roberta Quadrelli, Stefania Bracco, Philippe Benoit, and Ralph Sims
Earth Syst. Sci. Data, 14, 811–821, https://doi.org/10.5194/essd-14-811-2022, https://doi.org/10.5194/essd-14-811-2022, 2022
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Fossil-fuel-based energy used in agriculture, for crop and livestock production as well as in fisheries, generates significant amounts of greenhouse gases (GHG), which are typically not accounted for within the agriculture sector of national GHG inventories. Using activity data from UNSD and IEA, we construct a new database of energy use in agriculture and related emissions, covering the period 1970–2019 by country and by fossil fuel type, including emissions from electricity used on the farm.
Philippe Ciais, Ana Bastos, Frédéric Chevallier, Ronny Lauerwald, Ben Poulter, Josep G. Canadell, Gustaf Hugelius, Robert B. Jackson, Atul Jain, Matthew Jones, Masayuki Kondo, Ingrid T. Luijkx, Prabir K. Patra, Wouter Peters, Julia Pongratz, Ana Maria Roxana Petrescu, Shilong Piao, Chunjing Qiu, Celso Von Randow, Pierre Regnier, Marielle Saunois, Robert Scholes, Anatoly Shvidenko, Hanqin Tian, Hui Yang, Xuhui Wang, and Bo Zheng
Geosci. Model Dev., 15, 1289–1316, https://doi.org/10.5194/gmd-15-1289-2022, https://doi.org/10.5194/gmd-15-1289-2022, 2022
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The second phase of the Regional Carbon Cycle Assessment and Processes (RECCAP) will provide updated quantification and process understanding of CO2, CH4, and N2O emissions and sinks for ten regions of the globe. In this paper, we give definitions, review different methods, and make recommendations for estimating different components of the total land–atmosphere carbon exchange for each region in a consistent and complete approach.
Katherine V. Calvin, Abigail Snyder, Xin Zhao, and Marshall Wise
Geosci. Model Dev., 15, 429–447, https://doi.org/10.5194/gmd-15-429-2022, https://doi.org/10.5194/gmd-15-429-2022, 2022
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Future changes in land use and cover have important implications for agriculture, energy, water use, and climate. In this study, we demonstrate a more systematic and empirically based approach to estimating a few key parameters for an economic model of land use and land cover change, gcamland. We identify parameter combinations that best replicate historical land use in the United States.
Simon Besnard, Sujan Koirala, Maurizio Santoro, Ulrich Weber, Jacob Nelson, Jonas Gütter, Bruno Herault, Justin Kassi, Anny N'Guessan, Christopher Neigh, Benjamin Poulter, Tao Zhang, and Nuno Carvalhais
Earth Syst. Sci. Data, 13, 4881–4896, https://doi.org/10.5194/essd-13-4881-2021, https://doi.org/10.5194/essd-13-4881-2021, 2021
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Forest age can determine the capacity of a forest to uptake carbon from the atmosphere. Yet, a lack of global diagnostics that reflect the forest stage and associated disturbance regimes hampers the quantification of age-related differences in forest carbon dynamics. In this paper, we introduced a new global distribution of forest age inferred from forest inventory, remote sensing and climate data in support of a better understanding of the global dynamics in the forest water and carbon cycles.
Abhijeet Mishra, Florian Humpenöder, Jan Philipp Dietrich, Benjamin Leon Bodirsky, Brent Sohngen, Christopher P. O. Reyer, Hermann Lotze-Campen, and Alexander Popp
Geosci. Model Dev., 14, 6467–6494, https://doi.org/10.5194/gmd-14-6467-2021, https://doi.org/10.5194/gmd-14-6467-2021, 2021
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Timber plantations are an increasingly important source of roundwood production, next to harvest from natural forests. However, timber plantations are currently underrepresented in global land-use models. Here, we include timber production and plantations in the MAgPIE modeling framework. This allows one to capture the competition for land between agriculture and forestry. We show that increasing timber plantations in the coming decades partly compete with cropland for limited land resources.
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.
Louise Chini, George Hurtt, Ritvik Sahajpal, Steve Frolking, Kees Klein Goldewijk, Stephen Sitch, Raphael Ganzenmüller, Lei Ma, Lesley Ott, Julia Pongratz, and Benjamin Poulter
Earth Syst. Sci. Data, 13, 4175–4189, https://doi.org/10.5194/essd-13-4175-2021, https://doi.org/10.5194/essd-13-4175-2021, 2021
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Carbon emissions from land-use change are a large and uncertain component of the global carbon cycle. The Land-Use Harmonization 2 (LUH2) dataset was developed as an input to carbon and climate simulations and has been updated annually for the Global Carbon Budget (GCB) assessments. Here we discuss the methodology for producing these annual LUH2 updates and describe the 2019 version which used new cropland and grazing land data inputs for the globally important region of Brazil.
Kyle B. Delwiche, Sara Helen Knox, Avni Malhotra, Etienne Fluet-Chouinard, Gavin McNicol, Sarah Feron, Zutao Ouyang, Dario Papale, Carlo Trotta, Eleonora Canfora, You-Wei Cheah, Danielle Christianson, Ma. Carmelita R. Alberto, Pavel Alekseychik, Mika Aurela, Dennis Baldocchi, Sheel Bansal, David P. Billesbach, Gil Bohrer, Rosvel Bracho, Nina Buchmann, David I. Campbell, Gerardo Celis, Jiquan Chen, Weinan Chen, Housen Chu, Higo J. Dalmagro, Sigrid Dengel, Ankur R. Desai, Matteo Detto, Han Dolman, Elke Eichelmann, Eugenie Euskirchen, Daniela Famulari, Kathrin Fuchs, Mathias Goeckede, Sébastien Gogo, Mangaliso J. Gondwe, Jordan P. Goodrich, Pia Gottschalk, Scott L. Graham, Martin Heimann, Manuel Helbig, Carole Helfter, Kyle S. Hemes, Takashi Hirano, David Hollinger, Lukas Hörtnagl, Hiroki Iwata, Adrien Jacotot, Gerald Jurasinski, Minseok Kang, Kuno Kasak, John King, Janina Klatt, Franziska Koebsch, Ken W. Krauss, Derrick Y. F. Lai, Annalea Lohila, Ivan Mammarella, Luca Belelli Marchesini, Giovanni Manca, Jaclyn Hatala Matthes, Trofim Maximov, Lutz Merbold, Bhaskar Mitra, Timothy H. Morin, Eiko Nemitz, Mats B. Nilsson, Shuli Niu, Walter C. Oechel, Patricia Y. Oikawa, Keisuke Ono, Matthias Peichl, Olli Peltola, Michele L. Reba, Andrew D. Richardson, William Riley, Benjamin R. K. Runkle, Youngryel Ryu, Torsten Sachs, Ayaka Sakabe, Camilo Rey Sanchez, Edward A. Schuur, Karina V. R. Schäfer, Oliver Sonnentag, Jed P. Sparks, Ellen Stuart-Haëntjens, Cove Sturtevant, Ryan C. Sullivan, Daphne J. Szutu, Jonathan E. Thom, Margaret S. Torn, Eeva-Stiina Tuittila, Jessica Turner, Masahito Ueyama, Alex C. Valach, Rodrigo Vargas, Andrej Varlagin, Alma Vazquez-Lule, Joseph G. Verfaillie, Timo Vesala, George L. Vourlitis, Eric J. Ward, Christian Wille, Georg Wohlfahrt, Guan Xhuan Wong, Zhen Zhang, Donatella Zona, Lisamarie Windham-Myers, Benjamin Poulter, and Robert B. Jackson
Earth Syst. Sci. Data, 13, 3607–3689, https://doi.org/10.5194/essd-13-3607-2021, https://doi.org/10.5194/essd-13-3607-2021, 2021
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Methane is an important greenhouse gas, yet we lack knowledge about its global emissions and drivers. We present FLUXNET-CH4, a new global collection of methane measurements and a critical resource for the research community. We use FLUXNET-CH4 data to quantify the seasonality of methane emissions from freshwater wetlands, finding that methane seasonality varies strongly with latitude. Our new database and analysis will improve wetland model accuracy and inform greenhouse gas budgets.
Eva Sinha, Kate Calvin, Ben Bond-Lamberty, Beth Drewniak, Dan Ricciuto, Khachik Sargsyan, Yanyan Cheng, Carl Bernacchi, and Caitlin Moore
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2021-244, https://doi.org/10.5194/gmd-2021-244, 2021
Preprint withdrawn
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Perennial bioenergy crops are not well represented in global land models, despite projected increase in their production. Our study expands Energy Exascale Earth System Model (E3SM) Land Model (ELM) to include perennial bioenergy crops and calibrates the model for miscanthus and switchgrass. The calibrated model captures the seasonality and magnitude of carbon and energy fluxes. This study provides the foundation for future research examining the impact of perennial bioenergy crop expansion.
Sian Kou-Giesbrecht, Sergey Malyshev, Isabel Martínez Cano, Stephen W. Pacala, Elena Shevliakova, Thomas A. Bytnerowicz, and Duncan N. L. Menge
Biogeosciences, 18, 4143–4183, https://doi.org/10.5194/bg-18-4143-2021, https://doi.org/10.5194/bg-18-4143-2021, 2021
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Representing biological nitrogen fixation (BNF) is an important challenge for land models. We present a novel representation of BNF and updated nitrogen cycling in a land model. It includes a representation of asymbiotic BNF by soil microbes and the competitive dynamics between nitrogen-fixing and non-fixing plants. It improves estimations of major carbon and nitrogen pools and fluxes and their temporal dynamics in comparison to previous representations of BNF in land models.
Daniel M. Ricciuto, Xiaojuan Yang, Dali Wang, and Peter E. Thornton
Biogeosciences Discuss., https://doi.org/10.5194/bg-2021-163, https://doi.org/10.5194/bg-2021-163, 2021
Publication in BG not foreseen
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This paper uses a novel approach to quantify the impacts of the choice of decomposition model on carbon and nitrogen cycling. We compare the models to experimental data that examined litter decomposition over five different biomes. Despite widely differing assumptions, the models produce similar patterns of decomposition when nutrients are limiting. This differs from past analyses that did not consider the impacts of changing environmental conditions or nutrients.
Jed O. Kaplan and Katie Hong-Kiu Lau
Earth Syst. Sci. Data, 13, 3219–3237, https://doi.org/10.5194/essd-13-3219-2021, https://doi.org/10.5194/essd-13-3219-2021, 2021
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Lightning is an important atmospheric phenomenon and natural hazard, but few long-term data are freely available on lightning stroke location, timing, and power. Here, we present a new, open-access dataset of lightning strokes covering 2010–2020, based on a network of low-frequency radio detectors. The dataset is comprised of GIS maps and is intended for researchers, government, industry, and anyone for whom knowing when and where lightning is likely to strike is useful information.
Kerstin Hartung, Ana Bastos, Louise Chini, Raphael Ganzenmüller, Felix Havermann, George C. Hurtt, Tammas Loughran, Julia E. M. S. Nabel, Tobias Nützel, Wolfgang A. Obermeier, and Julia Pongratz
Earth Syst. Dynam., 12, 763–782, https://doi.org/10.5194/esd-12-763-2021, https://doi.org/10.5194/esd-12-763-2021, 2021
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In this study, we model the relative importance of several contributors to the land-use and land-cover change (LULCC) flux based on a LULCC dataset including uncertainty estimates. The uncertainty of LULCC is as relevant as applying wood harvest and gross transitions for the cumulative LULCC flux over the industrial period. However, LULCC uncertainty matters less than the other two factors for the LULCC flux in 2014; historical LULCC uncertainty is negligible for estimates of future scenarios.
Brad Weir, Lesley E. Ott, George J. Collatz, Stephan R. Kawa, Benjamin Poulter, Abhishek Chatterjee, Tomohiro Oda, and Steven Pawson
Atmos. Chem. Phys., 21, 9609–9628, https://doi.org/10.5194/acp-21-9609-2021, https://doi.org/10.5194/acp-21-9609-2021, 2021
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We present a collection of carbon surface fluxes, the Low-order Flux Inversion (LoFI), derived from satellite observations of the Earth's surface and calibrated to match long-term inventories and atmospheric and oceanic records. Simulations using LoFI reproduce background atmospheric carbon dioxide measurements with comparable skill to the leading surface flux products. Available both retrospectively and as a forecast, LoFI enables the study of the carbon cycle as it occurs.
Patricio Velasquez, Jed O. Kaplan, Martina Messmer, Patrick Ludwig, and Christoph C. Raible
Clim. Past, 17, 1161–1180, https://doi.org/10.5194/cp-17-1161-2021, https://doi.org/10.5194/cp-17-1161-2021, 2021
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This study assesses the importance of resolution and land–atmosphere feedbacks for European climate. We performed an asynchronously coupled experiment that combined a global climate model (~ 100 km), a regional climate model (18 km), and a dynamic vegetation model (18 km). Modelled climate and land cover agree reasonably well with independent reconstructions based on pollen and other paleoenvironmental proxies. The regional climate is significantly influenced by land cover.
Jun'ya Takakura, Shinichiro Fujimori, Kiyoshi Takahashi, Naota Hanasaki, Tomoko Hasegawa, Yukiko Hirabayashi, Yasushi Honda, Toshichika Iizumi, Chan Park, Makoto Tamura, and Yasuaki Hijioka
Geosci. Model Dev., 14, 3121–3140, https://doi.org/10.5194/gmd-14-3121-2021, https://doi.org/10.5194/gmd-14-3121-2021, 2021
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To simplify calculating economic impacts of climate change, statistical methods called emulators are developed and evaluated. There are trade-offs between model complexity and emulation performance. Aggregated economic impacts can be approximated by relatively simple emulators, but complex emulators are necessary to accommodate finer-scale economic impacts.
Ana Maria Roxana Petrescu, Chunjing Qiu, Philippe Ciais, Rona L. Thompson, Philippe Peylin, Matthew J. McGrath, Efisio Solazzo, Greet Janssens-Maenhout, Francesco N. Tubiello, Peter Bergamaschi, Dominik Brunner, Glen P. Peters, Lena Höglund-Isaksson, Pierre Regnier, Ronny Lauerwald, David Bastviken, Aki Tsuruta, Wilfried Winiwarter, Prabir K. Patra, Matthias Kuhnert, Gabriel D. Oreggioni, Monica Crippa, Marielle Saunois, Lucia Perugini, Tiina Markkanen, Tuula Aalto, Christine D. Groot Zwaaftink, Hanqin Tian, Yuanzhi Yao, Chris Wilson, Giulia Conchedda, Dirk Günther, Adrian Leip, Pete Smith, Jean-Matthieu Haussaire, Antti Leppänen, Alistair J. Manning, Joe McNorton, Patrick Brockmann, and Albertus Johannes Dolman
Earth Syst. Sci. Data, 13, 2307–2362, https://doi.org/10.5194/essd-13-2307-2021, https://doi.org/10.5194/essd-13-2307-2021, 2021
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This study is topical and provides a state-of-the-art scientific overview of data availability from bottom-up and top-down CH4 and N2O emissions in the EU27 and UK. The data integrate recent emission inventories with process-based model data and regional/global inversions for the European domain, aiming at reconciling them with official country-level UNFCCC national GHG inventories in support to policy and to facilitate real-time verification procedures.
Ana Maria Roxana Petrescu, Matthew J. McGrath, Robbie M. Andrew, Philippe Peylin, Glen P. Peters, Philippe Ciais, Gregoire Broquet, Francesco N. Tubiello, Christoph Gerbig, Julia Pongratz, Greet Janssens-Maenhout, Giacomo Grassi, Gert-Jan Nabuurs, Pierre Regnier, Ronny Lauerwald, Matthias Kuhnert, Juraj Balkovič, Mart-Jan Schelhaas, Hugo A. C. Denier van der
Gon, Efisio Solazzo, Chunjing Qiu, Roberto Pilli, Igor B. Konovalov, Richard A. Houghton, Dirk Günther, Lucia Perugini, Monica Crippa, Raphael Ganzenmüller, Ingrid T. Luijkx, Pete Smith, Saqr Munassar, Rona L. Thompson, Giulia Conchedda, Guillaume Monteil, Marko Scholze, Ute Karstens, Patrick Brockmann, and Albertus Johannes Dolman
Earth Syst. Sci. Data, 13, 2363–2406, https://doi.org/10.5194/essd-13-2363-2021, https://doi.org/10.5194/essd-13-2363-2021, 2021
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This study is topical and provides a state-of-the-art scientific overview of data availability from bottom-up and top-down CO2 fossil emissions and CO2 land fluxes in the EU27+UK. The data integrate recent emission inventories with ecosystem data, land carbon models and regional/global inversions for the European domain, aiming at reconciling CO2 estimates with official country-level UNFCCC national GHG inventories in support to policy and facilitating real-time verification procedures.
Wolfgang A. Obermeier, Julia E. M. S. Nabel, Tammas Loughran, Kerstin Hartung, Ana Bastos, Felix Havermann, Peter Anthoni, Almut Arneth, Daniel S. Goll, Sebastian Lienert, Danica Lombardozzi, Sebastiaan Luyssaert, Patrick C. McGuire, Joe R. Melton, Benjamin Poulter, Stephen Sitch, Michael O. Sullivan, Hanqin Tian, Anthony P. Walker, Andrew J. Wiltshire, Soenke Zaehle, and Julia Pongratz
Earth Syst. Dynam., 12, 635–670, https://doi.org/10.5194/esd-12-635-2021, https://doi.org/10.5194/esd-12-635-2021, 2021
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We provide the first spatio-temporally explicit comparison of different model-derived fluxes from land use and land cover changes (fLULCCs) by using the TRENDY v8 dynamic global vegetation models used in the 2019 global carbon budget. We find huge regional fLULCC differences resulting from environmental assumptions, simulated periods, and the timing of land use and land cover changes, and we argue for a method consistent across time and space and for carefully choosing the accounting period.
Zhen Zhang, Etienne Fluet-Chouinard, Katherine Jensen, Kyle McDonald, Gustaf Hugelius, Thomas Gumbricht, Mark Carroll, Catherine Prigent, Annett Bartsch, and Benjamin Poulter
Earth Syst. Sci. Data, 13, 2001–2023, https://doi.org/10.5194/essd-13-2001-2021, https://doi.org/10.5194/essd-13-2001-2021, 2021
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The spatiotemporal distribution of wetlands is one of the important and yet uncertain factors determining the time and locations of methane fluxes. The Wetland Area and Dynamics for Methane Modeling (WAD2M) dataset describes the global data product used to quantify the areal dynamics of natural wetlands and how global wetlands are changing in response to climate.
Leonardo Calle and Benjamin Poulter
Geosci. Model Dev., 14, 2575–2601, https://doi.org/10.5194/gmd-14-2575-2021, https://doi.org/10.5194/gmd-14-2575-2021, 2021
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We developed a model to simulate and track the age of ecosystems on Earth. We found that the effect of ecosystem age on net primary production and ecosystem respiration is as important as climate in large areas of every vegetated continent. The LPJ-wsl v2.0 age-class model simulates dynamic age-class distributions on Earth and represents another step forward towards understanding the role of demography in global ecosystems.
Garry D. Hayman, Edward Comyn-Platt, Chris Huntingford, Anna B. Harper, Tom Powell, Peter M. Cox, William Collins, Christopher Webber, Jason Lowe, Stephen Sitch, Joanna I. House, Jonathan C. Doelman, Detlef P. van Vuuren, Sarah E. Chadburn, Eleanor Burke, and Nicola Gedney
Earth Syst. Dynam., 12, 513–544, https://doi.org/10.5194/esd-12-513-2021, https://doi.org/10.5194/esd-12-513-2021, 2021
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We model greenhouse gas emission scenarios consistent with limiting global warming to either 1.5 or 2 °C above pre-industrial levels. We quantify the effectiveness of methane emission control and land-based mitigation options regionally. Our results highlight the importance of reducing methane emissions for realistic emission pathways that meet the global warming targets. For land-based mitigation, growing bioenergy crops on existing agricultural land is preferable to replacing forests.
Zichong Chen, Junjie Liu, Daven K. Henze, Deborah N. Huntzinger, Kelley C. Wells, Stephen Sitch, Pierre Friedlingstein, Emilie Joetzjer, Vladislav Bastrikov, Daniel S. Goll, Vanessa Haverd, Atul K. Jain, Etsushi Kato, Sebastian Lienert, Danica L. Lombardozzi, Patrick C. McGuire, Joe R. Melton, Julia E. M. S. Nabel, Benjamin Poulter, Hanqin Tian, Andrew J. Wiltshire, Sönke Zaehle, and Scot M. Miller
Atmos. Chem. Phys., 21, 6663–6680, https://doi.org/10.5194/acp-21-6663-2021, https://doi.org/10.5194/acp-21-6663-2021, 2021
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NASA's Orbiting Carbon Observatory 2 (OCO-2) satellite observes atmospheric CO2 globally. We use a multiple regression and inverse model to quantify the relationships between OCO-2 and environmental drivers within individual years for 2015–2018 and within seven global biomes. Our results point to limitations of current space-based observations for inferring environmental relationships but also indicate the potential to inform key relationships that are very uncertain in process-based models.
Oliver Gutjahr, Nils Brüggemann, Helmuth Haak, Johann H. Jungclaus, Dian A. Putrasahan, Katja Lohmann, and Jin-Song von Storch
Geosci. Model Dev., 14, 2317–2349, https://doi.org/10.5194/gmd-14-2317-2021, https://doi.org/10.5194/gmd-14-2317-2021, 2021
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We compare four ocean vertical mixing schemes in 100-year coupled simulations with the Max Planck Institute Earth System Model (MPI-ESM1.2) and analyse their model biases. Overall, the mixing schemes modify biases in the ocean interior that vary with region and variable but produce a similar global bias pattern. We therefore cannot classify any scheme as superior but conclude that the chosen mixing scheme may be important for regional biases.
Francesco N. Tubiello, Giulia Conchedda, Nathan Wanner, Sandro Federici, Simone Rossi, and Giacomo Grassi
Earth Syst. Sci. Data, 13, 1681–1691, https://doi.org/10.5194/essd-13-1681-2021, https://doi.org/10.5194/essd-13-1681-2021, 2021
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This paper presents the first estimates of forest carbon fluxes (1990–2020) based on the new Global Forest Resources Assessment (FRA) 2020. We document for the first time in the literature forest carbon fluxes for the last decade 2011–2020. Results show that carbon losses from net forest conversion (3.1 billion tonnes of CO2) were counterbalanced by carbon gains on forest land (−3.3 billion tonnes of CO2), resulting in the world's forests acting overall as a small carbon sink in the past decade.
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.
Sudhanshu Pandey, Sander Houweling, Alba Lorente, Tobias Borsdorff, Maria Tsivlidou, A. Anthony Bloom, Benjamin Poulter, Zhen Zhang, and Ilse Aben
Biogeosciences, 18, 557–572, https://doi.org/10.5194/bg-18-557-2021, https://doi.org/10.5194/bg-18-557-2021, 2021
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We use atmospheric methane observations from the novel TROPOspheric Monitoring Instrument (TROPOMI; Sentinel-5p) to estimate methane emissions from South Sudan's wetlands. Our emission estimates are an order of magnitude larger than the estimate of process-based wetland models. We find that this underestimation by the models is likely due to their misrepresentation of the wetlands' inundation extent and temperature dependences.
Xiaoying Shi, Daniel M. Ricciuto, Peter E. Thornton, Xiaofeng Xu, Fengming Yuan, Richard J. Norby, Anthony P. Walker, Jeffrey M. Warren, Jiafu Mao, Paul J. Hanson, Lin Meng, David Weston, and Natalie A. Griffiths
Biogeosciences, 18, 467–486, https://doi.org/10.5194/bg-18-467-2021, https://doi.org/10.5194/bg-18-467-2021, 2021
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The Sphagnum mosses are the important species of a wetland ecosystem. To better represent the peatland ecosystem, we introduced the moss species to the land model component (ELM) of the Energy Exascale Earth System Model (E3SM) by developing water content dynamics and nonvascular photosynthetic processes for moss. We tested the model against field observations and used the model to make projections of the site's carbon cycle under warming and atmospheric CO2 concentration scenarios.
Yang Li, Loretta J. Mickley, and Jed O. Kaplan
Atmos. Chem. Phys., 21, 57–68, https://doi.org/10.5194/acp-21-57-2021, https://doi.org/10.5194/acp-21-57-2021, 2021
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Climate models predict a shift toward warmer, drier environments in southwestern North America. Under future climate, the two main drivers of dust trends play opposing roles: (1) CO2 fertilization enhances vegetation and, in turn, decreases dust, and (2) increasing land use enhances dust emissions from northern Mexico. In the worst-case scenario, elevated dust concentrations spread widely over the domain by 2100 in spring, suggesting a large climate penalty on air quality and human health.
Katherine Dagon, Benjamin M. Sanderson, Rosie A. Fisher, and David M. Lawrence
Adv. Stat. Clim. Meteorol. Oceanogr., 6, 223–244, https://doi.org/10.5194/ascmo-6-223-2020, https://doi.org/10.5194/ascmo-6-223-2020, 2020
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Uncertainties in land model projections are important to understand in order to build confidence in Earth system modeling. In this paper, we introduce a framework for estimating uncertain land model parameters with machine learning. This method increases the computational efficiency of this process relative to traditional hand tuning approaches and provides objective methods to assess the results. We further identify key processes and parameters that are important for accurate land modeling.
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.
Giulia Conchedda and Francesco N. Tubiello
Earth Syst. Sci. Data, 12, 3113–3137, https://doi.org/10.5194/essd-12-3113-2020, https://doi.org/10.5194/essd-12-3113-2020, 2020
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This paper describes the FAO methodology used to globally assess areas of drained organic soils and peatlands due to agriculture over the period 1990–2019. We overlay geospatial information of soil type, land cover, agro-climatic zones, livestock distribution and IPCC coefficients, then aggregate it at national level for over 200 countries and territories. Results are compared to inventory data reported to UNFCCC, showing good agreement between the FAO estimates and country data.
Zhipin Ai, Naota Hanasaki, Vera Heck, Tomoko Hasegawa, and Shinichiro Fujimori
Geosci. Model Dev., 13, 6077–6092, https://doi.org/10.5194/gmd-13-6077-2020, https://doi.org/10.5194/gmd-13-6077-2020, 2020
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Incorporating bioenergy crops into the well-established global hydrological models is seldom seen today. Here, we successfully enhance a state-of-the-art global hydrological model H08 to simulate bioenergy crop yield. We found that unconstrained irrigation more than doubled the yield under rainfed conditions while simultaneously reducing the water use efficiency by 32 % globally. Our enhanced model provides a new tool for the future assessment of bioenergy–water tradeoffs.
Jinnan Gong, Nigel Roulet, Steve Frolking, Heli Peltola, Anna M. Laine, Nicola Kokkonen, and Eeva-Stiina Tuittila
Biogeosciences, 17, 5693–5719, https://doi.org/10.5194/bg-17-5693-2020, https://doi.org/10.5194/bg-17-5693-2020, 2020
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In this study, which combined a field and lab experiment with modelling, we developed a process-based model for simulating dynamics within peatland moss communities. The model is useful because Sphagnum mosses are key engineers in peatlands; their response to changes in climate via altered hydrology controls the feedback of peatland biogeochemistry to climate. Our work showed that moss capitulum traits related to water retention are the mechanism controlling moss layer dynamics in peatlands.
Tea Thum, Julia E. M. S. Nabel, Aki Tsuruta, Tuula Aalto, Edward J. Dlugokencky, Jari Liski, Ingrid T. Luijkx, Tiina Markkanen, Julia Pongratz, Yukio Yoshida, and Sönke Zaehle
Biogeosciences, 17, 5721–5743, https://doi.org/10.5194/bg-17-5721-2020, https://doi.org/10.5194/bg-17-5721-2020, 2020
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Global vegetation models are important tools in estimating the impacts of global climate change. The fate of soil carbon is of the upmost importance as its emissions will enhance the atmospheric carbon dioxide concentration. To evaluate the skill of global vegetation models to model the soil carbon and its responses to environmental factors, it is important to use different data sources. We evaluated two different soil carbon models by using atmospheric carbon dioxide concentrations.
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.
Rachel L. Tunnicliffe, Anita L. Ganesan, Robert J. Parker, Hartmut Boesch, Nicola Gedney, Benjamin Poulter, Zhen Zhang, Jošt V. Lavrič, David Walter, Matthew Rigby, Stephan Henne, Dickon Young, and Simon O'Doherty
Atmos. Chem. Phys., 20, 13041–13067, https://doi.org/10.5194/acp-20-13041-2020, https://doi.org/10.5194/acp-20-13041-2020, 2020
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This study quantifies Brazil’s emissions of a potent atmospheric greenhouse gas, methane. This is in the field of atmospheric modelling and uses remotely sensed data and surface measurements of methane concentrations as well as an atmospheric transport model to interpret the data. Because of Brazil’s large emissions from wetlands, agriculture and biomass burning, these emissions affect global methane concentrations and thus are of global significance.
Matthew J. Rowlinson, Alexandru Rap, Douglas S. Hamilton, Richard J. Pope, Stijn Hantson, Steve R. Arnold, Jed O. Kaplan, Almut Arneth, Martyn P. Chipperfield, Piers M. Forster, and Lars Nieradzik
Atmos. Chem. Phys., 20, 10937–10951, https://doi.org/10.5194/acp-20-10937-2020, https://doi.org/10.5194/acp-20-10937-2020, 2020
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Tropospheric ozone is an important greenhouse gas which contributes to anthropogenic climate change; however, the effect of human emissions is uncertain because pre-industrial ozone concentrations are not well understood. We use revised inventories of pre-industrial natural emissions to estimate the human contribution to changes in tropospheric ozone. We find that tropospheric ozone radiative forcing is up to 34 % lower when using improved pre-industrial biomass burning and vegetation emissions.
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.
Yang Li, Loretta J. Mickley, Pengfei Liu, and Jed O. Kaplan
Atmos. Chem. Phys., 20, 8827–8838, https://doi.org/10.5194/acp-20-8827-2020, https://doi.org/10.5194/acp-20-8827-2020, 2020
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Using a coupled vegetation–fire–climate modeling framework, we show a northward shift in forests and increased lightning fire activity in northern US states, including Idaho, Montana, and Wyoming. Our findings suggest a large climate penalty on ecosystem, air quality, visibility, and human health in a region valued for its national forests and parks. The fine-scale smoke PM predictions provided in this study should prove useful to human health and environmental assessments.
Marielle Saunois, Ann R. Stavert, Ben Poulter, Philippe Bousquet, Josep G. Canadell, Robert B. Jackson, Peter A. Raymond, Edward J. Dlugokencky, Sander Houweling, Prabir K. Patra, Philippe Ciais, Vivek K. Arora, David Bastviken, Peter Bergamaschi, Donald R. Blake, Gordon Brailsford, Lori Bruhwiler, Kimberly M. Carlson, Mark Carrol, Simona Castaldi, Naveen Chandra, Cyril Crevoisier, Patrick M. Crill, Kristofer Covey, Charles L. Curry, Giuseppe Etiope, Christian Frankenberg, Nicola Gedney, Michaela I. Hegglin, Lena Höglund-Isaksson, Gustaf Hugelius, Misa Ishizawa, Akihiko Ito, Greet Janssens-Maenhout, Katherine M. Jensen, Fortunat Joos, Thomas Kleinen, Paul B. Krummel, Ray L. Langenfelds, Goulven G. Laruelle, Licheng Liu, Toshinobu Machida, Shamil Maksyutov, Kyle C. McDonald, Joe McNorton, Paul A. Miller, Joe R. Melton, Isamu Morino, Jurek Müller, Fabiola Murguia-Flores, Vaishali Naik, Yosuke Niwa, Sergio Noce, Simon O'Doherty, Robert J. Parker, Changhui Peng, Shushi Peng, Glen P. Peters, Catherine Prigent, Ronald Prinn, Michel Ramonet, Pierre Regnier, William J. Riley, Judith A. Rosentreter, Arjo Segers, Isobel J. Simpson, Hao Shi, Steven J. Smith, L. Paul Steele, Brett F. Thornton, Hanqin Tian, Yasunori Tohjima, Francesco N. Tubiello, Aki Tsuruta, Nicolas Viovy, Apostolos Voulgarakis, Thomas S. Weber, Michiel van Weele, Guido R. van der Werf, Ray F. Weiss, Doug Worthy, Debra Wunch, Yi Yin, Yukio Yoshida, Wenxin Zhang, Zhen Zhang, Yuanhong Zhao, Bo Zheng, Qing Zhu, Qiuan Zhu, and Qianlai Zhuang
Earth Syst. Sci. Data, 12, 1561–1623, https://doi.org/10.5194/essd-12-1561-2020, https://doi.org/10.5194/essd-12-1561-2020, 2020
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Understanding and quantifying the global methane (CH4) budget is important for assessing realistic pathways to mitigate climate change. We have established a consortium of multidisciplinary scientists under the umbrella of the Global Carbon Project to synthesize and stimulate new research aimed at improving and regularly updating the global methane budget. This is the second version of the review dedicated to the decadal methane budget, integrating results of top-down and bottom-up estimates.
Lei Ma, George C. Hurtt, Louise P. Chini, Ritvik Sahajpal, Julia Pongratz, Steve Frolking, Elke Stehfest, Kees Klein Goldewijk, Donal O'Leary, and Jonathan C. Doelman
Geosci. Model Dev., 13, 3203–3220, https://doi.org/10.5194/gmd-13-3203-2020, https://doi.org/10.5194/gmd-13-3203-2020, 2020
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Earth system models require information on historical land cover change. We present transition rules to generate land cover change from newly developed land use dataset (Land-use Harmonization, LUH2). The resulting forest cover, vegetation carbon, and emissions from land use and land cover change are simulated and evaluated against remote sensing data and other studies. The rules can guide the incorporation of land-cover information within earth system models for CMIP6.
Hideo Shiogama, Ryuichi Hirata, Tomoko Hasegawa, Shinichiro Fujimori, Noriko N. Ishizaki, Satoru Chatani, Masahiro Watanabe, Daniel Mitchell, and Y. T. Eunice Lo
Earth Syst. Dynam., 11, 435–445, https://doi.org/10.5194/esd-11-435-2020, https://doi.org/10.5194/esd-11-435-2020, 2020
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Based on climate simulations, we suggested that historical warming increased chances of drought exceeding the severe 2015 event in equatorial Asia due to El Niño. The fire and fire emissions of CO2/PM2.5 will largely increase at 1.5 and 2 °C warming. If global warming reaches 3 °C, as is expected from the current mitigation policies, chances of fire and CO2/PM2.5 emissions exceeding the 2015 event become approximately 100 %. Future climate policy has to consider these climate change effects.
Ana Maria Roxana Petrescu, Glen P. Peters, Greet Janssens-Maenhout, Philippe Ciais, Francesco N. Tubiello, Giacomo Grassi, Gert-Jan Nabuurs, Adrian Leip, Gema Carmona-Garcia, Wilfried Winiwarter, Lena Höglund-Isaksson, Dirk Günther, Efisio Solazzo, Anja Kiesow, Ana Bastos, Julia Pongratz, Julia E. M. S. Nabel, Giulia Conchedda, Roberto Pilli, Robbie M. Andrew, Mart-Jan Schelhaas, and Albertus J. Dolman
Earth Syst. Sci. Data, 12, 961–1001, https://doi.org/10.5194/essd-12-961-2020, https://doi.org/10.5194/essd-12-961-2020, 2020
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This study is topical and provides a state-of-the-art scientific overview of data availability from bottom-up GHG anthropogenic emissions from agriculture, forestry and other land use (AFOLU) in the EU28. The data integrate recent AFOLU emission inventories with ecosystem data and land carbon models, aiming at reconciling GHG budgets with official country-level UNFCCC inventories. We provide comprehensive emission assessments in support to policy, facilitating real-time verification procedures.
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.
Wei Li, Philippe Ciais, Elke Stehfest, Detlef van Vuuren, Alexander Popp, Almut Arneth, Fulvio Di Fulvio, Jonathan Doelman, Florian Humpenöder, Anna B. Harper, Taejin Park, David Makowski, Petr Havlik, Michael Obersteiner, Jingmeng Wang, Andreas Krause, and Wenfeng Liu
Earth Syst. Sci. Data, 12, 789–804, https://doi.org/10.5194/essd-12-789-2020, https://doi.org/10.5194/essd-12-789-2020, 2020
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We generated spatially explicit bioenergy crop yields based on field measurements with climate, soil condition and remote-sensing variables as explanatory variables and the machine-learning method. We further compared our yield maps with the maps from three integrated assessment models (IAMs; IMAGE, MAgPIE and GLOBIOM) and found that the median yields in our maps are > 50 % higher than those in the IAM maps.
Tzu-Shun Lin, Yang Song, Atul K. Jain, Peter Lawrence, and Haroon S. Kheshgi
Biogeosciences Discuss., https://doi.org/10.5194/bg-2020-68, https://doi.org/10.5194/bg-2020-68, 2020
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ISAM model was used to estimate soybean and maize crop yields over 1901–2100 driven by changes in environmental factors and management factors. Over the 20th century, each of these factors contributes to the increase in global crop yield with increasing nitrogen fertilizer application the strongest of these drivers for maize and increasing [CO2] the strongest for soybean. Over the 21st century, changing climate drives yield lower, while rising [CO2] drives yield higher for both crops.
Shufen Pan, Naiqing Pan, Hanqin Tian, Pierre Friedlingstein, Stephen Sitch, Hao Shi, Vivek K. Arora, Vanessa Haverd, Atul K. Jain, Etsushi Kato, Sebastian Lienert, Danica Lombardozzi, Julia E. M. S. Nabel, Catherine Ottlé, Benjamin Poulter, Sönke Zaehle, and Steven W. Running
Hydrol. Earth Syst. Sci., 24, 1485–1509, https://doi.org/10.5194/hess-24-1485-2020, https://doi.org/10.5194/hess-24-1485-2020, 2020
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Evapotranspiration (ET) links global water, carbon and energy cycles. We used 4 remote sensing models, 2 machine-learning algorithms and 14 land surface models to analyze the changes in global terrestrial ET. These three categories of approaches agreed well in terms of ET intensity. For 1982–2011, all models showed that Earth greening enhanced terrestrial ET. The small interannual variability of global terrestrial ET suggests it has a potential planetary boundary of around 600 mm yr-1.
Martin Jung, Christopher Schwalm, Mirco Migliavacca, Sophia Walther, Gustau Camps-Valls, Sujan Koirala, Peter Anthoni, Simon Besnard, Paul Bodesheim, Nuno Carvalhais, Frédéric Chevallier, Fabian Gans, Daniel S. Goll, Vanessa Haverd, Philipp Köhler, Kazuhito Ichii, Atul K. Jain, Junzhi Liu, Danica Lombardozzi, Julia E. M. S. Nabel, Jacob A. Nelson, Michael O'Sullivan, Martijn Pallandt, Dario Papale, Wouter Peters, Julia Pongratz, Christian Rödenbeck, Stephen Sitch, Gianluca Tramontana, Anthony Walker, Ulrich Weber, and Markus Reichstein
Biogeosciences, 17, 1343–1365, https://doi.org/10.5194/bg-17-1343-2020, https://doi.org/10.5194/bg-17-1343-2020, 2020
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We test the approach of producing global gridded carbon fluxes based on combining machine learning with local measurements, remote sensing and climate data. We show that we can reproduce seasonal variations in carbon assimilated by plants via photosynthesis and in ecosystem net carbon balance. The ecosystem’s mean carbon balance and carbon flux trends require cautious interpretation. The analysis paves the way for future improvements of the data-driven assessment of carbon fluxes.
Adriano Vinca, Simon Parkinson, Edward Byers, Peter Burek, Zarrar Khan, Volker Krey, Fabio A. Diuana, Yaoping Wang, Ansir Ilyas, Alexandre C. Köberle, Iain Staffell, Stefan Pfenninger, Abubakr Muhammad, Andrew Rowe, Roberto Schaeffer, Narasimha D. Rao, Yoshihide Wada, Ned Djilali, and Keywan Riahi
Geosci. Model Dev., 13, 1095–1121, https://doi.org/10.5194/gmd-13-1095-2020, https://doi.org/10.5194/gmd-13-1095-2020, 2020
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This article describes a newly developed numerical model that can assess impacts of long-term policies for the energy, water and land (WEL) sectors at the scale of a river basin. We show the importance of having an integrated method when jointly considering multiple policies as opposed to conventional sectoral analysis. This model can be useful for studying river basins, such as the Indus basin, that are exposed to challenges over WEL sectors, like water scarcity or food and energy access.
Binghao Jia, Xin Luo, Ximing Cai, Atul Jain, Deborah N. Huntzinger, Zhenghui Xie, Ning Zeng, Jiafu Mao, Xiaoying Shi, Akihiko Ito, Yaxing Wei, Hanqin Tian, Benjamin Poulter, Dan Hayes, and Kevin Schaefer
Earth Syst. Dynam., 11, 235–249, https://doi.org/10.5194/esd-11-235-2020, https://doi.org/10.5194/esd-11-235-2020, 2020
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We quantitatively examined the relative contributions of climate change, land
use and land cover change, and elevated CO2 to interannual variations and seasonal cycle amplitude of gross primary productivity (GPP) in China based on multi-model ensemble simulations. The contributions of major subregions to the temporal change in China's total GPP are also presented. This work may help us better understand GPP spatiotemporal patterns and their responses to regional changes and human activities.
Camilo Melo-Aguilar, J. Fidel González-Rouco, Elena García-Bustamante, Norman Steinert, Johann H. Jungclaus, Jorge Navarro, and Pedro J. Roldán-Gómez
Clim. Past, 16, 453–474, https://doi.org/10.5194/cp-16-453-2020, https://doi.org/10.5194/cp-16-453-2020, 2020
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This study explores potential sources of bias on borehole-based temperature reconstruction from both methodological and physical factors using pseudo-proxy experiments that consider ensembles of simulations from the Community Earth System Model. The results indicate that both methodological and physical factors may have an impact on the estimation of the recent temperature trends at different spatial scales. Internal variability arises also as an important issue influencing pseudo-proxy results.
Sandy P. Harrison, Marie-José Gaillard, Benjamin D. Stocker, Marc Vander Linden, Kees Klein Goldewijk, Oliver Boles, Pascale Braconnot, Andria Dawson, Etienne Fluet-Chouinard, Jed O. Kaplan, Thomas Kastner, Francesco S. R. Pausata, Erick Robinson, Nicki J. Whitehouse, Marco Madella, and Kathleen D. Morrison
Geosci. Model Dev., 13, 805–824, https://doi.org/10.5194/gmd-13-805-2020, https://doi.org/10.5194/gmd-13-805-2020, 2020
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The Past Global Changes LandCover6k initiative will use archaeological records to refine scenarios of land use and land cover change through the Holocene to reduce the uncertainties about the impacts of human-induced changes before widespread industrialization. We describe how archaeological data are used to map land use change and how the maps can be evaluated using independent palaeoenvironmental data. We propose simulations to test land use and land cover change impacts on past climates.
Christian G. Andresen, David M. Lawrence, Cathy J. Wilson, A. David McGuire, Charles Koven, Kevin Schaefer, Elchin Jafarov, Shushi Peng, Xiaodong Chen, Isabelle Gouttevin, Eleanor Burke, Sarah Chadburn, Duoying Ji, Guangsheng Chen, Daniel Hayes, and Wenxin Zhang
The Cryosphere, 14, 445–459, https://doi.org/10.5194/tc-14-445-2020, https://doi.org/10.5194/tc-14-445-2020, 2020
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Widely-used land models project near-surface drying of the terrestrial Arctic despite increases in the net water balance driven by climate change. Drying was generally associated with increases of active-layer depth and permafrost thaw in a warming climate. However, models lack important mechanisms such as thermokarst and soil subsidence that will change the hydrological regime and add to the large uncertainty in the future Arctic hydrological state and the associated permafrost carbon feedback.
Julia E. M. S. Nabel, Kim Naudts, and Julia Pongratz
Geosci. Model Dev., 13, 185–200, https://doi.org/10.5194/gmd-13-185-2020, https://doi.org/10.5194/gmd-13-185-2020, 2020
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Models need to account for forest age structures when investigating land use influences on land–atmosphere feedbacks. We present a consolidated scheme to introduce forest age classes, combining age-dependent simulations of important processes with the possibility to trace forest age, and describe its implementation in JSBACH4, the land surface model of the ICON Earth system model. We evaluate simulations with and without age classes demonstrating the benefit of forest age classes in JSBACH4.
Bing Pu, Paul Ginoux, Huan Guo, N. Christina Hsu, John Kimball, Beatrice Marticorena, Sergey Malyshev, Vaishali Naik, Norman T. O'Neill, Carlos Pérez García-Pando, Juliette Paireau, Joseph M. Prospero, Elena Shevliakova, and Ming Zhao
Atmos. Chem. Phys., 20, 55–81, https://doi.org/10.5194/acp-20-55-2020, https://doi.org/10.5194/acp-20-55-2020, 2020
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Dust emission initiates when surface wind velocities exceed a threshold depending on soil and surface characteristics and varying spatially and temporally. Climate models widely use wind erosion thresholds. The climatological monthly global distribution of the wind erosion threshold, Vthreshold, is retrieved using satellite and reanalysis products and improves the simulation of dust frequency, magnitude, and the seasonal cycle in the Geophysical Fluid Dynamics Laboratory land–atmosphere model.
Altug Ekici, Hanna Lee, David M. Lawrence, Sean C. Swenson, and Catherine Prigent
Geosci. Model Dev., 12, 5291–5300, https://doi.org/10.5194/gmd-12-5291-2019, https://doi.org/10.5194/gmd-12-5291-2019, 2019
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Ice-rich permafrost thaw can create expanding thermokarst lakes as well as shrinking large wetlands. Such processes can have major biogeochemical implications and feedbacks to climate systems by altering the pathways and rates of permafrost carbon release. We developed a new model parameterization that allows a direct representation of surface water dynamics with subsidence. Our results show increased surface water fractions around western Siberian plains and northeastern territories of Canada.
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.
Zhipin Ai, Naota Hanasaki, Vera Heck, Tomoko Hasegawa, and Shinichiro Fujimori
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2019-277, https://doi.org/10.5194/gmd-2019-277, 2019
Revised manuscript not accepted
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Reliable bioenergy crop yield simulation remains a challenge at the global scale. Here, we enhanced a state-of-the-art global hydrological model to simulate bioenergy yield. We found that unconstrained irrigation more than doubled the yield under rainfed condition, while simultaneously reducing the water-use efficiency by 29 % globally. This is the first trial to use a global hydrological model to simulate the bioenergy crop and offers an effective tool to assess the bioenergy-water relations.
Sajeev Philip, Matthew S. Johnson, Christopher Potter, Vanessa Genovesse, David F. Baker, Katherine D. Haynes, Daven K. Henze, Junjie Liu, and Benjamin Poulter
Atmos. Chem. Phys., 19, 13267–13287, https://doi.org/10.5194/acp-19-13267-2019, https://doi.org/10.5194/acp-19-13267-2019, 2019
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This research was conducted to quantify the impact of different prior global biosphere models on the estimate of terrestrial CO2 fluxes when assimilating Orbiting Carbon Observatory-2 (OCO-2) satellite observations. To determine the prior model impact, we apply observing system simulation experiments (OSSEs). Even with the substantial spatiotemporal coverage of OCO-2 data, residual differences in posterior CO2 flux estimates remain due to the choice of prior flux mean and uncertainties.
Anina Gilgen, Stiig Wilkenskjeld, Jed O. Kaplan, Thomas Kühn, and Ulrike Lohmann
Clim. Past, 15, 1885–1911, https://doi.org/10.5194/cp-15-1885-2019, https://doi.org/10.5194/cp-15-1885-2019, 2019
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Using the global aerosol–climate model ECHAM-HAM-SALSA, the effect of humans on European climate in the Roman Empire was quantified. Both land use and novel estimates of anthropogenic aerosol emissions were considered. We conducted simulations with fixed sea-surface temperatures to gain a first impression about the anthropogenic impact. While land use effects induced a regional warming for one of the reconstructions, aerosol emissions led to a cooling associated with aerosol–cloud interactions.
Maarten C. Braakhekke, Jonathan C. Doelman, Peter Baas, Christoph Müller, Sibyll Schaphoff, Elke Stehfest, and Detlef P. van Vuuren
Earth Syst. Dynam., 10, 617–630, https://doi.org/10.5194/esd-10-617-2019, https://doi.org/10.5194/esd-10-617-2019, 2019
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We developed a computer model that simulates forests plantations at global scale and how fast such forests can take up CO2 from the atmosphere. Using this new model, we performed simulations for a scenario in which a large fraction (14 %) of global croplands and pastures are either converted to planted forests or natural forests. We find that planted forests take up CO2 substantially faster than natural forests and are therefore a viable strategy for reducing climate change.
Tine Nilsen, Dmitry V. Divine, Annika Hofgaard, Andreas Born, Johann Jungclaus, and Igor Drobyshev
Clim. Past Discuss., https://doi.org/10.5194/cp-2019-123, https://doi.org/10.5194/cp-2019-123, 2019
Revised manuscript not accepted
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Using a set of three climate model simulations we cannot find a consistent relationship between atmospheric conditions favorable for forest fire activity in northern Scandinavia and weaker ocean circulation in the North Atlantic subpolar gyre on seasonal timescales. In the literature there is support of such a relationship for longer timescales. With the motivation to improve seasonal prediction systems, we conclude that the gyre circulation alone does not indicate forthcoming model drought.
Ana Bastos, Philippe Ciais, Frédéric Chevallier, Christian Rödenbeck, Ashley P. Ballantyne, Fabienne Maignan, Yi Yin, Marcos Fernández-Martínez, Pierre Friedlingstein, Josep Peñuelas, Shilong L. Piao, Stephen Sitch, William K. Smith, Xuhui Wang, Zaichun Zhu, Vanessa Haverd, Etsushi Kato, Atul K. Jain, Sebastian Lienert, Danica Lombardozzi, Julia E. M. S. Nabel, Philippe Peylin, Benjamin Poulter, and Dan Zhu
Atmos. Chem. Phys., 19, 12361–12375, https://doi.org/10.5194/acp-19-12361-2019, https://doi.org/10.5194/acp-19-12361-2019, 2019
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Here we show that land-surface models improved their ability to simulate the increase in the amplitude of seasonal CO2-cycle exchange (SCANBP) by ecosystems compared to estimates by two atmospheric inversions. We find a dominant role of vegetation growth over boreal Eurasia to the observed increase in SCANBP, strongly driven by CO2 fertilization, and an overall negative effect of temperature on SCANBP. Biases can be explained by the sensitivity of simulated microbial respiration to temperature.
Oliver Gutjahr, Dian Putrasahan, Katja Lohmann, Johann H. Jungclaus, Jin-Song von Storch, Nils Brüggemann, Helmuth Haak, and Achim Stössel
Geosci. Model Dev., 12, 3241–3281, https://doi.org/10.5194/gmd-12-3241-2019, https://doi.org/10.5194/gmd-12-3241-2019, 2019
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We analyse how climatic mean states of the atmosphere and ocean change with increasing the horizontal model resolution of the Max Planck Institute Earth System Model (MPI-ESM1.2) and how they are affected by the representation of vertical mixing in the ocean. It is in particular a high-resolution ocean that reduces biases not only in the ocean but also in the atmosphere. The vertical mixing scheme affects the strength and stability of the Atlantic meridional overturning circulation (AMOC).
Leonardo Calle, Benjamin Poulter, and Prabir K. Patra
Atmos. Meas. Tech., 12, 2611–2629, https://doi.org/10.5194/amt-12-2611-2019, https://doi.org/10.5194/amt-12-2611-2019, 2019
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Satellite observations of atmospheric carbon dioxide offer extraordinary insights into terrestrial ecosystem activity on Earth. The algorithm we present provides researchers with a great deal more information from these satellite data than has been available in the past. We hope the application of this algorithm and analyses tools provides insight into atmospheric dynamics of carbon dioxide and helps inform the development of global ecosystem models in the future.
Min Chen, Chris R. Vernon, Maoyi Huang, Katherine V. Calvin, and Ian P. Kraucunas
Geosci. Model Dev., 12, 1753–1764, https://doi.org/10.5194/gmd-12-1753-2019, https://doi.org/10.5194/gmd-12-1753-2019, 2019
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Demeter is a community spatial downscaling model that disaggregates land use and land cover changes projected by integrated human–Earth system models. However, Demeter has not been intensively calibrated, and we still lack good knowledge about its sensitivity to key parameters and parameter uncertainties. This paper aims to solve this problem.
Matthew J. Gidden, Keywan Riahi, Steven J. Smith, Shinichiro Fujimori, Gunnar Luderer, Elmar Kriegler, Detlef P. van Vuuren, Maarten van den Berg, Leyang Feng, David Klein, Katherine Calvin, Jonathan C. Doelman, Stefan Frank, Oliver Fricko, Mathijs Harmsen, Tomoko Hasegawa, Petr Havlik, Jérôme Hilaire, Rachel Hoesly, Jill Horing, Alexander Popp, Elke Stehfest, and Kiyoshi Takahashi
Geosci. Model Dev., 12, 1443–1475, https://doi.org/10.5194/gmd-12-1443-2019, https://doi.org/10.5194/gmd-12-1443-2019, 2019
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We present a suite of nine scenarios of future emissions trajectories of anthropogenic sources for use in CMIP6. Integrated assessment model results are provided for each scenario with consistent transitions from the historical data to future trajectories. We find that the set of scenarios enables the exploration of a variety of warming pathways. A wide range of scenario data products are provided for the CMIP6 scientific community including global, regional, and gridded emissions datasets.
Abigail Snyder, Katherine V. Calvin, Meridel Phillips, and Alex C. Ruane
Geosci. Model Dev., 12, 1319–1350, https://doi.org/10.5194/gmd-12-1319-2019, https://doi.org/10.5194/gmd-12-1319-2019, 2019
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Future changes in Earth system state will impact agricultural yields and therefore the global economy. Global gridded crop models estimate the influence of these Earth system changes on future crop yields, but are often too computationally intensive to dynamically couple into global multi-sector economic models, such as GCAM and other similar-in-scale models. This work describes a new crop yield change emulator, Persephone, that can capture yield changes in a computationally efficient way.
Jan Philipp Dietrich, Benjamin Leon Bodirsky, Florian Humpenöder, Isabelle Weindl, Miodrag Stevanović, Kristine Karstens, Ulrich Kreidenweis, Xiaoxi Wang, Abhijeet Mishra, David Klein, Geanderson Ambrósio, Ewerton Araujo, Amsalu Woldie Yalew, Lavinia Baumstark, Stephen Wirth, Anastasis Giannousakis, Felicitas Beier, David Meng-Chuen Chen, Hermann Lotze-Campen, and Alexander Popp
Geosci. Model Dev., 12, 1299–1317, https://doi.org/10.5194/gmd-12-1299-2019, https://doi.org/10.5194/gmd-12-1299-2019, 2019
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We provides an overview on version 4 of the MAgPIE open-source framework for modeling global land systems. Among others, MAgPIE has been used to simulate marker scenarios of the Shared Socioeconomic Pathways (SSPs) and contributed substantially to multiple IPCC assessments. Its recent version marks the first open-source release of the framework and introduces several new features. Via its modularity and spatial flexibility it can serve as a tool for a broad range of land-related research topics.
Stephanie Fiedler, Bjorn Stevens, Matthew Gidden, Steven J. Smith, Keywan Riahi, and Detlef van Vuuren
Geosci. Model Dev., 12, 989–1007, https://doi.org/10.5194/gmd-12-989-2019, https://doi.org/10.5194/gmd-12-989-2019, 2019
Katherine Calvin, Pralit Patel, Leon Clarke, Ghassem Asrar, Ben Bond-Lamberty, Ryna Yiyun Cui, Alan Di Vittorio, Kalyn Dorheim, Jae Edmonds, Corinne Hartin, Mohamad Hejazi, Russell Horowitz, Gokul Iyer, Page Kyle, Sonny Kim, Robert Link, Haewon McJeon, Steven J. Smith, Abigail Snyder, Stephanie Waldhoff, and Marshall Wise
Geosci. Model Dev., 12, 677–698, https://doi.org/10.5194/gmd-12-677-2019, https://doi.org/10.5194/gmd-12-677-2019, 2019
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This paper describes GCAM v5.1, an open source model that represents the linkages between energy, water, land, climate, and economic systems. GCAM examines the future evolution of these systems through the end of the 21st century. It can be used to examine, for example, how changes in population, income, or technology cost might alter crop production, energy demand, or water withdrawals, or how changes in one region’s demand for energy affect energy, water, and land in other regions.
Jianqiu Zheng, Peter E. Thornton, Scott L. Painter, Baohua Gu, Stan D. Wullschleger, and David E. Graham
Biogeosciences, 16, 663–680, https://doi.org/10.5194/bg-16-663-2019, https://doi.org/10.5194/bg-16-663-2019, 2019
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Arctic warming exposes soil carbon to increased degradation, increasing CO2 and CH4 emissions. Models underrepresent anaerobic decomposition that predominates wet soils. We simulated microbial growth, pH regulation, and anaerobic carbon decomposition in a new model, parameterized and validated with prior soil incubation data. The model accurately simulated CO2 production and strong influences of water content, pH, methanogen biomass, and competing electron acceptors on CH4 production.
Rongting Xu, Hanqin Tian, Shufen Pan, Shree R. S. Dangal, Jian Chen, Jinfeng Chang, Yonglong Lu, Ute Maria Skiba, Francesco N. Tubiello, and Bowen Zhang
Earth Syst. Sci. Data, 11, 175–187, https://doi.org/10.5194/essd-11-175-2019, https://doi.org/10.5194/essd-11-175-2019, 2019
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We provide three gridded datasets of synthetic nitrogen (N) fertilizer and manure N inputs in global pastures and rangelands at a resolution of 0.5° × 0.5° for the period 1860–2016 (i.e., annual manure N deposition (by grazing animals) rate, synthetic N fertilizer use rate and manure N application rate). These three datasets could fill data gaps of N inputs in global and regional grasslands and serve as input drivers for earth system models.
Fabien Paulot, Sergey Malyshev, Tran Nguyen, John D. Crounse, Elena Shevliakova, and Larry W. Horowitz
Atmos. Chem. Phys., 18, 17963–17978, https://doi.org/10.5194/acp-18-17963-2018, https://doi.org/10.5194/acp-18-17963-2018, 2018
Gerhard Krinner, Chris Derksen, Richard Essery, Mark Flanner, Stefan Hagemann, Martyn Clark, Alex Hall, Helmut Rott, Claire Brutel-Vuilmet, Hyungjun Kim, Cécile B. Ménard, Lawrence Mudryk, Chad Thackeray, Libo Wang, Gabriele Arduini, Gianpaolo Balsamo, Paul Bartlett, Julia Boike, Aaron Boone, Frédérique Chéruy, Jeanne Colin, Matthias Cuntz, Yongjiu Dai, Bertrand Decharme, Jeff Derry, Agnès Ducharne, Emanuel Dutra, Xing Fang, Charles Fierz, Josephine Ghattas, Yeugeniy Gusev, Vanessa Haverd, Anna Kontu, Matthieu Lafaysse, Rachel Law, Dave Lawrence, Weiping Li, Thomas Marke, Danny Marks, Martin Ménégoz, Olga Nasonova, Tomoko Nitta, Masashi Niwano, John Pomeroy, Mark S. Raleigh, Gerd Schaedler, Vladimir Semenov, Tanya G. Smirnova, Tobias Stacke, Ulrich Strasser, Sean Svenson, Dmitry Turkov, Tao Wang, Nander Wever, Hua Yuan, Wenyan Zhou, and Dan Zhu
Geosci. Model Dev., 11, 5027–5049, https://doi.org/10.5194/gmd-11-5027-2018, https://doi.org/10.5194/gmd-11-5027-2018, 2018
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This paper provides an overview of a coordinated international experiment to determine the strengths and weaknesses in how climate models treat snow. The models will be assessed at point locations using high-quality reference measurements and globally using satellite-derived datasets. How well climate models simulate snow-related processes is important because changing snow cover is an important part of the global climate system and provides an important freshwater resource for human use.
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.
HyeJin Kim, Isabel M. D. Rosa, Rob Alkemade, Paul Leadley, George Hurtt, Alexander Popp, Detlef P. van Vuuren, Peter Anthoni, Almut Arneth, Daniele Baisero, Emma Caton, Rebecca Chaplin-Kramer, Louise Chini, Adriana De Palma, Fulvio Di Fulvio, Moreno Di Marco, Felipe Espinoza, Simon Ferrier, Shinichiro Fujimori, Ricardo E. Gonzalez, Maya Gueguen, Carlos Guerra, Mike Harfoot, Thomas D. Harwood, Tomoko Hasegawa, Vanessa Haverd, Petr Havlík, Stefanie Hellweg, Samantha L. L. Hill, Akiko Hirata, Andrew J. Hoskins, Jan H. Janse, Walter Jetz, Justin A. Johnson, Andreas Krause, David Leclère, Ines S. Martins, Tetsuya Matsui, Cory Merow, Michael Obersteiner, Haruka Ohashi, Benjamin Poulter, Andy Purvis, Benjamin Quesada, Carlo Rondinini, Aafke M. Schipper, Richard Sharp, Kiyoshi Takahashi, Wilfried Thuiller, Nicolas Titeux, Piero Visconti, Christopher Ware, Florian Wolf, and Henrique M. Pereira
Geosci. Model Dev., 11, 4537–4562, https://doi.org/10.5194/gmd-11-4537-2018, https://doi.org/10.5194/gmd-11-4537-2018, 2018
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This paper lays out the protocol for the Biodiversity and Ecosystem Services Scenario-based Intercomparison of Models (BES-SIM) that projects the global impacts of land use and climate change on biodiversity and ecosystem services over the coming decades, compared to the 20th century. BES-SIM uses harmonized scenarios and input data and a set of common output metrics at multiple scales, and identifies model uncertainties and research gaps.
Eunjee Lee, Fan-Wei Zeng, Randal D. Koster, Brad Weir, Lesley E. Ott, and Benjamin Poulter
Biogeosciences, 15, 5635–5652, https://doi.org/10.5194/bg-15-5635-2018, https://doi.org/10.5194/bg-15-5635-2018, 2018
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Land carbon fluxes are controlled in part by the responses of terrestrial ecosystems to atmospheric conditions near the Earth's surface. This study offers a comprehensive evaluation of the consequences of multiple facets of spatiotemporal variability in atmospheric CO2 for carbon cycle dynamics. Globally, consideration of the diurnal CO2 variability reduces the gross primary production and net land carbon uptake. The relative contributions of other variability vary regionally and seasonally.
Emilie Joetzjer, Fabienne Maignan, Jérôme Chave, Daniel Goll, Ben Poulter, Jonathan Barichivich, Isabelle Maréchaux, Sebastiaan Luyssaert, Matthieu Guimberteau, Kim Naudts, Damien Bonal, and Philippe Ciais
Biogeosciences Discuss., https://doi.org/10.5194/bg-2018-308, https://doi.org/10.5194/bg-2018-308, 2018
Revised manuscript not accepted
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This study explores the relative contributions of tree demographic, canopy structure and hydraulic processes on the Amazonian carbon and water cycles using large-scale process-based model. Our results imply that explicit coupling of the water and carbon cycles improves the representation of biogeochemical cycles and their spatial variability. Representing the variation in the ecological functioning of Amazonia should be the next step to improve the performance and predictive ability of models.
Gregory Duveiller, Giovanni Forzieri, Eddy Robertson, Wei Li, Goran Georgievski, Peter Lawrence, Andy Wiltshire, Philippe Ciais, Julia Pongratz, Stephen Sitch, Almut Arneth, and Alessandro Cescatti
Earth Syst. Sci. Data, 10, 1265–1279, https://doi.org/10.5194/essd-10-1265-2018, https://doi.org/10.5194/essd-10-1265-2018, 2018
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Changing the vegetation cover of the Earth's surface can alter the local energy balance, which can result in a local warming or cooling depending on the specific vegetation transition, its timing and location, as well as on the background climate. While models can theoretically simulate these effects, their skill is not well documented across space and time. Here we provide a dedicated framework to evaluate such models against measurements derived from satellite observations.
Nathaniel W. Chaney, Marjolein H. J. Van Huijgevoort, Elena Shevliakova, Sergey Malyshev, Paul C. D. Milly, Paul P. G. Gauthier, and Benjamin N. Sulman
Hydrol. Earth Syst. Sci., 22, 3311–3330, https://doi.org/10.5194/hess-22-3311-2018, https://doi.org/10.5194/hess-22-3311-2018, 2018
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The petabytes of existing global environmental data provide an invaluable asset to improve the characterization of land heterogeneity in Earth system models. This study introduces a clustering algorithm that summarizes a domain's heterogeneity through spatially interconnected clusters. A series of land model simulations in central California using this approach illustrate the critical role that multi-scale heterogeneity can have on the macroscale water, energy, and carbon cycles.
Donghai Wu, Philippe Ciais, Nicolas Viovy, Alan K. Knapp, Kevin Wilcox, Michael Bahn, Melinda D. Smith, Sara Vicca, Simone Fatichi, Jakob Zscheischler, Yue He, Xiangyi Li, Akihiko Ito, Almut Arneth, Anna Harper, Anna Ukkola, Athanasios Paschalis, Benjamin Poulter, Changhui Peng, Daniel Ricciuto, David Reinthaler, Guangsheng Chen, Hanqin Tian, Hélène Genet, Jiafu Mao, Johannes Ingrisch, Julia E. S. M. Nabel, Julia Pongratz, Lena R. Boysen, Markus Kautz, Michael Schmitt, Patrick Meir, Qiuan Zhu, Roland Hasibeder, Sebastian Sippel, Shree R. S. Dangal, Stephen Sitch, Xiaoying Shi, Yingping Wang, Yiqi Luo, Yongwen Liu, and Shilong Piao
Biogeosciences, 15, 3421–3437, https://doi.org/10.5194/bg-15-3421-2018, https://doi.org/10.5194/bg-15-3421-2018, 2018
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Our results indicate that most ecosystem models do not capture the observed asymmetric responses under normal precipitation conditions, suggesting an overestimate of the drought effects and/or underestimate of the watering impacts on primary productivity, which may be the result of inadequate representation of key eco-hydrological processes. Collaboration between modelers and site investigators needs to be strengthened to improve the specific processes in ecosystem models in following studies.
Masa Kageyama, Pascale Braconnot, Sandy P. Harrison, Alan M. Haywood, Johann H. Jungclaus, Bette L. Otto-Bliesner, Jean-Yves Peterschmitt, Ayako Abe-Ouchi, Samuel Albani, Patrick J. Bartlein, Chris Brierley, Michel Crucifix, Aisling Dolan, Laura Fernandez-Donado, Hubertus Fischer, Peter O. Hopcroft, Ruza F. Ivanovic, Fabrice Lambert, Daniel J. Lunt, Natalie M. Mahowald, W. Richard Peltier, Steven J. Phipps, Didier M. Roche, Gavin A. Schmidt, Lev Tarasov, Paul J. Valdes, Qiong Zhang, and Tianjun Zhou
Geosci. Model Dev., 11, 1033–1057, https://doi.org/10.5194/gmd-11-1033-2018, https://doi.org/10.5194/gmd-11-1033-2018, 2018
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The Paleoclimate Modelling Intercomparison Project (PMIP) takes advantage of the existence of past climate states radically different from the recent past to test climate models used for climate projections and to better understand these climates. This paper describes the PMIP contribution to CMIP6 (Coupled Model Intercomparison Project, 6th phase) and possible analyses based on PMIP results, as well as on other CMIP6 projects.
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.
Emeline Chaste, Martin P. Girardin, Jed O. Kaplan, Jeanne Portier, Yves Bergeron, and Christelle Hély
Biogeosciences, 15, 1273–1292, https://doi.org/10.5194/bg-15-1273-2018, https://doi.org/10.5194/bg-15-1273-2018, 2018
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A vegetation model was used to reconstruct fire activity from 1901 to 2012 in relation to changes in lightning ignition, climate, and vegetation in eastern Canada's boreal forest. The model correctly simulated the history of fire activity. The results showed that fire activity is ignition limited but is also greatly affected by both climate and vegetation. This research aims to develop a vegetation model that could be used to predict the future impacts of climate changes on fire activity.
Sam S. Rabin, Daniel S. Ward, Sergey L. Malyshev, Brian I. Magi, Elena Shevliakova, and Stephen W. Pacala
Geosci. Model Dev., 11, 815–842, https://doi.org/10.5194/gmd-11-815-2018, https://doi.org/10.5194/gmd-11-815-2018, 2018
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This paper describes a new fire model that for the first time simulates how fire is used on cropland and pasture in the modern day, as imposed using a recently developed dataset. A non-agricultural fire module is fit algorithmically against non-agricultural burned area. Fitting improves performance and the general global pattern of fire is represented, but some gaps remain. The novel separation of agricultural burning from other fire may necessitate new design thinking in the future.
Hans Visser, Sönke Dangendorf, Detlef P. van Vuuren, Bram Bregman, and Arthur C. Petersen
Clim. Past, 14, 139–155, https://doi.org/10.5194/cp-14-139-2018, https://doi.org/10.5194/cp-14-139-2018, 2018
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In December 2015, 195 countries agreed in Paris to hold the increase in global temperature well below 2.0 °C. However, the Paris Agreement is not conclusive as regards methods to calculate it. To find answers to these questions we performed an uncertainty and sensitivity analysis where datasets, model choices, choices for pre-industrial and warming definitions have been varied. Based on these findings we propose an estimate for signal progression in global temperature since pre-industrial time.
Susanne Rolinski, Christoph Müller, Jens Heinke, Isabelle Weindl, Anne Biewald, Benjamin Leon Bodirsky, Alberte Bondeau, Eltje R. Boons-Prins, Alexander F. Bouwman, Peter A. Leffelaar, Johnny A. te Roller, Sibyll Schaphoff, and Kirsten Thonicke
Geosci. Model Dev., 11, 429–451, https://doi.org/10.5194/gmd-11-429-2018, https://doi.org/10.5194/gmd-11-429-2018, 2018
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One-third of the global land area is covered with grasslands which are grazed by or mowed for livestock feed. These areas contribute significantly to the carbon capture from the atmosphere when managed sensibly. To assess the effect of this management, we included different options of grazing and mowing into the global model LPJmL 3.6. We found in polar regions even low grazing pressure leads to soil carbon loss whereas in temperate regions up to 1.4 livestock units per hectare can be sustained.
Brian J. Dermody, Murugesu Sivapalan, Elke Stehfest, Detlef P. van Vuuren, Martin J. Wassen, Marc F. P. Bierkens, and Stefan C. Dekker
Earth Syst. Dynam., 9, 103–118, https://doi.org/10.5194/esd-9-103-2018, https://doi.org/10.5194/esd-9-103-2018, 2018
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Ensuring sustainable food and water security is an urgent and complex challenge. As the world becomes increasingly globalised and interdependent, food and water management policies may have unintended consequences across regions, sectors and scales. Current decision-making tools do not capture these complexities and thus miss important dynamics. We present a modelling framework to capture regional and sectoral interdependence and cross-scale feedbacks within the global food system.
Nicholas C. Parazoo, Charles D. Koven, David M. Lawrence, Vladimir Romanovsky, and Charles E. Miller
The Cryosphere, 12, 123–144, https://doi.org/10.5194/tc-12-123-2018, https://doi.org/10.5194/tc-12-123-2018, 2018
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Carbon models suggest the permafrost carbon feedback (soil carbon emissions from permafrost thaw) acts as a slow, unobservable leak. We investigate if permafrost temperature provides an observable signal to detect feedbacks. We find a slow carbon feedback in warm sub-Arctic permafrost soils, but potentially rapid feedback in cold Arctic permafrost. This is surprising since the cold permafrost region is dominated by tundra and underlain by deep, cold permafrost thought impervious to such changes.
PAGES Hydro2k Consortium
Clim. Past, 13, 1851–1900, https://doi.org/10.5194/cp-13-1851-2017, https://doi.org/10.5194/cp-13-1851-2017, 2017
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Water availability is fundamental to societies and ecosystems, but our understanding of variations in hydroclimate (including extreme events, flooding, and decadal periods of drought) is limited due to a paucity of modern instrumental observations. We review how proxy records of past climate and climate model simulations can be used in tandem to understand hydroclimate variability over the last 2000 years and how these tools can also inform risk assessments of future hydroclimatic extremes.
Yannick Le Page, Douglas Morton, Corinne Hartin, Ben Bond-Lamberty, José Miguel Cardoso Pereira, George Hurtt, and Ghassem Asrar
Earth Syst. Dynam., 8, 1237–1246, https://doi.org/10.5194/esd-8-1237-2017, https://doi.org/10.5194/esd-8-1237-2017, 2017
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Fires damage large areas of eastern Amazon forests when ignitions from human activity coincide with droughts, while more humid central and western regions are less affected. Here, we use a fire model to estimate that fire activity could increase by an order of magnitude without climate mitigation. Our results show that avoiding further agricultural expansion can limit fire ignitions but that tackling climate change is essential to insulate the interior Amazon through the 21st century.
Kees Klein Goldewijk, Arthur Beusen, Jonathan Doelman, and Elke Stehfest
Earth Syst. Sci. Data, 9, 927–953, https://doi.org/10.5194/essd-9-927-2017, https://doi.org/10.5194/essd-9-927-2017, 2017
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This is an update of HYDE, which is an internally consistent combination of historical population estimates and time-dependent land use allocation algorithms for 10 000 BCE–2015 CE. Categories include cropland, separated into irrigated and rain-fed rice and non-rice crops. Grazing lands are divided into more intensely used pasture and less intensively used rangelands. Population includes total, urban, and rural population and population density and built-up area.
Katja Frieler, Stefan Lange, Franziska Piontek, Christopher P. O. Reyer, Jacob Schewe, Lila Warszawski, Fang Zhao, Louise Chini, Sebastien Denvil, Kerry Emanuel, Tobias Geiger, Kate Halladay, George Hurtt, Matthias Mengel, Daisuke Murakami, Sebastian Ostberg, Alexander Popp, Riccardo Riva, Miodrag Stevanovic, Tatsuo Suzuki, Jan Volkholz, Eleanor Burke, Philippe Ciais, Kristie Ebi, Tyler D. Eddy, Joshua Elliott, Eric Galbraith, Simon N. Gosling, Fred Hattermann, Thomas Hickler, Jochen Hinkel, Christian Hof, Veronika Huber, Jonas Jägermeyr, Valentina Krysanova, Rafael Marcé, Hannes Müller Schmied, Ioanna Mouratiadou, Don Pierson, Derek P. Tittensor, Robert Vautard, Michelle van Vliet, Matthias F. Biber, Richard A. Betts, Benjamin Leon Bodirsky, Delphine Deryng, Steve Frolking, Chris D. Jones, Heike K. Lotze, Hermann Lotze-Campen, Ritvik Sahajpal, Kirsten Thonicke, Hanqin Tian, and Yoshiki Yamagata
Geosci. Model Dev., 10, 4321–4345, https://doi.org/10.5194/gmd-10-4321-2017, https://doi.org/10.5194/gmd-10-4321-2017, 2017
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This paper describes the simulation scenario design for the next phase of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP), which is designed to facilitate a contribution to the scientific basis for the IPCC Special Report on the impacts of 1.5 °C global warming. ISIMIP brings together over 80 climate-impact models, covering impacts on hydrology, biomes, forests, heat-related mortality, permafrost, tropical cyclones, fisheries, agiculture, energy, and coastal infrastructure.
Abigail C. Snyder, Robert P. Link, and Katherine V. Calvin
Geosci. Model Dev., 10, 4307–4319, https://doi.org/10.5194/gmd-10-4307-2017, https://doi.org/10.5194/gmd-10-4307-2017, 2017
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Experiments conducting a model forecast for a period in which observational data are available are rarely undertaken in the integrated assessment model (IAM) community. When undertaken, results are often evaluated using global aggregates that mask deficiencies. Comparing land allocation simulations in GCAM with FAO observational data from 1990 to 2010, we find quantitative evidence that global aggregates alone are not sufficient for evaluating IAMs with global supply constraints similar to GCAM.
Wei Li, Philippe Ciais, Shushi Peng, Chao Yue, Yilong Wang, Martin Thurner, Sassan S. Saatchi, Almut Arneth, Valerio Avitabile, Nuno Carvalhais, Anna B. Harper, Etsushi Kato, Charles Koven, Yi Y. Liu, Julia E.M.S. Nabel, Yude Pan, Julia Pongratz, Benjamin Poulter, Thomas A. M. Pugh, Maurizio Santoro, Stephen Sitch, Benjamin D. Stocker, Nicolas Viovy, Andy Wiltshire, Rasoul Yousefpour, and Sönke Zaehle
Biogeosciences, 14, 5053–5067, https://doi.org/10.5194/bg-14-5053-2017, https://doi.org/10.5194/bg-14-5053-2017, 2017
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We used several observation-based biomass datasets to constrain the historical land-use change carbon emissions simulated by models. Compared to the range of the original modeled emissions (from 94 to 273 Pg C), the observationally constrained global cumulative emission estimate is 155 ± 50 Pg C (1σ Gaussian error) from 1901 to 2012. Our approach can also be applied to evaluate the LULCC impact of land-based climate mitigation policies.
Johann H. Jungclaus, Edouard Bard, Mélanie Baroni, Pascale Braconnot, Jian Cao, Louise P. Chini, Tania Egorova, Michael Evans, J. Fidel González-Rouco, Hugues Goosse, George C. Hurtt, Fortunat Joos, Jed O. Kaplan, Myriam Khodri, Kees Klein Goldewijk, Natalie Krivova, Allegra N. LeGrande, Stephan J. Lorenz, Jürg Luterbacher, Wenmin Man, Amanda C. Maycock, Malte Meinshausen, Anders Moberg, Raimund Muscheler, Christoph Nehrbass-Ahles, Bette I. Otto-Bliesner, Steven J. Phipps, Julia Pongratz, Eugene Rozanov, Gavin A. Schmidt, Hauke Schmidt, Werner Schmutz, Andrew Schurer, Alexander I. Shapiro, Michael Sigl, Jason E. Smerdon, Sami K. Solanki, Claudia Timmreck, Matthew Toohey, Ilya G. Usoskin, Sebastian Wagner, Chi-Ju Wu, Kok Leng Yeo, Davide Zanchettin, Qiong Zhang, and Eduardo Zorita
Geosci. Model Dev., 10, 4005–4033, https://doi.org/10.5194/gmd-10-4005-2017, https://doi.org/10.5194/gmd-10-4005-2017, 2017
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Climate model simulations covering the last millennium provide context for the evolution of the modern climate and for the expected changes during the coming centuries. They can help identify plausible mechanisms underlying palaeoclimatic reconstructions. Here, we describe the forcing boundary conditions and the experimental protocol for simulations covering the pre-industrial millennium. We describe the PMIP4 past1000 simulations as contributions to CMIP6 and additional sensitivity experiments.
Andreas Krause, Thomas A. M. Pugh, Anita D. Bayer, Jonathan C. Doelman, Florian Humpenöder, Peter Anthoni, Stefan Olin, Benjamin L. Bodirsky, Alexander Popp, Elke Stehfest, and Almut Arneth
Biogeosciences, 14, 4829–4850, https://doi.org/10.5194/bg-14-4829-2017, https://doi.org/10.5194/bg-14-4829-2017, 2017
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Many climate change mitigation scenarios require negative emissions from land management. However, environmental side effects are often not considered. Here, we use projections of future land use from two land-use models as input to a vegetation model. We show that carbon removal via bioenergy production or forest maintenance and expansion affect a range of ecosystem functions. Largest impacts are found for crop production, nitrogen losses, and emissions of biogenic volatile organic compounds.
Philipp S. Sommer and Jed O. Kaplan
Geosci. Model Dev., 10, 3771–3791, https://doi.org/10.5194/gmd-10-3771-2017, https://doi.org/10.5194/gmd-10-3771-2017, 2017
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We present GWGEN, a computer program for converting monthly climate data into estimates of daily weather, using statistical methods. The GWGEN weather generator program was developed using a global database of more than 5 million observations of daily weather, and it simulates daily values of minimum and maximum temperature, precipitation, cloud cover, and wind speed. GWGEN may be used in a range of applications, for example, in global vegetation, crop, soil erosion, or hydrological models.
Henrique F. Duarte, Brett M. Raczka, Daniel M. Ricciuto, John C. Lin, Charles D. Koven, Peter E. Thornton, David R. Bowling, Chun-Ta Lai, Kenneth J. Bible, and James R. Ehleringer
Biogeosciences, 14, 4315–4340, https://doi.org/10.5194/bg-14-4315-2017, https://doi.org/10.5194/bg-14-4315-2017, 2017
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We evaluate the Community Land Model (CLM4.5) against observations at an old-growth coniferous forest site that is subjected to water stress each summer. We found that, after calibration, CLM was able to reasonably simulate the observed fluxes of energy and carbon, carbon stocks, carbon isotope ratios, and ecosystem response to water stress. This study demonstrates that carbon isotopes can expose structural weaknesses in CLM and provide a key constraint that may guide future model development.
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, Lori Bruhwiler, Cyril Crevoisier, Patrick Crill, Kristofer Covey, 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, 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, Ronald Prinn, Michel Ramonet, William J. Riley, Makoto Saito, Monia Santini, Ronny Schroeder, Isobel J. Simpson, Renato Spahni, Atsushi Takizawa, Brett F. Thornton, Hanqin Tian, Yasunori Tohjima, Nicolas Viovy, Apostolos Voulgarakis, Ray Weiss, David J. Wilton, Andy Wiltshire, Doug Worthy, Debra Wunch, Xiyan Xu, Yukio Yoshida, Bowen Zhang, Zhen Zhang, and Qiuan Zhu
Atmos. Chem. Phys., 17, 11135–11161, https://doi.org/10.5194/acp-17-11135-2017, https://doi.org/10.5194/acp-17-11135-2017, 2017
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Following the Global Methane Budget 2000–2012 published in Saunois et al. (2016), we use the same dataset of bottom-up and top-down approaches to discuss the variations in methane emissions over the period 2000–2012. The changes in emissions are discussed both in terms of trends and quasi-decadal changes. The ensemble gathered here allows us to synthesise the robust changes in terms of regional and sectorial contributions to the increasing methane emissions.
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.
Reinhard Prestele, Almut Arneth, Alberte Bondeau, Nathalie de Noblet-Ducoudré, Thomas A. M. Pugh, Stephen Sitch, Elke Stehfest, and Peter H. Verburg
Earth Syst. Dynam., 8, 369–386, https://doi.org/10.5194/esd-8-369-2017, https://doi.org/10.5194/esd-8-369-2017, 2017
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Land-use change is still overly simplistically implemented in global ecosystem and climate models. We identify and discuss three major challenges at the interface of land-use and climate modeling and propose ways for how to improve land-use representation in climate models. We conclude that land-use data-provider and user communities need to engage in the joint development and evaluation of enhanced land-use datasets to improve the quantification of land use–climate interactions and feedback.
Andrew G. Slater, David M. Lawrence, and Charles D. Koven
The Cryosphere, 11, 989–996, https://doi.org/10.5194/tc-11-989-2017, https://doi.org/10.5194/tc-11-989-2017, 2017
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This work defines a metric for evaluation of a specific model snow process, namely, heat transfer through snow into soil. Heat transfer through snow regulates the difference in air temperature versus soil temperature. Accurate representation of the snow heat transfer process is critically important for accurate representation of the current and future state of permafrost. Utilizing this metric, we can clearly identify models that can and cannot reasonably represent snow heat transfer.
Christoph Müller, Joshua Elliott, James Chryssanthacopoulos, Almut Arneth, Juraj Balkovic, Philippe Ciais, Delphine Deryng, Christian Folberth, Michael Glotter, Steven Hoek, Toshichika Iizumi, Roberto C. Izaurralde, Curtis Jones, Nikolay Khabarov, Peter Lawrence, Wenfeng Liu, Stefan Olin, Thomas A. M. Pugh, Deepak K. Ray, Ashwan Reddy, Cynthia Rosenzweig, Alex C. Ruane, Gen Sakurai, Erwin Schmid, Rastislav Skalsky, Carol X. Song, Xuhui Wang, Allard de Wit, and Hong Yang
Geosci. Model Dev., 10, 1403–1422, https://doi.org/10.5194/gmd-10-1403-2017, https://doi.org/10.5194/gmd-10-1403-2017, 2017
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Crop models are increasingly used in climate change impact research and integrated assessments. For the Agricultural Model Intercomparison and Improvement Project (AgMIP), 14 global gridded crop models (GGCMs) have supplied crop yield simulations (1980–2010) for maize, wheat, rice and soybean. We evaluate the performance of these models against observational data at global, national and grid cell level. We propose an open-access benchmark system against which future model versions can be tested.
Sam S. Rabin, Joe R. Melton, Gitta Lasslop, Dominique Bachelet, Matthew Forrest, Stijn Hantson, Jed O. Kaplan, Fang Li, Stéphane Mangeon, Daniel S. Ward, Chao Yue, Vivek K. Arora, Thomas Hickler, Silvia Kloster, Wolfgang Knorr, Lars Nieradzik, Allan Spessa, Gerd A. Folberth, Tim Sheehan, Apostolos Voulgarakis, Douglas I. Kelley, I. Colin Prentice, Stephen Sitch, Sandy Harrison, and Almut Arneth
Geosci. Model Dev., 10, 1175–1197, https://doi.org/10.5194/gmd-10-1175-2017, https://doi.org/10.5194/gmd-10-1175-2017, 2017
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Global vegetation models are important tools for understanding how the Earth system will change in the future, and fire is a critical process to include. A number of different methods have been developed to represent vegetation burning. This paper describes the protocol for the first systematic comparison of global fire models, which will allow the community to explore various drivers and evaluate what mechanisms are important for improving performance. It also includes equations for all models.
Christian Folberth, Joshua Elliott, Christoph Müller, Juraj Balkovic, James Chryssanthacopoulos, Roberto C. Izaurralde, Curtis D. Jones, Nikolay Khabarov, Wenfeng Liu, Ashwan Reddy, Erwin Schmid, Rastislav Skalský, Hong Yang, Almut Arneth, Philippe Ciais, Delphine Deryng, Peter J. Lawrence, Stefan Olin, Thomas A. M. Pugh, Alex C. Ruane, and Xuhui Wang
Biogeosciences Discuss., https://doi.org/10.5194/bg-2016-527, https://doi.org/10.5194/bg-2016-527, 2016
Manuscript not accepted for further review
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Global crop models differ in numerous aspects such as algorithms, parameterization, input data, and management assumptions. This study compares five global crop model frameworks, all based on the same field-scale model, to identify differences induced by the latter three. Results indicate that foremost nutrient supply, soil handling, and crop management induce substantial differences in crop yield estimates whereas crop cultivars primarily result in scaling of yield levels.
Ole Mertz, Kjeld Rasmussen, and Laura Vang Rasmussen
Earth Syst. Dynam., 7, 969–976, https://doi.org/10.5194/esd-7-969-2016, https://doi.org/10.5194/esd-7-969-2016, 2016
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Conflicts over land and water resources between livestock herders and farmers are common in the Sahelian region of Africa. In this paper we show that improved information on weather, grazing areas, and water resources may reduce the level of conflict if communicated in such a way so that not too many livestock herds go to the same areas. However, if this information is not accompanied by information on herd crowding and potential conflict areas, it may lead to more conflict.
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.
Dóra Hidy, Zoltán Barcza, Hrvoje Marjanović, Maša Zorana Ostrogović Sever, Laura Dobor, Györgyi Gelybó, Nándor Fodor, Krisztina Pintér, Galina Churkina, Steven Running, Peter Thornton, Gianni Bellocchi, László Haszpra, Ferenc Horváth, Andrew Suyker, and Zoltán Nagy
Geosci. Model Dev., 9, 4405–4437, https://doi.org/10.5194/gmd-9-4405-2016, https://doi.org/10.5194/gmd-9-4405-2016, 2016
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This paper provides detailed documentation on the changes implemented in the widely used biogeochemical model Biome-BGC. The version containing all improvements is referred to as Biome-BGCMuSo (Biome-BGC with multilayer soil module). Case studies on forest, cropland, and grassland are presented to demonstrate the effect of developments on the simulation. By using Biome-BGCMuSo, it became possible to analyze the effects of different environmental conditions and human activities on the ecosystems.
Kerstin Engström, Stefan Olin, Mark D. A. Rounsevell, Sara Brogaard, Detlef P. van Vuuren, Peter Alexander, Dave Murray-Rust, and Almut Arneth
Earth Syst. Dynam., 7, 893–915, https://doi.org/10.5194/esd-7-893-2016, https://doi.org/10.5194/esd-7-893-2016, 2016
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The development of global cropland in the future depends on how many people there will be, how much meat and milk we will eat, how much food we will waste and how well farms will be managed. Uncertainties in these factors mean that global cropland could decrease from today's 1500 Mha to only 893 Mha in 2100, which would free land for biofuel production. However, if population rises towards 12 billion and global yields remain low, global cropland could also increase up to 2380 Mha in 2100.
Corinne Le Quéré, Robbie M. Andrew, Josep G. Canadell, Stephen Sitch, Jan Ivar Korsbakken, Glen P. Peters, Andrew C. Manning, Thomas A. Boden, Pieter P. Tans, Richard A. Houghton, Ralph F. Keeling, Simone Alin, Oliver D. Andrews, Peter Anthoni, Leticia Barbero, Laurent Bopp, Frédéric Chevallier, Louise P. Chini, Philippe Ciais, Kim Currie, Christine Delire, Scott C. Doney, Pierre Friedlingstein, Thanos Gkritzalis, Ian Harris, Judith Hauck, Vanessa Haverd, Mario Hoppema, Kees Klein Goldewijk, Atul K. Jain, Etsushi Kato, Arne Körtzinger, Peter Landschützer, Nathalie Lefèvre, Andrew Lenton, Sebastian Lienert, Danica Lombardozzi, Joe R. Melton, Nicolas Metzl, Frank Millero, Pedro M. S. Monteiro, David R. Munro, Julia E. M. S. Nabel, Shin-ichiro Nakaoka, Kevin O'Brien, Are Olsen, Abdirahman M. Omar, Tsuneo Ono, Denis Pierrot, Benjamin Poulter, Christian Rödenbeck, Joe Salisbury, Ute Schuster, Jörg Schwinger, Roland Séférian, Ingunn Skjelvan, Benjamin D. Stocker, Adrienne J. Sutton, Taro Takahashi, Hanqin Tian, Bronte Tilbrook, Ingrid T. van der Laan-Luijkx, Guido R. van der Werf, Nicolas Viovy, Anthony P. Walker, Andrew J. Wiltshire, and Sönke Zaehle
Earth Syst. Sci. Data, 8, 605–649, https://doi.org/10.5194/essd-8-605-2016, https://doi.org/10.5194/essd-8-605-2016, 2016
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The Global Carbon Budget 2016 is the 11th annual update of emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, land, and ocean. This data synthesis brings together measurements, statistical information, and analyses of model results in order to provide an assessment of the global carbon budget and their uncertainties for years 1959 to 2015, with a projection for year 2016.
Jonathan M. Gregory, Nathaelle Bouttes, Stephen M. Griffies, Helmuth Haak, William J. Hurlin, Johann Jungclaus, Maxwell Kelley, Warren G. Lee, John Marshall, Anastasia Romanou, Oleg A. Saenko, Detlef Stammer, and Michael Winton
Geosci. Model Dev., 9, 3993–4017, https://doi.org/10.5194/gmd-9-3993-2016, https://doi.org/10.5194/gmd-9-3993-2016, 2016
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As a consequence of greenhouse gas emissions, changes in ocean temperature, salinity, circulation and sea level are expected in coming decades. Among the models used for climate projections for the 21st century, there is a large spread in projections of these effects. The Flux-Anomaly-Forced Model Intercomparison Project (FAFMIP) aims to investigate and explain this spread by prescribing a common set of changes in the input of heat, water and wind stress to the ocean in the participating models.
Alex C. Ruane, Claas Teichmann, Nigel W. Arnell, Timothy R. Carter, Kristie L. Ebi, Katja Frieler, Clare M. Goodess, Bruce Hewitson, Radley Horton, R. Sari Kovats, Heike K. Lotze, Linda O. Mearns, Antonio Navarra, Dennis S. Ojima, Keywan Riahi, Cynthia Rosenzweig, Matthias Themessl, and Katharine Vincent
Geosci. Model Dev., 9, 3493–3515, https://doi.org/10.5194/gmd-9-3493-2016, https://doi.org/10.5194/gmd-9-3493-2016, 2016
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The Vulnerability, Impacts, Adaptation, and Climate Services (VIACS) Advisory Board for CMIP6 was created to improve communications between communities that apply climate model output for societal benefit and the climate model centers. This manuscript describes the establishment of the VIACS Advisory Board as a coherent avenue for communication utilizing leading networks, experts, and programs; results of initial interactions during the development of CMIP6; and its potential next activities.
Brian C. O'Neill, Claudia Tebaldi, Detlef P. van Vuuren, Veronika Eyring, Pierre Friedlingstein, George Hurtt, Reto Knutti, Elmar Kriegler, Jean-Francois Lamarque, Jason Lowe, Gerald A. Meehl, Richard Moss, Keywan Riahi, and Benjamin M. Sanderson
Geosci. Model Dev., 9, 3461–3482, https://doi.org/10.5194/gmd-9-3461-2016, https://doi.org/10.5194/gmd-9-3461-2016, 2016
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The Scenario Model Intercomparison Project (ScenarioMIP) will provide multi-model climate projections based on alternative scenarios of future emissions and land use changes produced with integrated assessment models. The design consists of eight alternative 21st century scenarios plus one large initial condition ensemble and a set of long-term extensions. Climate model projections will facilitate integrated studies of climate change as well as address targeted scientific questions.
Jitendra Kumar, Nathan Collier, Gautam Bisht, Richard T. Mills, Peter E. Thornton, Colleen M. Iversen, and Vladimir Romanovsky
The Cryosphere, 10, 2241–2274, https://doi.org/10.5194/tc-10-2241-2016, https://doi.org/10.5194/tc-10-2241-2016, 2016
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Microtopography of the low-gradient polygonal tundra plays a critical role in these ecosystem; however, patterns and drivers are poorly understood. A modeling-based approach was developed in this study to characterize and represent the permafrost soils in the model and simulate the thermal dynamics using a mechanistic high-resolution model. Results shows the ability of the model to simulate the patterns and variability of thermal regimes and improve our understanding of polygonal tundra.
Brett Raczka, Henrique F. Duarte, Charles D. Koven, Daniel Ricciuto, Peter E. Thornton, John C. Lin, and David R. Bowling
Biogeosciences, 13, 5183–5204, https://doi.org/10.5194/bg-13-5183-2016, https://doi.org/10.5194/bg-13-5183-2016, 2016
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We use carbon isotopes of CO2 to improve the performance of a land surface model, a component with earth system climate models. We found that isotope observations can provide important information related to the exchange of carbon and water from vegetation driven by environmental stress from low atmospheric moisture and nitrogen limitation. It follows that isotopes have a unique potential to improve model performance and provide insight into land surface model development.
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.
Fang Zhao, Ning Zeng, Ghassem Asrar, Pierre Friedlingstein, Akihiko Ito, Atul Jain, Eugenia Kalnay, Etsushi Kato, Charles D. Koven, Ben Poulter, Rashid Rafique, Stephen Sitch, Shijie Shu, Beni Stocker, Nicolas Viovy, Andy Wiltshire, and Sonke Zaehle
Biogeosciences, 13, 5121–5137, https://doi.org/10.5194/bg-13-5121-2016, https://doi.org/10.5194/bg-13-5121-2016, 2016
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The increasing seasonality of atmospheric CO2 is strongly linked with enhanced land vegetation activities in the last 5 decades, for which the importance of increasing CO2, climate and land use/cover change was evaluated in single model studies (Zeng et al., 2014; Forkel et al., 2016). Here we examine the relative importance of these factors in multiple models. Our results highlight models can show similar results in some benchmarks with different underlying regional dynamics.
Xiyan Xu, William J. Riley, Charles D. Koven, Dave P. Billesbach, Rachel Y.-W. Chang, Róisín Commane, Eugénie S. Euskirchen, Sean Hartery, Yoshinobu Harazono, Hiroki Iwata, Kyle C. McDonald, Charles E. Miller, Walter C. Oechel, Benjamin Poulter, Naama Raz-Yaseef, Colm Sweeney, Margaret Torn, Steven C. Wofsy, Zhen Zhang, and Donatella Zona
Biogeosciences, 13, 5043–5056, https://doi.org/10.5194/bg-13-5043-2016, https://doi.org/10.5194/bg-13-5043-2016, 2016
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Wetlands are the largest global natural methane source. Peat-rich bogs and fens lying between 50°N and 70°N contribute 10–30% to this source. The predictive capability of the seasonal methane cycle can directly affect the estimation of global methane budget. We present multiscale methane seasonal emission by observations and modeling and find that the uncertainties in predicting the seasonal methane emissions are from the wetland extent, cold-season CH4 production and CH4 transport processes.
Guoping Tang, Jianqiu Zheng, Xiaofeng Xu, Ziming Yang, David E. Graham, Baohua Gu, Scott L. Painter, and Peter E. Thornton
Biogeosciences, 13, 5021–5041, https://doi.org/10.5194/bg-13-5021-2016, https://doi.org/10.5194/bg-13-5021-2016, 2016
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We extend the Community Land Model coupled with carbon and nitrogen (CLM-CN) decomposition cascade to include simple organic substrate turnover, fermentation, Fe(III) reduction, and methanogenesis reactions, and assess the efficacy of various temperature and pH response functions. Incorporating the Windermere Humic Aqueous Model (WHAM) describes the observed pH evolution. Fe reduction can increase pH toward neutral pH to facilitate methanogenesis.
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.
Bart van den Hurk, Hyungjun Kim, Gerhard Krinner, Sonia I. Seneviratne, Chris Derksen, Taikan Oki, Hervé Douville, Jeanne Colin, Agnès Ducharne, Frederique Cheruy, Nicholas Viovy, Michael J. Puma, Yoshihide Wada, Weiping Li, Binghao Jia, Andrea Alessandri, Dave M. Lawrence, Graham P. Weedon, Richard Ellis, Stefan Hagemann, Jiafu Mao, Mark G. Flanner, Matteo Zampieri, Stefano Materia, Rachel M. Law, and Justin Sheffield
Geosci. Model Dev., 9, 2809–2832, https://doi.org/10.5194/gmd-9-2809-2016, https://doi.org/10.5194/gmd-9-2809-2016, 2016
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This manuscript describes the setup of the CMIP6 project Land Surface, Snow and Soil Moisture Model Intercomparison Project (LS3MIP).
Wenli Wang, Annette Rinke, John C. Moore, Duoying Ji, Xuefeng Cui, Shushi Peng, David M. Lawrence, A. David McGuire, Eleanor J. Burke, Xiaodong Chen, Bertrand Decharme, Charles Koven, Andrew MacDougall, Kazuyuki Saito, Wenxin Zhang, Ramdane Alkama, Theodore J. Bohn, Philippe Ciais, Christine Delire, Isabelle Gouttevin, Tomohiro Hajima, Gerhard Krinner, Dennis P. Lettenmaier, Paul A. Miller, Benjamin Smith, Tetsuo Sueyoshi, and Artem B. Sherstiukov
The Cryosphere, 10, 1721–1737, https://doi.org/10.5194/tc-10-1721-2016, https://doi.org/10.5194/tc-10-1721-2016, 2016
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The winter snow insulation is a key process for air–soil temperature coupling and is relevant for permafrost simulations. Differences in simulated air–soil temperature relationships and their modulation by climate conditions are found to be related to the snow model physics. Generally, models with better performance apply multilayer snow schemes.
Rosa Maria Roman-Cuesta, Mariana C. Rufino, Martin Herold, Klaus Butterbach-Bahl, Todd S. Rosenstock, Mario Herrero, Stephen Ogle, Changsheng Li, Benjamin Poulter, Louis Verchot, Christopher Martius, John Stuiver, and Sytze de Bruin
Biogeosciences, 13, 4253–4269, https://doi.org/10.5194/bg-13-4253-2016, https://doi.org/10.5194/bg-13-4253-2016, 2016
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This research provides spatial data on gross emissions from the land use sector for the tropical region for the period 2000–2005. This sector contributes up to 24 % of the global emissions, but there is little understanding of where the hotspots of emissions are, how uncertain they are, and what the human activities behind these emissions are. Data provided here should assist countries to identify priority areas for mitigation action and contrast the effectiveness of their current measures.
Anastasios Matsikaris, Martin Widmann, and Johann Jungclaus
Clim. Past, 12, 1555–1563, https://doi.org/10.5194/cp-12-1555-2016, https://doi.org/10.5194/cp-12-1555-2016, 2016
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We have assimilated proxy-based (PAGES 2K) and instrumental (HadCRUT3v) observations into a General Circulation Model (MPI-ESM-CR). Assimilating instrumental data improves the performance of Data Assimilation. No skill on small spatial scales is however found for either of the two schemes. Errors in the assimilated data are therefore not the main reason for this lack of skill; continental mean temperatures cannot provide skill on small spatial scales in palaeoclimate reconstructions.
Jinfeng Chang, Philippe Ciais, Mario Herrero, Petr Havlik, Matteo Campioli, Xianzhou Zhang, Yongfei Bai, Nicolas Viovy, Joanna Joiner, Xuhui Wang, Shushi Peng, Chao Yue, Shilong Piao, Tao Wang, Didier A. Hauglustaine, Jean-Francois Soussana, Anna Peregon, Natalya Kosykh, and Nina Mironycheva-Tokareva
Biogeosciences, 13, 3757–3776, https://doi.org/10.5194/bg-13-3757-2016, https://doi.org/10.5194/bg-13-3757-2016, 2016
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We derived the global maps of grassland management intensity of 1901–2012, including the minimum area of managed grassland with fraction of mown/grazed part. These maps, to our knowledge for the first time, provide global, time-dependent information for drawing up global estimates of management impact on biomass production and yields and for global vegetation models to enable simulations of carbon stocks and GHG budgets beyond simple tuning of grassland productivities to account for management.
Xiaofeng Xu, Fengming Yuan, Paul J. Hanson, Stan D. Wullschleger, Peter E. Thornton, William J. Riley, Xia Song, David E. Graham, Changchun Song, and Hanqin Tian
Biogeosciences, 13, 3735–3755, https://doi.org/10.5194/bg-13-3735-2016, https://doi.org/10.5194/bg-13-3735-2016, 2016
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Accurately projecting future climate change requires a good methane modeling. However, how good the current models are and what are the key improvements needed remain unclear. This paper reviews the 40 published methane models to characterize the strengths and weakness of current methane models and further lay out the roadmap for future model improvements.
Stijn Hantson, Almut Arneth, Sandy P. Harrison, Douglas I. Kelley, I. Colin Prentice, Sam S. Rabin, Sally Archibald, Florent Mouillot, Steve R. Arnold, Paulo Artaxo, Dominique Bachelet, Philippe Ciais, Matthew Forrest, Pierre Friedlingstein, Thomas Hickler, Jed O. Kaplan, Silvia Kloster, Wolfgang Knorr, Gitta Lasslop, Fang Li, Stephane Mangeon, Joe R. Melton, Andrea Meyn, Stephen Sitch, Allan Spessa, Guido R. van der Werf, Apostolos Voulgarakis, and Chao Yue
Biogeosciences, 13, 3359–3375, https://doi.org/10.5194/bg-13-3359-2016, https://doi.org/10.5194/bg-13-3359-2016, 2016
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Our ability to predict the magnitude and geographic pattern of past and future fire impacts rests on our ability to model fire regimes. A large variety of models exist, and it is unclear which type of model or degree of complexity is required to model fire adequately at regional to global scales. In this paper we summarize the current state of the art in fire-regime modelling and model evaluation, and outline what lessons may be learned from the Fire Model Intercomparison Project – FireMIP.
M. Clare Smith, Joy S. Singarayer, Paul J. Valdes, Jed O. Kaplan, and Nicholas P. Branch
Clim. Past, 12, 923–941, https://doi.org/10.5194/cp-12-923-2016, https://doi.org/10.5194/cp-12-923-2016, 2016
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We used climate modelling to estimate the biogeophysical impacts of agriculture on the climate over the last 8000 years of the Holocene. Our results show statistically significant surface temperature changes (mainly cooling) from as early as 7000 BP in the JJA season and throughout the entire annual cycle by 2–3000 BP. The changes were greatest in the areas of land use change but were also seen in other areas. Precipitation was also affected, particularly in Europe, India, and the ITCZ region.
Detlef P. van Vuuren, Paul L. Lucas, Tiina Häyhä, Sarah E. Cornell, and Mark Stafford-Smith
Earth Syst. Dynam., 7, 267–279, https://doi.org/10.5194/esd-7-267-2016, https://doi.org/10.5194/esd-7-267-2016, 2016
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There is a need for further integrated research on developing a set of sustainable development objectives, based on the proposed framework of planetary boundary indicators. This paper organises the research questions in four key categories. It subsequently discusses how different categories of scientific disciplines and in particular models can contribute to the necessary analysis.
Zhen Zhang, Niklaus E. Zimmermann, Jed O. Kaplan, and Benjamin Poulter
Biogeosciences, 13, 1387–1408, https://doi.org/10.5194/bg-13-1387-2016, https://doi.org/10.5194/bg-13-1387-2016, 2016
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This study investigates improvements and uncertainties associated with estimating global inundated area and wetland CH4 emissions using TOPMODEL. Different topographic information and catchment aggregation schemes are evaluated against seasonal and permanently inundated wetland observations. Reducing uncertainty in prognostic wetland dynamics modeling must take into account forcing data as well as topographic scaling schemes.
Guoping Tang, Fengming Yuan, Gautam Bisht, Glenn E. Hammond, Peter C. Lichtner, Jitendra Kumar, Richard T. Mills, Xiaofeng Xu, Ben Andre, Forrest M. Hoffman, Scott L. Painter, and Peter E. Thornton
Geosci. Model Dev., 9, 927–946, https://doi.org/10.5194/gmd-9-927-2016, https://doi.org/10.5194/gmd-9-927-2016, 2016
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We demonstrate that CLM-PFLOTRAN predictions are consistent with CLM4.5 for Arctic, temperate, and tropical sites. A tight relative tolerance may be needed to avoid false convergence when scaling, clipping, or log transformation is used to avoid negative concentration in implicit time stepping and Newton-Raphson methods. The log transformation method is accurate and robust while relaxing relative tolerance or using the clipping or scaling method can result in efficient solutions.
W. Wang, A. Rinke, J. C. Moore, X. Cui, D. Ji, Q. Li, N. Zhang, C. Wang, S. Zhang, D. M. Lawrence, A. D. McGuire, W. Zhang, C. Delire, C. Koven, K. Saito, A. MacDougall, E. Burke, and B. Decharme
The Cryosphere, 10, 287–306, https://doi.org/10.5194/tc-10-287-2016, https://doi.org/10.5194/tc-10-287-2016, 2016
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We use a model-ensemble approach for simulating permafrost on the Tibetan Plateau. We identify the uncertainties across models (state-of-the-art land surface models) and across methods (most commonly used methods to define permafrost).
We differentiate between uncertainties stemming from climatic driving data or from physical process parameterization, and show how these uncertainties vary seasonally and inter-annually, and how estimates are subject to the definition of permafrost used.
We differentiate between uncertainties stemming from climatic driving data or from physical process parameterization, and show how these uncertainties vary seasonally and inter-annually, and how estimates are subject to the definition of permafrost used.
J. Mao, D. M. Ricciuto, P. E. Thornton, J. M. Warren, A. W. King, X. Shi, C. M. Iversen, and R. J. Norby
Biogeosciences, 13, 641–657, https://doi.org/10.5194/bg-13-641-2016, https://doi.org/10.5194/bg-13-641-2016, 2016
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The aim of this study is to implement, calibrate and evaluate the CLM4 against carbon and hydrology observations from a shading and labeling experiment in a stand of young loblolly pines. We found a combination of parameters measured on-site and calibration targeting biomass, transpiration, and 13C discrimination gave good agreement with pretreatment measurements. We also used observations from the experiment to develop a conceptual model of short-term photosynthate storage and transport.
S. Peng, P. Ciais, G. Krinner, T. Wang, I. Gouttevin, A. D. McGuire, D. Lawrence, E. Burke, X. Chen, B. Decharme, C. Koven, A. MacDougall, A. Rinke, K. Saito, W. Zhang, R. Alkama, T. J. Bohn, C. Delire, T. Hajima, D. Ji, D. P. Lettenmaier, P. A. Miller, J. C. Moore, B. Smith, and T. Sueyoshi
The Cryosphere, 10, 179–192, https://doi.org/10.5194/tc-10-179-2016, https://doi.org/10.5194/tc-10-179-2016, 2016
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Soil temperature change is a key indicator of the dynamics of permafrost. Using nine process-based ecosystem models with permafrost processes, a large spread of soil temperature trends across the models. Air temperature and longwave downward radiation are the main drivers of soil temperature trends. Based on an emerging observation constraint method, the total boreal near-surface permafrost area decrease comprised between 39 ± 14 × 103 and 75 ± 14 × 103 km2 yr−1 from 1960 to 2000.
G. Murray-Tortarolo, P. Friedlingstein, S. Sitch, V. J. Jaramillo, F. Murguía-Flores, A. Anav, Y. Liu, A. Arneth, A. Arvanitis, A. Harper, A. Jain, E. Kato, C. Koven, B. Poulter, B. D. Stocker, A. Wiltshire, S. Zaehle, and N. Zeng
Biogeosciences, 13, 223–238, https://doi.org/10.5194/bg-13-223-2016, https://doi.org/10.5194/bg-13-223-2016, 2016
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We modelled the carbon (C) cycle in Mexico for three different time periods: past (20th century), present (2000-2005) and future (2006-2100). We used different available products to estimate C stocks and fluxes in the country. Contrary to other current estimates, our results showed that Mexico was a C sink and this is likely to continue in the next century (unless the most extreme climate-change scenarios are reached).
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.
S. S. Rabin, B. I. Magi, E. Shevliakova, and S. W. Pacala
Biogeosciences, 12, 6591–6604, https://doi.org/10.5194/bg-12-6591-2015, https://doi.org/10.5194/bg-12-6591-2015, 2015
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People worldwide use fire to manage agriculture, but often also suppress fire in the landscape surrounding their fields. Here, we estimate the net result of these effects of cropland and pasture on fire at a regional, monthly level. Pasture is shown, for the first time, to contribute strongly to global patterns of burning. Our results could be used to improve representations of burning in global vegetation and climate models, improving our understanding of how people affect the Earth system.
X. Shi, P. E. Thornton, D. M. Ricciuto, P. J. Hanson, J. Mao, S. D. Sebestyen, N. A. Griffiths, and G. Bisht
Biogeosciences, 12, 6463–6477, https://doi.org/10.5194/bg-12-6463-2015, https://doi.org/10.5194/bg-12-6463-2015, 2015
R. A. Fisher, S. Muszala, M. Verteinstein, P. Lawrence, C. Xu, N. G. McDowell, R. G. Knox, C. Koven, J. Holm, B. M. Rogers, A. Spessa, D. Lawrence, and G. Bonan
Geosci. Model Dev., 8, 3593–3619, https://doi.org/10.5194/gmd-8-3593-2015, https://doi.org/10.5194/gmd-8-3593-2015, 2015
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Predicting the distribution of vegetation under novel climates is important, both to understand how climate change will impact ecosystem services, but also to understand how vegetation changes might affect the carbon, energy and water cycles. Historically, predictions have been heavily dependent upon observations of existing vegetation boundaries. In this paper, we attempt to predict ecosystem boundaries from the ``bottom up'', and illustrate the complexities and promise of this approach.
K. M. Dahlin, R. A. Fisher, and P. J. Lawrence
Biogeosciences, 12, 5061–5074, https://doi.org/10.5194/bg-12-5061-2015, https://doi.org/10.5194/bg-12-5061-2015, 2015
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We compared monthly leaf area index (LAI) estimates from the Community Land Model (CLM) in stress/drought deciduous regions of the world to a satellite-derived estimate of LAI. This comparison revealed an issue in the CLM in which leaves begin to grow during the dry season due to unrealistic soil water movement. We introduced a rainfall trigger to the stress deciduous algorithm to address this issue, then showed the impacts of this change on the fire cycle and stored carbon.
T. Launois, P. Peylin, S. Belviso, and B. Poulter
Atmos. Chem. Phys., 15, 9285–9312, https://doi.org/10.5194/acp-15-9285-2015, https://doi.org/10.5194/acp-15-9285-2015, 2015
B. Poulter, N. MacBean, A. Hartley, I. Khlystova, O. Arino, R. Betts, S. Bontemps, M. Boettcher, C. Brockmann, P. Defourny, S. Hagemann, M. Herold, G. Kirches, C. Lamarche, D. Lederer, C. Ottlé, M. Peters, and P. Peylin
Geosci. Model Dev., 8, 2315–2328, https://doi.org/10.5194/gmd-8-2315-2015, https://doi.org/10.5194/gmd-8-2315-2015, 2015
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Land cover is an essential variable in earth system models and determines conditions driving biogeochemical, energy and water exchange between ecosystems and the atmosphere. A methodology is presented for mapping plant functional types used in global vegetation models from a updated land cover classification system and open-source conversion tool, resulting from a consultative process among map producers and modelers engaged in the European Space Agency’s Land Cover Climate Change Initiative.
L. Molina, G. Broquet, P. Imbach, F. Chevallier, B. Poulter, D. Bonal, B. Burban, M. Ramonet, L. V. Gatti, S. C. Wofsy, J. W. Munger, E. Dlugokencky, and P. Ciais
Atmos. Chem. Phys., 15, 8423–8438, https://doi.org/10.5194/acp-15-8423-2015, https://doi.org/10.5194/acp-15-8423-2015, 2015
D. Zhu, S. S. Peng, P. Ciais, N. Viovy, A. Druel, M. Kageyama, G. Krinner, P. Peylin, C. Ottlé, S. L. Piao, B. Poulter, D. Schepaschenko, and A. Shvidenko
Geosci. Model Dev., 8, 2263–2283, https://doi.org/10.5194/gmd-8-2263-2015, https://doi.org/10.5194/gmd-8-2263-2015, 2015
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This study presents a new parameterization of the vegetation dynamics module in the process-based ecosystem model ORCHIDEE for mid- to high-latitude regions, showing significant improvements in the modeled distribution of tree functional types north of 40°N. A new set of metrics is proposed to quantify the performance of ORCHIDEE, which integrates uncertainties in the observational data sets.
M. A. Rawlins, A. D. McGuire, J. S. Kimball, P. Dass, D. Lawrence, E. Burke, X. Chen, C. Delire, C. Koven, A. MacDougall, S. Peng, A. Rinke, K. Saito, W. Zhang, R. Alkama, T. J. Bohn, P. Ciais, B. Decharme, I. Gouttevin, T. Hajima, D. Ji, G. Krinner, D. P. Lettenmaier, P. Miller, J. C. Moore, B. Smith, and T. Sueyoshi
Biogeosciences, 12, 4385–4405, https://doi.org/10.5194/bg-12-4385-2015, https://doi.org/10.5194/bg-12-4385-2015, 2015
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We used outputs from nine models to better understand land-atmosphere CO2 exchanges across Northern Eurasia over the period 1960-1990. Model estimates were assessed against independent ground and satellite measurements. We find that the models show a weakening of the CO2 sink over time; the models tend to overestimate respiration, causing an underestimate in NEP; the model range in regional NEP is twice the multimodel mean. Residence time for soil carbon decreased, amid a gain in carbon storage.
W. D. Collins, A. P. Craig, J. E. Truesdale, A. V. Di Vittorio, A. D. Jones, B. Bond-Lamberty, K. V. Calvin, J. A. Edmonds, S. H. Kim, A. M. Thomson, P. Patel, Y. Zhou, J. Mao, X. Shi, P. E. Thornton, L. P. Chini, and G. C. Hurtt
Geosci. Model Dev., 8, 2203–2219, https://doi.org/10.5194/gmd-8-2203-2015, https://doi.org/10.5194/gmd-8-2203-2015, 2015
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The integrated Earth system model (iESM) has been developed as a
new tool for projecting the joint human-climate system. The
iESM is based upon coupling an integrated assessment model (IAM)
and an Earth system model (ESM) into a common modeling
infrastructure. By introducing heretofore-omitted
feedbacks between natural and societal drivers in iESM, we can improve
scientific understanding of the human-Earth system
dynamics.
M. J. McGrath, S. Luyssaert, P. Meyfroidt, J. O. Kaplan, M. Bürgi, Y. Chen, K. Erb, U. Gimmi, D. McInerney, K. Naudts, J. Otto, F. Pasztor, J. Ryder, M.-J. Schelhaas, and A. Valade
Biogeosciences, 12, 4291–4316, https://doi.org/10.5194/bg-12-4291-2015, https://doi.org/10.5194/bg-12-4291-2015, 2015
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Studying century-scale ecological processes and their legacy effects requires taking forest management into account. In this study we produce spatially and temporally explicit maps of European forest management from 1600 to 2010. The most important changes between 1600 and 2010 are an increase of 593 000km2 in conifers at the expense of deciduous forest, a 612 000km2 decrease in unmanaged forest, a 152 000km2 decrease in coppice management and a 818 000km2 increase in high stand management.
P. Achakulwisut, L. J. Mickley, L. T. Murray, A. P. K. Tai, J. O. Kaplan, and B. Alexander
Atmos. Chem. Phys., 15, 7977–7998, https://doi.org/10.5194/acp-15-7977-2015, https://doi.org/10.5194/acp-15-7977-2015, 2015
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The atmosphere’s oxidative capacity determines the lifetime of many trace gases important to climate, chemistry, and human health. Yet uncertainties remain about its past variations, its controlling factors, and the radiative forcing of short-lived species it influences. To reduce these uncertainties, we must better quantify the natural emissions and chemical reaction mechanisms of organic compounds in the atmosphere, which play a role in governing the oxidative capacity.
C. Safta, D. M. Ricciuto, K. Sargsyan, B. Debusschere, H. N. Najm, M. Williams, and P. E. Thornton
Geosci. Model Dev., 8, 1899–1918, https://doi.org/10.5194/gmd-8-1899-2015, https://doi.org/10.5194/gmd-8-1899-2015, 2015
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In this paper we propose a probabilistic framework for an uncertainty quantification study of a carbon cycle model and focus on the comparison between steady-state and transient
simulation setups. We study model parameters via global sensitivity analysis and employ a Bayesian approach to calibrate these parameters using NEE observations at the Harvard Forest site. The calibration results are then used to assess the predictive skill of the model via posterior predictive checks.
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.
C. Le Quéré, R. Moriarty, R. M. Andrew, G. P. Peters, P. Ciais, P. Friedlingstein, S. D. Jones, S. Sitch, P. Tans, A. Arneth, T. A. Boden, L. Bopp, Y. Bozec, J. G. Canadell, L. P. Chini, F. Chevallier, C. E. Cosca, I. Harris, M. Hoppema, R. A. Houghton, J. I. House, A. K. Jain, T. Johannessen, E. Kato, R. F. Keeling, V. Kitidis, K. Klein Goldewijk, C. Koven, C. S. Landa, P. Landschützer, A. Lenton, I. D. Lima, G. Marland, J. T. Mathis, N. Metzl, Y. Nojiri, A. Olsen, T. Ono, S. Peng, W. Peters, B. Pfeil, B. Poulter, M. R. Raupach, P. Regnier, C. Rödenbeck, S. Saito, J. E. Salisbury, U. Schuster, J. Schwinger, R. Séférian, J. Segschneider, T. Steinhoff, B. D. Stocker, A. J. Sutton, T. Takahashi, B. Tilbrook, G. R. van der Werf, N. Viovy, Y.-P. Wang, R. Wanninkhof, A. Wiltshire, and N. Zeng
Earth Syst. Sci. Data, 7, 47–85, https://doi.org/10.5194/essd-7-47-2015, https://doi.org/10.5194/essd-7-47-2015, 2015
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Carbon dioxide (CO2) emissions from human activities (burning fossil fuels and cement production, deforestation and other land-use change) are set to rise again in 2014.
This study (updated yearly) makes an accurate assessment of anthropogenic CO2 emissions and their redistribution between the atmosphere, ocean, and terrestrial biosphere in order to better understand the global carbon cycle, support the development of climate policies, and project future climate change.
E. S. Weng, S. Malyshev, J. W. Lichstein, C. E. Farrior, R. Dybzinski, T. Zhang, E. Shevliakova, and S. W. Pacala
Biogeosciences, 12, 2655–2694, https://doi.org/10.5194/bg-12-2655-2015, https://doi.org/10.5194/bg-12-2655-2015, 2015
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We present a model, LM3-PPA, which simulates vegetation dynamics and biogeochemical processes by explicitly scaling from individual plants to ecosystems using the perfect plasticity approximation. It includes height-structured competition for light- and root-allocation-dependent competition for belowground resources. Because of the tractability of the PPA, the coupled LM3-PPA model is able to retain computational tractability, as well as close linkages to mathematically tractable special cases.
K. Lohmann, J. Mignot, H. R. Langehaug, J. H. Jungclaus, D. Matei, O. H. Otterå, Y. Q. Gao, T. L. Mjell, U. S. Ninnemann, and H. F. Kleiven
Clim. Past, 11, 203–216, https://doi.org/10.5194/cp-11-203-2015, https://doi.org/10.5194/cp-11-203-2015, 2015
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We use model simulations to investigate mechanisms of similar Iceland--Scotland overflow (outflow from the Nordic seas) and North Atlantic sea surface temperature variability, suggested from palaeo-reconstructions (Mjell et al., 2015). Our results indicate the influence of Nordic Seas surface temperature on the pressure gradient across the Iceland--Scotland ridge, not a large-scale link through the meridional overturning circulation, is responsible for the (simulated) co-variability.
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
A. Matsikaris, M. Widmann, and J. Jungclaus
Clim. Past, 11, 81–93, https://doi.org/10.5194/cp-11-81-2015, https://doi.org/10.5194/cp-11-81-2015, 2015
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We compare an off-line and an on-line ensemble-based data assimilation method, for the climate of the 17th century. Both schemes perform better than the simulations without DA, and similar skill on the continental and hemispheric scales is found. This indicates either a lack of control of the slow components in our setup or a lack of skill in the information propagation on decadal timescales. The temporal consistency of the analysis in the on-line method makes it generally more preferable.
B. J. Dermody, R. P. H. van Beek, E. Meeks, K. Klein Goldewijk, W. Scheidel, Y. van der Velde, M. F. P. Bierkens, M. J. Wassen, and S. C. Dekker
Hydrol. Earth Syst. Sci., 18, 5025–5040, https://doi.org/10.5194/hess-18-5025-2014, https://doi.org/10.5194/hess-18-5025-2014, 2014
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Our virtual water network of the Roman World shows that virtual water trade and irrigation provided the Romans with resilience to interannual climate variability. Virtual water trade enabled the Romans to meet food demands from regions with a surplus. Irrigation provided stable water supplies for agriculture, particularly in large river catchments. However, virtual water trade also stimulated urbanization and population growth, which eroded Roman resilience to climate variability over time.
A. V. Di Vittorio, L. P. Chini, B. Bond-Lamberty, J. Mao, X. Shi, J. Truesdale, A. Craig, K. Calvin, A. Jones, W. D. Collins, J. Edmonds, G. C. Hurtt, P. Thornton, and A. Thomson
Biogeosciences, 11, 6435–6450, https://doi.org/10.5194/bg-11-6435-2014, https://doi.org/10.5194/bg-11-6435-2014, 2014
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Economic models provide scenarios of land use and greenhouse gas emissions to earth system models to project global change. We found, and partially addressed, inconsistencies in land cover between an economic and an earth system model that effectively alter a prescribed scenario, causing significant differences in projected terrestrial carbon and atmospheric CO2 between prescribed and altered scenarios. We outline a solution to this current problem in scenario-based global change projections.
C. Yue, P. Ciais, P. Cadule, K. Thonicke, S. Archibald, B. Poulter, W. M. Hao, S. Hantson, F. Mouillot, P. Friedlingstein, F. Maignan, and N. Viovy
Geosci. Model Dev., 7, 2747–2767, https://doi.org/10.5194/gmd-7-2747-2014, https://doi.org/10.5194/gmd-7-2747-2014, 2014
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ORCHIDEE-SPITFIRE model could moderately capture the decadal trend and variation of burned area during the 20th century, and the spatial and temporal patterns of contemporary vegetation fires. The model has a better performance in simulating fires for regions dominated by climate-driven fires, such as boreal forests. However, it has limited capability to reproduce the infrequent but important large fires in different ecosystems, where urgent model improvement is needed in the future.
B. Bond-Lamberty, K. Calvin, A. D. Jones, J. Mao, P. Patel, X. Y. Shi, A. Thomson, P. Thornton, and Y. Zhou
Geosci. Model Dev., 7, 2545–2555, https://doi.org/10.5194/gmd-7-2545-2014, https://doi.org/10.5194/gmd-7-2545-2014, 2014
A. Mauri, B. A. S. Davis, P. M. Collins, and J. O. Kaplan
Clim. Past, 10, 1925–1938, https://doi.org/10.5194/cp-10-1925-2014, https://doi.org/10.5194/cp-10-1925-2014, 2014
M. Lee, S. Malyshev, E. Shevliakova, P. C. D. Milly, and P. R. Jaffé
Biogeosciences, 11, 5809–5826, https://doi.org/10.5194/bg-11-5809-2014, https://doi.org/10.5194/bg-11-5809-2014, 2014
J. Deng, C. Li, S. Frolking, Y. Zhang, K. Bäckstrand, and P. Crill
Biogeosciences, 11, 4753–4770, https://doi.org/10.5194/bg-11-4753-2014, https://doi.org/10.5194/bg-11-4753-2014, 2014
J. B. Fisher, M. Sikka, W. C. Oechel, D. N. Huntzinger, J. R. Melton, C. D. Koven, A. Ahlström, M. A. Arain, I. Baker, J. M. Chen, P. Ciais, C. Davidson, M. Dietze, B. El-Masri, D. Hayes, C. Huntingford, A. K. Jain, P. E. Levy, M. R. Lomas, B. Poulter, D. Price, A. K. Sahoo, K. Schaefer, H. Tian, E. Tomelleri, H. Verbeeck, N. Viovy, R. Wania, N. Zeng, and C. E. Miller
Biogeosciences, 11, 4271–4288, https://doi.org/10.5194/bg-11-4271-2014, https://doi.org/10.5194/bg-11-4271-2014, 2014
M. I. Hejazi, J. Edmonds, L. Clarke, P. Kyle, E. Davies, V. Chaturvedi, M. Wise, P. Patel, J. Eom, and K. Calvin
Hydrol. Earth Syst. Sci., 18, 2859–2883, https://doi.org/10.5194/hess-18-2859-2014, https://doi.org/10.5194/hess-18-2859-2014, 2014
Z. M. Subin, P. C. D. Milly, B. N. Sulman, S. Malyshev, and E. Shevliakova
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hessd-11-8443-2014, https://doi.org/10.5194/hessd-11-8443-2014, 2014
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We provide a framework for including the effects of fine-scale hydrology on biogeochemistry in Earth-system models (ESMs). We simulate a representative hillslope in each ESM grid cell. While including the hillslope does not change the average hydrology, it causes greater vegetation and soil carbon to accumulate in lowlands. This is important for understanding how soil carbon might be affected by climate change, particularly in wetlands.
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
C. Le Quéré, G. P. Peters, R. J. Andres, R. M. Andrew, T. A. Boden, P. Ciais, P. Friedlingstein, R. A. Houghton, G. Marland, R. Moriarty, S. Sitch, P. Tans, A. Arneth, A. Arvanitis, D. C. E. Bakker, L. Bopp, J. G. Canadell, L. P. Chini, S. C. Doney, A. Harper, I. Harris, J. I. House, A. K. Jain, S. D. Jones, E. Kato, R. F. Keeling, K. Klein Goldewijk, A. Körtzinger, C. Koven, N. Lefèvre, F. Maignan, A. Omar, T. Ono, G.-H. Park, B. Pfeil, B. Poulter, M. R. Raupach, P. Regnier, C. Rödenbeck, S. Saito, J. Schwinger, J. Segschneider, B. D. Stocker, T. Takahashi, B. Tilbrook, S. van Heuven, N. Viovy, R. Wanninkhof, A. Wiltshire, and S. Zaehle
Earth Syst. Sci. Data, 6, 235–263, https://doi.org/10.5194/essd-6-235-2014, https://doi.org/10.5194/essd-6-235-2014, 2014
M. Balzarolo, S. Boussetta, G. Balsamo, A. Beljaars, F. Maignan, J.-C. Calvet, S. Lafont, A. Barbu, B. Poulter, F. Chevallier, C. Szczypta, and D. Papale
Biogeosciences, 11, 2661–2678, https://doi.org/10.5194/bg-11-2661-2014, https://doi.org/10.5194/bg-11-2661-2014, 2014
K. E. O. Todd-Brown, J. T. Randerson, F. Hopkins, V. Arora, T. Hajima, C. Jones, E. Shevliakova, J. Tjiputra, E. Volodin, T. Wu, Q. Zhang, and S. D. Allison
Biogeosciences, 11, 2341–2356, https://doi.org/10.5194/bg-11-2341-2014, https://doi.org/10.5194/bg-11-2341-2014, 2014
K. Lohmann, J. H. Jungclaus, D. Matei, J. Mignot, M. Menary, H. R. Langehaug, J. Ba, Y. Gao, O. H. Otterå, W. Park, and S. Lorenz
Ocean Sci., 10, 227–241, https://doi.org/10.5194/os-10-227-2014, https://doi.org/10.5194/os-10-227-2014, 2014
L. T. Murray, L. J. Mickley, J. O. Kaplan, E. D. Sofen, M. Pfeiffer, and B. Alexander
Atmos. Chem. Phys., 14, 3589–3622, https://doi.org/10.5194/acp-14-3589-2014, https://doi.org/10.5194/acp-14-3589-2014, 2014
X. Yang, P. E. Thornton, D. M. Ricciuto, and W. M. Post
Biogeosciences, 11, 1667–1681, https://doi.org/10.5194/bg-11-1667-2014, https://doi.org/10.5194/bg-11-1667-2014, 2014
G. Strandberg, E. Kjellström, A. Poska, S. Wagner, M.-J. Gaillard, A.-K. Trondman, A. Mauri, B. A. S. Davis, J. O. Kaplan, H. J. B. Birks, A. E. Bjune, R. Fyfe, T. Giesecke, L. Kalnina, M. Kangur, W. O. van der Knaap, U. Kokfelt, P. Kuneš, M. Lata\l owa, L. Marquer, F. Mazier, A. B. Nielsen, B. Smith, H. Seppä, and S. Sugita
Clim. Past, 10, 661–680, https://doi.org/10.5194/cp-10-661-2014, https://doi.org/10.5194/cp-10-661-2014, 2014
C. R. Schwalm, D. N. Huntinzger, R. B. Cook, Y. Wei, I. T. Baker, R. P. Neilson, B. Poulter, P. Caldwell, G. Sun, H. Q. Tian, and N. Zeng
Biogeosciences Discuss., https://doi.org/10.5194/bgd-11-1801-2014, https://doi.org/10.5194/bgd-11-1801-2014, 2014
Revised manuscript not accepted
D. N. Huntzinger, C. Schwalm, A. M. Michalak, K. Schaefer, A. W. King, Y. Wei, A. Jacobson, S. Liu, R. B. Cook, W. M. Post, G. Berthier, D. Hayes, M. Huang, A. Ito, H. Lei, C. Lu, J. Mao, C. H. Peng, S. Peng, B. Poulter, D. Riccuito, X. Shi, H. Tian, W. Wang, N. Zeng, F. Zhao, and Q. Zhu
Geosci. Model Dev., 6, 2121–2133, https://doi.org/10.5194/gmd-6-2121-2013, https://doi.org/10.5194/gmd-6-2121-2013, 2013
C. Yue, P. Ciais, S. Luyssaert, P. Cadule, J. Harden, J. Randerson, V. Bellassen, T. Wang, S. L. Piao, B. Poulter, and N. Viovy
Biogeosciences, 10, 8233–8252, https://doi.org/10.5194/bg-10-8233-2013, https://doi.org/10.5194/bg-10-8233-2013, 2013
T. Hoffmann, S. M. Mudd, K. van Oost, G. Verstraeten, G. Erkens, A. Lang, H. Middelkoop, J. Boyle, J. O. Kaplan, J. Willenbring, and R. Aalto
Earth Surf. Dynam., 1, 45–52, https://doi.org/10.5194/esurf-1-45-2013, https://doi.org/10.5194/esurf-1-45-2013, 2013
C. Ottlé, J. Lescure, F. Maignan, B. Poulter, T. Wang, and N. Delbart
Earth Syst. Sci. Data, 5, 331–348, https://doi.org/10.5194/essd-5-331-2013, https://doi.org/10.5194/essd-5-331-2013, 2013
C. D. Koven, W. J. Riley, Z. M. Subin, J. Y. Tang, M. S. Torn, W. D. Collins, G. B. Bonan, D. M. Lawrence, and S. C. Swenson
Biogeosciences, 10, 7109–7131, https://doi.org/10.5194/bg-10-7109-2013, https://doi.org/10.5194/bg-10-7109-2013, 2013
O. Bothe, J. H. Jungclaus, and D. Zanchettin
Clim. Past, 9, 2471–2487, https://doi.org/10.5194/cp-9-2471-2013, https://doi.org/10.5194/cp-9-2471-2013, 2013
P. C. Stoy, M. C. Dietze, A. D. Richardson, R. Vargas, A. G. Barr, R. S. Anderson, M. A. Arain, I. T. Baker, T. A. Black, J. M. Chen, R. B. Cook, C. M. Gough, R. F. Grant, D. Y. Hollinger, R. C. Izaurralde, C. J. Kucharik, P. Lafleur, B. E. Law, S. Liu, E. Lokupitiya, Y. Luo, J. W. Munger, C. Peng, B. Poulter, D. T. Price, D. M. Ricciuto, W. J. Riley, A. K. Sahoo, K. Schaefer, C. R. Schwalm, H. Tian, H. Verbeeck, and E. Weng
Biogeosciences, 10, 6893–6909, https://doi.org/10.5194/bg-10-6893-2013, https://doi.org/10.5194/bg-10-6893-2013, 2013
Q. Zhang, A. J. Pitman, Y. P. Wang, Y. J. Dai, and P. J. Lawrence
Earth Syst. Dynam., 4, 333–345, https://doi.org/10.5194/esd-4-333-2013, https://doi.org/10.5194/esd-4-333-2013, 2013
M. Scherstjanoi, J. O. Kaplan, E. Thürig, and H. Lischke
Geosci. Model Dev., 6, 1517–1542, https://doi.org/10.5194/gmd-6-1517-2013, https://doi.org/10.5194/gmd-6-1517-2013, 2013
V. Beck, C. Gerbig, T. Koch, M. M. Bela, K. M. Longo, S. R. Freitas, J. O. Kaplan, C. Prigent, P. Bergamaschi, and M. Heimann
Atmos. Chem. Phys., 13, 7961–7982, https://doi.org/10.5194/acp-13-7961-2013, https://doi.org/10.5194/acp-13-7961-2013, 2013
N. Hanasaki, S. Fujimori, T. Yamamoto, S. Yoshikawa, Y. Masaki, Y. Hijioka, M. Kainuma, Y. Kanamori, T. Masui, K. Takahashi, and S. Kanae
Hydrol. Earth Syst. Sci., 17, 2375–2391, https://doi.org/10.5194/hess-17-2375-2013, https://doi.org/10.5194/hess-17-2375-2013, 2013
N. Hanasaki, S. Fujimori, T. Yamamoto, S. Yoshikawa, Y. Masaki, Y. Hijioka, M. Kainuma, Y. Kanamori, T. Masui, K. Takahashi, and S. Kanae
Hydrol. Earth Syst. Sci., 17, 2393–2413, https://doi.org/10.5194/hess-17-2393-2013, https://doi.org/10.5194/hess-17-2393-2013, 2013
M. Pfeiffer, A. Spessa, and J. O. Kaplan
Geosci. Model Dev., 6, 643–685, https://doi.org/10.5194/gmd-6-643-2013, https://doi.org/10.5194/gmd-6-643-2013, 2013
O. Bothe, J. H. Jungclaus, D. Zanchettin, and E. Zorita
Clim. Past, 9, 1089–1110, https://doi.org/10.5194/cp-9-1089-2013, https://doi.org/10.5194/cp-9-1089-2013, 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
C. Le Quéré, R. J. Andres, T. Boden, T. Conway, R. A. Houghton, J. I. House, G. Marland, G. P. Peters, G. R. van der Werf, A. Ahlström, R. M. Andrew, L. Bopp, J. G. Canadell, P. Ciais, S. C. Doney, C. Enright, P. Friedlingstein, C. Huntingford, A. K. Jain, C. Jourdain, E. Kato, R. F. Keeling, K. Klein Goldewijk, S. Levis, P. Levy, M. Lomas, B. Poulter, M. R. Raupach, J. Schwinger, S. Sitch, B. D. Stocker, N. Viovy, S. Zaehle, and N. Zeng
Earth Syst. Sci. Data, 5, 165–185, https://doi.org/10.5194/essd-5-165-2013, https://doi.org/10.5194/essd-5-165-2013, 2013
N. A. Rosenbloom, B. L. Otto-Bliesner, E. C. Brady, and P. J. Lawrence
Geosci. Model Dev., 6, 549–561, https://doi.org/10.5194/gmd-6-549-2013, https://doi.org/10.5194/gmd-6-549-2013, 2013
X. Yang, W. M. Post, P. E. Thornton, and A. Jain
Biogeosciences, 10, 2525–2537, https://doi.org/10.5194/bg-10-2525-2013, https://doi.org/10.5194/bg-10-2525-2013, 2013
M. I. Hejazi, J. Edmonds, L. Clarke, P. Kyle, E. Davies, V. Chaturvedi, J. Eom, M. Wise, P. Patel, and K. Calvin
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hessd-10-3383-2013, https://doi.org/10.5194/hessd-10-3383-2013, 2013
Revised manuscript has not been submitted
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
T. W. Hudiburg, B. E. Law, and P. E. Thornton
Biogeosciences, 10, 453–470, https://doi.org/10.5194/bg-10-453-2013, https://doi.org/10.5194/bg-10-453-2013, 2013
S. Tietsche, D. Notz, J. H. Jungclaus, and J. Marotzke
Ocean Sci., 9, 19–36, https://doi.org/10.5194/os-9-19-2013, https://doi.org/10.5194/os-9-19-2013, 2013
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Evaluation of CMIP6 model simulations of PM2.5 and its components over China
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Carl Svenhag, Moa K. Sporre, Tinja Olenius, Daniel Yazgi, Sara M. Blichner, Lars P. Nieradzik, and Pontus Roldin
Geosci. Model Dev., 17, 4923–4942, https://doi.org/10.5194/gmd-17-4923-2024, https://doi.org/10.5194/gmd-17-4923-2024, 2024
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Our research shows the importance of modeling new particle formation (NPF) and growth of particles in the atmosphere on a global scale, as they influence the outcomes of clouds and our climate. With the global model EC-Earth3 we show that using a new method for NPF modeling, which includes new detailed processes with NH3 and H2SO4, significantly impacts the number of particles in the air and clouds and changes the radiation balance of the same magnitude as anthropogenic greenhouse emissions.
Mengjie Han, Qing Zhao, Xili Wang, Ying-Ping Wang, Philippe Ciais, Haicheng Zhang, Daniel S. Goll, Lei Zhu, Zhe Zhao, Zhixuan Guo, Chen Wang, Wei Zhuang, Fengchang Wu, and Wei Li
Geosci. Model Dev., 17, 4871–4890, https://doi.org/10.5194/gmd-17-4871-2024, https://doi.org/10.5194/gmd-17-4871-2024, 2024
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The impact of biochar (BC) on soil organic carbon (SOC) dynamics is not represented in most land carbon models used for assessing land-based climate change mitigation. Our study develops a BC model that incorporates our current understanding of BC effects on SOC based on a soil carbon model (MIMICS). The BC model can reproduce the SOC changes after adding BC, providing a useful tool to couple dynamic land models to evaluate the effectiveness of BC application for CO2 removal from the atmosphere.
Kalyn Dorheim, Skylar Gering, Robert Gieseke, Corinne Hartin, Leeya Pressburger, Alexey N. Shiklomanov, Steven J. Smith, Claudia Tebaldi, Dawn L. Woodard, and Ben Bond-Lamberty
Geosci. Model Dev., 17, 4855–4869, https://doi.org/10.5194/gmd-17-4855-2024, https://doi.org/10.5194/gmd-17-4855-2024, 2024
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Hector is an easy-to-use, global climate–carbon cycle model. With its quick run time, Hector can provide climate information from a run in a fraction of a second. Hector models on a global and annual basis. Here, we present an updated version of the model, Hector V3. In this paper, we document Hector’s new features. Hector V3 is capable of reproducing historical observations, and its future temperature projections are consistent with those of more complex models.
Fangxuan Ren, Jintai Lin, Chenghao Xu, Jamiu A. Adeniran, Jingxu Wang, Randall V. Martin, Aaron van Donkelaar, Melanie S. Hammer, Larry W. Horowitz, Steven T. Turnock, Naga Oshima, Jie Zhang, Susanne Bauer, Kostas Tsigaridis, Øyvind Seland, Pierre Nabat, David Neubauer, Gary Strand, Twan van Noije, Philippe Le Sager, and Toshihiko Takemura
Geosci. Model Dev., 17, 4821–4836, https://doi.org/10.5194/gmd-17-4821-2024, https://doi.org/10.5194/gmd-17-4821-2024, 2024
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We evaluate the performance of 14 CMIP6 ESMs in simulating total PM2.5 and its 5 components over China during 2000–2014. PM2.5 and its components are underestimated in almost all models, except that black carbon (BC) and sulfate are overestimated in two models, respectively. The underestimation is the largest for organic carbon (OC) and the smallest for BC. Models reproduce the observed spatial pattern for OC, sulfate, nitrate and ammonium well, yet the agreement is poorer for BC.
Yi Xi, Chunjing Qiu, Yuan Zhang, Dan Zhu, Shushi Peng, Gustaf Hugelius, Jinfeng Chang, Elodie Salmon, and Philippe Ciais
Geosci. Model Dev., 17, 4727–4754, https://doi.org/10.5194/gmd-17-4727-2024, https://doi.org/10.5194/gmd-17-4727-2024, 2024
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The ORCHIDEE-MICT model can simulate the carbon cycle and hydrology at a sub-grid scale but energy budgets only at a grid scale. This paper assessed the implementation of a multi-tiling energy budget approach in ORCHIDEE-MICT and found warmer surface and soil temperatures, higher soil moisture, and more soil organic carbon across the Northern Hemisphere compared with the original version.
Georgia Lazoglou, Theo Economou, Christina Anagnostopoulou, George Zittis, Anna Tzyrkalli, Pantelis Georgiades, and Jos Lelieveld
Geosci. Model Dev., 17, 4689–4703, https://doi.org/10.5194/gmd-17-4689-2024, https://doi.org/10.5194/gmd-17-4689-2024, 2024
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This study focuses on the important issue of the drizzle bias effect in regional climate models, described by an over-prediction of the number of rainy days while underestimating associated precipitation amounts. For this purpose, two distinct methodologies are applied and rigorously evaluated. These results are encouraging for using the multivariate machine learning method random forest to increase the accuracy of climate models concerning the projection of the number of wet days.
Xu Yue, Hao Zhou, Chenguang Tian, Yimian Ma, Yihan Hu, Cheng Gong, Hui Zheng, and Hong Liao
Geosci. Model Dev., 17, 4621–4642, https://doi.org/10.5194/gmd-17-4621-2024, https://doi.org/10.5194/gmd-17-4621-2024, 2024
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We develop the interactive Model for Air Pollution and Land Ecosystems (iMAPLE). The model considers the full coupling between carbon and water cycles, dynamic fire emissions, wetland methane emissions, biogenic volatile organic compound emissions, and trait-based ozone vegetation damage. Evaluations show that iMAPLE is a useful tool for the study of the interactions among climate, chemistry, and ecosystems.
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”.
Ross Mower, Ethan D. Gutmann, Glen E. Liston, Jessica Lundquist, and Soren Rasmussen
Geosci. Model Dev., 17, 4135–4154, https://doi.org/10.5194/gmd-17-4135-2024, https://doi.org/10.5194/gmd-17-4135-2024, 2024
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Higher-resolution model simulations are better at capturing winter snowpack changes across space and time. However, increasing resolution also increases the computational requirements. This work provides an overview of changes made to a distributed snow-evolution modeling system (SnowModel) to allow it to leverage high-performance computing resources. Continental simulations that were previously estimated to take 120 d can now be performed in 5 h.
Jiaxu Guo, Juepeng Zheng, Yidan Xu, Haohuan Fu, Wei Xue, Lanning Wang, Lin Gan, Ping Gao, Wubing Wan, Xianwei Wu, Zhitao Zhang, Liang Hu, Gaochao Xu, and Xilong Che
Geosci. Model Dev., 17, 3975–3992, https://doi.org/10.5194/gmd-17-3975-2024, https://doi.org/10.5194/gmd-17-3975-2024, 2024
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To enhance the efficiency of experiments using SCAM, we train a learning-based surrogate model to facilitate large-scale sensitivity analysis and tuning of combinations of multiple parameters. Employing a hybrid method, we investigate the joint sensitivity of multi-parameter combinations across typical cases, identifying the most sensitive three-parameter combination out of 11. Subsequently, we conduct a tuning process aimed at reducing output errors in these cases.
Yung-Yao Lan, Huang-Hsiung Hsu, and Wan-Ling Tseng
Geosci. Model Dev., 17, 3897–3918, https://doi.org/10.5194/gmd-17-3897-2024, https://doi.org/10.5194/gmd-17-3897-2024, 2024
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This study uses the CAM5–SIT coupled model to investigate the effects of SST feedback frequency on the MJO simulations with intervals at 30 min, 1, 3, 6, 12, 18, 24, and 30 d. The simulations become increasingly unrealistic as the frequency of the SST feedback decreases. Our results suggest that more spontaneous air--sea interaction (e.g., ocean response within 3 d in this study) with high vertical resolution in the ocean model is key to the realistic simulation of the MJO.
Jiwoo Lee, Peter J. Gleckler, Min-Seop Ahn, Ana Ordonez, Paul A. Ullrich, Kenneth R. Sperber, Karl E. Taylor, Yann Y. Planton, Eric Guilyardi, Paul Durack, Celine Bonfils, Mark D. Zelinka, Li-Wei Chao, Bo Dong, Charles Doutriaux, Chengzhu Zhang, Tom Vo, Jason Boutte, Michael F. Wehner, Angeline G. Pendergrass, Daehyun Kim, Zeyu Xue, Andrew T. Wittenberg, and John Krasting
Geosci. Model Dev., 17, 3919–3948, https://doi.org/10.5194/gmd-17-3919-2024, https://doi.org/10.5194/gmd-17-3919-2024, 2024
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We introduce an open-source software, the PCMDI Metrics Package (PMP), developed for a comprehensive comparison of Earth system models (ESMs) with real-world observations. Using diverse metrics evaluating climatology, variability, and extremes simulated in thousands of simulations from the Coupled Model Intercomparison Project (CMIP), PMP aids in benchmarking model improvements across generations. PMP also enables efficient tracking of performance evolutions during ESM developments.
Haoyue Zuo, Yonggang Liu, Gaojun Li, Zhifang Xu, Liang Zhao, Zhengtang Guo, and Yongyun Hu
Geosci. Model Dev., 17, 3949–3974, https://doi.org/10.5194/gmd-17-3949-2024, https://doi.org/10.5194/gmd-17-3949-2024, 2024
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Compared to the silicate weathering fluxes measured at large river basins, the current models tend to systematically overestimate the fluxes over the tropical region, which leads to an overestimation of the global total weathering flux. The most possible cause of such bias is found to be the overestimation of tropical surface erosion, which indicates that the tropical vegetation likely slows down physical erosion significantly. We propose a way of taking this effect into account in models.
Quentin Pikeroen, Didier Paillard, and Karine Watrin
Geosci. Model Dev., 17, 3801–3814, https://doi.org/10.5194/gmd-17-3801-2024, https://doi.org/10.5194/gmd-17-3801-2024, 2024
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All accurate climate models use equations with poorly defined parameters, where knobs for the parameters are turned to fit the observations. This process is called tuning. In this article, we use another paradigm. We use a thermodynamic hypothesis, the maximum entropy production, to compute temperatures, energy fluxes, and precipitation, where tuning is impossible. For now, the 1D vertical model is used for a tropical atmosphere. The correct order of magnitude of precipitation is computed.
Jishi Zhang, Peter Bogenschutz, Qi Tang, Philip Cameron-smith, and Chengzhu Zhang
Geosci. Model Dev., 17, 3687–3731, https://doi.org/10.5194/gmd-17-3687-2024, https://doi.org/10.5194/gmd-17-3687-2024, 2024
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We developed a regionally refined climate model that allows resolved convection and performed a 20-year projection to the end of the century. The model has a resolution of 3.25 km in California, which allows us to predict climate with unprecedented accuracy, and a resolution of 100 km for the rest of the globe to achieve efficient, self-consistent simulations. The model produces superior results in reproducing climate patterns over California that typical modern climate models cannot resolve.
Xiaohui Zhong, Xing Yu, and Hao Li
Geosci. Model Dev., 17, 3667–3685, https://doi.org/10.5194/gmd-17-3667-2024, https://doi.org/10.5194/gmd-17-3667-2024, 2024
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In order to forecast localized warm-sector rainfall in the south China region, numerical weather prediction models are being run with finer grid spacing. The conventional convection parameterization (CP) performs poorly in the gray zone, necessitating the development of a scale-aware scheme. We propose a machine learning (ML) model to replace the scale-aware CP scheme. Evaluation against the original CP scheme has shown that the ML-based CP scheme can provide accurate and reliable predictions.
Taufiq Hassan, Kai Zhang, Jianfeng Li, Balwinder Singh, Shixuan Zhang, Hailong Wang, and Po-Lun Ma
Geosci. Model Dev., 17, 3507–3532, https://doi.org/10.5194/gmd-17-3507-2024, https://doi.org/10.5194/gmd-17-3507-2024, 2024
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Anthropogenic aerosol emissions are an essential part of global aerosol models. Significant errors can exist from the loss of emission heterogeneity. We introduced an emission treatment that significantly improved aerosol emission heterogeneity in high-resolution model simulations, with improvements in simulated aerosol surface concentrations. The emission treatment will provide a more accurate representation of aerosol emissions and their effects on climate.
Feng Zhu, Julien Emile-Geay, Gregory J. Hakim, Dominique Guillot, Deborah Khider, Robert Tardif, and Walter A. Perkins
Geosci. Model Dev., 17, 3409–3431, https://doi.org/10.5194/gmd-17-3409-2024, https://doi.org/10.5194/gmd-17-3409-2024, 2024
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Climate field reconstruction encompasses methods that estimate the evolution of climate in space and time based on natural archives. It is useful to investigate climate variations and validate climate models, but its implementation and use can be difficult for non-experts. This paper introduces a user-friendly Python package called cfr to make these methods more accessible, thanks to the computational and visualization tools that facilitate efficient and reproducible research on past climates.
Rose V. Palermo, J. Taylor Perron, Jason M. Soderblom, Samuel P. D. Birch, Alexander G. Hayes, and Andrew D. Ashton
Geosci. Model Dev., 17, 3433–3445, https://doi.org/10.5194/gmd-17-3433-2024, https://doi.org/10.5194/gmd-17-3433-2024, 2024
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Models of rocky coastal erosion help us understand the controls on coastal morphology and evolution. In this paper, we present a simplified model of coastline erosion driven by either uniform erosion where coastline erosion is constant or wave-driven erosion where coastline erosion is a function of the wave power. This model can be used to evaluate how coastline changes reflect climate, sea-level history, material properties, and the relative influence of different erosional processes.
Safae Oumami, Joaquim Arteta, Vincent Guidard, Pierre Tulet, and Paul David Hamer
Geosci. Model Dev., 17, 3385–3408, https://doi.org/10.5194/gmd-17-3385-2024, https://doi.org/10.5194/gmd-17-3385-2024, 2024
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In this paper, we coupled the SURFEX and MEGAN models. The aim of this coupling is to improve the estimation of biogenic fluxes by using the SURFEX canopy environment model. The coupled model results were validated and several sensitivity tests were performed. The coupled-model total annual isoprene flux is 442 Tg; this value is within the range of other isoprene estimates reported. The ultimate aim of this coupling is to predict the impact of climate change on biogenic emissions.
Lars Ackermann, Thomas Rackow, Kai Himstedt, Paul Gierz, Gregor Knorr, and Gerrit Lohmann
Geosci. Model Dev., 17, 3279–3301, https://doi.org/10.5194/gmd-17-3279-2024, https://doi.org/10.5194/gmd-17-3279-2024, 2024
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We present long-term simulations with interactive icebergs in the Southern Ocean. By melting, icebergs reduce the temperature and salinity of the surrounding ocean. In our simulations, we find that this cooling effect of iceberg melting is not limited to the surface ocean but also reaches the deep ocean and propagates northward into all ocean basins. Additionally, the formation of deep-water masses in the Southern Ocean is enhanced.
Nanhong Xie, Tijian Wang, Xiaodong Xie, Xu Yue, Filippo Giorgi, Qian Zhang, Danyang Ma, Rong Song, Beiyao Xu, Shu Li, Bingliang Zhuang, Mengmeng Li, Min Xie, Natalya Andreeva Kilifarska, Georgi Gadzhev, and Reneta Dimitrova
Geosci. Model Dev., 17, 3259–3277, https://doi.org/10.5194/gmd-17-3259-2024, https://doi.org/10.5194/gmd-17-3259-2024, 2024
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For the first time, we coupled a regional climate chemistry model, RegCM-Chem, with a dynamic vegetation model, YIBs, to create a regional climate–chemistry–ecology model, RegCM-Chem–YIBs. We applied it to simulate climatic, chemical, and ecological parameters in East Asia and fully validated it on a variety of observational data. Results show that RegCM-Chem–YIBs model is a valuable tool for studying the terrestrial carbon cycle, atmospheric chemistry, and climate change on a regional scale.
Bryce E. Harrop, Jian Lu, L. Ruby Leung, William K. M. Lau, Kyu-Myong Kim, Brian Medeiros, Brian J. Soden, Gabriel A. Vecchi, Bosong Zhang, and Balwinder Singh
Geosci. Model Dev., 17, 3111–3135, https://doi.org/10.5194/gmd-17-3111-2024, https://doi.org/10.5194/gmd-17-3111-2024, 2024
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Seven new experimental setups designed to interfere with cloud radiative heating have been added to the Energy Exascale Earth System Model (E3SM). These experiments include both those that test the mean impact of cloud radiative heating and those examining its covariance with circulations. This paper documents the code changes and steps needed to run these experiments. Results corroborate prior findings for how cloud radiative heating impacts circulations and rainfall patterns.
Mario C. Acosta, Sergi Palomas, Stella V. Paronuzzi Ticco, Gladys Utrera, Joachim Biercamp, Pierre-Antoine Bretonniere, Reinhard Budich, Miguel Castrillo, Arnaud Caubel, Francisco Doblas-Reyes, Italo Epicoco, Uwe Fladrich, Sylvie Joussaume, Alok Kumar Gupta, Bryan Lawrence, Philippe Le Sager, Grenville Lister, Marie-Pierre Moine, Jean-Christophe Rioual, Sophie Valcke, Niki Zadeh, and Venkatramani Balaji
Geosci. Model Dev., 17, 3081–3098, https://doi.org/10.5194/gmd-17-3081-2024, https://doi.org/10.5194/gmd-17-3081-2024, 2024
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We present a collection of performance metrics gathered during the Coupled Model Intercomparison Project Phase 6 (CMIP6), a worldwide initiative to study climate change. We analyse the metrics that resulted from collaboration efforts among many partners and models and describe our findings to demonstrate the utility of our study for the scientific community. The research contributes to understanding climate modelling performance on the current high-performance computing (HPC) architectures.
Sabine Doktorowski, Jan Kretzschmar, Johannes Quaas, Marc Salzmann, and Odran Sourdeval
Geosci. Model Dev., 17, 3099–3110, https://doi.org/10.5194/gmd-17-3099-2024, https://doi.org/10.5194/gmd-17-3099-2024, 2024
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Especially over the midlatitudes, precipitation is mainly formed via the ice phase. In this study we focus on the initial snow formation process in the ICON-AES, the aggregation process. We use a stochastical approach for the aggregation parameterization and investigate the influence in the ICON-AES. Therefore, a distribution function of cloud ice is created, which is evaluated with satellite data. The new approach leads to cloud ice loss and an improvement in the process rate bias.
Katie R. Blackford, Matthew Kasoar, Chantelle Burton, Eleanor Burke, Iain Colin Prentice, and Apostolos Voulgarakis
Geosci. Model Dev., 17, 3063–3079, https://doi.org/10.5194/gmd-17-3063-2024, https://doi.org/10.5194/gmd-17-3063-2024, 2024
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Peatlands are globally important stores of carbon which are being increasingly threatened by wildfires with knock-on effects on the climate system. Here we introduce a novel peat fire parameterization in the northern high latitudes to the INFERNO global fire model. Representing peat fires increases annual burnt area across the high latitudes, alongside improvements in how we capture year-to-year variation in burning and emissions.
Pengfei Shi, L. Ruby Leung, Bin Wang, Kai Zhang, Samson M. Hagos, and Shixuan Zhang
Geosci. Model Dev., 17, 3025–3040, https://doi.org/10.5194/gmd-17-3025-2024, https://doi.org/10.5194/gmd-17-3025-2024, 2024
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Improving climate predictions have profound socio-economic impacts. This study introduces a new weakly coupled land data assimilation (WCLDA) system for a coupled climate model. We demonstrate improved simulation of soil moisture and temperature in many global regions and throughout the soil layers. Furthermore, significant improvements are also found in reproducing the time evolution of the 2012 US Midwest drought. The WCLDA system provides the groundwork for future predictability studies.
Justin Peter, Elisabeth Vogel, Wendy Sharples, Ulrike Bende-Michl, Louise Wilson, Pandora Hope, Andrew Dowdy, Greg Kociuba, Sri Srikanthan, Vi Co Duong, Jake Roussis, Vjekoslav Matic, Zaved Khan, Alison Oke, Margot Turner, Stuart Baron-Hay, Fiona Johnson, Raj Mehrotra, Ashish Sharma, Marcus Thatcher, Ali Azarvinand, Steven Thomas, Ghyslaine Boschat, Chantal Donnelly, and Robert Argent
Geosci. Model Dev., 17, 2755–2781, https://doi.org/10.5194/gmd-17-2755-2024, https://doi.org/10.5194/gmd-17-2755-2024, 2024
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We detail the production of datasets and communication to end users of high-resolution projections of rainfall, runoff, and soil moisture for the entire Australian continent. This is important as previous projections for Australia were for small regions and used differing techniques for their projections, making comparisons difficult across Australia's varied climate zones. The data will be beneficial for research purposes and to aid adaptation to climate change.
Daniele Visioni, Alan Robock, Jim Haywood, Matthew Henry, Simone Tilmes, Douglas G. MacMartin, Ben Kravitz, Sarah J. Doherty, John Moore, Chris Lennard, Shingo Watanabe, Helene Muri, Ulrike Niemeier, Olivier Boucher, Abu Syed, Temitope S. Egbebiyi, Roland Séférian, and Ilaria Quaglia
Geosci. Model Dev., 17, 2583–2596, https://doi.org/10.5194/gmd-17-2583-2024, https://doi.org/10.5194/gmd-17-2583-2024, 2024
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This paper describes a new experimental protocol for the Geoengineering Model Intercomparison Project (GeoMIP). In it, we describe the details of a new simulation of sunlight reflection using the stratospheric aerosols that climate models are supposed to run, and we explain the reasons behind each choice we made when defining the protocol.
Jose Rafael Guarin, Jonas Jägermeyr, Elizabeth A. Ainsworth, Fabio A. A. Oliveira, Senthold Asseng, Kenneth Boote, Joshua Elliott, Lisa Emberson, Ian Foster, Gerrit Hoogenboom, David Kelly, Alex C. Ruane, and Katrina Sharps
Geosci. Model Dev., 17, 2547–2567, https://doi.org/10.5194/gmd-17-2547-2024, https://doi.org/10.5194/gmd-17-2547-2024, 2024
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The effects of ozone (O3) stress on crop photosynthesis and leaf senescence were added to maize, rice, soybean, and wheat crop models. The modified models reproduced growth and yields under different O3 levels measured in field experiments and reported in the literature. The combined interactions between O3 and additional stresses were reproduced with the new models. These updated crop models can be used to simulate impacts of O3 stress under future climate change and air pollution scenarios.
Jiachen Lu, Negin Nazarian, Melissa Anne Hart, E. Scott Krayenhoff, and Alberto Martilli
Geosci. Model Dev., 17, 2525–2545, https://doi.org/10.5194/gmd-17-2525-2024, https://doi.org/10.5194/gmd-17-2525-2024, 2024
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This study enhances urban canopy models by refining key assumptions. Simulations for various urban scenarios indicate discrepancies in turbulent transport efficiency for flow properties. We propose two modifications that involve characterizing diffusion coefficients for momentum and turbulent kinetic energy separately and introducing a physics-based
mass-fluxterm. These adjustments enhance the model's performance, offering more reliable temperature and surface flux estimates.
Justin L. Willson, Kevin A. Reed, Christiane Jablonowski, James Kent, Peter H. Lauritzen, Ramachandran Nair, Mark A. Taylor, Paul A. Ullrich, Colin M. Zarzycki, David M. Hall, Don Dazlich, Ross Heikes, Celal Konor, David Randall, Thomas Dubos, Yann Meurdesoif, Xi Chen, Lucas Harris, Christian Kühnlein, Vivian Lee, Abdessamad Qaddouri, Claude Girard, Marco Giorgetta, Daniel Reinert, Hiroaki Miura, Tomoki Ohno, and Ryuji Yoshida
Geosci. Model Dev., 17, 2493–2507, https://doi.org/10.5194/gmd-17-2493-2024, https://doi.org/10.5194/gmd-17-2493-2024, 2024
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Accurate simulation of tropical cyclones (TCs) is essential to understanding their behavior in a changing climate. One way this is accomplished is through model intercomparison projects, where results from multiple climate models are analyzed to provide benchmark solutions for the wider climate modeling community. This study describes and analyzes the previously developed TC test case for nine climate models in an intercomparison project, providing solutions that aid in model development.
Stephanie Fiedler, Vaishali Naik, Fiona M. O'Connor, Christopher J. Smith, Paul Griffiths, Ryan J. Kramer, Toshihiko Takemura, Robert J. Allen, Ulas Im, Matthew Kasoar, Angshuman Modak, Steven Turnock, Apostolos Voulgarakis, Duncan Watson-Parris, Daniel M. Westervelt, Laura J. Wilcox, Alcide Zhao, William J. Collins, Michael Schulz, Gunnar Myhre, and Piers M. Forster
Geosci. Model Dev., 17, 2387–2417, https://doi.org/10.5194/gmd-17-2387-2024, https://doi.org/10.5194/gmd-17-2387-2024, 2024
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Climate scientists want to better understand modern climate change. Thus, climate model experiments are performed and compared. The results of climate model experiments differ, as assessed in the latest Intergovernmental Panel on Climate Change (IPCC) assessment report. This article gives insights into the challenges and outlines opportunities for further improving the understanding of climate change. It is based on views of a group of experts in atmospheric composition–climate interactions.
Sergey Danilov, Carolin Mehlmann, Dmitry Sidorenko, and Qiang Wang
Geosci. Model Dev., 17, 2287–2297, https://doi.org/10.5194/gmd-17-2287-2024, https://doi.org/10.5194/gmd-17-2287-2024, 2024
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Sea ice models are a necessary component of climate models. At very high resolution they are capable of simulating linear kinematic features, such as leads, which are important for better prediction of heat exchanges between the ocean and atmosphere. Two new discretizations are described which improve the sea ice component of the Finite volumE Sea ice–Ocean Model (FESOM version 2) by allowing simulations of finer scales.
Yangke Liu, Qing Bao, Bian He, Xiaofei Wu, Jing Yang, Yimin Liu, Guoxiong Wu, Tao Zhu, Siyuan Zhou, Yao Tang, Ankang Qu, Yalan Fan, Anling Liu, Dandan Chen, Zhaoming Luo, Xing Hu, and Tongwen Wu
EGUsphere, https://doi.org/10.5194/egusphere-2024-1, https://doi.org/10.5194/egusphere-2024-1, 2024
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This article gives an overview introduction of the IAP-CAS S2S (sub-seasonal to seasonal) ensemble forecasting system and MJO forecast evaluation of the system. Compared to other S2S models, the IAP-CAS model has its advantages but also exhibits some biases, including underdispersive ensemble, overestimated amplitude and faster propagation speed when forecasting MJO. We also provide the explanation towards these biases and prospects for further improvement of this system in the future.
Tian Gan, Gregory E. Tucker, Eric W. H. Hutton, Mark D. Piper, Irina Overeem, Albert J. Kettner, Benjamin Campforts, Julia M. Moriarty, Brianna Undzis, Ethan Pierce, and Lynn McCready
Geosci. Model Dev., 17, 2165–2185, https://doi.org/10.5194/gmd-17-2165-2024, https://doi.org/10.5194/gmd-17-2165-2024, 2024
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This study presents the design, implementation, and application of the CSDMS Data Components. The case studies demonstrate that the Data Components provide a consistent way to access heterogeneous datasets from multiple sources, and to seamlessly integrate them with various models for Earth surface process modeling. The Data Components support the creation of open data–model integration workflows to improve the research transparency and reproducibility.
Jérémy Bernard, Erwan Bocher, Matthieu Gousseff, François Leconte, and Elisabeth Le Saux Wiederhold
Geosci. Model Dev., 17, 2077–2116, https://doi.org/10.5194/gmd-17-2077-2024, https://doi.org/10.5194/gmd-17-2077-2024, 2024
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Geographical features may have a considerable effect on local climate. The local climate zone (LCZ) system proposed by Stewart and Oke (2012) is seen as a standard approach for classifying any zone according to a set of geographic indicators. While many methods already exist to map the LCZ, only a few tools are openly and freely available. We present the algorithm implemented in GeoClimate software to identify the LCZ of any place in the world using OpenStreetMap data.
Thomas Extier, Thibaut Caley, and Didier M. Roche
Geosci. Model Dev., 17, 2117–2139, https://doi.org/10.5194/gmd-17-2117-2024, https://doi.org/10.5194/gmd-17-2117-2024, 2024
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Stable water isotopes are used to infer changes in the hydrological cycle for different time periods in climatic archive and climate models. We present the implementation of the δ2H and δ17O water isotopes in the coupled climate model iLOVECLIM and calculate the d- and 17O-excess. Results of a simulation under preindustrial conditions show that the model correctly reproduces the water isotope distribution in the atmosphere and ocean in comparison to data and other global circulation models.
Joseph P. Hollowed, Christiane Jablonowski, Hunter Y. Brown, Benjamin R. Hillman, Diana L. Bull, and Joseph L. Hart
EGUsphere, https://doi.org/10.5194/egusphere-2024-335, https://doi.org/10.5194/egusphere-2024-335, 2024
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Large volcanic eruptions deposit material into the upper-atmosphere, which is capable of altering temperature and wind patterns of the Earth's atmosphere for years following. This research describes a new method of simulating these effects in an idealized, efficient atmospheric model. A volcanic eruption of sulfur dioxide is described with a simplified set of physical rules, which eventually cools the planetary surface. This model has been designed as a testbed for climate attribution studies.
Kirsten L. Findell, Zun Yin, Eunkyo Seo, Paul A. Dirmeyer, Nathan P. Arnold, Nathaniel Chaney, Megan D. Fowler, Meng Huang, David M. Lawrence, Po-Lun Ma, and Joseph A. Santanello Jr.
Geosci. Model Dev., 17, 1869–1883, https://doi.org/10.5194/gmd-17-1869-2024, https://doi.org/10.5194/gmd-17-1869-2024, 2024
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We outline a request for sub-daily data to accurately capture the process-level connections between land states, surface fluxes, and the boundary layer response. This high-frequency model output will allow for more direct comparison with observational field campaigns on process-relevant timescales, enable demonstration of inter-model spread in land–atmosphere coupling processes, and aid in targeted identification of sources of deficiencies and opportunities for improvement of the models.
Marlene Klockmann, Udo von Toussaint, and Eduardo Zorita
Geosci. Model Dev., 17, 1765–1787, https://doi.org/10.5194/gmd-17-1765-2024, https://doi.org/10.5194/gmd-17-1765-2024, 2024
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Reconstructions of climate variability before the observational period rely on climate proxies and sophisticated statistical models to link the proxy information and climate variability. Existing models tend to underestimate the true magnitude of variability, especially if the proxies contain non-climatic noise. We present and test a promising new framework for climate-index reconstructions, based on Gaussian processes, which reconstructs robust variability estimates from noisy and sparse data.
Aaron A. Naidoo-Bagwell, Fanny M. Monteiro, Katharine R. Hendry, Scott Burgan, Jamie D. Wilson, Ben A. Ward, Andy Ridgwell, and Daniel J. Conley
Geosci. Model Dev., 17, 1729–1748, https://doi.org/10.5194/gmd-17-1729-2024, https://doi.org/10.5194/gmd-17-1729-2024, 2024
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As an extension to the EcoGEnIE 1.0 Earth system model that features a diverse plankton community, EcoGEnIE 1.1 includes siliceous plankton diatoms and also considers their impact on biogeochemical cycles. With updates to existing nutrient cycles and the introduction of the silicon cycle, we see improved model performance relative to observational data. Through a more functionally diverse plankton community, the new model enables more comprehensive future study of ocean ecology.
Martin Butzin, Ying Ye, Christoph Völker, Özgür Gürses, Judith Hauck, and Peter Köhler
Geosci. Model Dev., 17, 1709–1727, https://doi.org/10.5194/gmd-17-1709-2024, https://doi.org/10.5194/gmd-17-1709-2024, 2024
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In this paper we describe the implementation of the carbon isotopes 13C and 14C into the marine biogeochemistry model FESOM2.1-REcoM3 and present results of long-term test simulations. Our model results are largely consistent with marine carbon isotope reconstructions for the pre-anthropogenic period, but also exhibit some discrepancies.
Sven Karsten, Hagen Radtke, Matthias Gröger, Ha T. M. Ho-Hagemann, Hossein Mashayekh, Thomas Neumann, and H. E. Markus Meier
Geosci. Model Dev., 17, 1689–1708, https://doi.org/10.5194/gmd-17-1689-2024, https://doi.org/10.5194/gmd-17-1689-2024, 2024
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This paper describes the development of a regional Earth System Model for the Baltic Sea region. In contrast to conventional coupling approaches, the presented model includes a flux calculator operating on a common exchange grid. This approach automatically ensures a locally consistent treatment of fluxes and simplifies the exchange of model components. The presented model can be used for various scientific questions, such as studies of natural variability and ocean–atmosphere interactions.
Skyler Graap and Colin M. Zarzycki
Geosci. Model Dev., 17, 1627–1650, https://doi.org/10.5194/gmd-17-1627-2024, https://doi.org/10.5194/gmd-17-1627-2024, 2024
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A key target for improving climate models is how low, bright clouds are predicted over tropical oceans, since they have important consequences for the Earth's energy budget. A climate model has been updated to improve the physical realism of the treatment of how momentum is moved up and down in the atmosphere. By comparing this updated model to real-world observations from balloon launches, it can be shown to more accurately depict atmospheric structure in trade-wind areas close to the Equator.
Marika M. Holland, Cecile Hannay, John Fasullo, Alexandra Jahn, Jennifer E. Kay, Michael Mills, Isla R. Simpson, William Wieder, Peter Lawrence, Erik Kluzek, and David Bailey
Geosci. Model Dev., 17, 1585–1602, https://doi.org/10.5194/gmd-17-1585-2024, https://doi.org/10.5194/gmd-17-1585-2024, 2024
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Climate evolves in response to changing forcings, as prescribed in simulations. Models and forcings are updated over time to reflect new understanding. This makes it difficult to attribute simulation differences to either model or forcing changes. Here we present new simulations which enable the separation of model structure and forcing influence between two widely used simulation sets. Results indicate a strong influence of aerosol emission uncertainty on historical climate.
Rongyun Tang, Mingzhou Jin, Jiafu Mao, Daniel M. Ricciuto, Anping Chen, and Yulong Zhang
Geosci. Model Dev., 17, 1525–1542, https://doi.org/10.5194/gmd-17-1525-2024, https://doi.org/10.5194/gmd-17-1525-2024, 2024
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Carbon-rich boreal peatlands are at risk of burning. The reproducibility and predictability of rare peatland fire events are investigated by constructing a two-step error-correcting machine learning framework to tackle such complex systems. Fire occurrence and impacts are highly predictable with our approach. Factor-controlling simulations revealed that temperature, moisture, and freeze–thaw cycles control boreal peatland fires, indicating thermal impacts on causing peat fires.
Allison B. Collow, Peter R. Colarco, Arlindo M. da Silva, Virginie Buchard, Huisheng Bian, Mian Chin, Sampa Das, Ravi Govindaraju, Dongchul Kim, and Valentina Aquila
Geosci. Model Dev., 17, 1443–1468, https://doi.org/10.5194/gmd-17-1443-2024, https://doi.org/10.5194/gmd-17-1443-2024, 2024
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The GOCART aerosol module within the Goddard Earth Observing System recently underwent a major refactoring and update to the representation of physical processes. Code changes that were included in GOCART Second Generation (GOCART-2G) are documented, and we establish a benchmark simulation that is to be used for future development of the system. The 4-year benchmark simulation was evaluated using in situ and spaceborne measurements to develop a baseline and prioritize future development.
Oksana Guba, Mark A. Taylor, Peter A. Bosler, Christopher Eldred, and Peter H. Lauritzen
Geosci. Model Dev., 17, 1429–1442, https://doi.org/10.5194/gmd-17-1429-2024, https://doi.org/10.5194/gmd-17-1429-2024, 2024
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We want to reduce errors in the moist energy budget in numerical atmospheric models. We study a few common assumptions and mechanisms that are used for the moist physics. Some mechanisms are more consistent with the underlying equations. Separately, we study how assumptions about models' thermodynamics affect the modeled energy of precipitation. We also explain how to conserve energy in the moist physics for nonhydrostatic models.
Konstantin Aiteew, Jarno Rouhiainen, Claas Nendel, and René Dechow
Geosci. Model Dev., 17, 1349–1385, https://doi.org/10.5194/gmd-17-1349-2024, https://doi.org/10.5194/gmd-17-1349-2024, 2024
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This study evaluated the biogeochemical model MONICA and its performance in simulating soil organic carbon changes. MONICA can reproduce plant growth, carbon and nitrogen dynamics, soil water and temperature. The model results were compared with five established carbon turnover models. With the exception of certain sites, adequate reproduction of soil organic carbon stock change rates was achieved. The MONICA model was capable of performing similar to or even better than the other models.
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Short summary
To estimate the effects of human land use activities on the carbon–climate system, a new set of global gridded land use forcing datasets was developed to link historical land use data to eight future scenarios in a standard format required by climate models. This new generation of land use harmonization (LUH2) includes updated inputs, higher spatial resolution, more detailed land use transitions, and the addition of important agricultural management layers; it will be used for CMIP6 simulations.
To estimate the effects of human land use activities on the carbon–climate system, a new set of...
