Articles | Volume 9, issue 9
Geosci. Model Dev., 9, 2999–3026, 2016
https://doi.org/10.5194/gmd-9-2999-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Geosci. Model Dev., 9, 2999–3026, 2016
https://doi.org/10.5194/gmd-9-2999-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Development and technical paper 02 Sep 2016
Development and technical paper | 02 Sep 2016
Constraining a land-surface model with multiple observations by application of the MPI-Carbon Cycle Data Assimilation System V1.0
Gregor J. Schürmann et al.
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Christian Rödenbeck, Tim DeVries, Judith Hauck, Corinne Le Quéré, and Ralph Keeling
Biogeosciences Discuss., https://doi.org/10.5194/bg-2021-304, https://doi.org/10.5194/bg-2021-304, 2021
Preprint under review for BG
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The ocean is an important part of the global carbon cycle, taking up about a quarter of the anthropgenic CO2 emitted by burning of fossil fuels, and thus slowing down climate change. However, the CO2 uptake by the ocean is, in turn, affected by variability and trends in climate. Here we use carbon measurements in the surface ocean to quantify the response of the oceanic CO2 exchange to environmental conditions, and discuss possible mechanisms underlying this response.
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 T. T. Chau, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Kim I. Currie, Bertrand Decharme, Laique 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 K. 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 van der Werf, Nicolas Vuichard, Chisato Wada, Rik Wanninkhof, Andrew Watson, David Willis, Andrew J. Wiltshire, Wenping Yuan, Chao Yue, Xu Yue, Sönke Zaehle, and Jiye Zeng
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2021-386, https://doi.org/10.5194/essd-2021-386, 2021
Preprint under review for ESSD
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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.
Saqr Munassar, Christian Rödenbeck, Thomas Koch, Kai U. Totsche, Michał Gałkowski, Sophia Walther, and Christoph Gerbig
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2021-873, https://doi.org/10.5194/acp-2021-873, 2021
Preprint under review for ACP
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The results obtained from ensembles of inversions over 13-year show the largest spread in the a-posteriori fluxes over the station set ensemble. using different prior fluxes in the inversions lead to smaller impact. Drought occurrences in 2018 and 2019 affected CO2 fluxes as noticed from NEE estimates. Our study highlights the importance of employing the atmospheric data available across Europe, especially since ICOS established, to better constrain NEE fluxes in the inverse modelling setups.
Taraka Davies-Barnard, Sönke Zaehle, and Pierre Friedlingstein
Biogeosciences Discuss., https://doi.org/10.5194/bg-2021-290, https://doi.org/10.5194/bg-2021-290, 2021
Preprint under review for BG
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Biological nitrogen fixation is the largest natural input of new nitrogen onto land. Earth System Models mainly represent global total terrestrial biological nitrogen fixation within observational uncertainties, but overestimate tropical fixation. The model range of increase in biological nitrogen fixation increase in the SSP3-7.0 scenario is 3 to 87 %. While biological nitrogen fixation is an key source of new nitrogen, its predictive power for net primary productivity in models is limited.
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.
Lina Teckentrup, Martin G. De Kauwe, Andrew J. Pitman, Daniel S. Goll, Vanessa Haverd, Atul K. Jain, Emilie Joetzjer, Etsushi Kato, Sebastian Lienert, Danica Lombardozzi, Patrick C. McGuire, Joe R. Melton, Julia E. M. S. Nabel, Julia Pongratz, Stephen Sitch, Anthony P. Walker, and Sönke Zaehle
Biogeosciences, 18, 5639–5668, https://doi.org/10.5194/bg-18-5639-2021, https://doi.org/10.5194/bg-18-5639-2021, 2021
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The Australian continent is included in global assessments of the carbon cycle such as the global carbon budget, yet the performance of dynamic global vegetation models (DGVMs) over Australia has rarely been evaluated. We assessed simulations by an ensemble of dynamic global vegetation models over Australia and highlighted a number of key areas that lead to model divergence on both short (inter-annual) and long (decadal) timescales.
Amanda R. Fay, Luke Gregor, Peter Landschützer, Galen A. McKinley, Nicolas Gruber, Marion Gehlen, Yosuke Iida, Goulven G. Laruelle, Christian Rödenbeck, Alizée Roobaert, and Jiye Zeng
Earth Syst. Sci. Data, 13, 4693–4710, https://doi.org/10.5194/essd-13-4693-2021, https://doi.org/10.5194/essd-13-4693-2021, 2021
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The movement of carbon dioxide from the atmosphere to the ocean is estimated using surface ocean carbon (pCO2) measurements and an equation including variables such as temperature and wind speed; the choices of these variables lead to uncertainties. We introduce the SeaFlux ensemble which provides carbon flux maps calculated in a consistent manner, thus reducing uncertainty by using common choices for wind speed and a set definition of "global" coverage.
Ana Bastos, René Orth, Markus Reichstein, Philippe Ciais, Nicolas Viovy, Sönke Zaehle, Peter Anthoni, Almut Arneth, Pierre Gentine, Emilie Joetzjer, Sebastian Lienert, Tammas Loughran, Patrick C. McGuire, Sungmin O, Julia Pongratz, and Stephen Sitch
Earth Syst. Dynam., 12, 1015–1035, https://doi.org/10.5194/esd-12-1015-2021, https://doi.org/10.5194/esd-12-1015-2021, 2021
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Temperate biomes in Europe are not prone to recurrent dry and hot conditions in summer. However, these conditions may become more frequent in the coming decades. Because stress conditions can leave legacies for many years, this may result in reduced ecosystem resilience under recurrent stress. We assess vegetation vulnerability to the hot and dry summers in 2018 and 2019 in Europe and find the important role of inter-annual legacy effects from 2018 in modulating the impacts of the 2019 event.
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.
Antoine Berchet, Espen Sollum, Rona L. Thompson, Isabelle Pison, Joël Thanwerdas, Grégoire Broquet, Frédéric Chevallier, Tuula Aalto, Adrien Berchet, Peter Bergamaschi, Dominik Brunner, Richard Engelen, Audrey Fortems-Cheiney, Christoph Gerbig, Christine D. Groot Zwaaftink, Jean-Matthieu Haussaire, Stephan Henne, Sander Houweling, Ute Karstens, Werner L. Kutsch, Ingrid T. Luijkx, Guillaume Monteil, Paul I. Palmer, Jacob C. A. van Peet, Wouter Peters, Philippe Peylin, Elise Potier, Christian Rödenbeck, Marielle Saunois, Marko Scholze, Aki Tsuruta, and Yuanhong Zhao
Geosci. Model Dev., 14, 5331–5354, https://doi.org/10.5194/gmd-14-5331-2021, https://doi.org/10.5194/gmd-14-5331-2021, 2021
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We present here the Community Inversion Framework (CIF) to help rationalize development efforts and leverage the strengths of individual inversion systems into a comprehensive framework. The CIF is a programming protocol to allow various inversion bricks to be exchanged among researchers.
The ensemble of bricks makes a flexible, transparent and open-source Python-based tool. We describe the main structure and functionalities and demonstrate it in a simple academic case.
Maurizio Santoro, Oliver Cartus, Nuno Carvalhais, Danaë M. A. Rozendaal, Valerio Avitabile, Arnan Araza, Sytze de Bruin, Martin Herold, Shaun Quegan, Pedro Rodríguez-Veiga, Heiko Balzter, João Carreiras, Dmitry Schepaschenko, Mikhail Korets, Masanobu Shimada, Takuya Itoh, Álvaro Moreno Martínez, Jura Cavlovic, Roberto Cazzolla Gatti, Polyanna da Conceição Bispo, Nasheta Dewnath, Nicolas Labrière, Jingjing Liang, Jeremy Lindsell, Edward T. A. Mitchard, Alexandra Morel, Ana Maria Pacheco Pascagaza, Casey M. Ryan, Ferry Slik, Gaia Vaglio Laurin, Hans Verbeeck, Arief Wijaya, and Simon Willcock
Earth Syst. Sci. Data, 13, 3927–3950, https://doi.org/10.5194/essd-13-3927-2021, https://doi.org/10.5194/essd-13-3927-2021, 2021
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Forests play a crucial role in Earth’s carbon cycle. To understand the carbon cycle better, we generated a global dataset of forest above-ground biomass, i.e. carbon stocks, from satellite data of 2010. This dataset provides a comprehensive and detailed portrait of the distribution of carbon in forests, although for dense forests in the tropics values are somewhat underestimated. This dataset will have a considerable impact on climate, carbon, and socio-economic modelling schemes.
Tina Trautmann, Sujan Koirala, Nuno Carvalhais, Andreas Güntner, and Martin Jung
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2021-394, https://doi.org/10.5194/hess-2021-394, 2021
Preprint under review for HESS
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We assess the effect of how vegetation is defined in a global hydrological model on the composition of total water storage (TWS). We compare 2 experiments, one with globally uniform and one with vegetation parameter that vary in space and time. While both experiments are constrained against observational data, we found a drastic change in the partitioning of TWS, highlighting an important role of the interaction between groundwater-soil moisture-vegetation to understand TWS variations.
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.
Martina Franz and Sönke Zaehle
Biogeosciences, 18, 3219–3241, https://doi.org/10.5194/bg-18-3219-2021, https://doi.org/10.5194/bg-18-3219-2021, 2021
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The combined effects of ozone and nitrogen deposition on the terrestrial carbon uptake and storage has been unclear. Our simulations, from 1850 to 2099, show that ozone-related damage considerably reduced gross primary production and carbon storage in the past. The growth-stimulating effect induced by nitrogen deposition is offset until the 2050s. Accounting for nitrogen deposition without considering ozone effects might lead to an overestimation of terrestrial carbon uptake and storage.
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.
Hanna Lappalainen, Tuukka Petäjä, Timo Vihma, Jouni Räisänen, Alexander Baklanov, Sergey Chalov, Igor Esau, Ekaterina Ezhova, Matti Leppäranta, Dmitry Pozdnyakov, Jukka Pumpanen, Meinrat O. Andreae, Michael Arshinov, Eija Asmi, Jianhui Bai, Igor Bashmachnikov, Boris Belan, Federico Bianchi, Boris Biskaborn, Michael Boy, Jaana Bäck, Bin Cheng, Natalia Ye Chubarova, Jonathan Duplissy, Egor Dyukarev, Konstantinos Eleftheriadis, Martin Forsius, Martin Heimann, Sirkku Juhola, Vladimir Konovalov, Igor Konovalov, Pavel Konstantinov, Kajar Koster, Elena Lapsina, Anna Lintunen, Alexander Mahura, Risto Makkonen, Svetlana Malkhazova, Ivan Mammarella, Stefano Mammola, Stephany Mazon, Outi Meinander, Eugene Mikhailov, Victoria Miles, Stanislav Myslenko, Dimitry Orlov, Jean-Daniel Paris, Robertta Pirazzini, Olga Popovicheva, Jouni Pulliainen, Kimmo Rautiainen, Torsten Sachs, Vladimir Shevchenko, Andrey Skorokhod, Andreas Stohl, Elli Suhonen, Erik S. Thomson, Marina Tsidilina, Veli-Pekka Tynkkynen, Petteri Uotila, Aki Virkkula, Nadezhda Voropay, Tobias Wolf, Sayaka Yasunaka, Jiahua Zhang, Yubao Qui, Aijun Ding, Huadong Guo, Valery Bondur, Nikolay Kasimov, Sergey Zilitinkevich, Veli-Matti Kerminen, and Markku Kulmala
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2021-341, https://doi.org/10.5194/acp-2021-341, 2021
Revised manuscript accepted for ACP
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We summarize results during the last five years in the Northern Eurasian region, especially from Russia, and introduce recent observations on the air quality in the urban environments in China. Although the scientific knowledge in these regions has increased, there are still gaps in our understanding of large-scale climate-Earth surface interactions and feedbacks. This arises from limitations in research infrastructures and integrative data analyses, hindering a comprehensive system analysis.
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.
Andrew J. Wiltshire, Eleanor J. Burke, Sarah E. Chadburn, Chris D. Jones, Peter M. Cox, Taraka Davies-Barnard, Pierre Friedlingstein, Anna B. Harper, Spencer Liddicoat, Stephen Sitch, and Sönke Zaehle
Geosci. Model Dev., 14, 2161–2186, https://doi.org/10.5194/gmd-14-2161-2021, https://doi.org/10.5194/gmd-14-2161-2021, 2021
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Limited nitrogen availbility can restrict the growth of plants and their ability to assimilate carbon. It is important to include the impact of this process on the global land carbon cycle. This paper presents a model of the coupled land carbon and nitrogen cycle, which is included within the UK Earth System model to improve projections of climate change and impacts on ecosystems.
Daniele Peano, Deborah Hemming, Stefano Materia, Christine Delire, Yuanchao Fan, Emilie Joetzjer, Hanna Lee, Julia E. M. S. Nabel, Taejin Park, Philippe Peylin, David Wårlind, Andy Wiltshire, and Sönke Zaehle
Biogeosciences, 18, 2405–2428, https://doi.org/10.5194/bg-18-2405-2021, https://doi.org/10.5194/bg-18-2405-2021, 2021
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Global climate models are the scientist’s tools used for studying past, present, and future climate conditions. This work examines the ability of a group of our tools in reproducing and capturing the right timing and length of the season when plants show their green leaves. This season, indeed, is fundamental for CO2 exchanges between land, atmosphere, and climate. This work shows that discrepancies compared to observations remain, demanding further polishing of these tools.
Meike Becker, Are Olsen, Peter Landschützer, Abdirhaman Omar, Gregor Rehder, Christian Rödenbeck, and Ingunn Skjelvan
Biogeosciences, 18, 1127–1147, https://doi.org/10.5194/bg-18-1127-2021, https://doi.org/10.5194/bg-18-1127-2021, 2021
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We developed a simple method to refine existing open-ocean maps towards different coastal seas. Using a multi-linear regression, we produced monthly maps of surface ocean fCO2 in the northern European coastal seas (the North Sea, the Baltic Sea, the Norwegian Coast and the Barents Sea) covering a time period from 1998 to 2016. Based on this fCO2 map, we calculate trends in surface ocean fCO2, pH and the air–sea gas exchange.
Carlos A. Sierra, Susan E. Crow, Martin Heimann, Holger Metzler, and Ernst-Detlef Schulze
Biogeosciences, 18, 1029–1048, https://doi.org/10.5194/bg-18-1029-2021, https://doi.org/10.5194/bg-18-1029-2021, 2021
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The climate benefit of carbon sequestration (CBS) is a metric developed to quantify avoided warming by two separate processes: the amount of carbon drawdown from the atmosphere and the time this carbon is stored in a reservoir. This metric can be useful for quantifying the role of forests and soils for climate change mitigation and to better quantify the benefits of carbon removals by sinks.
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.
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.
Guillaume Monteil, Grégoire Broquet, Marko Scholze, Matthew Lang, Ute Karstens, Christoph Gerbig, Frank-Thomas Koch, Naomi E. Smith, Rona L. Thompson, Ingrid T. Luijkx, Emily White, Antoon Meesters, Philippe Ciais, Anita L. Ganesan, Alistair Manning, Michael Mischurow, Wouter Peters, Philippe Peylin, Jerôme Tarniewicz, Matt Rigby, Christian Rödenbeck, Alex Vermeulen, and Evie M. Walton
Atmos. Chem. Phys., 20, 12063–12091, https://doi.org/10.5194/acp-20-12063-2020, https://doi.org/10.5194/acp-20-12063-2020, 2020
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The paper presents the first results from the EUROCOM project, a regional atmospheric inversion intercomparison exercise involving six European research groups. It aims to produce an estimate of the net carbon flux between the European terrestrial ecosystems and the atmosphere for the period 2006–2015, based on constraints provided by observed CO2 concentrations and using inverse modelling techniques. The use of six different models enables us to investigate the robustness of the results.
Taraka Davies-Barnard, Johannes Meyerholt, Sönke Zaehle, Pierre Friedlingstein, Victor Brovkin, Yuanchao Fan, Rosie A. Fisher, Chris D. Jones, Hanna Lee, Daniele Peano, Benjamin Smith, David Wårlind, and Andy J. Wiltshire
Biogeosciences, 17, 5129–5148, https://doi.org/10.5194/bg-17-5129-2020, https://doi.org/10.5194/bg-17-5129-2020, 2020
Naixin Fan, Sujan Koirala, Markus Reichstein, Martin Thurner, Valerio Avitabile, Maurizio Santoro, Bernhard Ahrens, Ulrich Weber, and Nuno Carvalhais
Earth Syst. Sci. Data, 12, 2517–2536, https://doi.org/10.5194/essd-12-2517-2020, https://doi.org/10.5194/essd-12-2517-2020, 2020
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The turnover time of terrestrial carbon (τ) controls the global carbon cycle–climate feedback. In this study, we provide a new, updated ensemble of diagnostic terrestrial carbon turnover times and associated uncertainties on a global scale. Despite the large variation in both magnitude and spatial patterns of τ, we identified robust features in the spatial patterns of τ which could contribute to uncertainty reductions in future projections of the carbon cycle–climate feedback.
Veronika Eyring, Lisa Bock, Axel Lauer, Mattia Righi, Manuel Schlund, Bouwe Andela, Enrico Arnone, Omar Bellprat, Björn Brötz, Louis-Philippe Caron, Nuno Carvalhais, Irene Cionni, Nicola Cortesi, Bas Crezee, Edouard L. Davin, Paolo Davini, Kevin Debeire, Lee de Mora, Clara Deser, David Docquier, Paul Earnshaw, Carsten Ehbrecht, Bettina K. Gier, Nube Gonzalez-Reviriego, Paul Goodman, Stefan Hagemann, Steven Hardiman, Birgit Hassler, Alasdair Hunter, Christopher Kadow, Stephan Kindermann, Sujan Koirala, Nikolay Koldunov, Quentin Lejeune, Valerio Lembo, Tomas Lovato, Valerio Lucarini, François Massonnet, Benjamin Müller, Amarjiit Pandde, Núria Pérez-Zanón, Adam Phillips, Valeriu Predoi, Joellen Russell, Alistair Sellar, Federico Serva, Tobias Stacke, Ranjini Swaminathan, Verónica Torralba, Javier Vegas-Regidor, Jost von Hardenberg, Katja Weigel, and Klaus Zimmermann
Geosci. Model Dev., 13, 3383–3438, https://doi.org/10.5194/gmd-13-3383-2020, https://doi.org/10.5194/gmd-13-3383-2020, 2020
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The Earth System Model Evaluation Tool (ESMValTool) is a community diagnostics and performance metrics tool designed to improve comprehensive and routine evaluation of earth system models (ESMs) participating in the Coupled Model Intercomparison Project (CMIP). It has undergone rapid development since the first release in 2016 and is now a well-tested tool that provides end-to-end provenance tracking to ensure reproducibility.
Barbara Marcolla, Mirco Migliavacca, Christian Rödenbeck, and Alessandro Cescatti
Biogeosciences, 17, 2365–2379, https://doi.org/10.5194/bg-17-2365-2020, https://doi.org/10.5194/bg-17-2365-2020, 2020
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This work investigates the sensitivity of terrestrial CO2 fluxes to climate drivers. We observed that CO2 flux is mostly controlled by temperature during the growing season and by radiation off season. We also observe that radiation importance is increasing over time while sensitivity to temperature is decreasing in Eurasia. Ultimately this analysis shows that ecosystem response to climate is changing, with potential repercussions for future terrestrial sink and land role in climate mitigation.
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.
Lin Yu, Bernhard Ahrens, Thomas Wutzler, Marion Schrumpf, and Sönke Zaehle
Geosci. Model Dev., 13, 783–803, https://doi.org/10.5194/gmd-13-783-2020, https://doi.org/10.5194/gmd-13-783-2020, 2020
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In this paper, we have developed a new soil organic carbon model that describes the formation and turnover of soil organic matter in a more mechanistic manner. With this model, we are able to better represent how microorganisms and nutrient processes influence the below-ground carbon storage and better explain some observed features of soil organic matter. We hope this model can increase our confidence in predictions of future climate change, particularly on how soil can mitigate the process.
Nora Linscheid, Lina M. Estupinan-Suarez, Alexander Brenning, Nuno Carvalhais, Felix Cremer, Fabian Gans, Anja Rammig, Markus Reichstein, Carlos A. Sierra, and Miguel D. Mahecha
Biogeosciences, 17, 945–962, https://doi.org/10.5194/bg-17-945-2020, https://doi.org/10.5194/bg-17-945-2020, 2020
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Vegetation typically responds to variation in temperature and rainfall within days. Yet seasonal changes in meteorological conditions, as well as decadal climate variability, additionally shape the state of ecosystems. It remains unclear how vegetation responds to climate variability on these different timescales. We find that the vegetation response to climate variability depends on the timescale considered. This scale dependency should be considered for modeling land–atmosphere interactions.
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.
Nicolas Vuichard, Palmira Messina, Sebastiaan Luyssaert, Bertrand Guenet, Sönke Zaehle, Josefine Ghattas, Vladislav Bastrikov, and Philippe Peylin
Geosci. Model Dev., 12, 4751–4779, https://doi.org/10.5194/gmd-12-4751-2019, https://doi.org/10.5194/gmd-12-4751-2019, 2019
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In this research, we present a new version of the global terrestrial ecosystem model ORCHIDEE in which carbon and nitrogen cycles are coupled. We evaluate its skills at simulating primary production at 78 sites and at a global scale. Based on a set of additional simulations in which carbon and nitrogen cycles are coupled and uncoupled, we show that the functional responses of the model with carbon–nitrogen interactions better agree with our current understanding of photosynthesis.
Tea Thum, Silvia Caldararu, Jan Engel, Melanie Kern, Marleen Pallandt, Reiner Schnur, Lin Yu, and Sönke Zaehle
Geosci. Model Dev., 12, 4781–4802, https://doi.org/10.5194/gmd-12-4781-2019, https://doi.org/10.5194/gmd-12-4781-2019, 2019
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To predict the response of the vegetation to climate change, we need global models that describe the relevant processes taking place in the vegetation. Recently, we have obtained more in-depth understanding of vegetation processes and the role of nutrients in the biogeochemical cycles. We have developed a new global vegetation model that includes carbon, water, nitrogen, and phosphorus cycles. We show that the model is successful in evaluation against a wide range of observations.
Friedemann Reum, Mathias Göckede, Jost V. Lavric, Olaf Kolle, Sergey Zimov, Nikita Zimov, Martijn Pallandt, and Martin Heimann
Atmos. Meas. Tech., 12, 5717–5740, https://doi.org/10.5194/amt-12-5717-2019, https://doi.org/10.5194/amt-12-5717-2019, 2019
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We present continuous in situ measurements of atmospheric CO2 and CH4 mole fractions at the new station Ambarchik, located in northeastern Siberia. We describe the site, measurements and quality control, characterize the signals in comparison with data from Barrow, Alaska, and show which regions the measurements are sensitive to. Ambarchik data are available upon request.
Eric J. Morgan, Jost V. Lavric, Damian L. Arévalo-Martínez, Hermann W. Bange, Tobias Steinhoff, Thomas Seifert, and Martin Heimann
Biogeosciences, 16, 4065–4084, https://doi.org/10.5194/bg-16-4065-2019, https://doi.org/10.5194/bg-16-4065-2019, 2019
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Taking a 2-year atmospheric record of atmospheric oxygen and the greenhouse gases N2O, CO2, and CH4, made at a coastal site in the Namib Desert, we estimated the fluxes of these gases from upwelling events in the northern Benguela Current region. We compared these results with flux measurements made on a research vessel in the study area at the same time and found that the two approaches agreed well. The study region was a source of N2O, CO2, and CH4 to the atmosphere during upwelling events.
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.
Jarmo Mäkelä, Jürgen Knauer, Mika Aurela, Andrew Black, Martin Heimann, Hideki Kobayashi, Annalea Lohila, Ivan Mammarella, Hank Margolis, Tiina Markkanen, Jouni Susiluoto, Tea Thum, Toni Viskari, Sönke Zaehle, and Tuula Aalto
Geosci. Model Dev., 12, 4075–4098, https://doi.org/10.5194/gmd-12-4075-2019, https://doi.org/10.5194/gmd-12-4075-2019, 2019
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We assess the differences of six stomatal conductance formulations, embedded into a land–vegetation model JSBACH, on 10 boreal coniferous evergreen forest sites. We calibrate the model parameters using all six functions in a multi-year experiment, as well as for a separate drought event at one of the sites, using the adaptive population importance sampler. The analysis reveals weaknesses in the stomatal conductance formulation-dependent model behaviour that we are able to partially amend.
Karel Castro-Morales, Gregor Schürmann, Christoph Köstler, Christian Rödenbeck, Martin Heimann, and Sönke Zaehle
Biogeosciences, 16, 3009–3032, https://doi.org/10.5194/bg-16-3009-2019, https://doi.org/10.5194/bg-16-3009-2019, 2019
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To obtain nearly 30 years of global terrestrial carbon fluxes, we simultaneously incorporated in a land surface model three different time periods of two observational data sets: absorbed photosynthetic active radiation and atmospheric CO2 concentrations. One decade of data is enough to improve the modeled long-term trends and seasonal amplitudes of the assimilated variables, particularly in boreal regions. This model has the potential to provide short-term predictions of land carbon fluxes.
Sven Boese, Martin Jung, Nuno Carvalhais, Adriaan J. Teuling, and Markus Reichstein
Biogeosciences, 16, 2557–2572, https://doi.org/10.5194/bg-16-2557-2019, https://doi.org/10.5194/bg-16-2557-2019, 2019
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This study examines how limited water availability during droughts affects water-use efficiency. This metric describes how much carbon an ecosystem can assimilate for each unit of water lost by transpiration. We test how well different water-use efficiency models can capture the dynamics of transpiration decrease due to increased soil-water limitation. Accounting for the interacting effects of radiation and water limitation is necessary to accurately predict transpiration during these periods.
Mingkai Jiang, Sönke Zaehle, Martin G. De Kauwe, Anthony P. Walker, Silvia Caldararu, David S. Ellsworth, and Belinda E. Medlyn
Geosci. Model Dev., 12, 2069–2089, https://doi.org/10.5194/gmd-12-2069-2019, https://doi.org/10.5194/gmd-12-2069-2019, 2019
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Here we used a simple analytical framework developed by Comins and McMurtrie (1993) to investigate how different model assumptions affected plant responses to elevated CO2. This framework is useful in revealing both the consequences and the mechanisms through which different assumptions affect predictions. We therefore recommend the use of this framework to analyze the likely outcomes of new assumptions before introducing them to complex model structures.
Xiaolu Tang, Nuno Carvalhais, Catarina Moura, Bernhard Ahrens, Sujan Koirala, Shaohui Fan, Fengying Guan, Wenjie Zhang, Sicong Gao, Vincenzo Magliulo, Pauline Buysse, Shibin Liu, Guo Chen, Wunian Yang, Zhen Yu, Jingjing Liang, Leilei Shi, Shenyan Pu, and Markus Reichstein
Biogeosciences Discuss., https://doi.org/10.5194/bg-2019-37, https://doi.org/10.5194/bg-2019-37, 2019
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Vegetation CUE is a key measure of carbon transfer from the atmosphere to terrestrial biomass. This study modelled global CUE with published observations using random forest. CUE varied with ecosystem types and spatially decreased with latitude, challenging the previous conclusion that CUE was independent of environmental controls. Our results emphasize a better understanding of environmental controls on CUE to reduce uncertainties in prognostic land-process model simulations.
Benjamin Gaubert, Britton B. Stephens, Sourish Basu, Frédéric Chevallier, Feng Deng, Eric A. Kort, Prabir K. Patra, Wouter Peters, Christian Rödenbeck, Tazu Saeki, David Schimel, Ingrid Van der Laan-Luijkx, Steven Wofsy, and Yi Yin
Biogeosciences, 16, 117–134, https://doi.org/10.5194/bg-16-117-2019, https://doi.org/10.5194/bg-16-117-2019, 2019
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We have compared global carbon budgets calculated from numerical inverse models and CO2 observations, and evaluated how these systems reproduce vertical gradients in atmospheric CO2 from aircraft measurements. We found that available models have converged on near-neutral tropical total fluxes for several decades, implying consistent sinks in intact tropical forests, and that assumed fossil fuel emissions and predicted atmospheric growth rates are now the dominant axes of disagreement.
Ekaterina Ezhova, Ilona Ylivinkka, Joel Kuusk, Kaupo Komsaare, Marko Vana, Alisa Krasnova, Steffen Noe, Mikhail Arshinov, Boris Belan, Sung-Bin Park, Jošt Valentin Lavrič, Martin Heimann, Tuukka Petäjä, Timo Vesala, Ivan Mammarella, Pasi Kolari, Jaana Bäck, Üllar Rannik, Veli-Matti Kerminen, and Markku Kulmala
Atmos. Chem. Phys., 18, 17863–17881, https://doi.org/10.5194/acp-18-17863-2018, https://doi.org/10.5194/acp-18-17863-2018, 2018
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Understanding the connections between aerosols, solar radiation and photosynthesis in terrestrial ecosystems is important for estimates of the CO2 balance in the atmosphere. Atmospheric aerosols and clouds influence solar radiation. In this study, we quantify the aerosol effect on solar radiation in boreal forests and study forest ecosystems response to this change in the radiation conditions. The analysis is based on atmospheric observations from several remote stations in Eurasian forests.
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.
Martina Franz, Rocio Alonso, Almut Arneth, Patrick Büker, Susana Elvira, Giacomo Gerosa, Lisa Emberson, Zhaozhong Feng, Didier Le Thiec, Riccardo Marzuoli, Elina Oksanen, Johan Uddling, Matthew Wilkinson, and Sönke Zaehle
Biogeosciences, 15, 6941–6957, https://doi.org/10.5194/bg-15-6941-2018, https://doi.org/10.5194/bg-15-6941-2018, 2018
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Four published ozone damage functions previously used in terrestrial biosphere models were evaluated regarding their ability to simulate observed biomass dose–response relationships using the O-CN model. Neither damage function was able to reproduce the observed ozone-induced biomass reductions. Calibrating a plant-functional-type-specific relationship between accumulated ozone uptake and leaf-level photosynthesis did lead to a good agreement between observed and modelled ozone damage.
Yilong Wang, Philippe Ciais, Daniel Goll, Yuanyuan Huang, Yiqi Luo, Ying-Ping Wang, A. Anthony Bloom, Grégoire Broquet, Jens Hartmann, Shushi Peng, Josep Penuelas, Shilong Piao, Jordi Sardans, Benjamin D. Stocker, Rong Wang, Sönke Zaehle, and Sophie Zechmeister-Boltenstern
Geosci. Model Dev., 11, 3903–3928, https://doi.org/10.5194/gmd-11-3903-2018, https://doi.org/10.5194/gmd-11-3903-2018, 2018
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We present a new modeling framework called Global Observation-based Land-ecosystems Utilization Model of Carbon, Nitrogen and Phosphorus (GOLUM-CNP) that combines a data-constrained C-cycle analysis with data-driven estimates of N and P inputs and losses and with observed stoichiometric ratios. GOLUM-CNP provides a traceable tool, where a consistency between different datasets of global C, N, and P cycles has been achieved.
Johannes Meyerholt and Sönke Zaehle
Biogeosciences, 15, 5677–5698, https://doi.org/10.5194/bg-15-5677-2018, https://doi.org/10.5194/bg-15-5677-2018, 2018
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Terrestrial biosphere models employ various representations of ecosystem nitrogen loss, some based on soil N availability, some based on net N mineralization. We show in local and global simulations that this variety leads to pronounced uncertainty in the predicted magnitude and sign of ecosystem N loss change under elevated CO2. Suprisingly, this uncertainty barely affects predicted carbon storage responses to elevated CO2, illustrating the need for new benchmarks especially in the boreal zone.
Thomas Kaminski, Frank Kauker, Leif Toudal Pedersen, Michael Voßbeck, Helmuth Haak, Laura Niederdrenk, Stefan Hendricks, Robert Ricker, Michael Karcher, Hajo Eicken, and Ola Gråbak
The Cryosphere, 12, 2569–2594, https://doi.org/10.5194/tc-12-2569-2018, https://doi.org/10.5194/tc-12-2569-2018, 2018
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We present mathematically rigorous assessments of the observation impact (added value) of remote-sensing products and in terms of the uncertainty reduction in a 4-week forecast of sea ice volume and snow volume for three regions along the Northern Sea Route by a coupled model of the sea-ice–ocean system. We quantify the difference in impact between rawer (freeboard) and higher-level (sea ice thickness) products, and the impact of adding a snow depth product.
Nemesio J. Rodríguez-Fernández, Arnaud Mialon, Stephane Mermoz, Alexandre Bouvet, Philippe Richaume, Ahmad Al Bitar, Amen Al-Yaari, Martin Brandt, Thomas Kaminski, Thuy Le Toan, Yann H. Kerr, and Jean-Pierre Wigneron
Biogeosciences, 15, 4627–4645, https://doi.org/10.5194/bg-15-4627-2018, https://doi.org/10.5194/bg-15-4627-2018, 2018
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Existing global scale above-ground biomass (AGB) maps are made at very high spatial resolution collecting data during several years. In this paper we discuss the use of a new data set from the SMOS satellite: the vegetation optical depth estimated from low microwave frequencies. It is shown that this new data set is highly sensitive to AGB. The spacial resolution of SMOS is coarse (40 km) but the new data set can be used to monitor AGB variations with time due to its high revisit frequency.
Tina Trautmann, Sujan Koirala, Nuno Carvalhais, Annette Eicker, Manfred Fink, Christoph Niemann, and Martin Jung
Hydrol. Earth Syst. Sci., 22, 4061–4082, https://doi.org/10.5194/hess-22-4061-2018, https://doi.org/10.5194/hess-22-4061-2018, 2018
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In this study, we adjust a simple hydrological model to several observational datasets, including satellite observations of the land's total water storage. We apply the model to northern latitudes and find that the dominating factor of changes in the total water storage depends on both the spatial and temporal scale of analysis. While snow dominates seasonal variations, liquid water determines year-to-year variations, yet with increasing contribution of snow when averaging over larger regions.
Werner von Bloh, Sibyll Schaphoff, Christoph Müller, Susanne Rolinski, Katharina Waha, and Sönke Zaehle
Geosci. Model Dev., 11, 2789–2812, https://doi.org/10.5194/gmd-11-2789-2018, https://doi.org/10.5194/gmd-11-2789-2018, 2018
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The dynamics of the terrestrial carbon cycle are of central importance for Earth system science. Nutrient limitations, especially from nitrogen, are important constraints on vegetation growth and the terrestrial carbon cycle. We extended the well-established global vegetation, hydrology, and crop model LPJmL with a nitrogen cycle. We find significant improvement in global patterns of crop productivity. Regional differences in crop productivity can now be largely reproduced by the model.
Karel Castro-Morales, Thomas Kleinen, Sonja Kaiser, Sönke Zaehle, Fanny Kittler, Min Jung Kwon, Christian Beer, and Mathias Göckede
Biogeosciences, 15, 2691–2722, https://doi.org/10.5194/bg-15-2691-2018, https://doi.org/10.5194/bg-15-2691-2018, 2018
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We present year-round methane emissions from wetlands in Northeast Siberia that were simulated with a land surface model. Ground-based flux measurements from the same area were used for evaluation of the model results, finding a best agreement with the observations in the summertime emissions that take place in this region predominantly through plants. During winter, methane emissions through the snow contribute 4 % of the total annual methane budget, but these are still underestimated.
Christian Rödenbeck, Sönke Zaehle, Ralph Keeling, and Martin Heimann
Biogeosciences, 15, 2481–2498, https://doi.org/10.5194/bg-15-2481-2018, https://doi.org/10.5194/bg-15-2481-2018, 2018
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In this paper we investigate how the CO2 exchange between the land vegetation and the atmosphere varies from year to year. We quantify the relation between variations in the CO2 exchange and variations in air temperature. For this quantification, we use long-term measurements of CO2 in the air at many locations, a simulation code for the transport of carbon dioxide through the atmosphere, and a data set of air temperature. The results help us to understand the mechanisms of CO2 exchange.
Jacob A. Nelson, Nuno Carvalhais, Mirco Migliavacca, Markus Reichstein, and Martin Jung
Biogeosciences, 15, 2433–2447, https://doi.org/10.5194/bg-15-2433-2018, https://doi.org/10.5194/bg-15-2433-2018, 2018
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Plants have typical daily carbon uptake and water loss cycles. However, these cycles may change under periods of duress, such as water limitation. Here we identify two types of patterns in response to water limitations: a tendency to lose more water in the morning than afternoon and a decoupling of the carbon and water cycles. The findings show differences in responses by trees and grasses and suggest that morning shifts may be more efficient at gaining carbon per unit water used.
Martin Kunz, Jost V. Lavric, Christoph Gerbig, Pieter Tans, Don Neff, Christine Hummelgård, Hans Martin, Henrik Rödjegård, Burkhard Wrenger, and Martin Heimann
Atmos. Meas. Tech., 11, 1833–1849, https://doi.org/10.5194/amt-11-1833-2018, https://doi.org/10.5194/amt-11-1833-2018, 2018
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Unmanned aircraft could provide a cost-effective way to close gaps in the observation of the carbon cycle, provided that small yet accurate analysers are available. We have developed a COmpact Carbon dioxide analyser for Airborne Platforms (COCAP). During validation of its CO2 measurements in simulated and real flights we found a measurement error of 1.2 μmol mol−1 or better with no indication of bias. COCAP is a self-contained package that has proven well suited for operation on board UASs.
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.
Panagiotis Kountouris, Christoph Gerbig, Christian Rödenbeck, Ute Karstens, Thomas Frank Koch, and Martin Heimann
Atmos. Chem. Phys., 18, 3027–3045, https://doi.org/10.5194/acp-18-3027-2018, https://doi.org/10.5194/acp-18-3027-2018, 2018
Panagiotis Kountouris, Christoph Gerbig, Christian Rödenbeck, Ute Karstens, Thomas F. Koch, and Martin Heimann
Atmos. Chem. Phys., 18, 3047–3064, https://doi.org/10.5194/acp-18-3047-2018, https://doi.org/10.5194/acp-18-3047-2018, 2018
Mathias Göckede, Fanny Kittler, Min Jung Kwon, Ina Burjack, Martin Heimann, Olaf Kolle, Nikita Zimov, and Sergey Zimov
The Cryosphere, 11, 2975–2996, https://doi.org/10.5194/tc-11-2975-2017, https://doi.org/10.5194/tc-11-2975-2017, 2017
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Shifts in hydrologic conditions will be a key factor for the sustainability of Arctic ecosystems under future climate change. Using a long-term manipulation experiment, we analyzed how energy exchange processes within a permafrost ecosystem react to sustained dry conditions. Changes in several important ecosystem characteristics lead to reduced evapotranspiration and increased sensible heat fluxes. Heat transfer into the soil was strongly reduced, keeping the permafrost colder.
Eugene F. Mikhailov, Svetlana Mironova, Gregory Mironov, Sergey Vlasenko, Alexey Panov, Xuguang Chi, David Walter, Samara Carbone, Paulo Artaxo, Martin Heimann, Jost Lavric, Ulrich Pöschl, and Meinrat O. Andreae
Atmos. Chem. Phys., 17, 14365–14392, https://doi.org/10.5194/acp-17-14365-2017, https://doi.org/10.5194/acp-17-14365-2017, 2017
Chao Yue, Philippe Ciais, Ana Bastos, Frederic Chevallier, Yi Yin, Christian Rödenbeck, and Taejin Park
Atmos. Chem. Phys., 17, 13903–13919, https://doi.org/10.5194/acp-17-13903-2017, https://doi.org/10.5194/acp-17-13903-2017, 2017
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The year 2015 appeared as a paradox regarding how global carbon cycle has responded to climate variation: it is the greenest year since 2000 according to satellite observation, but the atmospheric CO2 growth rate is also the highest since 1959. We found that this is due to a only moderate land carbon sink, because high growing-season sink in northern lands has been partly offset by autumn and winter release and the late-year El Niño has led to an abrupt transition to land source in the tropics.
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.
Thomas Kaminski and Peter Julian Rayner
Biogeosciences, 14, 4755–4766, https://doi.org/10.5194/bg-14-4755-2017, https://doi.org/10.5194/bg-14-4755-2017, 2017
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Observations can reduce uncertainties in past, current, and predicted natural and anthropogenic CO2 fluxes. They provide independent information for verification of actions as requested by the Paris Agreement. Quantitative network design (QND) is an objective approach to optimise in situ networks and space missions to achieve an optimal use of the observational capabilities. We describe recent progress and advocate an integrated QND system that simultaneously evaluates multiple data streams.
Daniel S. Goll, Nicolas Vuichard, Fabienne Maignan, Albert Jornet-Puig, Jordi Sardans, Aurelie Violette, Shushi Peng, Yan Sun, Marko Kvakic, Matthieu Guimberteau, Bertrand Guenet, Soenke Zaehle, Josep Penuelas, Ivan Janssens, and Philippe Ciais
Geosci. Model Dev., 10, 3745–3770, https://doi.org/10.5194/gmd-10-3745-2017, https://doi.org/10.5194/gmd-10-3745-2017, 2017
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We describe a representation of the terrestrial phosphorus cycle for the ORCHIDEE land surface model. The model is able to reproduce the observed shift from nitrogen to phosphorus limited net primary productivity along a soil formation chronosequence in Hawaii, as well as the contrasting responses of net primary productivity to nutrient addition. However, the simulated nutrient use efficiencies are lower, as observed primarily due to biases in the nutrient content and turnover of woody biomass.
Iulia Ilie, Peter Dittrich, Nuno Carvalhais, Martin Jung, Andreas Heinemeyer, Mirco Migliavacca, James I. L. Morison, Sebastian Sippel, Jens-Arne Subke, Matthew Wilkinson, and Miguel D. Mahecha
Geosci. Model Dev., 10, 3519–3545, https://doi.org/10.5194/gmd-10-3519-2017, https://doi.org/10.5194/gmd-10-3519-2017, 2017
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Accurate representation of land-atmosphere carbon fluxes is essential for future climate projections, although some of the responses of CO2 fluxes to climate often remain uncertain. The increase in available data allows for new approaches in their modelling. We automatically developed models for ecosystem and soil carbon respiration using a machine learning approach. When compared with established respiration models, we found that they are better in prediction as well as offering new insights.
Miguel D. Mahecha, Fabian Gans, Sebastian Sippel, Jonathan F. Donges, Thomas Kaminski, Stefan Metzger, Mirco Migliavacca, Dario Papale, Anja Rammig, and Jakob Zscheischler
Biogeosciences, 14, 4255–4277, https://doi.org/10.5194/bg-14-4255-2017, https://doi.org/10.5194/bg-14-4255-2017, 2017
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We investigate the likelihood of ecological in situ networks to detect and monitor the impact of extreme events in the terrestrial biosphere.
Barbara Marcolla, Christian Rödenbeck, and Alessandro Cescatti
Biogeosciences, 14, 3815–3829, https://doi.org/10.5194/bg-14-3815-2017, https://doi.org/10.5194/bg-14-3815-2017, 2017
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Patterns and controls of the inter-annual variability of carbon net ecosystem exchange were analysed using three different data streams: ecosystem-level observations (FLUXNET database), a global upscaling of site-level fluxes (MPI-MTE), and a top–down estimate of fluxes (Jena CarboScope Inversion). Consistencies and discrepancies in the temporal and spatial patterns and in the climatic and physiological controls of the inter-annual variability were investigated for the three data sources.
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.
Sven Boese, Martin Jung, Nuno Carvalhais, and Markus Reichstein
Biogeosciences, 14, 3015–3026, https://doi.org/10.5194/bg-14-3015-2017, https://doi.org/10.5194/bg-14-3015-2017, 2017
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For plants, the ratio of carbon uptake to water loss by transpiration is usually thought to depend on characteristic properties (their adaption to water scarcity) and the dryness of the atmosphere at any given moment. We show that, on the ecosystem scale, radiation has an independent effect on this ratio that had not been previously considered. When including this variable in models, predictions of transpiration improve considerably.
Thomas Kaminski, Bernard Pinty, Michael Voßbeck, Maciej Lopatka, Nadine Gobron, and Monica Robustelli
Biogeosciences, 14, 2527–2541, https://doi.org/10.5194/bg-14-2527-2017, https://doi.org/10.5194/bg-14-2527-2017, 2017
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We present the Joint Research Centre Two-stream Inversion Package (JRC-TIP) for retrieval of variables characterising the state of the vegetation–soil system. The system provides a set of land surface variables that satisfy all requirements for assimilation into the land component of climate and numerical weather prediction models.
Thomas Kaminski and Pierre-Philippe Mathieu
Biogeosciences, 14, 2343–2357, https://doi.org/10.5194/bg-14-2343-2017, https://doi.org/10.5194/bg-14-2343-2017, 2017
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This paper provides the formalism and examples of how observation operators can be used, in combination with data assimilation or retrieval techniques, to better ingest satellite products in a manner consistent with the dynamics of the Earth system expressed by models.
Shreeya Verma, Julia Marshall, Christoph Gerbig, Christian Rödenbeck, and Kai Uwe Totsche
Atmos. Chem. Phys., 17, 5665–5675, https://doi.org/10.5194/acp-17-5665-2017, https://doi.org/10.5194/acp-17-5665-2017, 2017
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The inverse modelling approach for estimating surface fluxes is based on transport models that have an imperfect representation of atmospheric processes like vertical mixing. In this paper, we show how assimilating commercial aircraft-based vertical profiles of CO2 into inverse models can help reduce error due to the transport model, thus providing more accurate estimates of surface fluxes. Further, the reduction in flux uncertainty due to aircraft profiles from the IAGOS project is quantified.
Tea Thum, Sönke Zaehle, Philipp Köhler, Tuula Aalto, Mika Aurela, Luis Guanter, Pasi Kolari, Tuomas Laurila, Annalea Lohila, Federico Magnani, Christiaan Van Der Tol, and Tiina Markkanen
Biogeosciences, 14, 1969–1987, https://doi.org/10.5194/bg-14-1969-2017, https://doi.org/10.5194/bg-14-1969-2017, 2017
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Modelling seasonal cycle at the coniferous forests poses a challenge. We implemented a model for sun-induced chlorophyll fluorescence (SIF) to a land surface model JSBACH. It was used to study the seasonality of the carbon cycle in the Fenno-Scandinavian region. Comparison was made to direct CO2 flux measurements and satellite observations of SIF. SIF proved to be a better proxy for photosynthesis than the fraction of absorbed photosynthetically active radiation.
Martina Franz, David Simpson, Almut Arneth, and Sönke Zaehle
Biogeosciences, 14, 45–71, https://doi.org/10.5194/bg-14-45-2017, https://doi.org/10.5194/bg-14-45-2017, 2017
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Ozone is a toxic air pollutant that can damage plant leaves and impact their carbon uptake from the atmosphere. We extend a terrestrial biosphere model to account for ozone damage of plants and investigate the impact on the terrestrial carbon cycle. Our approach accounts for ozone transport from the free troposphere to leaf level. We find that this substantially affects simulated ozone uptake into the plants. Simulations indicate that ozone damages plants less than expected from previous studies
Sander Houweling, Peter Bergamaschi, Frederic Chevallier, Martin Heimann, Thomas Kaminski, Maarten Krol, Anna M. Michalak, and Prabir Patra
Atmos. Chem. Phys., 17, 235–256, https://doi.org/10.5194/acp-17-235-2017, https://doi.org/10.5194/acp-17-235-2017, 2017
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The aim of this paper is to present an overview of inverse modeling methods, developed over the years, for estimating the global sources and sinks of the greenhouse gas methane from atmospheric measurements. It provides insight into how techniques and estimates have evolved over time, what the remaining shortcomings are, new developments, and promising future directions.
Hanna K. Lappalainen, Veli-Matti Kerminen, Tuukka Petäjä, Theo Kurten, Aleksander Baklanov, Anatoly Shvidenko, Jaana Bäck, Timo Vihma, Pavel Alekseychik, Meinrat O. Andreae, Stephen R. Arnold, Mikhail Arshinov, Eija Asmi, Boris Belan, Leonid Bobylev, Sergey Chalov, Yafang Cheng, Natalia Chubarova, Gerrit de Leeuw, Aijun Ding, Sergey Dobrolyubov, Sergei Dubtsov, Egor Dyukarev, Nikolai Elansky, Kostas Eleftheriadis, Igor Esau, Nikolay Filatov, Mikhail Flint, Congbin Fu, Olga Glezer, Aleksander Gliko, Martin Heimann, Albert A. M. Holtslag, Urmas Hõrrak, Juha Janhunen, Sirkku Juhola, Leena Järvi, Heikki Järvinen, Anna Kanukhina, Pavel Konstantinov, Vladimir Kotlyakov, Antti-Jussi Kieloaho, Alexander S. Komarov, Joni Kujansuu, Ilmo Kukkonen, Ella-Maria Duplissy, Ari Laaksonen, Tuomas Laurila, Heikki Lihavainen, Alexander Lisitzin, Alexsander Mahura, Alexander Makshtas, Evgeny Mareev, Stephany Mazon, Dmitry Matishov, Vladimir Melnikov, Eugene Mikhailov, Dmitri Moisseev, Robert Nigmatulin, Steffen M. Noe, Anne Ojala, Mari Pihlatie, Olga Popovicheva, Jukka Pumpanen, Tatjana Regerand, Irina Repina, Aleksei Shcherbinin, Vladimir Shevchenko, Mikko Sipilä, Andrey Skorokhod, Dominick V. Spracklen, Hang Su, Dmitry A. Subetto, Junying Sun, Arkady Y. Terzhevik, Yuri Timofeyev, Yuliya Troitskaya, Veli-Pekka Tynkkynen, Viacheslav I. Kharuk, Nina Zaytseva, Jiahua Zhang, Yrjö Viisanen, Timo Vesala, Pertti Hari, Hans Christen Hansson, Gennady G. Matvienko, Nikolai S. Kasimov, Huadong Guo, Valery Bondur, Sergej Zilitinkevich, and Markku Kulmala
Atmos. Chem. Phys., 16, 14421–14461, https://doi.org/10.5194/acp-16-14421-2016, https://doi.org/10.5194/acp-16-14421-2016, 2016
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After kick off in 2012, the Pan-Eurasian Experiment (PEEX) program has expanded fast and today the multi-disciplinary research community covers ca. 80 institutes and a network of ca. 500 scientists from Europe, Russia, and China. Here we introduce scientific topics relevant in this context. This is one of the first multi-disciplinary overviews crossing scientific boundaries, from atmospheric sciences to socio-economics and social sciences.
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.
Christoph Zellweger, Lukas Emmenegger, Mohd Firdaus, Juha Hatakka, Martin Heimann, Elena Kozlova, T. Gerard Spain, Martin Steinbacher, Marcel V. van der Schoot, and Brigitte Buchmann
Atmos. Meas. Tech., 9, 4737–4757, https://doi.org/10.5194/amt-9-4737-2016, https://doi.org/10.5194/amt-9-4737-2016, 2016
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We compared instruments using more traditional techniques for measuring CO2 and CH4 at different stations of the Global Atmosphere Watch (GAW) programme with a travelling instrument using a spectroscopic technique. Our results show that the newer analytical techniques have clear advantages over the traditional methods which will lead to the improved accuracy of atmospheric CO2 and CH4 measurement. The work was carried out in the framework of the GAW quality assurance/quality control system.
Fanny Kittler, Ina Burjack, Chiara A. R. Corradi, Martin Heimann, Olaf Kolle, Lutz Merbold, Nikita Zimov, Sergey Zimov, and Mathias Göckede
Biogeosciences, 13, 5315–5332, https://doi.org/10.5194/bg-13-5315-2016, https://doi.org/10.5194/bg-13-5315-2016, 2016
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We compared growing season CO2 fluxes of a wet tussock tundra ecosystem from an area affected by decadal drainage and an undisturbed area on the Kolyma floodplain in northeastern Siberia. The results show systematically reduced CO2 uptake within the drained area, caused by increased respiration, and that the local permafrost ecosystem is capable of adapting to significantly different hydrologic conditions without losing its capacity to act as a net sink for CO2.
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.
Chris D. Jones, Vivek Arora, Pierre Friedlingstein, Laurent Bopp, Victor Brovkin, John Dunne, Heather Graven, Forrest Hoffman, Tatiana Ilyina, Jasmin G. John, Martin Jung, Michio Kawamiya, Charlie Koven, Julia Pongratz, Thomas Raddatz, James T. Randerson, and Sönke Zaehle
Geosci. Model Dev., 9, 2853–2880, https://doi.org/10.5194/gmd-9-2853-2016, https://doi.org/10.5194/gmd-9-2853-2016, 2016
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How the carbon cycle interacts with climate will affect future climate change and how society plans emissions reductions to achieve climate targets. The Coupled Climate Carbon Cycle Model Intercomparison Project (C4MIP) is an endorsed activity of CMIP6 and aims to quantify these interactions and feedbacks in state-of-the-art climate models. This paper lays out the experimental protocol for modelling groups to follow to contribute to C4MIP. It is a contribution to the CMIP6 GMD Special Issue.
Min Jung Kwon, Martin Heimann, Olaf Kolle, Kristina A. Luus, Edward A. G. Schuur, Nikita Zimov, Sergey A. Zimov, and Mathias Göckede
Biogeosciences, 13, 4219–4235, https://doi.org/10.5194/bg-13-4219-2016, https://doi.org/10.5194/bg-13-4219-2016, 2016
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A decade-long drainage on an Arctic floodplain has altered dominant plant species and soil temperature regimes. Consequently, CO2 exchange rates between the atmosphere and the terrestrial ecosystem were modified: CO2 uptake rates by the terrestrial ecosystem decreased and CO2 emission rates to the atmosphere increased. Ongoing global warming may thaw ice-rich permafrost and make some regions drier in the Arctic, and this will reduce carbon accumulation in the terrestrial ecosystem.
Lisa R. Welp, Prabir K. Patra, Christian Rödenbeck, Rama Nemani, Jian Bi, Stephen C. Piper, and Ralph F. Keeling
Atmos. Chem. Phys., 16, 9047–9066, https://doi.org/10.5194/acp-16-9047-2016, https://doi.org/10.5194/acp-16-9047-2016, 2016
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Boreal and arctic ecosystems have been responding to elevated temperatures and atmospheric CO2 over the last decades. It is not clear if these ecosystems are sequestering more carbon or possibly becoming sources. This is an important feedback of the carbon cycle to global warming. We studied monthly biological land CO2 fluxes inferred from atmospheric CO2 concentrations using inverse models and found that net summer CO2 uptake increased, resulting in a small increase in annual CO2 uptake.
Anna B. Harper, Peter M. Cox, Pierre Friedlingstein, Andy J. Wiltshire, Chris D. Jones, Stephen Sitch, Lina M. Mercado, Margriet Groenendijk, Eddy Robertson, Jens Kattge, Gerhard Bönisch, Owen K. Atkin, Michael Bahn, Johannes Cornelissen, Ülo Niinemets, Vladimir Onipchenko, Josep Peñuelas, Lourens Poorter, Peter B. Reich, Nadjeda A. Soudzilovskaia, and Peter van Bodegom
Geosci. Model Dev., 9, 2415–2440, https://doi.org/10.5194/gmd-9-2415-2016, https://doi.org/10.5194/gmd-9-2415-2016, 2016
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Dynamic global vegetation models (DGVMs) are used to predict the response of vegetation to climate change. We improved the representation of carbon uptake by ecosystems in a DGVM by including a wider range of trade-offs between nutrient allocation to photosynthetic capacity and leaf structure, based on observed plant traits from a worldwide data base. The improved model has higher rates of photosynthesis and net C uptake by plants, and more closely matches observations at site and global scales.
Johannes Meyerholt, Sönke Zaehle, and Matthew J. Smith
Biogeosciences, 13, 1491–1518, https://doi.org/10.5194/bg-13-1491-2016, https://doi.org/10.5194/bg-13-1491-2016, 2016
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We investigated how today's state-of-the-art terrestrial biosphere models represent biological nitrogen fixation and what the consequences of varying representation are for model predictions under ambient conditions and under scenarios of elevated atmospheric carbon dioxide concentrations. We found that varying global nitrogen fixation rates are simulated under ambient conditions and that the responses of the simulated carbon and nitrogen cycles are significantly affected under perturbation.
Dmitry A. Belikov, Shamil Maksyutov, Alexey Yaremchuk, Alexander Ganshin, Thomas Kaminski, Simon Blessing, Motoki Sasakawa, Angel J. Gomez-Pelaez, and Alexander Starchenko
Geosci. Model Dev., 9, 749–764, https://doi.org/10.5194/gmd-9-749-2016, https://doi.org/10.5194/gmd-9-749-2016, 2016
S. Sippel, F. E. L. Otto, M. Forkel, M. R. Allen, B. P. Guillod, M. Heimann, M. Reichstein, S. I. Seneviratne, K. Thonicke, and M. D. Mahecha
Earth Syst. Dynam., 7, 71–88, https://doi.org/10.5194/esd-7-71-2016, https://doi.org/10.5194/esd-7-71-2016, 2016
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We introduce a novel technique to bias correct climate model output for impact simulations that preserves its physical consistency and multivariate structure. The methodology considerably improves the representation of extremes in climatic variables relative to conventional bias correction strategies. Illustrative simulations of biosphere–atmosphere carbon and water fluxes with a biosphere model (LPJmL) show that the novel technique can be usefully applied to drive climate impact models.
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).
D. Fowler, C. E. Steadman, D. Stevenson, M. Coyle, R. M. Rees, U. M. Skiba, M. A. Sutton, J. N. Cape, A. J. Dore, M. Vieno, D. Simpson, S. Zaehle, B. D. Stocker, M. Rinaldi, M. C. Facchini, C. R. Flechard, E. Nemitz, M. Twigg, J. W. Erisman, K. Butterbach-Bahl, and J. N. Galloway
Atmos. Chem. Phys., 15, 13849–13893, https://doi.org/10.5194/acp-15-13849-2015, https://doi.org/10.5194/acp-15-13849-2015, 2015
C. Rödenbeck, D. C. E. Bakker, N. Gruber, Y. Iida, A. R. Jacobson, S. Jones, P. Landschützer, N. Metzl, S. Nakaoka, A. Olsen, G.-H. Park, P. Peylin, K. B. Rodgers, T. P. Sasse, U. Schuster, J. D. Shutler, V. Valsala, R. Wanninkhof, and J. Zeng
Biogeosciences, 12, 7251–7278, https://doi.org/10.5194/bg-12-7251-2015, https://doi.org/10.5194/bg-12-7251-2015, 2015
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This study investigates variations in the CO2 uptake of the ocean from year to year. These variations have been calculated from measurements of the surface-ocean carbon content by various different interpolation methods. The equatorial Pacific is estimated to be the region with the strongest year-to-year variations, tied to the El Nino phase. The global ocean CO2 uptake gradually increased from about the year 2000. The comparison of the interpolation methods identifies these findings as robust.
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. Olin, M. Lindeskog, T. A. M. Pugh, G. Schurgers, D. Wårlind, M. Mishurov, S. Zaehle, B. D. Stocker, B. Smith, and A. Arneth
Earth Syst. Dynam., 6, 745–768, https://doi.org/10.5194/esd-6-745-2015, https://doi.org/10.5194/esd-6-745-2015, 2015
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Croplands are vital ecosystems for human well-being. Properly managed they can supply food, store carbon and even sequester carbon from the atmosphere. Conversely, if poorly managed, croplands can be a source of nitrogen to inland and coastal waters, causing algal blooms, and a source of carbon dioxide to the atmosphere, accentuating climate change. Here we studied cropland management types for their potential to store carbon and minimize nitrogen losses while maintaining crop yields.
O. Perez-Priego, J. Guan, M. Rossini, F. Fava, T. Wutzler, G. Moreno, N. Carvalhais, A. Carrara, O. Kolle, T. Julitta, M. Schrumpf, M. Reichstein, and M. Migliavacca
Biogeosciences, 12, 6351–6367, https://doi.org/10.5194/bg-12-6351-2015, https://doi.org/10.5194/bg-12-6351-2015, 2015
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Sun-induced chlorophyll fluorescence and photochemical reflectance index revealed controls of climate and nutrient availability on photosynthesis (gross primary production, GPP). Meteo-driven models (MMs) were unable to describe nutrient-induced effects on GPP. Important implications can be derived from these results, and uncertainties in the prediction of global GPP still remain when MMs do not account for plant nutrient availability.
M. O. Andreae, O. C. Acevedo, A. Araùjo, P. Artaxo, C. G. G. Barbosa, H. M. J. Barbosa, J. Brito, S. Carbone, X. Chi, B. B. L. Cintra, N. F. da Silva, N. L. Dias, C. Q. Dias-Júnior, F. Ditas, R. Ditz, A. F. L. Godoi, R. H. M. Godoi, M. Heimann, T. Hoffmann, J. Kesselmeier, T. Könemann, M. L. Krüger, J. V. Lavric, A. O. Manzi, A. P. Lopes, D. L. Martins, E. F. Mikhailov, D. Moran-Zuloaga, B. W. Nelson, A. C. Nölscher, D. Santos Nogueira, M. T. F. Piedade, C. Pöhlker, U. Pöschl, C. A. Quesada, L. V. Rizzo, C.-U. Ro, N. Ruckteschler, L. D. A. Sá, M. de Oliveira Sá, C. B. Sales, R. M. N. dos Santos, J. Saturno, J. Schöngart, M. Sörgel, C. M. de Souza, R. A. F. de Souza, H. Su, N. Targhetta, J. Tóta, I. Trebs, S. Trumbore, A. van Eijck, D. Walter, Z. Wang, B. Weber, J. Williams, J. Winderlich, F. Wittmann, S. Wolff, and A. M. Yáñez-Serrano
Atmos. Chem. Phys., 15, 10723–10776, https://doi.org/10.5194/acp-15-10723-2015, https://doi.org/10.5194/acp-15-10723-2015, 2015
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This paper describes the Amazon Tall Tower Observatory (ATTO), a new atmosphere-biosphere observatory located in the remote Amazon Basin. It presents results from ecosystem ecology, meteorology, trace gas, and aerosol measurements collected at the ATTO site during the first 3 years of operation.
T. Kaminski, F. Kauker, H. Eicken, and M. Karcher
The Cryosphere, 9, 1721–1733, https://doi.org/10.5194/tc-9-1721-2015, https://doi.org/10.5194/tc-9-1721-2015, 2015
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We present a quantitative network design study of the Arctic sea ice-ocean system. For a demonstration, we evaluate two idealised hypothetical flight transects derived from NASA’s Operation IceBridge airborne ice surveys in terms of their potential to improve 10-day to 5-month sea ice forecasts. Our analysis quantifies the benefits of sampling upstream of the target area and of reducing the sampling uncertainty. It further quantifies the complementarity of combining two flight transects.
K. Naudts, J. Ryder, M. J. McGrath, J. Otto, Y. Chen, A. Valade, V. Bellasen, G. Berhongaray, G. Bönisch, M. Campioli, J. Ghattas, T. De Groote, V. Haverd, J. Kattge, N. MacBean, F. Maignan, P. Merilä, J. Penuelas, P. Peylin, B. Pinty, H. Pretzsch, E. D. Schulze, D. Solyga, N. Vuichard, Y. Yan, and S. Luyssaert
Geosci. Model Dev., 8, 2035–2065, https://doi.org/10.5194/gmd-8-2035-2015, https://doi.org/10.5194/gmd-8-2035-2015, 2015
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Despite the potential of forest management to mitigate climate change, none of today's predictions of future climate accounts for the impact of forest management. To address this gap in modelling capability, we developed and parametrised a land-surface model to simulate biogeochemical and biophysical effects of forest management. Comparison of model output against data showed an increased model performance in reproducing large-scale spatial patterns and inter-annual variability over Europe.
S. Hashimoto, N. Carvalhais, A. Ito, M. Migliavacca, K. Nishina, and M. Reichstein
Biogeosciences, 12, 4121–4132, https://doi.org/10.5194/bg-12-4121-2015, https://doi.org/10.5194/bg-12-4121-2015, 2015
E. J. Morgan, J. V. Lavrič, T. Seifert, T. Chicoine, A. Day, J. Gomez, R. Logan, J. Sack, T. Shuuya, E. G. Uushona, K. Vincent, U. Schultz, E.-G. Brunke, C. Labuschagne, R. L. Thompson, S. Schmidt, A. C. Manning, and M. Heimann
Atmos. Meas. Tech., 8, 2233–2250, https://doi.org/10.5194/amt-8-2233-2015, https://doi.org/10.5194/amt-8-2233-2015, 2015
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We describe the analytical techniques used in the creation of a new background site for continuous measurements of greenhouse gases, carbon monoxide, and atmospheric oxygen in the Namib Desert. The measurement system is semi-automated and optimized for operation in a remote locale. Measurement uncertainties, gas handling, calibration schemes, drift corrections, and instrument performance are discussed.
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.
M. Forkel, N. Carvalhais, S. Schaphoff, W. v. Bloh, M. Migliavacca, M. Thurner, and K. Thonicke
Biogeosciences, 11, 7025–7050, https://doi.org/10.5194/bg-11-7025-2014, https://doi.org/10.5194/bg-11-7025-2014, 2014
C. Rödenbeck, D. C. E. Bakker, N. Metzl, A. Olsen, C. Sabine, N. Cassar, F. Reum, R. F. Keeling, and M. Heimann
Biogeosciences, 11, 4599–4613, https://doi.org/10.5194/bg-11-4599-2014, https://doi.org/10.5194/bg-11-4599-2014, 2014
S. Kemp, M. Scholze, T. Ziehn, and T. Kaminski
Geosci. Model Dev., 7, 1609–1619, https://doi.org/10.5194/gmd-7-1609-2014, https://doi.org/10.5194/gmd-7-1609-2014, 2014
P. Ciais, A. J. Dolman, A. Bombelli, R. Duren, A. Peregon, P. J. Rayner, C. Miller, N. Gobron, G. Kinderman, G. Marland, N. Gruber, F. Chevallier, R. J. Andres, G. Balsamo, L. Bopp, F.-M. Bréon, G. Broquet, R. Dargaville, T. J. Battin, A. Borges, H. Bovensmann, M. Buchwitz, J. Butler, J. G. Canadell, R. B. Cook, R. DeFries, R. Engelen, K. R. Gurney, C. Heinze, M. Heimann, A. Held, M. Henry, B. Law, S. Luyssaert, J. Miller, T. Moriyama, C. Moulin, R. B. Myneni, C. Nussli, M. Obersteiner, D. Ojima, Y. Pan, J.-D. Paris, S. L. Piao, B. Poulter, S. Plummer, S. Quegan, P. Raymond, M. Reichstein, L. Rivier, C. Sabine, D. Schimel, O. Tarasova, R. Valentini, R. Wang, G. van der Werf, D. Wickland, M. Williams, and C. Zehner
Biogeosciences, 11, 3547–3602, https://doi.org/10.5194/bg-11-3547-2014, https://doi.org/10.5194/bg-11-3547-2014, 2014
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
J. Winderlich, C. Gerbig, O. Kolle, and M. Heimann
Biogeosciences, 11, 2055–2068, https://doi.org/10.5194/bg-11-2055-2014, https://doi.org/10.5194/bg-11-2055-2014, 2014
B. Smith, D. Wårlind, A. Arneth, T. Hickler, P. Leadley, J. Siltberg, and S. Zaehle
Biogeosciences, 11, 2027–2054, https://doi.org/10.5194/bg-11-2027-2014, https://doi.org/10.5194/bg-11-2027-2014, 2014
W. Knorr, T. Kaminski, A. Arneth, and U. Weber
Biogeosciences, 11, 1085–1102, https://doi.org/10.5194/bg-11-1085-2014, https://doi.org/10.5194/bg-11-1085-2014, 2014
M. Heimann
Earth Syst. Dynam., 5, 41–42, https://doi.org/10.5194/esd-5-41-2014, https://doi.org/10.5194/esd-5-41-2014, 2014
X. Chi, J. Winderlich, J.-C. Mayer, A. V. Panov, M. Heimann, W. Birmili, J. Heintzenberg, Y. Cheng, and M. O. Andreae
Atmos. Chem. Phys., 13, 12271–12298, https://doi.org/10.5194/acp-13-12271-2013, https://doi.org/10.5194/acp-13-12271-2013, 2013
P. Peylin, R. M. Law, K. R. Gurney, F. Chevallier, A. R. Jacobson, T. Maki, Y. Niwa, P. K. Patra, W. Peters, P. J. Rayner, C. Rödenbeck, I. T. van der Laan-Luijkx, and X. Zhang
Biogeosciences, 10, 6699–6720, https://doi.org/10.5194/bg-10-6699-2013, https://doi.org/10.5194/bg-10-6699-2013, 2013
T. J. Bohn, E. Podest, R. Schroeder, N. Pinto, K. C. McDonald, M. Glagolev, I. Filippov, S. Maksyutov, M. Heimann, X. Chen, and D. P. Lettenmaier
Biogeosciences, 10, 6559–6576, https://doi.org/10.5194/bg-10-6559-2013, https://doi.org/10.5194/bg-10-6559-2013, 2013
B. Badawy, C. Rödenbeck, M. Reichstein, N. Carvalhais, and M. Heimann
Biogeosciences, 10, 6485–6508, https://doi.org/10.5194/bg-10-6485-2013, https://doi.org/10.5194/bg-10-6485-2013, 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
L. M. Verheijen, V. Brovkin, R. Aerts, G. Bönisch, J. H. C. Cornelissen, J. Kattge, P. B. Reich, I. J. Wright, and P. M. van Bodegom
Biogeosciences, 10, 5497–5515, https://doi.org/10.5194/bg-10-5497-2013, https://doi.org/10.5194/bg-10-5497-2013, 2013
A. Lenton, B. Tilbrook, R. M. Law, D. Bakker, S. C. Doney, N. Gruber, M. Ishii, M. Hoppema, N. S. Lovenduski, R. J. Matear, B. I. McNeil, N. Metzl, S. E. Mikaloff Fletcher, P. M. S. Monteiro, C. Rödenbeck, C. Sweeney, and T. Takahashi
Biogeosciences, 10, 4037–4054, https://doi.org/10.5194/bg-10-4037-2013, https://doi.org/10.5194/bg-10-4037-2013, 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
C. Rödenbeck, R. F. Keeling, D. C. E. Bakker, N. Metzl, A. Olsen, C. Sabine, and M. Heimann
Ocean Sci., 9, 193–216, https://doi.org/10.5194/os-9-193-2013, https://doi.org/10.5194/os-9-193-2013, 2013
U. Schuster, G. A. McKinley, N. Bates, F. Chevallier, S. C. Doney, A. R. Fay, M. González-Dávila, N. Gruber, S. Jones, J. Krijnen, P. Landschützer, N. Lefèvre, M. Manizza, J. Mathis, N. Metzl, A. Olsen, A. F. Rios, C. Rödenbeck, J. M. Santana-Casiano, T. Takahashi, R. Wanninkhof, and A. J. Watson
Biogeosciences, 10, 607–627, https://doi.org/10.5194/bg-10-607-2013, https://doi.org/10.5194/bg-10-607-2013, 2013
M. C. Braakhekke, T. Wutzler, C. Beer, J. Kattge, M. Schrumpf, B. Ahrens, I. Schöning, M. R. Hoosbeek, B. Kruijt, P. Kabat, and M. Reichstein
Biogeosciences, 10, 399–420, https://doi.org/10.5194/bg-10-399-2013, https://doi.org/10.5194/bg-10-399-2013, 2013
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Testing stomatal models at the stand level in deciduous angiosperm and evergreen gymnosperm forests using CliMA Land (v0.1)
Comparing an exponential respiration model to alternative models for soil respiration components in a Canadian wildfire chronosequence (FireResp v1.0)
Accounting for forest management in the estimation of forest carbon balance using the dynamic vegetation model LPJ-GUESS (v4.0, r9710): implementation and evaluation of simulations for Europe
FABM-NflexPD 1.0: assessing an instantaneous acclimation approach for modeling phytoplankton growth
A model for marine sedimentary carbonate diagenesis and paleoclimate proxy signal tracking: IMP v1.0
Using the International Tree-Ring Data Bank (ITRDB) records as century-long benchmarks for global land-surface models
A model-independent data assimilation (MIDA) module and its applications in ecology
Optical model for the Baltic Sea with an explicit CDOM state variable: a case study with Model ERGOM (version 1.2)
WAP-1D-VAR v1.0: development and evaluation of a one-dimensional variational data assimilation model for the marine ecosystem along the West Antarctic Peninsula
SCOPE 2.0: a model to simulate vegetated land surface fluxes and satellite signals
SolveSAPHE-r2 (v2.0.1): revisiting and extending the Solver Suite for Alkalinity-PH Equations for usage with CO2, HCO3− or CO32− input data
Modeling gas exchange and biomass production in West African Sahelian and Sudanian ecological zones
Partitioning soil organic carbon into its centennially stable and active fractions with machine-learning models based on Rock-Eval® thermal analysis (PARTYSOCv2.0 and PARTYSOCv2.0EU)
Addressing biases in Arctic–boreal carbon cycling in the Community Land Model Version 5
Modeling the short-term fire effects on vegetation dynamics and surface energy in Southern Africa using the improved SSiB4/TRIFFID-Fire model
Performance analysis of regional AquaCrop (v6.1) biomass and surface soil moisture simulations using satellite and in situ observations
Cutting out the middleman: calibrating and validating a dynamic vegetation model (ED2-PROSPECT5) using remotely sensed surface reflectance
Ecosystem age-class dynamics and distribution in the LPJ-wsl v2.0 global ecosystem model
CLASSIC v1.0: the open-source community successor to the Canadian Land Surface Scheme (CLASS) and the Canadian Terrestrial Ecosystem Model (CTEM) – Part 2: Global benchmarking
How to reconstruct aerosol-induced diffuse radiation scenario for simulating GPP in land surface models? An evaluation of reconstruction methods with ORCHIDEE_DFv1.0_DFforc
SPEAD 1.0 – Simulating Plankton Evolution with Adaptive Dynamics in a two-trait continuous fitness landscape applied to the Sargasso Sea
Rapid development of fast and flexible environmental models: the Mobius framework v1.0
Potential yield simulated by global gridded crop models: using a process-based emulator to explain their differences
Integrated modeling of canopy photosynthesis, fluorescence, and the transfer of energy, mass, and momentum in the soil–plant–atmosphere continuum (STEMMUS–SCOPE v1.0.0)
OMEN-SED(-RCM) (v1.1): A pseudo reactive continuum representation of organic matter degradation dynamics for OMEN-SED
CoupModel (v6.0): an ecosystem model for coupled phosphorus, nitrogen, and carbon dynamics – evaluated against empirical data from a climatic and fertility gradient in Sweden
Improving the representation of cropland sites in the Community Land Model (CLM) version 5.0
Numerical model to simulate long-term soil organic carbon and ground ice budget with permafrost and ice sheets (SOC-ICE-v1.0)
Calibrating soybean parameters in JULES 5.0 from the US-Ne2/3 FLUXNET sites and the SoyFACE-O3 experiment
Modeling long-term fire impact on ecosystem characteristics and surface energy using a process-based vegetation–fire model SSiB4/TRIFFID-Fire v1.0
Energy, water and carbon exchanges in managed forest ecosystems: description, sensitivity analysis and evaluation of the INRAE GO+ model, version 3.0
Improving Yasso15 soil carbon model estimates with ensemble adjustment Kalman filter state data assimilation
Oceanic and atmospheric methane cycling in the cGENIE Earth system model – release v0.9.14
Modeling the impacts of diffuse light fraction on photosynthesis in ORCHIDEE (v5453) land surface model
Description and evaluation of the process-based forest model 4C v2.2 at four European forest sites
A multi-isotope model for simulating soil organic carbon cycling in eroding landscapes (WATEM_C v1.0)
One-dimensional models of radiation transfer in heterogeneous canopies: a review, re-evaluation, and improved model
An improved mechanistic model for ammonia volatilization in Earth system models: Flow of Agricultural Nitrogen version 2 (FANv2)
Stoichiometrically coupled carbon and nitrogen cycling in the MIcrobial-MIneral Carbon Stabilization model version 1.0 (MIMICS-CN v1.0)
Explicit silicate cycling in the Kiel Marine Biogeochemistry Model, version 3 (KMBM3) embedded in the UVic ESCM version 2.9
Short-term forecasting of regional biospheric CO2 fluxes in Europe using a light-use-efficiency model (VPRM, MPI-BGC version 1.2)
FLiES-SIF version 1.0: three-dimensional radiative transfer model for estimating solar induced fluorescence
The importance of management information and soil moisture representation for simulating tillage effects on N2O emissions in LPJmL5.0-tillage
Evaluation of CH4MODwetland and Terrestrial Ecosystem Model (TEM) used to estimate global CH4 emissions from natural wetlands
Simulating stable carbon isotopes in the ocean component of the FAMOUS general circulation model with MOSES1 (XOAVI)
Quantitative assessment of fire and vegetation properties in simulations with fire-enabled vegetation models from the Fire Model Intercomparison Project
BioRT-Flux-PIHM v1.0: a watershed biogeochemical reactive transport model
Marine biogeochemical cycling and oceanic CO2 uptake simulated by the NUIST Earth System Model version 3 (NESM v3)
CLASSIC v1.0: the open-source community successor to the Canadian Land Surface Scheme (CLASS) and the Canadian Terrestrial Ecosystem Model (CTEM) – Part 1: Model framework and site-level performance
HR3DHG version 1: modeling the spatiotemporal dynamics of mercury in the Augusta Bay (southern Italy)
Yujie Wang, Philipp Köhler, Liyin He, Russell Doughty, Renato K. Braghiere, Jeffrey D. Wood, and Christian Frankenberg
Geosci. Model Dev., 14, 6741–6763, https://doi.org/10.5194/gmd-14-6741-2021, https://doi.org/10.5194/gmd-14-6741-2021, 2021
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We present the first step in testing a new land model as part of a new Earth system model. Our model links plant hydraulics, stomatal optimization theory, and a comprehensive canopy radiation scheme. We compared model-predicted carbon and water fluxes to flux tower observations and model-predicted sun-induced chlorophyll fluorescence to satellite retrievals. Our model quantitatively predicted the carbon and water fluxes as well as the canopy fluorescence yield.
John Zobitz, Heidi Aaltonen, Xuan Zhou, Frank Berninger, Jukka Pumpanen, and Kajar Köster
Geosci. Model Dev., 14, 6605–6622, https://doi.org/10.5194/gmd-14-6605-2021, https://doi.org/10.5194/gmd-14-6605-2021, 2021
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Forest fires heavily affect carbon stocks and fluxes of carbon in high-latitude forests. Long-term trends in soil respiration following forest fires are associated with recovery of aboveground biomass. We evaluated models for soil autotrophic and heterotrophic respiration with data from a chronosequence of stand-replacing forest fires in northern Canada. The best model that reproduced expected patterns in soil respiration components takes into account soil microbe carbon as a model variable.
Mats Lindeskog, Benjamin Smith, Fredrik Lagergren, Ekaterina Sycheva, Andrej Ficko, Hans Pretzsch, and Anja Rammig
Geosci. Model Dev., 14, 6071–6112, https://doi.org/10.5194/gmd-14-6071-2021, https://doi.org/10.5194/gmd-14-6071-2021, 2021
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Forests play an important role in the global carbon cycle and for carbon storage. In Europe, forests are intensively managed. To understand how management influences carbon storage in European forests, we implement detailed forest management into the dynamic vegetation model LPJ-GUESS. We test the model by comparing model output to typical forestry measures, such as growing stock and harvest data, for different countries in Europe.
Onur Kerimoglu, Prima Anugerahanti, and Sherwood Lan Smith
Geosci. Model Dev., 14, 6025–6047, https://doi.org/10.5194/gmd-14-6025-2021, https://doi.org/10.5194/gmd-14-6025-2021, 2021
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In large-scale models, variations in cellular composition of phytoplankton are often insufficiently represented. Detailed modeling approaches exist, but they require additional state variables that increase the computational costs. In this study, we test an instantaneous acclimation model in a spatially explicit setup and show that its behavior is mostly similar to that of a variant with an additional state variable but different from that of a fixed composition variant.
Yoshiki Kanzaki, Dominik Hülse, Sandra Kirtland Turner, and Andy Ridgwell
Geosci. Model Dev., 14, 5999–6023, https://doi.org/10.5194/gmd-14-5999-2021, https://doi.org/10.5194/gmd-14-5999-2021, 2021
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Sedimentary carbonate plays a central role in regulating Earth’s carbon cycle and climate, and also serves as an archive of paleoenvironments, hosting various trace elements/isotopes. To help obtain
trueenvironmental changes from carbonate records over diagenetic distortion, IMP has been newly developed and has the capability to simulate the diagenesis of multiple carbonate particles and implement different styles of particle mixing by benthos using an adapted transition matrix method.
Jina Jeong, Jonathan Barichivich, Philippe Peylin, Vanessa Haverd, Matthew Joseph McGrath, Nicolas Vuichard, Michael Neil Evans, Flurin Babst, and Sebastiaan Luyssaert
Geosci. Model Dev., 14, 5891–5913, https://doi.org/10.5194/gmd-14-5891-2021, https://doi.org/10.5194/gmd-14-5891-2021, 2021
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We have proposed and evaluated the use of four benchmarks that leverage tree-ring width observations to provide more nuanced verification targets for land-surface models (LSMs), which currently lack a long-term benchmark for forest ecosystem functioning. Using relatively unbiased European biomass network datasets, we identify the extent to which presumed biases in the much larger International Tree-Ring Data Bank might degrade the validation of LSMs.
Xin Huang, Dan Lu, Daniel M. Ricciuto, Paul J. Hanson, Andrew D. Richardson, Xuehe Lu, Ensheng Weng, Sheng Nie, Lifen Jiang, Enqing Hou, Igor F. Steinmacher, and Yiqi Luo
Geosci. Model Dev., 14, 5217–5238, https://doi.org/10.5194/gmd-14-5217-2021, https://doi.org/10.5194/gmd-14-5217-2021, 2021
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In the data-rich era, data assimilation is widely used to integrate abundant observations into models to reduce uncertainty in ecological forecasting. However, applications of data assimilation are restricted by highly technical requirements. To alleviate this technical burden, we developed a model-independent data assimilation (MIDA) module which is friendly to ecologists with limited programming skills. MIDA also supports a flexible switch of different models or observations in DA analysis.
Thomas Neumann, Sampsa Koponen, Jenni Attila, Carsten Brockmann, Kari Kallio, Mikko Kervinen, Constant Mazeran, Dagmar Müller, Petra Philipson, Susanne Thulin, Sakari Väkevä, and Pasi Ylöstalo
Geosci. Model Dev., 14, 5049–5062, https://doi.org/10.5194/gmd-14-5049-2021, https://doi.org/10.5194/gmd-14-5049-2021, 2021
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The Baltic Sea is heavily impacted by surrounding land. Therefore, the concentration of colored dissolved organic matter (CDOM) of terrestrial origin is relatively high and impacts the light penetration depth. Estimating a correct light climate is essential for ecosystem models. In this study, a method is developed to derive riverine CDOM from Earth observation methods. The data are used as boundary conditions for an ecosystem model, and the advantage over former approaches is shown.
Hyewon Heather Kim, Ya-Wei Luo, Hugh W. Ducklow, Oscar M. Schofield, Deborah K. Steinberg, and Scott C. Doney
Geosci. Model Dev., 14, 4939–4975, https://doi.org/10.5194/gmd-14-4939-2021, https://doi.org/10.5194/gmd-14-4939-2021, 2021
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The West Antarctic Peninsula (WAP) is a rapidly warming region, revealed by multi-decadal observations. Despite the region being data rich, there is a lack of focus on ecosystem model development. Here, we introduce a data assimilation ecosystem model for the WAP region. Experiments by assimilating data from an example growth season capture key WAP features. This study enables us to glue the snapshots from available data sets together to explain the observations in the WAP.
Peiqi Yang, Egor Prikaziuk, Wout Verhoef, and Christiaan van der Tol
Geosci. Model Dev., 14, 4697–4712, https://doi.org/10.5194/gmd-14-4697-2021, https://doi.org/10.5194/gmd-14-4697-2021, 2021
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Since the first publication 12 years ago, the SCOPE model has been applied in remote sensing studies of solar-induced chlorophyll fluorescence (SIF), energy balance fluxes, gross primary productivity (GPP), and directional thermal signals. Here, we present a thoroughly revised version, SCOPE 2.0, which features a number of new elements.
Guy Munhoven
Geosci. Model Dev., 14, 4225–4240, https://doi.org/10.5194/gmd-14-4225-2021, https://doi.org/10.5194/gmd-14-4225-2021, 2021
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SolveSAPHE (Munhoven, 2013) was the first package to calculate pH reliably from any physically sensible pair of total alkalinity (AlkT) and dissolved inorganic carbon (CT) data and to do so in an autonomous and efficient way. Here, we extend it to use CO2, HCO3 or CO3 instead of CT. For each one of these pairs, the new SolveSAPHE calculates all of the possible pH values (0, 1, or 2), again without any prior knowledge of the solutions.
Jaber Rahimi, Expedit Evariste Ago, Augustine Ayantunde, Sina Berger, Jan Bogaert, Klaus Butterbach-Bahl, Bernard Cappelaere, Jean-Martial Cohard, Jérôme Demarty, Abdoul Aziz Diouf, Ulrike Falk, Edwin Haas, Pierre Hiernaux, David Kraus, Olivier Roupsard, Clemens Scheer, Amit Kumar Srivastava, Torbern Tagesson, and Rüdiger Grote
Geosci. Model Dev., 14, 3789–3812, https://doi.org/10.5194/gmd-14-3789-2021, https://doi.org/10.5194/gmd-14-3789-2021, 2021
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West African Sahelian and Sudanian ecosystems are important regions for global carbon exchange, and they provide valuable food and fodder resources. Therefore, we simulated net ecosystem exchange and aboveground biomass of typical ecosystems in this region with an improved process-based biogeochemical model, LandscapeDNDC. Carbon stocks and exchange rates were particularly correlated with the abundance of trees. Grass and crop yields increased under humid climatic conditions.
Lauric Cécillon, François Baudin, Claire Chenu, Bent T. Christensen, Uwe Franko, Sabine Houot, Eva Kanari, Thomas Kätterer, Ines Merbach, Folkert van Oort, Christopher Poeplau, Juan Carlos Quezada, Florence Savignac, Laure N. Soucémarianadin, and Pierre Barré
Geosci. Model Dev., 14, 3879–3898, https://doi.org/10.5194/gmd-14-3879-2021, https://doi.org/10.5194/gmd-14-3879-2021, 2021
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Partitioning soil organic carbon (SOC) into fractions that are stable or active on a century scale is key for more accurate models of the carbon cycle. Here, we describe the second version of a machine-learning model, named PARTYsoc, which reliably predicts the proportion of the centennially stable SOC fraction at its northwestern European validation sites with Cambisols and Luvisols, the two dominant soil groups in this region, fostering modelling works of SOC dynamics.
Leah Birch, Christopher R. Schwalm, Sue Natali, Danica Lombardozzi, Gretchen Keppel-Aleks, Jennifer Watts, Xin Lin, Donatella Zona, Walter Oechel, Torsten Sachs, Thomas Andrew Black, and Brendan M. Rogers
Geosci. Model Dev., 14, 3361–3382, https://doi.org/10.5194/gmd-14-3361-2021, https://doi.org/10.5194/gmd-14-3361-2021, 2021
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The high-latitude landscape or Arctic–boreal zone has been warming rapidly, impacting the carbon balance both regionally and globally. Given the possible global effects of climate change, it is important to have accurate climate model simulations. We assess the simulation of the Arctic–boreal carbon cycle in the Community Land Model (CLM 5.0). We find biases in both the timing and magnitude photosynthesis. We then use observational data to improve the simulation of the carbon cycle.
Huilin Huang, Yongkang Xue, Ye Liu, Fang Li, and Gregory Okin
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2021-116, https://doi.org/10.5194/gmd-2021-116, 2021
Revised manuscript accepted for GMD
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This study applies a fire-coupled dynamic vegetation model to quantify the fire impact at monthly to annual scales. We find fire reduces grass cover by 4–8 % annually for widespread areas in Southern Africa savanna and reduces tree cover by 1 % at the periphery of tropical Congolese rainforest. The grass cover reduction peaks at the beginning of the rainy season which quickly diminishes before the next fire season. In contrast, the reduction of tree cover is irreversible within one growing season.
Shannon de Roos, Gabriëlle J. M. De Lannoy, and Dirk Raes
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2021-98, https://doi.org/10.5194/gmd-2021-98, 2021
Revised manuscript accepted for GMD
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A spatially distributed version of the field-scale crop model AquaCrop v6.1 was developed for applications at various spatial scales. Multi-year 1-km simulations over Europe were evaluated against biomass and surface soil moisture products derived from optical and microwave satellite missions, and in situ observations of soil moisture. Even when using easily accessible global input data, the model is able to capture the temporal and spatial variability at the field to regional scale.
Alexey N. Shiklomanov, Michael C. Dietze, Istem Fer, Toni Viskari, and Shawn P. Serbin
Geosci. Model Dev., 14, 2603–2633, https://doi.org/10.5194/gmd-14-2603-2021, https://doi.org/10.5194/gmd-14-2603-2021, 2021
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Airborne and satellite images are a great resource for calibrating and evaluating computer models of ecosystems. Typically, researchers derive ecosystem properties from these images and then compare models against these derived properties. Here, we present an alternative approach where we modify a model to predict what the satellite would see more directly. We then show how this approach can be used to calibrate model parameters using airborne data from forest sites in the northeastern US.
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.
Christian Seiler, Joe R. Melton, Vivek K. Arora, and Libo Wang
Geosci. Model Dev., 14, 2371–2417, https://doi.org/10.5194/gmd-14-2371-2021, https://doi.org/10.5194/gmd-14-2371-2021, 2021
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This study evaluates how well the CLASSIC land surface model reproduces the energy, water, and carbon cycle when compared against a wide range of global observations. Special attention is paid to how uncertainties in the data used to drive and evaluate the model affect model skill. Our results show the importance of incorporating uncertainties when evaluating land surface models and that failing to do so may potentially misguide future model development.
Yuan Zhang, Olivier Boucher, Philippe Ciais, Laurent Li, and Nicolas Bellouin
Geosci. Model Dev., 14, 2029–2039, https://doi.org/10.5194/gmd-14-2029-2021, https://doi.org/10.5194/gmd-14-2029-2021, 2021
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We investigated different methods to reconstruct spatiotemporal distribution of the fraction of diffuse radiation (Fdf) to qualify the aerosol impacts on GPP using the ORCHIDEE_DF land surface model. We find that climatological-averaging methods which dampen the variability of Fdf can cause significant bias in the modeled diffuse radiation impacts on GPP. Better methods to reconstruct Fdf are recommended.
Guillaume Le Gland, Sergio M. Vallina, S. Lan Smith, and Pedro Cermeño
Geosci. Model Dev., 14, 1949–1985, https://doi.org/10.5194/gmd-14-1949-2021, https://doi.org/10.5194/gmd-14-1949-2021, 2021
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We present an ecological model called SPEAD wherein various phytoplankton compete for nutrients. Phytoplankton in SPEAD are characterized by two continuously distributed traits: optimal temperature and nutrient half-saturation. Trait diversity is sustained by allowing the traits to mutate at each generation. We show that SPEAD agrees well with a more classical discrete model for only a fraction of the cost. We also identify realistic values for the mutation rates to be used in future models.
Magnus Dahler Norling, Leah Amber Jackson-Blake, José-Luis Guerrero Calidonio, and James Edward Sample
Geosci. Model Dev., 14, 1885–1897, https://doi.org/10.5194/gmd-14-1885-2021, https://doi.org/10.5194/gmd-14-1885-2021, 2021
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In order to allow researchers to quickly prototype and build models of natural systems, we have created the Mobius framework. Such models can, for instance, be used to ask questions about what the impacts of land-use changes are to water quality in a river or lake, or the response of biogeochemical systems to climate change. The Mobius framework makes it quick to build models that run fast, which enables the user to explore many different scenarios and model formulations.
Bruno Ringeval, Christoph Müller, Thomas A. M. Pugh, Nathaniel D. Mueller, Philippe Ciais, Christian Folberth, Wenfeng Liu, Philippe Debaeke, and Sylvain Pellerin
Geosci. Model Dev., 14, 1639–1656, https://doi.org/10.5194/gmd-14-1639-2021, https://doi.org/10.5194/gmd-14-1639-2021, 2021
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We assess how and why global gridded crop models (GGCMs) differ in their simulation of potential yield. We build a GCCM emulator based on generic formalism and fit its parameters against aboveground biomass and yield at harvest simulated by eight GGCMs. Despite huge differences between GGCMs, we show that the calibration of a few key parameters allows the emulator to reproduce the GGCM simulations. Our simple but mechanistic model could help to improve the global simulation of potential yield.
Yunfei Wang, Yijian Zeng, Lianyu Yu, Peiqi Yang, Christiaan Van der Tol, Qiang Yu, Xiaoliang Lü, Huanjie Cai, and Zhongbo Su
Geosci. Model Dev., 14, 1379–1407, https://doi.org/10.5194/gmd-14-1379-2021, https://doi.org/10.5194/gmd-14-1379-2021, 2021
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This study integrates photosynthesis and transfer of energy, mass, and momentum in the soil–plant–atmosphere continuum system, via a simplified 1D root growth model. The results indicated that the simulation of land surface fluxes was significantly improved by considering the root water uptake, especially when vegetation was experiencing severe water stress. This finding highlights the importance of enhanced soil heat and moisture transfer in simulating ecosystem functioning.
Philip Pika, Dominik Hülse, and Sandra Arndt
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2021-4, https://doi.org/10.5194/gmd-2021-4, 2021
Revised manuscript accepted for GMD
Hongxing He, Per-Erik Jansson, and Annemieke I. Gärdenäs
Geosci. Model Dev., 14, 735–761, https://doi.org/10.5194/gmd-14-735-2021, https://doi.org/10.5194/gmd-14-735-2021, 2021
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This study presents the integration of the phosphorus (P) cycle into CoupModel (v6.0, Coup-CNP). The extended Coup-CNP, which explicitly considers the symbiosis between soil microbes and plant roots, enables simulations of coupled C, N, and P dynamics for terrestrial ecosystems. Simulations from the new Coup-CNP model provide strong evidence that P fluxes need to be further considered in studies of how ecosystems and C turnover react to climate change.
Theresa Boas, Heye Bogena, Thomas Grünwald, Bernard Heinesch, Dongryeol Ryu, Marius Schmidt, Harry Vereecken, Andrew Western, and Harrie-Jan Hendricks Franssen
Geosci. Model Dev., 14, 573–601, https://doi.org/10.5194/gmd-14-573-2021, https://doi.org/10.5194/gmd-14-573-2021, 2021
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In this study we were able to significantly improve CLM5 model performance for European cropland sites by adding a winter wheat representation, specific plant parameterizations for important cash crops, and a cover-cropping and crop rotation subroutine to its crop module. Our modifications should be applied in future studies of CLM5 to improve regional yield predictions and to better understand large-scale impacts of agricultural management on carbon, water, and energy fluxes.
Kazuyuki Saito, Hirokazu Machiya, Go Iwahana, Tokuta Yokohata, and Hiroshi Ohno
Geosci. Model Dev., 14, 521–542, https://doi.org/10.5194/gmd-14-521-2021, https://doi.org/10.5194/gmd-14-521-2021, 2021
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Soil organic carbon (SOC) and ground ice (ICE) are essential but under-documented information to assess the circum-Arctic permafrost degradation impacts. A simple numerical model of essential SOC and ICE dynamics, developed and integrated north of 50° N for 125,000 years since the last interglacial, reconstructed the history and 1° distribution of SOC and ICE consistent with current knowledge, together with successful demonstration of climatic and topographical controls on SOC evolution.
Felix Leung, Karina Williams, Stephen Sitch, Amos P. K. Tai, Andy Wiltshire, Jemma Gornall, Elizabeth A. Ainsworth, Timothy Arkebauer, and David Scoby
Geosci. Model Dev., 13, 6201–6213, https://doi.org/10.5194/gmd-13-6201-2020, https://doi.org/10.5194/gmd-13-6201-2020, 2020
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Ground-level ozone (O3) is detrimental to plant productivity and crop yield. Currently, the Joint UK Land Environment Simulator (JULES) includes a representation of crops (JULES-crop). The parameters for O3 damage in soybean in JULES-crop were calibrated against photosynthesis measurements from the Soybean Free Air Concentration Enrichment (SoyFACE). The result shows good performance for yield, and it helps contribute to understanding of the impacts of climate and air pollution on food security.
Huilin Huang, Yongkang Xue, Fang Li, and Ye Liu
Geosci. Model Dev., 13, 6029–6050, https://doi.org/10.5194/gmd-13-6029-2020, https://doi.org/10.5194/gmd-13-6029-2020, 2020
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We developed a fire-coupled dynamic vegetation model that captures the spatial distribution, temporal variability, and especially the seasonal variability of fire regimes. The fire model is applied to assess the long-term fire impact on ecosystems and surface energy. We find that fire is an important determinant of the structure and function of the tropical savanna. By changing the vegetation composition and ecosystem characteristics, fire significantly alters surface energy balance.
Virginie Moreaux, Simon Martel, Alexandre Bosc, Delphine Picart, David Achat, Christophe Moisy, Raphael Aussenac, Christophe Chipeaux, Jean-Marc Bonnefond, Soisick Figuères, Pierre Trichet, Rémi Vezy, Vincent Badeau, Bernard Longdoz, André Granier, Olivier Roupsard, Manuel Nicolas, Kim Pilegaard, Giorgio Matteucci, Claudy Jolivet, Andrew T. Black, Olivier Picard, and Denis Loustau
Geosci. Model Dev., 13, 5973–6009, https://doi.org/10.5194/gmd-13-5973-2020, https://doi.org/10.5194/gmd-13-5973-2020, 2020
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The model GO+ describes the functioning of managed forests based upon biophysical and biogeochemical processes. It accounts for the impacts of forest operations on energy, water and carbon exchanges within the soil–vegetation–atmosphere continuum. It includes versatile descriptions of management operations. Its sensitivity and uncertainty are detailed and predictions are compared with observations about mass and energy exchanges, hydrological data, and tree growth variables from different sites.
Toni Viskari, Maisa Laine, Liisa Kulmala, Jarmo Mäkelä, Istem Fer, and Jari Liski
Geosci. Model Dev., 13, 5959–5971, https://doi.org/10.5194/gmd-13-5959-2020, https://doi.org/10.5194/gmd-13-5959-2020, 2020
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The research here established whether a Bayesian statistical method called state data assimilation could be used to improve soil organic carbon (SOC) forecasts. Our test case was a fallow experiment where SOC content was measured over several decades from a plot where all vegetation was removed. Our results showed that state data assimilation improved projections and allowed for the detailed model state be updated with coarse total carbon measurements.
Christopher T. Reinhard, Stephanie L. Olson, Sandra Kirtland Turner, Cecily Pälike, Yoshiki Kanzaki, and Andy Ridgwell
Geosci. Model Dev., 13, 5687–5706, https://doi.org/10.5194/gmd-13-5687-2020, https://doi.org/10.5194/gmd-13-5687-2020, 2020
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We provide documentation and testing of new developments for the oceanic and atmospheric methane cycles in the cGENIE Earth system model. The model is designed to explore Earth's methane cycle across a wide range of timescales and scenarios, in particular assessing the mean climate state and climate perturbations in Earth's deep past. We further document the impact of atmospheric oxygen levels and ocean chemistry on fluxes of methane to the atmosphere from the ocean biosphere.
Yuan Zhang, Ana Bastos, Fabienne Maignan, Daniel Goll, Olivier Boucher, Laurent Li, Alessandro Cescatti, Nicolas Vuichard, Xiuzhi Chen, Christof Ammann, M. Altaf Arain, T. Andrew Black, Bogdan Chojnicki, Tomomichi Kato, Ivan Mammarella, Leonardo Montagnani, Olivier Roupsard, Maria J. Sanz, Lukas Siebicke, Marek Urbaniak, Francesco Primo Vaccari, Georg Wohlfahrt, Will Woodgate, and Philippe Ciais
Geosci. Model Dev., 13, 5401–5423, https://doi.org/10.5194/gmd-13-5401-2020, https://doi.org/10.5194/gmd-13-5401-2020, 2020
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We improved the ORCHIDEE LSM by distinguishing diffuse and direct light in canopy and evaluated the new model with observations from 159 sites. Compared with the old model, the new model has better sunny GPP and reproduced the diffuse light fertilization effect observed at flux sites. Our simulations also indicate different mechanisms causing the observed GPP enhancement under cloudy conditions at different times. The new model has the potential to study large-scale impacts of aerosol changes.
Petra Lasch-Born, Felicitas Suckow, Christopher P. O. Reyer, Martin Gutsch, Chris Kollas, Franz-Werner Badeck, Harald K. M. Bugmann, Rüdiger Grote, Cornelia Fürstenau, Marcus Lindner, and Jörg Schaber
Geosci. Model Dev., 13, 5311–5343, https://doi.org/10.5194/gmd-13-5311-2020, https://doi.org/10.5194/gmd-13-5311-2020, 2020
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The process-based model 4C has been developed to study climate impacts on forests and is now freely available as an open-source tool. This paper provides a comprehensive description of the 4C version (v2.2) for scientific users of the model and presents an evaluation of 4C. The evaluation focused on forest growth, carbon water, and heat fluxes. We conclude that 4C is widely applicable, reliable, and ready to be released to the scientific community to use and further develop the model.
Zhengang Wang, Jianxiu Qiu, and Kristof Van Oost
Geosci. Model Dev., 13, 4977–4992, https://doi.org/10.5194/gmd-13-4977-2020, https://doi.org/10.5194/gmd-13-4977-2020, 2020
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This study developed a spatially distributed carbon cycling model applicable in an eroding landscape. It includes all three carbon isotopes so that it is able to represent the carbon isotopic compositions. The model is able to represent the observations that eroding area is enriched in 13C and depleted of 14C compared to depositional area. Our simulations show that the spatial variability of carbon isotopic properties in an eroding landscape is mainly caused by the soil redistribution.
Brian N. Bailey, María A. Ponce de León, and E. Scott Krayenhoff
Geosci. Model Dev., 13, 4789–4808, https://doi.org/10.5194/gmd-13-4789-2020, https://doi.org/10.5194/gmd-13-4789-2020, 2020
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Numerous models of plant radiation interception based on a range of assumptions are available in the literature, but the importance of each assumption is not well understood. In this work, we evaluate several assumptions common in simple models of radiation interception in canopies with widely spaced plants by comparing against a detailed 3-D model. This yielded a simple model based on readily measurable parameters that could accurately predict interception for a wide range of architectures.
Julius Vira, Peter Hess, Jeff Melkonian, and William R. Wieder
Geosci. Model Dev., 13, 4459–4490, https://doi.org/10.5194/gmd-13-4459-2020, https://doi.org/10.5194/gmd-13-4459-2020, 2020
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Mostly emitted by the agricultural sector, ammonia has an important role in atmospheric chemistry. We developed a model to simulate how ammonia emissions respond to changes in temperature and soil moisture, and we evaluated agricultural ammonia emissions globally. The simulated emissions agree with earlier estimates over many regions, but the results highlight the variability of ammonia emissions and suggest that emissions in warm climates may be higher than previously thought.
Emily Kyker-Snowman, William R. Wieder, Serita D. Frey, and A. Stuart Grandy
Geosci. Model Dev., 13, 4413–4434, https://doi.org/10.5194/gmd-13-4413-2020, https://doi.org/10.5194/gmd-13-4413-2020, 2020
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Microbes drive carbon (C) and nitrogen (N) transformations in soil, and soil models have started to include explicit microbial physiology and functioning to try to reduce uncertainty in soil–climate feedbacks. Here, we add N cycling to a microbially explicit soil C model and reproduce C and N dynamics in soil during litter decomposition across a range of sites. We discuss model-generated hypotheses about soil C and N cycling and highlight the need for landscape-scale model evaluation data.
Karin Kvale, David P. Keller, Wolfgang Koeve, Katrin J. Meissner, Chris Somes, Wanxuan Yao, and Andreas Oschlies
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-235, https://doi.org/10.5194/gmd-2020-235, 2020
Revised manuscript accepted for GMD
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We present a new model of biological marine silicate cycling for the University of Victoria Earth System Climate Model (UVic ESCM). This new model adds diatoms, which are a key aspect of the biological carbon pump, to an existing ecosystem model. Our modifications change how the model responds to warming, with net primary production declining more strongly than in previous versions. Diatoms in particular are simulated to decline with climate warming due to their high nutrient requirements.
Jinxuan Chen, Christoph Gerbig, Julia Marshall, and Kai Uwe Totsche
Geosci. Model Dev., 13, 4091–4106, https://doi.org/10.5194/gmd-13-4091-2020, https://doi.org/10.5194/gmd-13-4091-2020, 2020
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One of the essential challenge for atmospheric CO2 forecasting is predicting CO2 flux variation on synoptic timescale. For CAMS CO2 forecast, a process-based vegetation model is used.
In this research we evaluate another type of model (i.e., the light-use-efficiency model VPRM), which is a data-driven approach and thus ideal for realistic estimation, on its ability of flux prediction. Errors from different sources are assessed, and overall the model is capable of CO2 flux prediction.
Yuma Sakai, Hideki Kobayashi, and Tomomichi Kato
Geosci. Model Dev., 13, 4041–4066, https://doi.org/10.5194/gmd-13-4041-2020, https://doi.org/10.5194/gmd-13-4041-2020, 2020
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Chlorophyll fluorescence is one of the energy release pathways of excess incident light in the photosynthetic process. The canopy-scale Sun-induced chlorophyll fluorescence (SIF), which potentially provides a direct pathway to link leaf-level photosynthesis to global GPP, can be observed from satellites. We develop the three-dimensional Monte Carlo plant canopy radiative transfer model to understand the biological and physical mechanisms behind SIF emission from complex forest canopies.
Femke Lutz, Stephen Del Grosso, Stephen Ogle, Stephen Williams, Sara Minoli, Susanne Rolinski, Jens Heinke, Jetse J. Stoorvogel, and Christoph Müller
Geosci. Model Dev., 13, 3905–3923, https://doi.org/10.5194/gmd-13-3905-2020, https://doi.org/10.5194/gmd-13-3905-2020, 2020
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Previous findings have shown deviations between the LPJmL5.0-tillage model and results from meta-analyses on global estimates of tillage effects on N2O emissions. By comparing model results with observational data of four experimental sites and outputs from field-scale DayCent model simulations, we show that advancing information on agricultural management, as well as the representation of soil moisture dynamics, improves LPJmL5.0-tillage and the estimates of tillage effects on N2O emissions.
Tingting Li, Yanyu Lu, Lingfei Yu, Wenjuan Sun, Qing Zhang, Wen Zhang, Guocheng Wang, Zhangcai Qin, Lijun Yu, Hailing Li, and Ran Zhang
Geosci. Model Dev., 13, 3769–3788, https://doi.org/10.5194/gmd-13-3769-2020, https://doi.org/10.5194/gmd-13-3769-2020, 2020
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Reliable models are required to estimate global wetland CH4 emissions, which are the largest and most uncertain source of atmospheric CH4. This paper evaluated CH4MODwetland and TEM models against CH4 measurements from different continents and wetland types. Based on best-model performance, we estimated 117–125 Tg yr−1 of global CH4 emissions from wetlands for the period 2000–2010. Efforts should be made to reduce estimate uncertainties for different wetland types and regions.
Jennifer E. Dentith, Ruza F. Ivanovic, Lauren J. Gregoire, Julia C. Tindall, and Laura F. Robinson
Geosci. Model Dev., 13, 3529–3552, https://doi.org/10.5194/gmd-13-3529-2020, https://doi.org/10.5194/gmd-13-3529-2020, 2020
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We have added a new tracer (13C) into the ocean of the FAMOUS climate model to study large-scale circulation and the marine carbon cycle. The model captures the large-scale spatial pattern of observations but the simulated values are consistently higher than observed. In the first instance, our new tracer is therefore useful for recalibrating the physical and biogeochemical components of the model.
Stijn Hantson, Douglas I. Kelley, Almut Arneth, Sandy P. Harrison, Sally Archibald, Dominique Bachelet, Matthew Forrest, Thomas Hickler, Gitta Lasslop, Fang Li, Stephane Mangeon, Joe R. Melton, Lars Nieradzik, Sam S. Rabin, I. Colin Prentice, Tim Sheehan, Stephen Sitch, Lina Teckentrup, Apostolos Voulgarakis, and Chao Yue
Geosci. Model Dev., 13, 3299–3318, https://doi.org/10.5194/gmd-13-3299-2020, https://doi.org/10.5194/gmd-13-3299-2020, 2020
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Global fire–vegetation models are widely used, but there has been limited evaluation of how well they represent various aspects of fire regimes. Here we perform a systematic evaluation of simulations made by nine FireMIP models in order to quantify their ability to reproduce a range of fire and vegetation benchmarks. While some FireMIP models are better at representing certain aspects of the fire regime, no model clearly outperforms all other models across the full range of variables assessed.
Wei Zhi, Yuning Shi, Hang Wen, Leila Saberi, Gene-Hua Crystal Ng, and Li Li
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-157, https://doi.org/10.5194/gmd-2020-157, 2020
Revised manuscript accepted for GMD
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Watersheds are the fundamental Earth surface functioning unit that connects the land to aquatic systems. Here we present a recently developed BioRT-Flux-PIHM (BFP) v1.0, a watershed-scale biogeochemical reactive transport model to improve our ability to understand and predict solute export and water quality. The model has been verified against the benchmark code CrunchTope and has recently been applied to understand reactive transport processes in multiple watersheds of different conditions.
Yifei Dai, Long Cao, and Bin Wang
Geosci. Model Dev., 13, 3119–3144, https://doi.org/10.5194/gmd-13-3119-2020, https://doi.org/10.5194/gmd-13-3119-2020, 2020
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NESM v3 is one of the CMIP6 registered Earth system models. We evaluate its ocean carbon cycle component and present its present-day and future oceanic CO2 uptake based on the CMIP6 historical and SSP5–8.5 scenarios. We hope that this paper can serve as a documentation of the marine biogeochemical cycle in NESM v3. Also, the model defects found and their underlying causes analyzed in this paper could help users and further model development.
Joe R. Melton, Vivek K. Arora, Eduard Wisernig-Cojoc, Christian Seiler, Matthew Fortier, Ed Chan, and Lina Teckentrup
Geosci. Model Dev., 13, 2825–2850, https://doi.org/10.5194/gmd-13-2825-2020, https://doi.org/10.5194/gmd-13-2825-2020, 2020
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We transitioned the CLASS-CTEM land surface model to an open-source community model format by modernizing the code base to make the model easier to use and understand, providing a complete software environment to run the model within, developing a benchmarking suite for model evaluation, and creating an infrastructure to support community involvement. The new model, the Canadian Land Surface Scheme including Biogeochemical Cycles (CLASSIC), is now available for the community to use and develop.
Giovanni Denaro, Daniela Salvagio Manta, Alessandro Borri, Maria Bonsignore, Davide Valenti, Enza Quinci, Andrea Cucco, Bernardo Spagnolo, Mario Sprovieri, and Andrea De Gaetano
Geosci. Model Dev., 13, 2073–2093, https://doi.org/10.5194/gmd-13-2073-2020, https://doi.org/10.5194/gmd-13-2073-2020, 2020
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The HR3DHG (high-resolution 3D mercury model) investigates the spatiotemporal behavior, in seawater and marine sediments, of three mercury species (elemental, inorganic, and organic mercury) in a highly polluted marine environment (Augusta Bay, southern Italy). The model shows fair agreement with the experimental data collected during six different oceanographic cruises and can possibly be used for a detailed exploration of the effects of climate change on mercury distribution.
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Short summary
We describe the Max Planck Institute Carbon Cycle Data Assimilation System (MPI-CCDAS). The system improves the modelled carbon cycle of the terrestrial biosphere by systematically confronting (or assimilating) the model with observations of atmospheric CO2 and fractions of absorbed photosynthetically active radiation. Jointly assimilating both data streams outperforms the single-data stream experiments, thus showing the value of a multi-data stream assimilation.
We describe the Max Planck Institute Carbon Cycle Data Assimilation System (MPI-CCDAS). The...
