Articles | Volume 9, issue 2
https://doi.org/10.5194/gmd-9-479-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-9-479-2016
© 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
| 
08 Feb 2016
Development and technical paper |
| 08 Feb 2016
Validation of 3D-CMCC Forest Ecosystem Model (v.5.1) against eddy covariance data for 10 European forest sites
Euro-Mediterranean Center on Climate Change – Division on
Impacts on Agriculture, Forests and Ecosystem Services (IAFES), 01100
Viterbo, Italy
University of Tuscia – Department for Innovation in
Biological, Agro-Food and Forest Systems (DIBAF), 01100 Viterbo,
Italy
S. Marconi
Euro-Mediterranean Center on Climate Change – Division on
Impacts on Agriculture, Forests and Ecosystem Services (IAFES), 01100
Viterbo, Italy
University of Tuscia – Department for Innovation in
Biological, Agro-Food and Forest Systems (DIBAF), 01100 Viterbo,
Italy
Centre for Ecosystems and Environmental Sustainability,
Dept. Chem. Engineering, Technical University of Denmark (DTU), Roskilde,
Denmark
C. Trotta
University of Tuscia – Department for Innovation in
Biological, Agro-Food and Forest Systems (DIBAF), 01100 Viterbo,
Italy
A. Anav
College of Engineering, Mathematics, and Physical
Sciences, University of Exeter, Exeter, UK
E. D'Andrea
CNR-IBAF – National Research Council of Italy, Institute
of Agroenvironmental and Forest Biology, 00015 Monterotondo Scalo, RM,
Italy
G. Matteucci
CNR-IBAF – National Research Council of Italy, Institute
of Agroenvironmental and Forest Biology, 00015 Monterotondo Scalo, RM,
Italy
CNR-ISAFOM – National Research Council of Italy,
Institute for Agriculture and Forestry Systems in the Mediterranean, 87036
Rende, CS, Italy
L. Montagnani
Forest Services, Autonomous Province of Bolzano, 39100,
Bolzano, Italy; and Faculty of Science and Technology, Free University of
Bolzano, Piazza Università 5, 39100 Bolzano, Italy
B. Gielen
Research Group of Plant and Vegetation Ecology, Department
of Biology, University of Antwerp, Belgium
I. Mammarella
University of Helsinki – Department of Physics, Division
of Atmospheric Sciences, 00014 Helsinki, Finland
T. Grünwald
Technische Universität (TU) Dresden, Institute of
Hydrology and Meteorology, Chair of Meteorology, 01062 Dresden,
Germany
Bioclimatology, Faculty of Forest Sciences and Forest
Ecology, Georg-August University of Göttingen, Büsgenweg 2, 37077 Göttingen, Germany
F. Berninger
Department of Forest Sciences, University of Helsinki,
POBox 27, 00014, Helsinki
Y. Zhao
LOCEAN/IPSL, UMR 7159, Sorbonne Universitès,
Unitè mixte UPMC-CNRS-IRD-MNHN, 4 place Jussieu, 75005, Paris,
France
R. Valentini
Euro-Mediterranean Center on Climate Change – Division on
Impacts on Agriculture, Forests and Ecosystem Services (IAFES), 01100
Viterbo, Italy
University of Tuscia – Department for Innovation in
Biological, Agro-Food and Forest Systems (DIBAF), 01100 Viterbo,
Italy
M. Santini
Euro-Mediterranean Center on Climate Change – Division on
Impacts on Agriculture, Forests and Ecosystem Services (IAFES), 01100
Viterbo, Italy
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Kim A. P. Faassen, Linh N. T. Nguyen, Eadin R. Broekema, Bert A. M. Kers, Ivan Mammarella, Timo Vesala, Penelope A. Pickers, Andrew C. Manning, Jordi Vilà-Guerau de Arellano, Harro A. J. Meijer, Wouter Peters, and Ingrid T. Luijkx
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Xin Yu, René Orth, Markus Reichstein, Michael Bahn, Anne Klosterhalfen, Alexander Knohl, Franziska Koebsch, Mirco Migliavacca, Martina Mund, Jacob A. Nelson, Benjamin D. Stocker, Sophia Walther, and Ana Bastos
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Joonatan Ala-Könni, Kukka-Maaria Kohonen, Matti Leppäranta, and Ivan Mammarella
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Malgorzata Golub, Wim Thiery, Rafael Marcé, Don Pierson, Inne Vanderkelen, Daniel Mercado-Bettin, R. Iestyn Woolway, Luke Grant, Eleanor Jennings, Benjamin M. Kraemer, Jacob Schewe, Fang Zhao, Katja Frieler, Matthias Mengel, Vasiliy Y. Bogomolov, Damien Bouffard, Marianne Côté, Raoul-Marie Couture, Andrey V. Debolskiy, Bram Droppers, Gideon Gal, Mingyang Guo, Annette B. G. Janssen, Georgiy Kirillin, Robert Ladwig, Madeline Magee, Tadhg Moore, Marjorie Perroud, Sebastiano Piccolroaz, Love Raaman Vinnaa, Martin Schmid, Tom Shatwell, Victor M. Stepanenko, Zeli Tan, Bronwyn Woodward, Huaxia Yao, Rita Adrian, Mathew Allan, Orlane Anneville, Lauri Arvola, Karen Atkins, Leon Boegman, Cayelan Carey, Kyle Christianson, Elvira de Eyto, Curtis DeGasperi, Maria Grechushnikova, Josef Hejzlar, Klaus Joehnk, Ian D. Jones, Alo Laas, Eleanor B. Mackay, Ivan Mammarella, Hampus Markensten, Chris McBride, Deniz Özkundakci, Miguel Potes, Karsten Rinke, Dale Robertson, James A. Rusak, Rui Salgado, Leon van der Linden, Piet Verburg, Danielle Wain, Nicole K. Ward, Sabine Wollrab, and Galina Zdorovennova
Geosci. Model Dev., 15, 4597–4623, https://doi.org/10.5194/gmd-15-4597-2022, https://doi.org/10.5194/gmd-15-4597-2022, 2022
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Jarmo Mäkelä, Laila Melkas, Ivan Mammarella, Tuomo Nieminen, Suyog Chandramouli, Rafael Savvides, and Kai Puolamäki
Biogeosciences, 19, 2095–2099, https://doi.org/10.5194/bg-19-2095-2022, https://doi.org/10.5194/bg-19-2095-2022, 2022
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Causal structure discovery algorithms have been making headway into Earth system sciences, and they can be used to increase our understanding on biosphere–atmosphere interactions. In this paper we present a procedure on how to utilize prior knowledge of the domain experts together with these algorithms in order to find more robust causal structure models. We also demonstrate how to avoid pitfalls such as over-fitting and concept drift during this process.
Hanna K. Lappalainen, Tuukka Petäjä, Timo Vihma, Jouni Räisänen, Alexander Baklanov, Sergey Chalov, Igor Esau, Ekaterina Ezhova, Matti Leppäranta, Dmitry Pozdnyakov, Jukka Pumpanen, Meinrat O. Andreae, Mikhail Arshinov, Eija Asmi, Jianhui Bai, Igor Bashmachnikov, Boris Belan, Federico Bianchi, Boris Biskaborn, Michael Boy, Jaana Bäck, Bin Cheng, Natalia Chubarova, Jonathan Duplissy, Egor Dyukarev, Konstantinos Eleftheriadis, Martin Forsius, Martin Heimann, Sirkku Juhola, Vladimir Konovalov, Igor Konovalov, Pavel Konstantinov, Kajar Köster, Elena Lapshina, Anna Lintunen, Alexander Mahura, Risto Makkonen, Svetlana Malkhazova, Ivan Mammarella, Stefano Mammola, Stephany Buenrostro Mazon, Outi Meinander, Eugene Mikhailov, Victoria Miles, Stanislav Myslenkov, Dmitry Orlov, Jean-Daniel Paris, Roberta 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 Qiu, Aijun Ding, Huadong Guo, Valery Bondur, Nikolay Kasimov, Sergej Zilitinkevich, Veli-Matti Kerminen, and Markku Kulmala
Atmos. Chem. Phys., 22, 4413–4469, https://doi.org/10.5194/acp-22-4413-2022, https://doi.org/10.5194/acp-22-4413-2022, 2022
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We summarize results during the last 5 years in the northern Eurasian region, especially from Russia, and introduce recent observations of 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.
Timo Vesala, Kukka-Maaria Kohonen, Linda M. J. Kooijmans, Arnaud P. Praplan, Lenka Foltýnová, Pasi Kolari, Markku Kulmala, Jaana Bäck, David Nelson, Dan Yakir, Mark Zahniser, and Ivan Mammarella
Atmos. Chem. Phys., 22, 2569–2584, https://doi.org/10.5194/acp-22-2569-2022, https://doi.org/10.5194/acp-22-2569-2022, 2022
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Carbonyl sulfide (COS) provides new insights into carbon cycle research. We present an easy-to-use flux parameterization and the longest existing time series of forest–atmosphere COS exchange measurements, which allow us to study both seasonal and interannual variability. We observed only uptake of COS by the forest on an annual basis, with 37 % variability between years. Upscaling the boreal COS uptake using a biosphere model indicates a significant missing COS sink at high latitudes.
Anna-Maria Virkkala, Susan M. Natali, Brendan M. Rogers, Jennifer D. Watts, Kathleen Savage, Sara June Connon, Marguerite Mauritz, Edward A. G. Schuur, Darcy Peter, Christina Minions, Julia Nojeim, Roisin Commane, Craig A. Emmerton, Mathias Goeckede, Manuel Helbig, David Holl, Hiroki Iwata, Hideki Kobayashi, Pasi Kolari, Efrén López-Blanco, Maija E. Marushchak, Mikhail Mastepanov, Lutz Merbold, Frans-Jan W. Parmentier, Matthias Peichl, Torsten Sachs, Oliver Sonnentag, Masahito Ueyama, Carolina Voigt, Mika Aurela, Julia Boike, Gerardo Celis, Namyi Chae, Torben R. Christensen, M. Syndonia Bret-Harte, Sigrid Dengel, Han Dolman, Colin W. Edgar, Bo Elberling, Eugenie Euskirchen, Achim Grelle, Juha Hatakka, Elyn Humphreys, Järvi Järveoja, Ayumi Kotani, Lars Kutzbach, Tuomas Laurila, Annalea Lohila, Ivan Mammarella, Yojiro Matsuura, Gesa Meyer, Mats B. Nilsson, Steven F. Oberbauer, Sang-Jong Park, Roman Petrov, Anatoly S. Prokushkin, Christopher Schulze, Vincent L. St. Louis, Eeva-Stiina Tuittila, Juha-Pekka Tuovinen, William Quinton, Andrej Varlagin, Donatella Zona, and Viacheslav I. Zyryanov
Earth Syst. Sci. Data, 14, 179–208, https://doi.org/10.5194/essd-14-179-2022, https://doi.org/10.5194/essd-14-179-2022, 2022
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The effects of climate warming on carbon cycling across the Arctic–boreal zone (ABZ) remain poorly understood due to the relatively limited distribution of ABZ flux sites. Fortunately, this flux network is constantly increasing, but new measurements are published in various platforms, making it challenging to understand the ABZ carbon cycle as a whole. Here, we compiled a new database of Arctic–boreal CO2 fluxes to help facilitate large-scale assessments of the ABZ carbon cycle.
Linda M. J. Kooijmans, Ara Cho, Jin Ma, Aleya Kaushik, Katherine D. Haynes, Ian Baker, Ingrid T. Luijkx, Mathijs Groenink, Wouter Peters, John B. Miller, Joseph A. Berry, Jerome Ogée, Laura K. Meredith, Wu Sun, Kukka-Maaria Kohonen, Timo Vesala, Ivan Mammarella, Huilin Chen, Felix M. Spielmann, Georg Wohlfahrt, Max Berkelhammer, Mary E. Whelan, Kadmiel Maseyk, Ulli Seibt, Roisin Commane, Richard Wehr, and Maarten Krol
Biogeosciences, 18, 6547–6565, https://doi.org/10.5194/bg-18-6547-2021, https://doi.org/10.5194/bg-18-6547-2021, 2021
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The gas carbonyl sulfide (COS) can be used to estimate photosynthesis. To adopt this approach on regional and global scales, we need biosphere models that can simulate COS exchange. So far, such models have not been evaluated against observations. We evaluate the COS biosphere exchange of the SiB4 model against COS flux observations. We find that the model is capable of simulating key processes in COS biosphere exchange. Still, we give recommendations for further improvement of the model.
Auke J. Visser, Laurens N. Ganzeveld, Ignacio Goded, Maarten C. Krol, Ivan Mammarella, Giovanni Manca, and K. Folkert Boersma
Atmos. Chem. Phys., 21, 18393–18411, https://doi.org/10.5194/acp-21-18393-2021, https://doi.org/10.5194/acp-21-18393-2021, 2021
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Dry deposition is an important sink for tropospheric ozone that affects ecosystem carbon uptake, but process understanding remains incomplete. We apply a common deposition representation in atmospheric chemistry models and a multi-layer canopy model to multi-year ozone deposition observations. The multi-layer canopy model performs better on diurnal timescales compared to the common approach, leading to a substantially improved simulation of ozone deposition and vegetation ozone impact metrics.
Matthias Mauder, Andreas Ibrom, Luise Wanner, Frederik De Roo, Peter Brugger, Ralf Kiese, and Kim Pilegaard
Atmos. Meas. Tech., 14, 7835–7850, https://doi.org/10.5194/amt-14-7835-2021, https://doi.org/10.5194/amt-14-7835-2021, 2021
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Turbulent flux measurements suffer from a general systematic underestimation. One reason for this bias is non-local transport by large-scale circulations. A recently developed model for this additional transport of sensible and latent energy is evaluated for three different test sites. Different options on how to apply this correction are presented, and the results are evaluated against independent measurements.
Alex Resovsky, Michel Ramonet, Leonard Rivier, Jerome Tarniewicz, Philippe Ciais, Martin Steinbacher, Ivan Mammarella, Meelis Mölder, Michal Heliasz, Dagmar Kubistin, Matthias Lindauer, Jennifer Müller-Williams, Sebastien Conil, and Richard Engelen
Atmos. Meas. Tech., 14, 6119–6135, https://doi.org/10.5194/amt-14-6119-2021, https://doi.org/10.5194/amt-14-6119-2021, 2021
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We present a technical description of a statistical methodology for extracting synoptic- and seasonal-length anomalies from greenhouse gas time series. The definition of what represents an anomalous signal is somewhat subjective, which we touch on throughout the paper. We show, however, that the method performs reasonably well in extracting portions of time series influenced by significant North Atlantic Oscillation weather episodes and continent-wide terrestrial biospheric aberrations.
Pavel Alekseychik, Aino Korrensalo, Ivan Mammarella, Samuli Launiainen, Eeva-Stiina Tuittila, Ilkka Korpela, and Timo Vesala
Biogeosciences, 18, 4681–4704, https://doi.org/10.5194/bg-18-4681-2021, https://doi.org/10.5194/bg-18-4681-2021, 2021
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Bogs of northern Eurasia represent a major type of peatland ecosystem and contain vast amounts of carbon, but carbon balance monitoring studies on bogs are scarce. The current project explores 6 years of carbon balance data obtained using the state-of-the-art eddy-covariance technique at a Finnish bog Siikaneva. The results reveal relatively low interannual variability indicative of ecosystem resilience to both cool and hot summers and provide new insights into the seasonal course of C fluxes.
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.
Toprak Aslan, Olli Peltola, Andreas Ibrom, Eiko Nemitz, Üllar Rannik, and Ivan Mammarella
Atmos. Meas. Tech., 14, 5089–5106, https://doi.org/10.5194/amt-14-5089-2021, https://doi.org/10.5194/amt-14-5089-2021, 2021
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Vertical turbulent fluxes of gases measured by the eddy covariance (EC) technique are subject to high-frequency losses. There are different methods used to describe this low-pass filtering effect and to correct the measured fluxes. In this study, we analysed the systematic uncertainty related to this correction for various attenuation and signal-to-noise ratios. A new and robust transfer function method is finally proposed.
Olli Peltola, Toprak Aslan, Andreas Ibrom, Eiko Nemitz, Üllar Rannik, and Ivan Mammarella
Atmos. Meas. Tech., 14, 5071–5088, https://doi.org/10.5194/amt-14-5071-2021, https://doi.org/10.5194/amt-14-5071-2021, 2021
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Gas fluxes measured by the eddy covariance (EC) technique are subject to filtering due to non-ideal instrumentation. For linear first-order systems this filtering causes also a time lag between vertical wind speed and gas signal which is additional to the gas travel time in the sampling line. The effect of this additional time lag on EC fluxes is ignored in current EC data processing routines. Here we show that this oversight biases EC fluxes and hence propose an approach to rectify this bias.
Rafael Poyatos, Víctor Granda, Víctor Flo, Mark A. Adams, Balázs Adorján, David Aguadé, Marcos P. M. Aidar, Scott Allen, M. Susana Alvarado-Barrientos, Kristina J. Anderson-Teixeira, Luiza Maria Aparecido, M. Altaf Arain, Ismael Aranda, Heidi Asbjornsen, Robert Baxter, Eric Beamesderfer, Z. Carter Berry, Daniel Berveiller, Bethany Blakely, Johnny Boggs, Gil Bohrer, Paul V. Bolstad, Damien Bonal, Rosvel Bracho, Patricia Brito, Jason Brodeur, Fernando Casanoves, Jérôme Chave, Hui Chen, Cesar Cisneros, Kenneth Clark, Edoardo Cremonese, Hongzhong Dang, Jorge S. David, Teresa S. David, Nicolas Delpierre, Ankur R. Desai, Frederic C. Do, Michal Dohnal, Jean-Christophe Domec, Sebinasi Dzikiti, Colin Edgar, Rebekka Eichstaedt, Tarek S. El-Madany, Jan Elbers, Cleiton B. Eller, Eugénie S. Euskirchen, Brent Ewers, Patrick Fonti, Alicia Forner, David I. Forrester, Helber C. Freitas, Marta Galvagno, Omar Garcia-Tejera, Chandra Prasad Ghimire, Teresa E. Gimeno, John Grace, André Granier, Anne Griebel, Yan Guangyu, Mark B. Gush, Paul J. Hanson, Niles J. Hasselquist, Ingo Heinrich, Virginia Hernandez-Santana, Valentine Herrmann, Teemu Hölttä, Friso Holwerda, James Irvine, Supat Isarangkool Na Ayutthaya, Paul G. Jarvis, Hubert Jochheim, Carlos A. Joly, Julia Kaplick, Hyun Seok Kim, Leif Klemedtsson, Heather Kropp, Fredrik Lagergren, Patrick Lane, Petra Lang, Andrei Lapenas, Víctor Lechuga, Minsu Lee, Christoph Leuschner, Jean-Marc Limousin, Juan Carlos Linares, Maj-Lena Linderson, Anders Lindroth, Pilar Llorens, Álvaro López-Bernal, Michael M. Loranty, Dietmar Lüttschwager, Cate Macinnis-Ng, Isabelle Maréchaux, Timothy A. Martin, Ashley Matheny, Nate McDowell, Sean McMahon, Patrick Meir, Ilona Mészáros, Mirco Migliavacca, Patrick Mitchell, Meelis Mölder, Leonardo Montagnani, Georgianne W. Moore, Ryogo Nakada, Furong Niu, Rachael H. Nolan, Richard Norby, Kimberly Novick, Walter Oberhuber, Nikolaus Obojes, A. Christopher Oishi, Rafael S. Oliveira, Ram Oren, Jean-Marc Ourcival, Teemu Paljakka, Oscar Perez-Priego, Pablo L. Peri, Richard L. Peters, Sebastian Pfautsch, William T. Pockman, Yakir Preisler, Katherine Rascher, George Robinson, Humberto Rocha, Alain Rocheteau, Alexander Röll, Bruno H. P. Rosado, Lucy Rowland, Alexey V. Rubtsov, Santiago Sabaté, Yann Salmon, Roberto L. Salomón, Elisenda Sánchez-Costa, Karina V. R. Schäfer, Bernhard Schuldt, Alexandr Shashkin, Clément Stahl, Marko Stojanović, Juan Carlos Suárez, Ge Sun, Justyna Szatniewska, Fyodor Tatarinov, Miroslav Tesař, Frank M. Thomas, Pantana Tor-ngern, Josef Urban, Fernando Valladares, Christiaan van der Tol, Ilja van Meerveld, Andrej Varlagin, Holm Voigt, Jeffrey Warren, Christiane Werner, Willy Werner, Gerhard Wieser, Lisa Wingate, Stan Wullschleger, Koong Yi, Roman Zweifel, Kathy Steppe, Maurizio Mencuccini, and Jordi Martínez-Vilalta
Earth Syst. Sci. Data, 13, 2607–2649, https://doi.org/10.5194/essd-13-2607-2021, https://doi.org/10.5194/essd-13-2607-2021, 2021
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Transpiration is a key component of global water balance, but it is poorly constrained from available observations. We present SAPFLUXNET, the first global database of tree-level transpiration from sap flow measurements, containing 202 datasets and covering a wide range of ecological conditions. SAPFLUXNET and its accompanying R software package
sapfluxnetrwill facilitate new data syntheses on the ecological factors driving water use and drought responses of trees and forests.
Anna B. Harper, Karina E. Williams, Patrick C. McGuire, Maria Carolina Duran Rojas, Debbie Hemming, Anne Verhoef, Chris Huntingford, Lucy Rowland, Toby Marthews, Cleiton Breder Eller, Camilla Mathison, Rodolfo L. B. Nobrega, Nicola Gedney, Pier Luigi Vidale, Fred Otu-Larbi, Divya Pandey, Sebastien Garrigues, Azin Wright, Darren Slevin, Martin G. De Kauwe, Eleanor Blyth, Jonas Ardö, Andrew Black, Damien Bonal, Nina Buchmann, Benoit Burban, Kathrin Fuchs, Agnès de Grandcourt, Ivan Mammarella, Lutz Merbold, Leonardo Montagnani, Yann Nouvellon, Natalia Restrepo-Coupe, and Georg Wohlfahrt
Geosci. Model Dev., 14, 3269–3294, https://doi.org/10.5194/gmd-14-3269-2021, https://doi.org/10.5194/gmd-14-3269-2021, 2021
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We evaluated 10 representations of soil moisture stress in the JULES land surface model against site observations of GPP and latent heat flux. Increasing the soil depth and plant access to deep soil moisture improved many aspects of the simulations, and we recommend these settings in future work using JULES. In addition, using soil matric potential presents the opportunity to include parameters specific to plant functional type to further improve modeled fluxes.
Florian Ellsäßer, Christian Stiegler, Alexander Röll, Tania June, Hendrayanto, Alexander Knohl, and Dirk Hölscher
Biogeosciences, 18, 861–872, https://doi.org/10.5194/bg-18-861-2021, https://doi.org/10.5194/bg-18-861-2021, 2021
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Recording land surface temperatures using drones offers new options to predict evapotranspiration based on energy balance models. This study compares predictions from three energy balance models with the eddy covariance method. A model II Deming regression indicates interchangeability for latent heat flux estimates from certain modeling methods and eddy covariance measurements. This complements the available methods for evapotranspiration studies by fine grain and spatially explicit assessments.
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.
Jan Pisek, Angela Erb, Lauri Korhonen, Tobias Biermann, Arnaud Carrara, Edoardo Cremonese, Matthias Cuntz, Silvano Fares, Giacomo Gerosa, Thomas Grünwald, Niklas Hase, Michal Heliasz, Andreas Ibrom, Alexander Knohl, Johannes Kobler, Bart Kruijt, Holger Lange, Leena Leppänen, Jean-Marc Limousin, Francisco Ramon Lopez Serrano, Denis Loustau, Petr Lukeš, Lars Lundin, Riccardo Marzuoli, Meelis Mölder, Leonardo Montagnani, Johan Neirynck, Matthias Peichl, Corinna Rebmann, Eva Rubio, Margarida Santos-Reis, Crystal Schaaf, Marius Schmidt, Guillaume Simioni, Kamel Soudani, and Caroline Vincke
Biogeosciences, 18, 621–635, https://doi.org/10.5194/bg-18-621-2021, https://doi.org/10.5194/bg-18-621-2021, 2021
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Understory vegetation is the most diverse, least understood component of forests worldwide. Understory communities are important drivers of overstory succession and nutrient cycling. Multi-angle remote sensing enables us to describe surface properties by means that are not possible when using mono-angle data. Evaluated over an extensive set of forest ecosystem experimental sites in Europe, our reported method can deliver good retrievals, especially over different forest types with open canopies.
Tamara Emmerichs, Astrid Kerkweg, Huug Ouwersloot, Silvano Fares, Ivan Mammarella, and Domenico Taraborrelli
Geosci. Model Dev., 14, 495–519, https://doi.org/10.5194/gmd-14-495-2021, https://doi.org/10.5194/gmd-14-495-2021, 2021
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Dry deposition to vegetation is a major sink of ground-level ozone. Its parameterization in atmospheric chemistry models represents a significant source of uncertainty for global tropospheric ozone. We extended the current model parameterization with a relevant pathway and important meteorological adjustment factors. The comparison with measurements shows that this enables a more realistic model representation of ozone dry deposition velocity. Globally, annual dry deposition loss increases.
Camille Yver-Kwok, Carole Philippon, Peter Bergamaschi, Tobias Biermann, Francescopiero Calzolari, Huilin Chen, Sebastien Conil, Paolo Cristofanelli, Marc Delmotte, Juha Hatakka, Michal Heliasz, Ove Hermansen, Kateřina Komínková, Dagmar Kubistin, Nicolas Kumps, Olivier Laurent, Tuomas Laurila, Irene Lehner, Janne Levula, Matthias Lindauer, Morgan Lopez, Ivan Mammarella, Giovanni Manca, Per Marklund, Jean-Marc Metzger, Meelis Mölder, Stephen M. Platt, Michel Ramonet, Leonard Rivier, Bert Scheeren, Mahesh Kumar Sha, Paul Smith, Martin Steinbacher, Gabriela Vítková, and Simon Wyss
Atmos. Meas. Tech., 14, 89–116, https://doi.org/10.5194/amt-14-89-2021, https://doi.org/10.5194/amt-14-89-2021, 2021
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The Integrated Carbon Observation System (ICOS) is a pan-European research infrastructure which provides harmonized and high-precision scientific data on the carbon cycle and the greenhouse gas (GHG) budget. All stations have to undergo a rigorous assessment before being labeled, i.e., receiving approval to join the network. In this paper, we present the labeling process for the ICOS atmospheric network through the 23 stations that were labeled between November 2017 and November 2019.
Jelka Braden-Behrens, Lukas Siebicke, and Alexander Knohl
Biogeosciences Discuss., https://doi.org/10.5194/bg-2020-398, https://doi.org/10.5194/bg-2020-398, 2020
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We use directly measured isotopic compositions and isoforcing values in combination with meteorological data and PBL height information to gain a better understanding of the variability of the isotopic composition of H2Ov. We directly compare the measured changes in isotopic composition with isoforcing-related changes (driven by local evapotranspiration ET). We conclude that it is important to account for PBL height when interpreting isoforcing data.
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.
Christian Markwitz, Alexander Knohl, and Lukas Siebicke
Biogeosciences, 17, 5183–5208, https://doi.org/10.5194/bg-17-5183-2020, https://doi.org/10.5194/bg-17-5183-2020, 2020
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Agroforestry has been shown to alter the microclimate and to lead to higher carbon sequestration above ground and in the soil. In this study, we investigated the impact of agroforestry systems on system-scale evapotranspiration (ET) due to concerns about increased water losses to the atmosphere. Results showed small differences in annual sums of ET over agroforestry relative to monoculture systems, indicating that agroforestry in Germany can be a land use alternative to monoculture agriculture.
Kukka-Maaria Kohonen, Pasi Kolari, Linda M. J. Kooijmans, Huilin Chen, Ulli Seibt, Wu Sun, and Ivan Mammarella
Atmos. Meas. Tech., 13, 3957–3975, https://doi.org/10.5194/amt-13-3957-2020, https://doi.org/10.5194/amt-13-3957-2020, 2020
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Biosphere–atmosphere gas exchange (flux) measurements of carbonyl sulfide (COS) are becoming popular for estimating biospheric photosynthesis. To compare COS flux measurements across different measurement sites, we need standardized protocols for data processing. We analyze how various data processing steps affect the calculated COS flux and how they differ from carbon dioxide (CO2) flux processing steps, and we aim to settle on a set of recommended protocols for COS flux calculation.
Sheng Wang, Monica Garcia, Andreas Ibrom, and Peter Bauer-Gottwein
Hydrol. Earth Syst. Sci., 24, 3643–3661, https://doi.org/10.5194/hess-24-3643-2020, https://doi.org/10.5194/hess-24-3643-2020, 2020
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Remote sensing only provides snapshots of rapidly changing land surface variables; this limits its application for water resources and ecosystem management. To obtain continuous estimates of surface temperature, soil moisture, evapotranspiration, and ecosystem productivity, a simple and operational modelling scheme is presented. We demonstrate it with temporally sparse optical and thermal remote sensing data from an unmanned aerial system at a Danish bioenergy plantation eddy covariance site.
Xuefei Li, Outi Wahlroos, Sami Haapanala, Jukka Pumpanen, Harri Vasander, Anne Ojala, Timo Vesala, and Ivan Mammarella
Biogeosciences, 17, 3409–3425, https://doi.org/10.5194/bg-17-3409-2020, https://doi.org/10.5194/bg-17-3409-2020, 2020
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We measured CO2 and CH4 fluxes and quantified the global warming potential of different surface areas in a recently created urban wetland in Southern Finland. The ecosystem has a small net climate warming effect which was mainly contributed by the open-water areas. Our results suggest that limiting open-water areas and setting a design preference for areas of emergent vegetation in the establishment of urban wetlands can be a beneficial practice when considering solely the climate impact.
Christopher P. O. Reyer, Ramiro Silveyra Gonzalez, Klara Dolos, Florian Hartig, Ylva Hauf, Matthias Noack, Petra Lasch-Born, Thomas Rötzer, Hans Pretzsch, Henning Meesenburg, Stefan Fleck, Markus Wagner, Andreas Bolte, Tanja G. M. Sanders, Pasi Kolari, Annikki Mäkelä, Timo Vesala, Ivan Mammarella, Jukka Pumpanen, Alessio Collalti, Carlo Trotta, Giorgio Matteucci, Ettore D'Andrea, Lenka Foltýnová, Jan Krejza, Andreas Ibrom, Kim Pilegaard, Denis Loustau, Jean-Marc Bonnefond, Paul Berbigier, Delphine Picart, Sébastien Lafont, Michael Dietze, David Cameron, Massimo Vieno, Hanqin Tian, Alicia Palacios-Orueta, Victor Cicuendez, Laura Recuero, Klaus Wiese, Matthias Büchner, Stefan Lange, Jan Volkholz, Hyungjun Kim, Joanna A. Horemans, Friedrich Bohn, Jörg Steinkamp, Alexander Chikalanov, Graham P. Weedon, Justin Sheffield, Flurin Babst, Iliusi Vega del Valle, Felicitas Suckow, Simon Martel, Mats Mahnken, Martin Gutsch, and Katja Frieler
Earth Syst. Sci. Data, 12, 1295–1320, https://doi.org/10.5194/essd-12-1295-2020, https://doi.org/10.5194/essd-12-1295-2020, 2020
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Process-based vegetation models are widely used to predict local and global ecosystem dynamics and climate change impacts. Due to their complexity, they require careful parameterization and evaluation to ensure that projections are accurate and reliable. The PROFOUND Database provides a wide range of empirical data to calibrate and evaluate vegetation models that simulate climate impacts at the forest stand scale to support systematic model intercomparisons and model development in Europe.
Uta Moderow, Stefanie Fischer, Thomas Grünwald, Ronald Queck, and Christian Bernhofer
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2020-202, https://doi.org/10.5194/hess-2020-202, 2020
Preprint withdrawn
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We analyzed three different estimates of evapotranspiration (ET) for four different sites along an elevation gradient of a low mountain range over 11 years. We found similar dependencies on meteorological variables for all three different ET estimates. Based on our analyses we recommend using a distinct ET estimate. Analysis further suggests that water temporally stored on plant surfaces should receive more attention. Our results contribute to determining reliable ET estimates.
Kurt C. Solander, Brent D. Newman, Alessandro Carioca de Araujo, Holly R. Barnard, Z. Carter Berry, Damien Bonal, Mario Bretfeld, Benoit Burban, Luiz Antonio Candido, Rolando Célleri, Jeffery Q. Chambers, Bradley O. Christoffersen, Matteo Detto, Wouter A. Dorigo, Brent E. Ewers, Savio José Filgueiras Ferreira, Alexander Knohl, L. Ruby Leung, Nate G. McDowell, Gretchen R. Miller, Maria Terezinha Ferreira Monteiro, Georgianne W. Moore, Robinson Negron-Juarez, Scott R. Saleska, Christian Stiegler, Javier Tomasella, and Chonggang Xu
Hydrol. Earth Syst. Sci., 24, 2303–2322, https://doi.org/10.5194/hess-24-2303-2020, https://doi.org/10.5194/hess-24-2303-2020, 2020
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We evaluate the soil moisture response in the humid tropics to El Niño during the three most recent super El Niño events. Our estimates are compared to in situ soil moisture estimates that span five continents. We find the strongest and most consistent soil moisture decreases in the Amazon and maritime southeastern Asia, while the most consistent increases occur over eastern Africa. Our results can be used to improve estimates of soil moisture in tropical ecohydrology models at multiple scales.
Chris R. Flechard, Andreas Ibrom, Ute M. Skiba, Wim de Vries, Marcel van Oijen, David R. Cameron, Nancy B. Dise, Janne F. J. Korhonen, Nina Buchmann, Arnaud Legout, David Simpson, Maria J. Sanz, Marc Aubinet, Denis Loustau, Leonardo Montagnani, Johan Neirynck, Ivan A. Janssens, Mari Pihlatie, Ralf Kiese, Jan Siemens, André-Jean Francez, Jürgen Augustin, Andrej Varlagin, Janusz Olejnik, Radosław Juszczak, Mika Aurela, Daniel Berveiller, Bogdan H. Chojnicki, Ulrich Dämmgen, Nicolas Delpierre, Vesna Djuricic, Julia Drewer, Eric Dufrêne, Werner Eugster, Yannick Fauvel, David Fowler, Arnoud Frumau, André Granier, Patrick Gross, Yannick Hamon, Carole Helfter, Arjan Hensen, László Horváth, Barbara Kitzler, Bart Kruijt, Werner L. Kutsch, Raquel Lobo-do-Vale, Annalea Lohila, Bernard Longdoz, Michal V. Marek, Giorgio Matteucci, Marta Mitosinkova, Virginie Moreaux, Albrecht Neftel, Jean-Marc Ourcival, Kim Pilegaard, Gabriel Pita, Francisco Sanz, Jan K. Schjoerring, Maria-Teresa Sebastià, Y. Sim Tang, Hilde Uggerud, Marek Urbaniak, Netty van Dijk, Timo Vesala, Sonja Vidic, Caroline Vincke, Tamás Weidinger, Sophie Zechmeister-Boltenstern, Klaus Butterbach-Bahl, Eiko Nemitz, and Mark A. Sutton
Biogeosciences, 17, 1583–1620, https://doi.org/10.5194/bg-17-1583-2020, https://doi.org/10.5194/bg-17-1583-2020, 2020
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Experimental evidence from a network of 40 monitoring sites in Europe suggests that atmospheric nitrogen deposition to forests and other semi-natural vegetation impacts the carbon sequestration rates in ecosystems, as well as the net greenhouse gas balance including other greenhouse gases such as nitrous oxide and methane. Excess nitrogen deposition in polluted areas also leads to other environmental impacts such as nitrogen leaching to groundwater and other pollutant gaseous emissions.
Chris R. Flechard, Marcel van Oijen, David R. Cameron, Wim de Vries, Andreas Ibrom, Nina Buchmann, Nancy B. Dise, Ivan A. Janssens, Johan Neirynck, Leonardo Montagnani, Andrej Varlagin, Denis Loustau, Arnaud Legout, Klaudia Ziemblińska, Marc Aubinet, Mika Aurela, Bogdan H. Chojnicki, Julia Drewer, Werner Eugster, André-Jean Francez, Radosław Juszczak, Barbara Kitzler, Werner L. Kutsch, Annalea Lohila, Bernard Longdoz, Giorgio Matteucci, Virginie Moreaux, Albrecht Neftel, Janusz Olejnik, Maria J. Sanz, Jan Siemens, Timo Vesala, Caroline Vincke, Eiko Nemitz, Sophie Zechmeister-Boltenstern, Klaus Butterbach-Bahl, Ute M. Skiba, and Mark A. Sutton
Biogeosciences, 17, 1621–1654, https://doi.org/10.5194/bg-17-1621-2020, https://doi.org/10.5194/bg-17-1621-2020, 2020
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Nitrogen deposition from the atmosphere to unfertilized terrestrial vegetation such as forests can increase carbon dioxide uptake and favour carbon sequestration by ecosystems. However the data from observational networks are difficult to interpret in terms of a carbon-to-nitrogen response, because there are a number of other confounding factors, such as climate, soil physical properties and fertility, and forest age. We propose a model-based method to untangle the different influences.
Paul C. Stoy, Tarek S. El-Madany, Joshua B. Fisher, Pierre Gentine, Tobias Gerken, Stephen P. Good, Anne Klosterhalfen, Shuguang Liu, Diego G. Miralles, Oscar Perez-Priego, Angela J. Rigden, Todd H. Skaggs, Georg Wohlfahrt, Ray G. Anderson, A. Miriam J. Coenders-Gerrits, Martin Jung, Wouter H. Maes, Ivan Mammarella, Matthias Mauder, Mirco Migliavacca, Jacob A. Nelson, Rafael Poyatos, Markus Reichstein, Russell L. Scott, and Sebastian Wolf
Biogeosciences, 16, 3747–3775, https://doi.org/10.5194/bg-16-3747-2019, https://doi.org/10.5194/bg-16-3747-2019, 2019
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Key findings are the nearly optimal response of T to atmospheric water vapor pressure deficits across methods and scales. Additionally, the notion that T / ET intermittently approaches 1, which is a basis for many partitioning methods, does not hold for certain methods and ecosystems. To better constrain estimates of E and T from combined ET measurements, we propose a combination of independent measurement techniques to better constrain E and T at the ecosystem scale.
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.
Petri Kiuru, Anne Ojala, Ivan Mammarella, Jouni Heiskanen, Kukka-Maaria Erkkilä, Heli Miettinen, Timo Vesala, and Timo Huttula
Biogeosciences, 16, 3297–3317, https://doi.org/10.5194/bg-16-3297-2019, https://doi.org/10.5194/bg-16-3297-2019, 2019
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Many boreal lakes emit the greenhouse gas carbon dioxide (CO2) to the atmosphere. We incorporated four different gas exchange models into a physico-biochemical lake model and studied their ability to simulate lake air–water CO2 fluxes. The inclusion of refined gas exchange models in lake models that simulate carbon cycling is important to assess lake carbon budgets. However, higher estimates for inorganic carbon sources in boreal lakes are needed to balance the CO2 losses to the atmosphere.
Olli Peltola, Timo Vesala, Yao Gao, Olle Räty, Pavel Alekseychik, Mika Aurela, Bogdan Chojnicki, Ankur R. Desai, Albertus J. Dolman, Eugenie S. Euskirchen, Thomas Friborg, Mathias Göckede, Manuel Helbig, Elyn Humphreys, Robert B. Jackson, Georg Jocher, Fortunat Joos, Janina Klatt, Sara H. Knox, Natalia Kowalska, Lars Kutzbach, Sebastian Lienert, Annalea Lohila, Ivan Mammarella, Daniel F. Nadeau, Mats B. Nilsson, Walter C. Oechel, Matthias Peichl, Thomas Pypker, William Quinton, Janne Rinne, Torsten Sachs, Mateusz Samson, Hans Peter Schmid, Oliver Sonnentag, Christian Wille, Donatella Zona, and Tuula Aalto
Earth Syst. Sci. Data, 11, 1263–1289, https://doi.org/10.5194/essd-11-1263-2019, https://doi.org/10.5194/essd-11-1263-2019, 2019
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Here we develop a monthly gridded dataset of northern (> 45 N) wetland methane (CH4) emissions. The data product is derived using a random forest machine-learning technique and eddy covariance CH4 fluxes from 25 wetland sites. Annual CH4 emissions from these wetlands calculated from the derived data product are comparable to prior studies focusing on these areas. This product is an independent estimate of northern wetland CH4 emissions and hence could be used, e.g. for process model evaluation.
Christian Stiegler, Ana Meijide, Yuanchao Fan, Ashehad Ashween Ali, Tania June, and Alexander Knohl
Biogeosciences, 16, 2873–2890, https://doi.org/10.5194/bg-16-2873-2019, https://doi.org/10.5194/bg-16-2873-2019, 2019
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We show the response of a commercial oil palm plantation in Indonesia to the extreme El Niño–Southern Oscillation (ENSO) event in 2015. Our measurements and model suggest that without human-induced forest fires and related smoke emissions, the observed negative impact on oil palm carbon dioxide greenhouse gas fluxes, carbon accumulation and yield due to ENSO-related drought would have been less pronounced. With respect to climate change we highlight the importance of fire prevention in the area.
Elisa Männistö, Aino Korrensalo, Pavel Alekseychik, Ivan Mammarella, Olli Peltola, Timo Vesala, and Eeva-Stiina Tuittila
Biogeosciences, 16, 2409–2421, https://doi.org/10.5194/bg-16-2409-2019, https://doi.org/10.5194/bg-16-2409-2019, 2019
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We studied methane emitted as episodic bubble release (ebullition) from water and bare peat surfaces of a boreal bog over three years. There was more ebullition from water than from bare peat surfaces, and it was controlled by peat temperature, water level, atmospheric pressure and the weekly temperature sum. However, the contribution of methane bubbles to the total ecosystem methane emission was small. This new information can be used to improve process models of peatland methane dynamics.
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.
Qiaozhi Zha, Chao Yan, Heikki Junninen, Matthieu Riva, Nina Sarnela, Juho Aalto, Lauriane Quéléver, Simon Schallhart, Lubna Dada, Liine Heikkinen, Otso Peräkylä, Jun Zou, Clémence Rose, Yonghong Wang, Ivan Mammarella, Gabriel Katul, Timo Vesala, Douglas R. Worsnop, Markku Kulmala, Tuukka Petäjä, Federico Bianchi, and Mikael Ehn
Atmos. Chem. Phys., 18, 17437–17450, https://doi.org/10.5194/acp-18-17437-2018, https://doi.org/10.5194/acp-18-17437-2018, 2018
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Vertical measurements of highly oxygenated molecules (HOMs) below and above the forest canopy were performed for the first time in a boreal forest during September 2016. Our results highlight that near-ground HOM measurements may only be representative of a small fraction of the entire nocturnal boundary layer, which may sequentially influence the growth of newly formed particles and SOA formation close to ground surface, where the majority of measurements are conducted.
Ashehad A. Ali, Yuanchao Fan, Marife D. Corre, Martyna M. Kotowska, Evelyn Hassler, Fernando E. Moyano, Christian Stiegler, Alexander Röll, Ana Meijide, Andre Ringeler, Christoph Leuschner, Tania June, Suria Tarigan, Holger Kreft, Dirk Hölscher, Chonggang Xu, Charles D. Koven, Rosie Fisher, Edzo Veldkamp, and Alexander Knohl
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2018-236, https://doi.org/10.5194/gmd-2018-236, 2018
Revised manuscript not accepted
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We used carbon-use and water-use related datasets of small-holder rubber plantations from Jambi province, Indonesia to develop and calibrate a rubber plant functional type for the Community Land Model (CLM-rubber). Increased sensitivity of stomata to soil water stress and enhanced respiration costs enabled the model to capture the magnitude of transpiration and leaf area index. Including temporal variations in leaf life span enabled the model to better capture the seasonality of leaf litterfall.
Pertti Hari, Steffen Noe, Sigrid Dengel, Jan Elbers, Bert Gielen, Veli-Matti Kerminen, Bart Kruijt, Liisa Kulmala, Anders Lindroth, Ivan Mammarella, Tuukka Petäjä, Guy Schurgers, Anni Vanhatalo, Markku Kulmala, and Jaana Bäck
Atmos. Chem. Phys., 18, 13321–13328, https://doi.org/10.5194/acp-18-13321-2018, https://doi.org/10.5194/acp-18-13321-2018, 2018
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The development of eddy-covariance measurements of ecosystem CO2 fluxes began a new era in the field studies of photosynthesis. The interpretation of the very variable CO2 fluxes in evergreen forests has been problematic especially in seasonal transition times. We apply two theoretical needle-level equations and show they can predict photosynthetic CO2 flux between the atmosphere and Scots pine forests. This has strong implications for the interpretation of the global change and boreal forests.
Jason A. Ducker, Christopher D. Holmes, Trevor F. Keenan, Silvano Fares, Allen H. Goldstein, Ivan Mammarella, J. William Munger, and Jordan Schnell
Biogeosciences, 15, 5395–5413, https://doi.org/10.5194/bg-15-5395-2018, https://doi.org/10.5194/bg-15-5395-2018, 2018
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We have developed an accurate method (SynFlux) to estimate ozone deposition and stomatal uptake across 103 flux tower sites (43 US, 60 Europe), where ozone concentrations and fluxes have not been measured. In all, the SynFlux public dataset provides monthly values of ozone dry deposition for 926 site years across a wide array of ecosystems. The SynFlux dataset will promote further applications to ecosystem, air quality, or climate modeling across the geoscience community.
Mary E. Whelan, Sinikka T. Lennartz, Teresa E. Gimeno, Richard Wehr, Georg Wohlfahrt, Yuting Wang, Linda M. J. Kooijmans, Timothy W. Hilton, Sauveur Belviso, Philippe Peylin, Róisín Commane, Wu Sun, Huilin Chen, Le Kuai, Ivan Mammarella, Kadmiel Maseyk, Max Berkelhammer, King-Fai Li, Dan Yakir, Andrew Zumkehr, Yoko Katayama, Jérôme Ogée, Felix M. Spielmann, Florian Kitz, Bharat Rastogi, Jürgen Kesselmeier, Julia Marshall, Kukka-Maaria Erkkilä, Lisa Wingate, Laura K. Meredith, Wei He, Rüdiger Bunk, Thomas Launois, Timo Vesala, Johan A. Schmidt, Cédric G. Fichot, Ulli Seibt, Scott Saleska, Eric S. Saltzman, Stephen A. Montzka, Joseph A. Berry, and J. Elliott Campbell
Biogeosciences, 15, 3625–3657, https://doi.org/10.5194/bg-15-3625-2018, https://doi.org/10.5194/bg-15-3625-2018, 2018
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Measurements of the trace gas carbonyl sulfide (OCS) are helpful in quantifying photosynthesis at previously unknowable temporal and spatial scales. While CO2 is both consumed and produced within ecosystems, OCS is mostly produced in the oceans or from specific industries, and destroyed in plant leaves in proportion to CO2. This review summarizes the advancements we have made in the understanding of OCS exchange and applications to vital ecosystem water and carbon cycle questions.
Maria Provenzale, Anne Ojala, Jouni Heiskanen, Kukka-Maaria Erkkilä, Ivan Mammarella, Pertti Hari, and Timo Vesala
Biogeosciences, 15, 2021–2032, https://doi.org/10.5194/bg-15-2021-2018, https://doi.org/10.5194/bg-15-2021-2018, 2018
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We extensively tested and refined a direct, high-frequency free-water CO2 measurement method to study the lake net ecosystem productivity. The method was first proposed in 2008, but neglected ever since.
With high-frequency direct methods, we can calculate the lake productivity more precisely, and parameterise its dependency on environmental variables. This helps us expand our knowledge on the carbon cycle in the water, and leads to a better integration of water bodies in carbon budgets.
Aino Korrensalo, Elisa Männistö, Pavel Alekseychik, Ivan Mammarella, Janne Rinne, Timo Vesala, and Eeva-Stiina Tuittila
Biogeosciences, 15, 1749–1761, https://doi.org/10.5194/bg-15-1749-2018, https://doi.org/10.5194/bg-15-1749-2018, 2018
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We measured methane fluxes of a boreal bog from six different plant community types in 2012–2014. We found only little variation in methane fluxes among plant community types. Peat temperature as well as both leaf area of plant species with air channels and of all vegetation are important factors controlling the fluxes. We also detected negative net fluxes indicating methane consumption each year. Our results can be used to improve the models of peatland methane dynamics under climate change.
Marta Camino-Serrano, Bertrand Guenet, Sebastiaan Luyssaert, Philippe Ciais, Vladislav Bastrikov, Bruno De Vos, Bert Gielen, Gerd Gleixner, Albert Jornet-Puig, Klaus Kaiser, Dolly Kothawala, Ronny Lauerwald, Josep Peñuelas, Marion Schrumpf, Sara Vicca, Nicolas Vuichard, David Walmsley, and Ivan A. Janssens
Geosci. Model Dev., 11, 937–957, https://doi.org/10.5194/gmd-11-937-2018, https://doi.org/10.5194/gmd-11-937-2018, 2018
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Global models generally oversimplify the representation of soil organic carbon (SOC), and thus its response to global warming remains uncertain. We present the new soil module ORCHIDEE-SOM, within the global model ORCHIDEE, that refines the representation of SOC dynamics and includes the dissolved organic carbon (DOC) processes. The model is able to reproduce SOC stocks and DOC concentrations in four different ecosystems, opening an opportunity for improved predictions of SOC in global models.
Jannis von Buttlar, Jakob Zscheischler, Anja Rammig, Sebastian Sippel, Markus Reichstein, Alexander Knohl, Martin Jung, Olaf Menzer, M. Altaf Arain, Nina Buchmann, Alessandro Cescatti, Damiano Gianelle, Gerard Kiely, Beverly E. Law, Vincenzo Magliulo, Hank Margolis, Harry McCaughey, Lutz Merbold, Mirco Migliavacca, Leonardo Montagnani, Walter Oechel, Marian Pavelka, Matthias Peichl, Serge Rambal, Antonio Raschi, Russell L. Scott, Francesco P. Vaccari, Eva van Gorsel, Andrej Varlagin, Georg Wohlfahrt, and Miguel D. Mahecha
Biogeosciences, 15, 1293–1318, https://doi.org/10.5194/bg-15-1293-2018, https://doi.org/10.5194/bg-15-1293-2018, 2018
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Our work systematically quantifies extreme heat and drought event impacts on gross primary productivity (GPP) and ecosystem respiration globally across a wide range of ecosystems. We show that heat extremes typically increased mainly respiration whereas drought decreased both fluxes. Combined heat and drought extremes had opposing effects offsetting each other for respiration, but there were also strong reductions in GPP and hence the strongest reductions in the ecosystems carbon sink capacity.
Mahdi Nakhavali, Pierre Friedlingstein, Ronny Lauerwald, Jing Tang, Sarah Chadburn, Marta Camino-Serrano, Bertrand Guenet, Anna Harper, David Walmsley, Matthias Peichl, and Bert Gielen
Geosci. Model Dev., 11, 593–609, https://doi.org/10.5194/gmd-11-593-2018, https://doi.org/10.5194/gmd-11-593-2018, 2018
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In order to provide a better understanding of the Earth's carbon cycle, we need a model that represents the whole continuum from atmosphere to land and into the ocean. In this study we include in JULES a representation of dissolved organic carbon (DOC) processes. Our results show that the model is able to reproduce the DOC concentration and controlling processes, including leaching to the riverine system, which is fundamental for integrating the terrestrial and aquatic ecosystem.
Chunjing Qiu, Dan Zhu, Philippe Ciais, Bertrand Guenet, Gerhard Krinner, Shushi Peng, Mika Aurela, Christian Bernhofer, Christian Brümmer, Syndonia Bret-Harte, Housen Chu, Jiquan Chen, Ankur R. Desai, Jiří Dušek, Eugénie S. Euskirchen, Krzysztof Fortuniak, Lawrence B. Flanagan, Thomas Friborg, Mateusz Grygoruk, Sébastien Gogo, Thomas Grünwald, Birger U. Hansen, David Holl, Elyn Humphreys, Miriam Hurkuck, Gerard Kiely, Janina Klatt, Lars Kutzbach, Chloé Largeron, Fatima Laggoun-Défarge, Magnus Lund, Peter M. Lafleur, Xuefei Li, Ivan Mammarella, Lutz Merbold, Mats B. Nilsson, Janusz Olejnik, Mikaell Ottosson-Löfvenius, Walter Oechel, Frans-Jan W. Parmentier, Matthias Peichl, Norbert Pirk, Olli Peltola, Włodzimierz Pawlak, Daniel Rasse, Janne Rinne, Gaius Shaver, Hans Peter Schmid, Matteo Sottocornola, Rainer Steinbrecher, Torsten Sachs, Marek Urbaniak, Donatella Zona, and Klaudia Ziemblinska
Geosci. Model Dev., 11, 497–519, https://doi.org/10.5194/gmd-11-497-2018, https://doi.org/10.5194/gmd-11-497-2018, 2018
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Northern peatlands store large amount of soil carbon and are vulnerable to climate change. We implemented peatland hydrological and carbon accumulation processes into the ORCHIDEE land surface model. The model was evaluated against EC measurements from 30 northern peatland sites. The model generally well reproduced the spatial gradient and temporal variations in GPP and NEE at these sites. Water table depth was not well predicted but had only small influence on simulated NEE.
Wu Sun, Linda M. J. Kooijmans, Kadmiel Maseyk, Huilin Chen, Ivan Mammarella, Timo Vesala, Janne Levula, Helmi Keskinen, and Ulli Seibt
Atmos. Chem. Phys., 18, 1363–1378, https://doi.org/10.5194/acp-18-1363-2018, https://doi.org/10.5194/acp-18-1363-2018, 2018
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Most soils consume carbonyl sulfide (COS) and CO due to microbial uptake, but whether boreal forest soils act like this is uncertain. We measured growing season soil COS and CO fluxes in a Finnish pine forest. The soil behaved as a consistent and relatively invariant sink of COS and CO. Uptake rates of COS and CO decrease with soil moisture due to diffusion limitation and increase with respiration because of microbial control. Using COS to infer photosynthesis is not affected by soil COS flux.
Simon Schallhart, Pekka Rantala, Maija K. Kajos, Juho Aalto, Ivan Mammarella, Taina M. Ruuskanen, and Markku Kulmala
Atmos. Chem. Phys., 18, 815–832, https://doi.org/10.5194/acp-18-815-2018, https://doi.org/10.5194/acp-18-815-2018, 2018
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Emissions of volatile organic compounds (VOCs) have impact to air quality, human health and climate. We investigated the development of VOC exchange in a boreal forest between April and June 2013. VOC exchange and diversity increased towards summer, but over 75 % of the biogenic net exchange was driven by methanol, monoterpenes and acetone only. The boreal forest emitted less than 0.2 % carbon in form of VOCs in relation to the carbon uptake.
Kukka-Maaria Erkkilä, Anne Ojala, David Bastviken, Tobias Biermann, Jouni J. Heiskanen, Anders Lindroth, Olli Peltola, Miitta Rantakari, Timo Vesala, and Ivan Mammarella
Biogeosciences, 15, 429–445, https://doi.org/10.5194/bg-15-429-2018, https://doi.org/10.5194/bg-15-429-2018, 2018
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Global estimates of freshwater greenhouse gas emissions are usually based on simple gas transfer models that underestimate the emissions. Thus, comparison of different gas transfer models is required for evaluating the uncertainties. This study compares three commonly used methods for estimating greenhouse gas emissions over lakes. We conclude that simple gas transfer models underestimate the emissions and more recent models should be used for global freshwater greenhouse gas emission estimates.
Jelka Braden-Behrens, Yuan Yan, and Alexander Knohl
Atmos. Meas. Tech., 10, 4537–4560, https://doi.org/10.5194/amt-10-4537-2017, https://doi.org/10.5194/amt-10-4537-2017, 2017
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Here we present the instrument characteristics and field applicability of
the newly developed Delta Ray analyzer for stable isotope measurements
in CO2. We used this analyzer to measure the concentration and the
isotopic composition of CO2 exchange in a managed beech forest for 3
months in autumn 2015. During this period an early frost event occurred
and our measurements suggest that this short event strongly influenced
the measured isotopic composition of CO2 exchange.
Clifton R. Sabajo, Guerric le Maire, Tania June, Ana Meijide, Olivier Roupsard, and Alexander Knohl
Biogeosciences, 14, 4619–4635, https://doi.org/10.5194/bg-14-4619-2017, https://doi.org/10.5194/bg-14-4619-2017, 2017
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From the analysis of MODIS and Landsat satellite data of the Jambi province in Indonesia, this first study on the effects of oil palm expansion on the surface temperature in Indonesia shows shows a local and regional warming effect caused by the expansion of oil palm plantations and other cash or tree crops between 2000 and 2015. The observed warming effects may affect ecosystem services, reduce water availabilty in the dry period and increase the vulnerability to fires in the province.
Yao Gao, Tiina Markkanen, Mika Aurela, Ivan Mammarella, Tea Thum, Aki Tsuruta, Huiyi Yang, and Tuula Aalto
Biogeosciences, 14, 4409–4422, https://doi.org/10.5194/bg-14-4409-2017, https://doi.org/10.5194/bg-14-4409-2017, 2017
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We investigated the response of water use efficiency (WUE) to summer drought in a boreal Scots pine forest (Pinus sylvestris) on the daily time scale mainly using EC flux data from the Hyytiälä (southern Finland) flux site. Simulation results from the JSBACH land surface model were also evaluated against the observed results. The performance of three WUE metrics at the ecosystem level (EWUE, IWUE, and uWUE) during the severe summer drought were studied and showed different results.
Linda M. J. Kooijmans, Kadmiel Maseyk, Ulli Seibt, Wu Sun, Timo Vesala, Ivan Mammarella, Pasi Kolari, Juho Aalto, Alessandro Franchin, Roberta Vecchi, Gianluigi Valli, and Huilin Chen
Atmos. Chem. Phys., 17, 11453–11465, https://doi.org/10.5194/acp-17-11453-2017, https://doi.org/10.5194/acp-17-11453-2017, 2017
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Carbon cycle studies rely on the accuracy of models to estimate the amount of CO2 being taken up by vegetation. The gas carbonyl sulfide (COS) can serve as a tool to estimate the vegetative CO2 uptake by scaling the ecosystem uptake of COS to that of CO2. Here we investigate the nighttime fluxes of COS. The relationships found in this study will aid in implementing nighttime COS uptake in models, which is key to obtain accurate estimates of vegetative CO2 uptake with the use of COS.
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.
Pavel Alekseychik, Ivan Mammarella, Dmitry Karpov, Sigrid Dengel, Irina Terentieva, Alexander Sabrekov, Mikhail Glagolev, and Elena Lapshina
Atmos. Chem. Phys., 17, 9333–9345, https://doi.org/10.5194/acp-17-9333-2017, https://doi.org/10.5194/acp-17-9333-2017, 2017
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West Siberian peatlands occupy a large fraction of land area in the region, and yet little is known about their interaction with the atmosphere. We took the first measurements of CO2 and energy surface balances over a typical bog of West Siberian middle taiga, in the vicinity of the Mukhrino field station (Khanty–Mansiysk). The May–August study in a wet year (2015) revealed a relatively large photosynthetic sink of CO2 that was close to the high end of estimates at bog sites elsewhere.
Lore T. Verryckt, Maarten Op de Beeck, Johan Neirynck, Bert Gielen, Marilyn Roland, and Ivan A. Janssens
Biogeosciences, 14, 1839–1855, https://doi.org/10.5194/bg-14-1839-2017, https://doi.org/10.5194/bg-14-1839-2017, 2017
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Ozone (O3) is an air pollutant known to negatively affect vegetation. Typically, high O3 concentrations reduce growth. This study investigated the effect of O3 uptake on the total amount of carbon assimilated by vegetation for a Scots pine stand in Flanders over the period 1998–2013. Although the critical levels for AOT40 and POD1, two indices currently used to estimate O3 damage, were exceeded every year, no O3 effects on daily and growing season GPP were found.
Andreas Brændholt, Klaus Steenberg Larsen, Andreas Ibrom, and Kim Pilegaard
Biogeosciences, 14, 1603–1616, https://doi.org/10.5194/bg-14-1603-2017, https://doi.org/10.5194/bg-14-1603-2017, 2017
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In this study we found that CO2 fluxes from soil measured by the closed-chamber technique were overestimated during low atmospheric turbulence. This resulted in biased courses of CO2 fluxes during a day. We removed CO2 fluxes measured at low turbulence, which gave better flux estimates. We furthermore tested a novel technique that provided good measurement during low turbulence, thereby giving better estimates of CO2 emissions from soils, which is a crucial part of the global carbon cycle.
Christian Brümmer, Bjarne Lyshede, Dirk Lempio, Jean-Pierre Delorme, Jeremy J. Rüffer, Roland Fuß, Antje M. Moffat, Miriam Hurkuck, Andreas Ibrom, Per Ambus, Heinz Flessa, and Werner L. Kutsch
Biogeosciences, 14, 1365–1381, https://doi.org/10.5194/bg-14-1365-2017, https://doi.org/10.5194/bg-14-1365-2017, 2017
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We present a novel chamber design for measuring soil–atmosphere N2O fluxes and compare the performance of a commonly applied gas chromatography (GC) setup with laser-based (QCL) concentration detection. While GC was still a useful method for longer-term investigations, we found that closure times of 10 min and sampling every 5 s is sufficient when using a QCL system. Further, extremely low standard errors (< 2 % of flux value) were observed regardless of linear or exponential flux calculation.
Antti-Jussi Kieloaho, Mari Pihlatie, Samuli Launiainen, Markku Kulmala, Marja-Liisa Riekkola, Jevgeni Parshintsev, Ivan Mammarella, Timo Vesala, and Jussi Heinonsalo
Biogeosciences, 14, 1075–1091, https://doi.org/10.5194/bg-14-1075-2017, https://doi.org/10.5194/bg-14-1075-2017, 2017
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The alkylamines are important precursors in secondary aerosol formation in boreal forests. We quantified alkylamine concentrations in fungal species present in boreal forests in order to estimate soil as a source of atmospheric alkylamines. Based on our knowledge we estimated possible soil–atmosphere exchange of these compounds. The results shows that the boreal forest soil could act as a source of alkylamines depending on environmental conditions and studied compound.
Putian Zhou, Laurens Ganzeveld, Üllar Rannik, Luxi Zhou, Rosa Gierens, Ditte Taipale, Ivan Mammarella, and Michael Boy
Atmos. Chem. Phys., 17, 1361–1379, https://doi.org/10.5194/acp-17-1361-2017, https://doi.org/10.5194/acp-17-1361-2017, 2017
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We implemented a multi-layer O3 dry deposition model in a 1-D model SOSAA to simulate O3 flux and concentration within and above a boreal forest at SMEAR II in Hyytiälä, Finland, in August 2010. The results showed that when RH > 70 % the O3 uptake on leaf wet skin was ~ 51 % to the total deposition at night and ~ 19 % at daytime. The sub-canopy contribution below 4.2 m was ~ 38 % at daytime. The averaged daily chemical contribution to total O3 alteration inside the canopy was less than 10 %.
Aino Korrensalo, Pavel Alekseychik, Tomáš Hájek, Janne Rinne, Timo Vesala, Lauri Mehtätalo, Ivan Mammarella, and Eeva-Stiina Tuittila
Biogeosciences, 14, 257–269, https://doi.org/10.5194/bg-14-257-2017, https://doi.org/10.5194/bg-14-257-2017, 2017
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Photosynthetic parameters of peatland plant species were measured over one growing season in an ombrotrophic bog. Based on these measurements, ecosystem-level photosynthesis was calculated for the whole growing season and compared with an estimate derived from micrometeorological measurements. These two estimates corresponded well. Species with low areal cover at the site but high photosynthetic efficiency appeared to be potentially important for the ecosystem-level carbon balance.
Jarmo Mäkelä, Jouni Susiluoto, Tiina Markkanen, Mika Aurela, Heikki Järvinen, Ivan Mammarella, Stefan Hagemann, and Tuula Aalto
Nonlin. Processes Geophys., 23, 447–465, https://doi.org/10.5194/npg-23-447-2016, https://doi.org/10.5194/npg-23-447-2016, 2016
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The land-based hydrological cycle is one of the key processes controlling the growth and wilting of plants and the amount of carbon vegetation can assimilate. Recent studies have shown that many land surface models have biases in this area. We optimized parameters in one such model (JSBACH) and were able to enhance the model performance in many respects, but the response to drought remained unaffected. Further studies into this aspect should include alternative stomatal conductance formulations.
Üllar Rannik, Olli Peltola, and Ivan Mammarella
Atmos. Meas. Tech., 9, 5163–5181, https://doi.org/10.5194/amt-9-5163-2016, https://doi.org/10.5194/amt-9-5163-2016, 2016
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We review available methods for the random error estimation of turbulent fluxes that are widely used by the flux community. Flux errors are evaluated theoretically as well as via numerical calculations by using measured and simulated records. We recommend two flux random errors with clear physical meaning: the total error resulting from stochastic nature of turbulence, well approximated by the method of Finkelstein and Sims (2001), and the error of the flux due to the instrumental noise.
Marta Camino-Serrano, Elisabeth Graf Pannatier, Sara Vicca, Sebastiaan Luyssaert, Mathieu Jonard, Philippe Ciais, Bertrand Guenet, Bert Gielen, Josep Peñuelas, Jordi Sardans, Peter Waldner, Sophia Etzold, Guia Cecchini, Nicholas Clarke, Zoran Galić, Laure Gandois, Karin Hansen, Jim Johnson, Uwe Klinck, Zora Lachmanová, Antti-Jussi Lindroos, Henning Meesenburg, Tiina M. Nieminen, Tanja G. M. Sanders, Kasia Sawicka, Walter Seidling, Anne Thimonier, Elena Vanguelova, Arne Verstraeten, Lars Vesterdal, and Ivan A. Janssens
Biogeosciences, 13, 5567–5585, https://doi.org/10.5194/bg-13-5567-2016, https://doi.org/10.5194/bg-13-5567-2016, 2016
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We investigated the long-term trends of dissolved organic carbon (DOC) in soil solution and the drivers of changes in over 100 forest monitoring plots across Europe. An overall increasing trend was detected in the organic layers, but no overall trend was found in the mineral horizons. There are strong interactions between controls acting at local and regional scales. Our findings are relevant for researchers focusing on the link between terrestrial and aquatic ecosystems and for C-cycle models.
Ivan Mammarella, Olli Peltola, Annika Nordbo, Leena Järvi, and Üllar Rannik
Atmos. Meas. Tech., 9, 4915–4933, https://doi.org/10.5194/amt-9-4915-2016, https://doi.org/10.5194/amt-9-4915-2016, 2016
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In this study we have performed an inter-comparison between EddyUH and EddyPro, two public and commonly used software packages for eddy covariance data processing and calculation. The aims are to estimate the flux uncertainty due to the use of different software packages, and to assess the most critical processing steps, determining the largest deviations in the calculated fluxes. We focus not only on water vapour and carbon dioxide fluxes, but also on the methane flux.
Mari Pihlatie, Üllar Rannik, Sami Haapanala, Olli Peltola, Narasinha Shurpali, Pertti J. Martikainen, Saara Lind, Niina Hyvönen, Perttu Virkajärvi, Mark Zahniser, and Ivan Mammarella
Biogeosciences, 13, 5471–5485, https://doi.org/10.5194/bg-13-5471-2016, https://doi.org/10.5194/bg-13-5471-2016, 2016
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The sources and sinks of carbon monoxide (CO) in the biosphere are poorly understood. We report the first continuous data series of CO fluxes measured by eddy covariance method in an agricultural bioenergy crop. The CO fluxes were seasonally and diurnally variable demonstrating the parallel consumption and production processes. Radiation was the main driver of CO emissions, and the eddy covariance method was demonstrated as suitable for linking short-term flux dynamics to environmental drivers.
Undine Zöll, Christian Brümmer, Frederik Schrader, Christof Ammann, Andreas Ibrom, Christophe R. Flechard, David D. Nelson, Mark Zahniser, and Werner L. Kutsch
Atmos. Chem. Phys., 16, 11283–11299, https://doi.org/10.5194/acp-16-11283-2016, https://doi.org/10.5194/acp-16-11283-2016, 2016
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Accurate quantification of atmospheric ammonia concentration and exchange fluxes with the land surface has been a major metrological challenge. We demonstrate the applicability of a novel laser device to identify concentration and flux patterns over a peatland ecosystem influenced by nearby agricultural practices. Results help to strengthen air quality monitoring networks, lead to better understanding of ecosystem functionality and improve parameterizations in air chemistry and transport models.
Yiying Chen, James Ryder, Vladislav Bastrikov, Matthew J. McGrath, Kim Naudts, Juliane Otto, Catherine Ottlé, Philippe Peylin, Jan Polcher, Aude Valade, Andrew Black, Jan A. Elbers, Eddy Moors, Thomas Foken, Eva van Gorsel, Vanessa Haverd, Bernard Heinesch, Frank Tiedemann, Alexander Knohl, Samuli Launiainen, Denis Loustau, Jérôme Ogée, Timo Vessala, and Sebastiaan Luyssaert
Geosci. Model Dev., 9, 2951–2972, https://doi.org/10.5194/gmd-9-2951-2016, https://doi.org/10.5194/gmd-9-2951-2016, 2016
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In this study, we compiled a set of within-canopy and above-canopy measurements of energy and water fluxes, and used these data to parametrize and validate the new multi-layer energy budget scheme for a range of forest types. An adequate parametrization approach has been presented for the global-scale land surface model (ORCHIDEE-CAN). Furthermore, model performance of the new multi-layer parametrization was compared against the existing single-layer scheme.
Andrey Glazunov, Üllar Rannik, Victor Stepanenko, Vasily Lykosov, Mikko Auvinen, Timo Vesala, and Ivan Mammarella
Geosci. Model Dev., 9, 2925–2949, https://doi.org/10.5194/gmd-9-2925-2016, https://doi.org/10.5194/gmd-9-2925-2016, 2016
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Large-eddy simulation (LES) and Lagrangian stochastic modeling of passive particle dispersion were applied to the scalar flux footprint determination in the stable atmospheric boundary layer. The footprint functions obtained in LES were compared with the functions calculated with the use of first-order single-particle Lagrangian stochastic models (LSMs) and zeroth-order Lagrangian stochastic models - the random displacement models (RDMs).
Victor Stepanenko, Ivan Mammarella, Anne Ojala, Heli Miettinen, Vasily Lykosov, and Timo Vesala
Geosci. Model Dev., 9, 1977–2006, https://doi.org/10.5194/gmd-9-1977-2016, https://doi.org/10.5194/gmd-9-1977-2016, 2016
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A 1-D lake model is presented, reproducing temperature, oxygen, carbon dioxide and methane. All prognostic variables are treated in unified manner via generic 1-D transport equation. The model is validated vs. comprehensive observational data set gathered at Kuivajärvi Lake (Finland). Our results suggest that a gas transfer through thermocline under intense seiche motions is a bottleneck in quantifying greenhouse gas dynamics in dimictic lakes, calling for further research.
Veronika Eyring, Mattia Righi, Axel Lauer, Martin Evaldsson, Sabrina Wenzel, Colin Jones, Alessandro Anav, Oliver Andrews, Irene Cionni, Edouard L. Davin, Clara Deser, Carsten Ehbrecht, Pierre Friedlingstein, Peter Gleckler, Klaus-Dirk Gottschaldt, Stefan Hagemann, Martin Juckes, Stephan Kindermann, John Krasting, Dominik Kunert, Richard Levine, Alexander Loew, Jarmo Mäkelä, Gill Martin, Erik Mason, Adam S. Phillips, Simon Read, Catherine Rio, Romain Roehrig, Daniel Senftleben, Andreas Sterl, Lambertus H. van Ulft, Jeremy Walton, Shiyu Wang, and Keith D. Williams
Geosci. Model Dev., 9, 1747–1802, https://doi.org/10.5194/gmd-9-1747-2016, https://doi.org/10.5194/gmd-9-1747-2016, 2016
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A community diagnostics and performance metrics tool for the evaluation of Earth system models (ESMs) in CMIP has been developed that allows for routine comparison of single or multiple models, either against predecessor versions or against observations.
Üllar Rannik, Luxi Zhou, Putian Zhou, Rosa Gierens, Ivan Mammarella, Andrey Sogachev, and Michael Boy
Atmos. Chem. Phys., 16, 3145–3160, https://doi.org/10.5194/acp-16-3145-2016, https://doi.org/10.5194/acp-16-3145-2016, 2016
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Atmospheric boundary layer (ABL) model coupled with detailed atmospheric chemistry and aerosol dynamical model was used to quantify the role of aerosol and ABL dynamics in the vertical transport of aerosols at a pine forest site in southern Finland. Simulations showed that under dynamical conditions the particle fluxes above canopy can significantly deviate from the dry deposition into the canopy. The deviation can be systematic for certain particle sizes over a period of several days.
X. Wu, N. Vuichard, P. Ciais, N. Viovy, N. de Noblet-Ducoudré, X. Wang, V. Magliulo, M. Wattenbach, L. Vitale, P. Di Tommasi, E. J. Moors, W. Jans, J. Elbers, E. Ceschia, T. Tallec, C. Bernhofer, T. Grünwald, C. Moureaux, T. Manise, A. Ligne, P. Cellier, B. Loubet, E. Larmanou, and D. Ripoche
Geosci. Model Dev., 9, 857–873, https://doi.org/10.5194/gmd-9-857-2016, https://doi.org/10.5194/gmd-9-857-2016, 2016
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The response of crops to changing climate and atmospheric CO2 could have large effects on food production, terrestrial carbon, water, energy fluxes and the climate feedbacks. We developed a new process-oriented terrestrial biogeochemical model named ORCHIDEE-CROP (v0), which integrates a generic crop phenology and harvest module into the land surface model ORCHIDEE. Our model has good ability to capture the spatial gradients of crop phenology, carbon and energy-related variables across Europe.
Saara E. Lind, Narasinha J. Shurpali, Olli Peltola, Ivan Mammarella, Niina Hyvönen, Marja Maljanen, Mari Räty, Perttu Virkajärvi, and Pertti J. Martikainen
Biogeosciences, 13, 1255–1268, https://doi.org/10.5194/bg-13-1255-2016, https://doi.org/10.5194/bg-13-1255-2016, 2016
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We showed that the reed canary grass (RCG) was environmentally friendly from the CO2 balance point of view when cultivated on this mineral soil. When compared to the earlier findings on the same crop on organic soil site, the capacity of the crop to withdraw atmospheric CO2 was even stronger on the present mineral soil site than that on the organic soil site. For full estimation of the climatic impacts of this bioenergy system, a life cycle assessment will be needed.
Y. Gao, T. Markkanen, T. Thum, M. Aurela, A. Lohila, I. Mammarella, M. Kämäräinen, S. Hagemann, and T. Aalto
Hydrol. Earth Syst. Sci., 20, 175–191, https://doi.org/10.5194/hess-20-175-2016, https://doi.org/10.5194/hess-20-175-2016, 2016
S. Sabbatini, N. Arriga, T. Bertolini, S. Castaldi, T. Chiti, C. Consalvo, S. Njakou Djomo, B. Gioli, G. Matteucci, and D. Papale
Biogeosciences, 13, 95–113, https://doi.org/10.5194/bg-13-95-2016, https://doi.org/10.5194/bg-13-95-2016, 2016
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The suitability of a land use change (LUC) from cropland to short rotation coppice of poplar in Central Italy was investigated by comparing the respective greenhouse gas budgets. Biogenic and anthropogenic CO2, CH4, and N2O fluxes, change in soil C stocks, and effects of biomass use were considered. In 2 years the LUC saved 2358 ± 835 gCO2eq m-2. Net ecosystem exchange of CO2 and C exports represented the main contributions to the overall budgets, while soil non-CO2 fluxes were negligible.
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).
P. Kountouris, C. Gerbig, K.-U. Totsche, A. J. Dolman, A. G. C. A. Meesters, G. Broquet, F. Maignan, B. Gioli, L. Montagnani, and C. Helfter
Biogeosciences, 12, 7403–7421, https://doi.org/10.5194/bg-12-7403-2015, https://doi.org/10.5194/bg-12-7403-2015, 2015
Y. Fan, O. Roupsard, M. Bernoux, G. Le Maire, O. Panferov, M. M. Kotowska, and A. Knohl
Geosci. Model Dev., 8, 3785–3800, https://doi.org/10.5194/gmd-8-3785-2015, https://doi.org/10.5194/gmd-8-3785-2015, 2015
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A perennial crop model CLM-Palm is developed, including multilayer structure, phenology, and carbon and nitrogen allocation functions, for modeling an important oil palm agricultural system in the tropical regions. Simulated LAI, yield and NPP were calibrated and validated with multiple sites in Sumatra, Indonesia. The new model allows exploring the effects of tropical land use change, from natural ecosystems to monoculture plantations on carbon, water and energy cycles and regional climate.
A. Olchev, A. Ibrom, O. Panferov, D. Gushchina, H. Kreilein, V. Popov, P. Propastin, T. June, A. Rauf, G. Gravenhorst, and A. Knohl
Biogeosciences, 12, 6655–6667, https://doi.org/10.5194/bg-12-6655-2015, https://doi.org/10.5194/bg-12-6655-2015, 2015
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The time series analysis of the main meteorological parameters and components of CO2 and H2O fluxes showed a high evapotranspiration (ET) and gross primary production (GPP) sensitivity of the tropical rainforest to meteorological variations caused by El Niño-Southern Oscillation (ENSO) events. Incoming solar radiation is the main governing factor that is responsible for ET and GPP variability. Changes in precipitation due to moderate ENSO events did not have any notable effect on ET and GPP.
L. Wingate, J. Ogée, E. Cremonese, G. Filippa, T. Mizunuma, M. Migliavacca, C. Moisy, M. Wilkinson, C. Moureaux, G. Wohlfahrt, A. Hammerle, L. Hörtnagl, C. Gimeno, A. Porcar-Castell, M. Galvagno, T. Nakaji, J. Morison, O. Kolle, A. Knohl, W. Kutsch, P. Kolari, E. Nikinmaa, A. Ibrom, B. Gielen, W. Eugster, M. Balzarolo, D. Papale, K. Klumpp, B. Köstner, T. Grünwald, R. Joffre, J.-M. Ourcival, M. Hellstrom, A. Lindroth, C. George, B. Longdoz, B. Genty, J. Levula, B. Heinesch, M. Sprintsin, D. Yakir, T. Manise, D. Guyon, H. Ahrends, A. Plaza-Aguilar, J. H. Guan, and J. Grace
Biogeosciences, 12, 5995–6015, https://doi.org/10.5194/bg-12-5995-2015, https://doi.org/10.5194/bg-12-5995-2015, 2015
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The timing of plant development stages and their response to climate and management were investigated using a network of digital cameras installed across different European ecosystems. Using the relative red, green and blue content of images we showed that the green signal could be used to estimate the length of the growing season in broadleaf forests. We also developed a model that predicted the seasonal variations of camera RGB signals and how they relate to leaf pigment content and area well.
E. Varolo, D. Zanotelli, M. Tagliavini, S. Zerbe, and L. Montagnani
Biogeosciences Discuss., https://doi.org/10.5194/bgd-12-10271-2015, https://doi.org/10.5194/bgd-12-10271-2015, 2015
Revised manuscript not accepted
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Vegetation growth after glaciers retreat can be an important feedback to increasing atmospheric CO2. We monitored, with transparent and opaque chambers, the carbon fluxes of two vegetation communities on an alpine glacier forefield over two growing seasons. We showed that different plant physiology determines the sign of the net carbon exchange. A C3 grassland, having higher assimilation rates, was a net CO2 sink, while CAM rosettes were a net source.
F. Minunno, M. Peltoniemi, S. Launiainen, M. Aurela, A. Lindroth, A. Lohila, I. Mammarella, K. Minkkinen, and A. Mäkelä
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmdd-8-5089-2015, https://doi.org/10.5194/gmdd-8-5089-2015, 2015
Revised manuscript not accepted
Ü. Rannik, S. Haapanala, N. J. Shurpali, I. Mammarella, S. Lind, N. Hyvönen, O. Peltola, M. Zahniser, P. J. Martikainen, and T. Vesala
Biogeosciences, 12, 415–432, https://doi.org/10.5194/bg-12-415-2015, https://doi.org/10.5194/bg-12-415-2015, 2015
S. Kuppel, P. Peylin, F. Maignan, F. Chevallier, G. Kiely, L. Montagnani, and A. Cescatti
Geosci. Model Dev., 7, 2581–2597, https://doi.org/10.5194/gmd-7-2581-2014, https://doi.org/10.5194/gmd-7-2581-2014, 2014
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A consistent calibration of an advanced land surface model was performed by grouping in situ information on land-atmosphere exchanges of carbon and water using broad ecosystem and climate classes. Signatures of improved carbon cycle simulations were found across spatial and temporal scales, along with insights into current model limitations. These results hold promising perspectives within the ongoing efforts towards building robust model-data fusion frameworks for earth system models.
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
O. Peltola, A. Hensen, C. Helfter, L. Belelli Marchesini, F. C. Bosveld, W. C. M. van den Bulk, J. A. Elbers, S. Haapanala, J. Holst, T. Laurila, A. Lindroth, E. Nemitz, T. Röckmann, A. T. Vermeulen, and I. Mammarella
Biogeosciences, 11, 3163–3186, https://doi.org/10.5194/bg-11-3163-2014, https://doi.org/10.5194/bg-11-3163-2014, 2014
F. Fattore, T. Bertolini, S. Materia, S. Gualdi, A. Thongo M'Bou, G. Nicolini, R. Valentini, A. De Grandcourt, D. Tedesco, and S. Castaldi
Biogeosciences, 11, 3069–3081, https://doi.org/10.5194/bg-11-3069-2014, https://doi.org/10.5194/bg-11-3069-2014, 2014
J. Otto, D. Berveiller, F.-M. Bréon, N. Delpierre, G. Geppert, A. Granier, W. Jans, A. Knohl, A. Kuusk, B. Longdoz, E. Moors, M. Mund, B. Pinty, M.-J. Schelhaas, and S. Luyssaert
Biogeosciences, 11, 2411–2427, https://doi.org/10.5194/bg-11-2411-2014, https://doi.org/10.5194/bg-11-2411-2014, 2014
M. Verma, M. A. Friedl, A. D. Richardson, G. Kiely, A. Cescatti, B. E. Law, G. Wohlfahrt, B. Gielen, O. Roupsard, E. J. Moors, P. Toscano, F. P. Vaccari, D. Gianelle, G. Bohrer, A. Varlagin, N. Buchmann, E. van Gorsel, L. Montagnani, and P. Propastin
Biogeosciences, 11, 2185–2200, https://doi.org/10.5194/bg-11-2185-2014, https://doi.org/10.5194/bg-11-2185-2014, 2014
S. Turquety, L. Menut, B. Bessagnet, A. Anav, N. Viovy, F. Maignan, and M. Wooster
Geosci. Model Dev., 7, 587–612, https://doi.org/10.5194/gmd-7-587-2014, https://doi.org/10.5194/gmd-7-587-2014, 2014
S. Burri, P. Sturm, U. E. Prechsl, A. Knohl, and N. Buchmann
Biogeosciences, 11, 961–975, https://doi.org/10.5194/bg-11-961-2014, https://doi.org/10.5194/bg-11-961-2014, 2014
D. Dalmonech, A. M. Foley, A. Anav, P. Friedlingstein, A. D. Friend, M. Kidston, M. Willeit, and S. Zaehle
Biogeosciences Discuss., https://doi.org/10.5194/bgd-11-2083-2014, https://doi.org/10.5194/bgd-11-2083-2014, 2014
Revised manuscript has not been submitted
R. Valentini, A. Arneth, A. Bombelli, S. Castaldi, R. Cazzolla Gatti, F. Chevallier, P. Ciais, E. Grieco, J. Hartmann, M. Henry, R. A. Houghton, M. Jung, W. L. Kutsch, Y. Malhi, E. Mayorga, L. Merbold, G. Murray-Tortarolo, D. Papale, P. Peylin, B. Poulter, P. A. Raymond, M. Santini, S. Sitch, G. Vaglio Laurin, G. R. van der Werf, C. A. Williams, and R. J. Scholes
Biogeosciences, 11, 381–407, https://doi.org/10.5194/bg-11-381-2014, https://doi.org/10.5194/bg-11-381-2014, 2014
W. Yuan, S. Liu, W. Cai, W. Dong, J. Chen, A. Arain, P. D. Blanken, A. Cescatti, G. Wohlfahrt, T. Georgiadis, L. Genesio, D. Gianelle, A. Grelle, G. Kiely, A. Knohl, D. Liu, M. Marek, L. Merbold, L. Montagnani, O. Panferov, M. Peltoniemi, S. Rambal, A. Raschi, A. Varlagin, and J. Xia
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmdd-6-5475-2013, https://doi.org/10.5194/gmdd-6-5475-2013, 2013
Revised manuscript not accepted
J. H. Shim, H. H. Powers, C. W. Meyer, A. Knohl, T. E. Dawson, W. J. Riley, W. T. Pockman, and N. McDowell
Biogeosciences, 10, 4937–4956, https://doi.org/10.5194/bg-10-4937-2013, https://doi.org/10.5194/bg-10-4937-2013, 2013
M. C. Rulli, L. Offeddu, and M. Santini
Hydrol. Earth Syst. Sci., 17, 2323–2337, https://doi.org/10.5194/hess-17-2323-2013, https://doi.org/10.5194/hess-17-2323-2013, 2013
S. Castaldi, T. Bertolini, A. Valente, T. Chiti, and R. Valentini
Biogeosciences, 10, 4179–4187, https://doi.org/10.5194/bg-10-4179-2013, https://doi.org/10.5194/bg-10-4179-2013, 2013
O. Peltola, I. Mammarella, S. Haapanala, G. Burba, and T. Vesala
Biogeosciences, 10, 3749–3765, https://doi.org/10.5194/bg-10-3749-2013, https://doi.org/10.5194/bg-10-3749-2013, 2013
D. Zanotelli, L. Montagnani, G. Manca, and M. Tagliavini
Biogeosciences, 10, 3089–3108, https://doi.org/10.5194/bg-10-3089-2013, https://doi.org/10.5194/bg-10-3089-2013, 2013
L. Wang, A. Ibrom, J. F. J. Korhonen, K. F. Arnoud Frumau, J. Wu, M. Pihlatie, and J. K. Schjoerring
Biogeosciences, 10, 999–1011, https://doi.org/10.5194/bg-10-999-2013, https://doi.org/10.5194/bg-10-999-2013, 2013
G. Lasslop, M. Migliavacca, G. Bohrer, M. Reichstein, M. Bahn, A. Ibrom, C. Jacobs, P. Kolari, D. Papale, T. Vesala, G. Wohlfahrt, and A. Cescatti
Biogeosciences, 9, 5243–5259, https://doi.org/10.5194/bg-9-5243-2012, https://doi.org/10.5194/bg-9-5243-2012, 2012
Related subject area
Biogeosciences
Alquimia v1.0: a generic interface to biogeochemical codes – a tool for interoperable development, prototyping and benchmarking for multiphysics simulators
Soil nitrous oxide emissions from global land ecosystems and their drivers within the LPJ-GUESS model (v4.1)
Parameterization toolbox for a physical–biogeochemical model compatible with FABM – a case study: the coupled 1D GOTM–ECOSMO E2E for the Sylt–Rømø Bight, North Sea
H2MV (v1.0): global physically constrained deep learning water cycle model with vegetation
NN-TOC v1: global prediction of total organic carbon in marine sediments using deep neural networks
China Wildfire Emission Dataset (ChinaWED v1) for the period 2012–2022
Process-based modeling of solar-induced chlorophyll fluorescence with VISIT-SIF version 1.0
Including the phosphorus cycle into the LPJ-GUESS dynamic global vegetation model (v4.1, r10994) – global patterns and temporal trends of N and P primary production limitation
A comprehensive land-surface vegetation model for multi-stream data assimilation, D&B v1.0
Sources of uncertainty in the SPITFIRE global fire model: development of LPJmL-SPITFIRE1.9 and directions for future improvements
Spatially varying parameters improve carbon cycle modeling in the Amazon rainforest with ORCHIDEE r8849
The unicellular NUM v.0.91: a trait-based plankton model evaluated in two contrasting biogeographic provinces
FESOM2.1-REcoM3-MEDUSA2: an ocean–sea ice–biogeochemistry model coupled to a sediment model
Satellite-based modeling of wetland methane emissions on a global scale (SatWetCH4 1.0)
Emulating grid-based forest carbon dynamics using machine learning: an LPJ-GUESS v4.1.1 application
Systematic underestimation of type-specific ecosystem process variability in the Community Land Model v5 over Europe
pyVPRM: A next-generation Vegetation Photosynthesis and Respiration Model for the post-MODIS era
Lambda-PFLOTRAN 1.0: a workflow for incorporating organic matter chemistry informed by ultra high resolution mass spectrometry into biogeochemical modeling
An improved model for air–sea exchange of elemental mercury in MITgcm-ECCOv4-Hg: the role of surfactants and waves
BOATSv2: new ecological and economic features improve simulations of high seas catch and effort
A dynamical process-based model for quantifying global agricultural ammonia emissions – AMmonia–CLIMate v1.0 (AMCLIM v1.0) – Part 1: Land module for simulating emissions from synthetic fertilizer use
Simulating the drought response of European tree species with the dynamic vegetation model LPJ-GUESS (v4.1, 97c552c5)
Simulating Ips typographus L. outbreak dynamics and their influence on carbon balance estimates with ORCHIDEE r8627
Biological nitrogen fixation of natural and agricultural vegetation simulated with LPJmL 5.7.9
BIOPERIANT12: a mesoscale resolving coupled physics-biogeochemical model for the Southern Ocean
Learning from conceptual models – a study of the emergence of cooperation towards resource protection in a social–ecological system
Development and assessment of the physical-biogeochemical ocean regional model in the Northwest Pacific: NPRT v1.0 (ROMS v3.9–TOPAZ v2.0)
TROLL 4.0: representing water and carbon fluxes, leaf phenology and intraspecific trait variation in a mixed-species individual-based forest dynamics model – Part 1: Model description
The biogeochemical model Biome-BGCMuSo v6.2 provides plausible and accurate simulations of the carbon cycle in central European beech forests
TROLL 4.0: representing water and carbon fluxes, leaf phenology, and intraspecific trait variation in a mixed-species individual-based forest dynamics model – Part 2: Model evaluation for two Amazonian sites
Estimation of above- and below-ground ecosystem parameters for the DVM-DOS-TEM v0.7.0 model using MADS v1.7.3: a synthetic case study
DeepPhenoMem V1.0: deep learning modelling of canopy greenness dynamics accounting for multi-variate meteorological memory effects on vegetation phenology
Impacts of land-use change on biospheric carbon: an oriented benchmark using the ORCHIDEE land surface model
Implementing the iCORAL (version 1.0) coral reef CaCO3 production module in the iLOVECLIM climate model
Assimilation of carbonyl sulfide (COS) fluxes within the adjoint-based data assimilation system – Nanjing University Carbon Assimilation System (NUCAS v1.0)
ML4Fire-XGBv1.0: Improving North American wildfire prediction by integrating a machine-learning fire model in a land surface model
Quantifying the role of ozone-caused damage to vegetation in the Earth system: a new parameterization scheme for photosynthetic and stomatal responses
Radiocarbon analysis reveals underestimation of soil organic carbon persistence in new-generation soil models
Exploring the potential of history matching for land surface model calibration
EAT v1.0.0: a 1D test bed for physical–biogeochemical data assimilation in natural waters
Using deep learning to integrate paleoclimate and global biogeochemistry over the Phanerozoic Eon
Modelling boreal forest's mineral soil and peat C dynamics with the Yasso07 model coupled with the Ricker moisture modifier
Dynamic ecosystem assembly and escaping the “fire trap” in the tropics: insights from FATES_15.0.0
In silico calculation of soil pH by SCEPTER v1.0
Simple process-led algorithms for simulating habitats (SPLASH v.2.0): robust calculations of water and energy fluxes
A global behavioural model of human fire use and management: WHAM! v1.0
Terrestrial Ecosystem Model in R (TEMIR) version 1.0: simulating ecophysiological responses of vegetation to atmospheric chemical and meteorological changes
biospheremetrics v1.0.2: an R package to calculate two complementary terrestrial biosphere integrity indicators – human colonization of the biosphere (BioCol) and risk of ecosystem destabilization (EcoRisk)
Modeling boreal forest soil dynamics with the microbially explicit soil model MIMICS+ (v1.0)
Optimal enzyme allocation leads to the constrained enzyme hypothesis: the Soil Enzyme Steady Allocation Model (SESAM; v3.1)
Sergi Molins, Benjamin J. Andre, Jeffrey N. Johnson, Glenn E. Hammond, Benjamin N. Sulman, Konstantin Lipnikov, Marcus S. Day, James J. Beisman, Daniil Svyatsky, Hang Deng, Peter C. Lichtner, Carl I. Steefel, and J. David Moulton
Geosci. Model Dev., 18, 3241–3263, https://doi.org/10.5194/gmd-18-3241-2025, https://doi.org/10.5194/gmd-18-3241-2025, 2025
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Developing scientific software and making sure it functions properly requires a significant effort. As we advance our understanding of natural systems, however, there is the need to develop yet more complex models and codes. In this work, we present a piece of software that facilitates this work, specifically with regard to reactive processes. Existing tried-and-true codes are made available via this new interface, freeing up resources to focus on the new aspects of the problems at hand.
Jianyong Ma, Almut Arneth, Benjamin Smith, Peter Anthoni, Xu-Ri, Peter Eliasson, David Wårlind, Martin Wittenbrink, and Stefan Olin
Geosci. Model Dev., 18, 3131–3155, https://doi.org/10.5194/gmd-18-3131-2025, https://doi.org/10.5194/gmd-18-3131-2025, 2025
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Nitrous oxide (N2O) is a powerful greenhouse gas mainly released from natural and agricultural soils. This study examines how global soil N2O emissions changed from 1961 to 2020 and identifies key factors driving these changes using an ecological model. The findings highlight croplands as the largest source, with factors like fertilizer use and climate change enhancing emissions. Rising CO2 levels, however, can partially mitigate N2O emissions through increased plant nitrogen uptake.
Hoa Nguyen, Ute Daewel, Neil Banas, and Corinna Schrum
Geosci. Model Dev., 18, 2961–2982, https://doi.org/10.5194/gmd-18-2961-2025, https://doi.org/10.5194/gmd-18-2961-2025, 2025
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Parameterization is key in modeling to reproduce observations well but is often done manually. This study presents a particle-swarm-optimizer-based toolbox for marine ecosystem models, compatible with the Framework for Aquatic Biogeochemical Models, thus enhancing its reusability. Applied to the Sylt ecosystem, the toolbox effectively (1) identified multiple parameter sets that matched observations well, providing different insights into ecosystem dynamics, and (2) optimized model complexity.
Zavud Baghirov, Martin Jung, Markus Reichstein, Marco Körner, and Basil Kraft
Geosci. Model Dev., 18, 2921–2943, https://doi.org/10.5194/gmd-18-2921-2025, https://doi.org/10.5194/gmd-18-2921-2025, 2025
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We use an innovative approach to studying the Earth's water cycle by integrating advanced machine learning techniques with a traditional water cycle model. Our model is designed to learn from observational data, with a particular emphasis on understanding the influence of vegetation on water movement. By closely aligning with real-world observations, our model offers new possibilities for enhancing our understanding of the water cycle and its interactions with vegetation.
Naveenkumar Parameswaran, Everardo González, Ewa Burwicz-Galerne, Malte Braack, and Klaus Wallmann
Geosci. Model Dev., 18, 2521–2544, https://doi.org/10.5194/gmd-18-2521-2025, https://doi.org/10.5194/gmd-18-2521-2025, 2025
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Our research uses deep learning to predict organic carbon stocks in ocean sediments, which is crucial for understanding their role in the global carbon cycle. By analysing over 22 000 samples and various seafloor characteristics, our model gives more accurate results than traditional methods. We estimate that the top 10 cm of ocean sediments hold about 156 Pg of carbon. This work enhances carbon stock estimates and helps plan future sampling strategies to better understand oceanic carbon burial.
Zhengyang Lin, Ling Huang, Hanqin Tian, Anping Chen, and Xuhui Wang
Geosci. Model Dev., 18, 2509–2520, https://doi.org/10.5194/gmd-18-2509-2025, https://doi.org/10.5194/gmd-18-2509-2025, 2025
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The China Wildfire Emission Dataset (ChinaWED v1) estimated wildfire emissions in China during 2012–2022 as 78.13 Tg CO2, 279.47 Gg CH4, and 6.26 Gg N2O annually. Agricultural fires dominated emissions, while forest and grassland emissions decreased. Seasonal peaks occurred in late spring, with hotspots in northeast, southwest, and east China. The model emphasizes the importance of using localized emission factors and high-resolution fire estimates for accurate assessments.
Tatsuya Miyauchi, Makoto Saito, Hibiki M. Noda, Akihiko Ito, Tomomichi Kato, and Tsuneo Matsunaga
Geosci. Model Dev., 18, 2329–2347, https://doi.org/10.5194/gmd-18-2329-2025, https://doi.org/10.5194/gmd-18-2329-2025, 2025
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Solar-induced chlorophyll fluorescence (SIF) is an effective indicator for monitoring photosynthetic activity. This paper introduces VISIT-SIF, a biogeochemical model developed based on the Vegetation Integrative Simulator for Trace gases (VISIT) to represent satellite-observed SIF. Our simulations reproduced the global distribution and seasonal variations in observed SIF. VISIT-SIF helps to improve photosynthetic processes through a combination of biogeochemical modeling and observed SIF.
Mateus Dantas de Paula, Matthew Forrest, David Warlind, João Paulo Darela Filho, Katrin Fleischer, Anja Rammig, and Thomas Hickler
Geosci. Model Dev., 18, 2249–2274, https://doi.org/10.5194/gmd-18-2249-2025, https://doi.org/10.5194/gmd-18-2249-2025, 2025
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Our study maps global nitrogen (N) and phosphorus (P) availability and how they changed from 1901 to 2018. We find that tropical regions are mostly P-limited, while temperate and boreal areas face N limitations. Over time, P limitation increased, especially in the tropics, while N limitation decreased. These shifts are key to understanding global plant growth and carbon storage, highlighting the importance of including P dynamics in ecosystem models.
Wolfgang Knorr, Matthew Williams, Tea Thum, Thomas Kaminski, Michael Voßbeck, Marko Scholze, Tristan Quaife, T. Luke Smallman, Susan C. Steele-Dunne, Mariette Vreugdenhil, Tim Green, Sönke Zaehle, Mika Aurela, Alexandre Bouvet, Emanuel Bueechi, Wouter Dorigo, Tarek S. El-Madany, Mirco Migliavacca, Marika Honkanen, Yann H. Kerr, Anna Kontu, Juha Lemmetyinen, Hannakaisa Lindqvist, Arnaud Mialon, Tuuli Miinalainen, Gaétan Pique, Amanda Ojasalo, Shaun Quegan, Peter J. Rayner, Pablo Reyes-Muñoz, Nemesio Rodríguez-Fernández, Mike Schwank, Jochem Verrelst, Songyan Zhu, Dirk Schüttemeyer, and Matthias Drusch
Geosci. Model Dev., 18, 2137–2159, https://doi.org/10.5194/gmd-18-2137-2025, https://doi.org/10.5194/gmd-18-2137-2025, 2025
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When it comes to climate change, the land surface is where the vast majority of impacts happen. The task of monitoring those impacts across the globe is formidable and must necessarily rely on satellites – at a significant cost: the measurements are only indirect and require comprehensive physical understanding. We have created a comprehensive modelling system that we offer to the research community to explore how satellite data can be better exploited to help us capture the changes that happen on our lands.
Luke Oberhagemann, Maik Billing, Werner von Bloh, Markus Drüke, Matthew Forrest, Simon P. K. Bowring, Jessica Hetzer, Jaime Ribalaygua Batalla, and Kirsten Thonicke
Geosci. Model Dev., 18, 2021–2050, https://doi.org/10.5194/gmd-18-2021-2025, https://doi.org/10.5194/gmd-18-2021-2025, 2025
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Under climate change, the conditions necessary for wildfires to form are occurring more frequently in many parts of the world. To help predict how wildfires will change in future, global fire models are being developed. We analyze and further develop one such model, SPITFIRE. Our work identifies and corrects sources of substantial bias in the model that are important to the global fire modelling field. With this analysis and these developments, we help to provide a basis for future improvements.
Lei Zhu, Philippe Ciais, Yitong Yao, Daniel Goll, Sebastiaan Luyssaert, Isabel Martínez Cano, Arthur Fendrich, Laurent Li, Hui Yang, Sassan Saatchi, and Wei Li
EGUsphere, https://doi.org/10.5194/egusphere-2025-397, https://doi.org/10.5194/egusphere-2025-397, 2025
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This study enhances the accuracy of modeling the carbon dynamics of Amazon rainforest by optimizing key model parameters based on satellite data. Using spatially varying parameters for tree mortality and photosynthesis, we improved predictions of biomass, productivity, and tree mortality. Our findings highlight the critical role of wood density and water availability in forest processes, offering insights to refine global carbon cycle models.
Trine Frisbæk Hansen, Donald Eugene Canfield, Ken Haste Andersen, and Christian Jannik Bjerrum
Geosci. Model Dev., 18, 1895–1916, https://doi.org/10.5194/gmd-18-1895-2025, https://doi.org/10.5194/gmd-18-1895-2025, 2025
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We describe and test the size-based Nutrient-Unicellular-Multicellular model, which defines unicellular plankton using a single set of parameters, on a eutrophic and oligotrophic ecosystem. The results demonstrate that both sites can be modeled with similar parameters and robust performance over a wide range of parameters. The study shows that the model is useful for non-experts and applicable for modeling ecosystems with limited data. It holds promise for evolutionary and deep-time climate models.
Ying Ye, Guy Munhoven, Peter Köhler, Martin Butzin, Judith Hauck, Özgür Gürses, and Christoph Völker
Geosci. Model Dev., 18, 977–1000, https://doi.org/10.5194/gmd-18-977-2025, https://doi.org/10.5194/gmd-18-977-2025, 2025
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Many biogeochemistry models assume all material reaching the seafloor is remineralized and returned to solution, which is sufficient for studies on short-term climate change. Under long-term climate change, the carbon storage in sediments slows down carbon cycling and influences feedbacks in the atmosphere–ocean–sediment system. This paper describes the coupling of a sediment model to an ocean biogeochemistry model and presents results under the pre-industrial climate and under CO2 perturbation.
Juliette Bernard, Elodie Salmon, Marielle Saunois, Shushi Peng, Penélope Serrano-Ortiz, Antoine Berchet, Palingamoorthy Gnanamoorthy, Joachim Jansen, and Philippe Ciais
Geosci. Model Dev., 18, 863–883, https://doi.org/10.5194/gmd-18-863-2025, https://doi.org/10.5194/gmd-18-863-2025, 2025
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Despite their importance, uncertainties remain in the evaluation of the drivers of temporal variability of methane emissions from wetlands on a global scale. Here, a simplified global model is developed, taking advantage of advances in remote-sensing data and in situ observations. The model reproduces the large spatial and temporal patterns of emissions, albeit with limitations in the tropics due to data scarcity. This model, while simple, can provide valuable insights into sensitivity analyses.
Carolina Natel, David Martin Belda, Peter Anthoni, Neele Haß, Sam Rabin, and Almut Arneth
EGUsphere, https://doi.org/10.5194/egusphere-2024-4064, https://doi.org/10.5194/egusphere-2024-4064, 2025
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Complex models predict forest carbon responses to future climate change but are slow and computationally intensive, limiting large-scale analyses. We used machine learning to accelerate predictions from the LPJ-GUESS vegetation model. Our emulators, based on random forests and neural networks, achieved 97 % faster simulations. This approach enables rapid exploration of climate mitigation strategies and supports informed policy decisions.
Christian Poppe Terán, Bibi S. Naz, Harry Vereecken, Roland Baatz, Rosie A. Fisher, and Harrie-Jan Hendricks Franssen
Geosci. Model Dev., 18, 287–317, https://doi.org/10.5194/gmd-18-287-2025, https://doi.org/10.5194/gmd-18-287-2025, 2025
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Carbon and water exchanges between the atmosphere and the land surface contribute to water resource availability and climate change mitigation. Land surface models, like the Community Land Model version 5 (CLM5), simulate these. This study finds that CLM5 and other data sets underestimate the magnitudes of and variability in carbon and water exchanges for the most abundant plant functional types compared to observations. It provides essential insights for further research into these processes.
Theo Glauch, Julia Marshall, Christoph Gerbig, Santiago Botía, Michał Gałkowski, Sanam N. Vardag, and André Butz
EGUsphere, https://doi.org/10.5194/egusphere-2024-3692, https://doi.org/10.5194/egusphere-2024-3692, 2025
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The Vegetation Photosynthesis and Respiration Model (VPRM) estimates carbon exchange between the atmosphere and biosphere by modeling gross primary production and respiration using satellite data and weather variables. Our new version, pyVPRM, supports diverse satellite products like Sentinel-2, MODIS, VIIRS and new land cover maps, enabling high spatial and temporal resolution. This improves flux estimates, especially in complex landscapes, and ensures continuity as MODIS nears decommissioning.
Katherine A. Muller, Peishi Jiang, Glenn Hammond, Tasneem Ahmadullah, Hyun-Seob Song, Ravi Kukkadapu, Nicholas Ward, Madison Bowe, Rosalie K. Chu, Qian Zhao, Vanessa A. Garayburu-Caruso, Alan Roebuck, and Xingyuan Chen
Geosci. Model Dev., 17, 8955–8968, https://doi.org/10.5194/gmd-17-8955-2024, https://doi.org/10.5194/gmd-17-8955-2024, 2024
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The new Lambda-PFLOTRAN workflow incorporates organic matter chemistry into reaction networks to simulate aerobic respiration and biogeochemistry. Lambda-PFLOTRAN is a Python-based workflow in a Jupyter notebook interface that digests raw organic matter chemistry data via Fourier transform ion cyclotron resonance mass spectrometry, develops a representative reaction network, and completes a biogeochemical simulation with the open-source, parallel-reactive-flow, and transport code PFLOTRAN.
Ling Li, Peipei Wu, Peng Zhang, Shaojian Huang, and Yanxu Zhang
Geosci. Model Dev., 17, 8683–8695, https://doi.org/10.5194/gmd-17-8683-2024, https://doi.org/10.5194/gmd-17-8683-2024, 2024
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In this study, we incorporate sea surfactants and wave-breaking processes into MITgcm-ECCOv4-Hg. The updated model shows increased fluxes in high-wind-speed and high-wave regions and vice versa, enhancing spatial heterogeneity. It shows that elemental mercury (Hg0) transfer velocity is more sensitive to wind speed. These findings may elucidate the discrepancies in previous estimations and offer insights into global Hg cycling.
Jerome Guiet, Daniele Bianchi, Kim J. N. Scherrer, Ryan F. Heneghan, and Eric D. Galbraith
Geosci. Model Dev., 17, 8421–8454, https://doi.org/10.5194/gmd-17-8421-2024, https://doi.org/10.5194/gmd-17-8421-2024, 2024
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The BiOeconomic mArine Trophic Size-spectrum (BOATSv2) model dynamically simulates global commercial fish populations and their coupling with fishing activity, as emerging from environmental and economic drivers. New features, including separate pelagic and demersal populations, iron limitation, and spatial variation of fishing costs and management, improve the accuracy of high seas fisheries. The updated model code is available to simulate both historical and future scenarios.
Jize Jiang, David S. Stevenson, and Mark A. Sutton
Geosci. Model Dev., 17, 8181–8222, https://doi.org/10.5194/gmd-17-8181-2024, https://doi.org/10.5194/gmd-17-8181-2024, 2024
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A special model called AMmonia–CLIMate (AMCLIM) has been developed to understand and calculate NH3 emissions from fertilizer use and also taking into account how the environment influences these NH3 emissions. It is estimated that about 17 % of applied N in fertilizers was lost due to NH3 emissions. Hot and dry conditions and regions with high-pH soils can expect higher NH3 emissions.
Benjamin Franklin Meyer, João Paulo Darela-Filho, Konstantin Gregor, Allan Buras, Qiao-Lin Gu, Andreas Krause, Daijun Liu, Phillip Papastefanou, Sijeh Asuk, Thorsten E. E. Grams, Christian S. Zang, and Anja Rammig
EGUsphere, https://doi.org/10.5194/egusphere-2024-3352, https://doi.org/10.5194/egusphere-2024-3352, 2024
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Climate change has increased the likelihood of drought events across Europe, potentially threatening European forest carbon sink. Dynamic vegetation models with mechanistic plant hydraulic architecture are needed to model these developments. We evaluate the plant hydraulic architecture version of LPJ-GUESS and show it's capability at capturing species-specific evapotranspiration responses to drought and reproducing flux observations of both gross primary production and evapotranspiration.
Guillaume Marie, Jina Jeong, Hervé Jactel, Gunnar Petter, Maxime Cailleret, Matthew J. McGrath, Vladislav Bastrikov, Josefine Ghattas, Bertrand Guenet, Anne Sofie Lansø, Kim Naudts, Aude Valade, Chao Yue, and Sebastiaan Luyssaert
Geosci. Model Dev., 17, 8023–8047, https://doi.org/10.5194/gmd-17-8023-2024, https://doi.org/10.5194/gmd-17-8023-2024, 2024
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This research looks at how climate change influences forests, and particularly how altered wind and insect activities could make forests emit instead of absorb carbon. We have updated a land surface model called ORCHIDEE to better examine the effect of bark beetles on forest health. Our findings suggest that sudden events, such as insect outbreaks, can dramatically affect carbon storage, offering crucial insights into tackling climate change.
Stephen Björn Wirth, Johanna Braun, Jens Heinke, Sebastian Ostberg, Susanne Rolinski, Sibyll Schaphoff, Fabian Stenzel, Werner von Bloh, Friedhelm Taube, and Christoph Müller
Geosci. Model Dev., 17, 7889–7914, https://doi.org/10.5194/gmd-17-7889-2024, https://doi.org/10.5194/gmd-17-7889-2024, 2024
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We present a new approach to modelling biological nitrogen fixation (BNF) in the Lund–Potsdam–Jena managed Land dynamic global vegetation model. While in the original approach BNF depended on actual evapotranspiration, the new approach considers soil water content and temperature, vertical root distribution, the nitrogen (N) deficit and carbon (C) costs. The new approach improved simulated BNF compared to the scientific literature and the model ability to project future C and N cycle dynamics.
Nicolette Chang, Sarah-Anne Nicholson, Marcel du Plessis, Alice D. Lebehot, Thulwaneng Mashifane, Tumelo C. Moalusi, N. Precious Mongwe, and Pedro M. S. Monteiro
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-182, https://doi.org/10.5194/gmd-2024-182, 2024
Revised manuscript accepted for GMD
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Mesoscale features (10's to 100's of km) in the Southern Ocean (SO) are crucial for global heat and carbon transport, but often unresolved in models due to high computational costs. To address this source of uncertainty, we use a regional, NEMO model of the SO at 8 km resolution with coupled ocean, ice, and biogeochemistry, BIOPERIANT12. This serves as an experimental platform to explore physical-biogeochemical interactions, model parameters/formulations, and configuring future models.
Saeed Harati-Asl, Liliana Perez, and Roberto Molowny-Horas
Geosci. Model Dev., 17, 7423–7443, https://doi.org/10.5194/gmd-17-7423-2024, https://doi.org/10.5194/gmd-17-7423-2024, 2024
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Social–ecological systems are the subject of many sustainability problems. Because of the complexity of these systems, we must be careful when intervening in them; otherwise we may cause irreversible damage. Using computer models, we can gain insight about these complex systems without harming them. In this paper we describe how we connected an ecological model of forest insect infestation with a social model of cooperation and simulated an intervention measure to save a forest from infestation.
Daehyuk Kim, Hyun-Chae Jung, Jae-Hong Moon, and Na-Hyeon Lee
EGUsphere, https://doi.org/10.5194/egusphere-2024-1509, https://doi.org/10.5194/egusphere-2024-1509, 2024
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Physical–biogeochemical ocean global models is difficult to analyze oceanic environmental systems. To accurately understand the physical–biogeochemical processes at the regional scale, physical and biogeochemical models were coupled at a high resolution. The results successfully simulated the seasonal variations of chlorophyll and nutrients, particularly in the marginal seas, which were not captured by global models. The model is an important tool for studying physical–biogeochemical processes.
Isabelle Maréchaux, Fabian Jörg Fischer, Sylvain Schmitt, and Jérôme Chave
EGUsphere, https://doi.org/10.5194/egusphere-2024-3104, https://doi.org/10.5194/egusphere-2024-3104, 2024
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We describe TROLL 4.0, a simulator of forest dynamics that represents trees in a virtual space at one-meter resolution. Tree birth, growth, death and the underlying physiological processes such as carbon assimilation, water transpiration and leaf phenology depend on plant traits that are measured in the field for many individuals and species. The model is thus capable of jointly simulating forest structure, diversity and ecosystem functioning, a major challenge in modelling vegetation dynamics.
Katarína Merganičová, Ján Merganič, Laura Dobor, Roland Hollós, Zoltán Barcza, Dóra Hidy, Zuzana Sitková, Pavel Pavlenda, Hrvoje Marjanovic, Daniel Kurjak, Michal Bošel'a, Doroteja Bitunjac, Maša Zorana Ostrogović Sever, Jiří Novák, Peter Fleischer, and Tomáš Hlásny
Geosci. Model Dev., 17, 7317–7346, https://doi.org/10.5194/gmd-17-7317-2024, https://doi.org/10.5194/gmd-17-7317-2024, 2024
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We developed a multi-objective calibration approach leading to robust parameter values aiming to strike a balance between their local precision and broad applicability. Using the Biome-BGCMuSo model, we tested the calibrated parameter sets for simulating European beech forest dynamics across large environmental gradients. Leveraging data from 87 plots and five European countries, the results demonstrated reasonable local accuracy and plausible large-scale productivity responses.
Sylvain Schmitt, Fabian Fischer, James Ball, Nicolas Barbier, Marion Boisseaux, Damien Bonal, Benoit Burban, Xiuzhi Chen, Géraldine Derroire, Jeremy Lichstein, Daniela Nemetschek, Natalia Restrepo-Coupe, Scott Saleska, Giacomo Sellan, Philippe Verley, Grégoire Vincent, Camille Ziegler, Jérôme Chave, and Isabelle Maréchaux
EGUsphere, https://doi.org/10.5194/egusphere-2024-3106, https://doi.org/10.5194/egusphere-2024-3106, 2024
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We evaluate the capability of TROLL 4.0, a simulator of forest dynamics, to represent tropical forest structure, diversity and functioning in two Amazonian forests. Evaluation data include forest inventories, carbon and water fluxes between the forest and the atmosphere, and leaf area and canopy height from remote-sensing products. The model realistically predicts the structure and composition, and the seasonality of carbon and water fluxes at both sites.
Elchin E. Jafarov, Helene Genet, Velimir V. Vesselinov, Valeria Briones, Aiza Kabeer, Andrew L. Mullen, Benjamin Maglio, Tobey Carman, Ruth Rutter, Joy Clein, Chu-Chun Chang, Dogukan Teber, Trevor Smith, Joshua M. Rady, Christina Schädel, Jennifer D. Watts, Brendan M. Rogers, and Susan M. Natali
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-158, https://doi.org/10.5194/gmd-2024-158, 2024
Revised manuscript accepted for GMD
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Thawing permafrost could greatly impact global climate. Our study improves modeling of carbon cycling in Arctic ecosystems. We developed an automated method to fine-tune a model that simulates carbon and nitrogen flows, using computer-generated data. Using computer-generated data, we tested our method and found it enhances accuracy and reduces the time needed for calibration. This work helps make climate predictions more reliable in sensitive permafrost regions.
Guohua Liu, Mirco Migliavacca, Christian Reimers, Basil Kraft, Markus Reichstein, Andrew D. Richardson, Lisa Wingate, Nicolas Delpierre, Hui Yang, and Alexander J. Winkler
Geosci. Model Dev., 17, 6683–6701, https://doi.org/10.5194/gmd-17-6683-2024, https://doi.org/10.5194/gmd-17-6683-2024, 2024
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Our study employs long short-term memory (LSTM) networks to model canopy greenness and phenology, integrating meteorological memory effects. The LSTM model outperforms traditional methods, enhancing accuracy in predicting greenness dynamics and phenological transitions across plant functional types. Highlighting the importance of multi-variate meteorological memory effects, our research pioneers unlock the secrets of vegetation phenology responses to climate change with deep learning techniques.
Thi Lan Anh Dinh, Daniel Goll, Philippe Ciais, and Ronny Lauerwald
Geosci. Model Dev., 17, 6725–6744, https://doi.org/10.5194/gmd-17-6725-2024, https://doi.org/10.5194/gmd-17-6725-2024, 2024
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The study assesses the performance of the dynamic global vegetation model (DGVM) ORCHIDEE in capturing the impact of land-use change on carbon stocks across Europe. Comparisons with observations reveal that the model accurately represents carbon fluxes and stocks. Despite the underestimations in certain land-use conversions, the model describes general trends in soil carbon response to land-use change, aligning with the site observations.
Nathaelle Bouttes, Lester Kwiatkowski, Manon Berger, Victor Brovkin, and Guy Munhoven
Geosci. Model Dev., 17, 6513–6528, https://doi.org/10.5194/gmd-17-6513-2024, https://doi.org/10.5194/gmd-17-6513-2024, 2024
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Coral reefs are crucial for biodiversity, but they also play a role in the carbon cycle on long time scales of a few thousand years. To better simulate the future and past evolution of coral reefs and their effect on the global carbon cycle, hence on atmospheric CO2 concentration, it is necessary to include coral reefs within a climate model. Here we describe the inclusion of coral reef carbonate production in a carbon–climate model and its validation in comparison to existing modern data.
Huajie Zhu, Mousong Wu, Fei Jiang, Michael Vossbeck, Thomas Kaminski, Xiuli Xing, Jun Wang, Weimin Ju, and Jing M. Chen
Geosci. Model Dev., 17, 6337–6363, https://doi.org/10.5194/gmd-17-6337-2024, https://doi.org/10.5194/gmd-17-6337-2024, 2024
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In this work, we developed the Nanjing University Carbon Assimilation System (NUCAS v1.0). Data assimilation experiments were conducted to demonstrate the robustness and investigate the feasibility and applicability of NUCAS. The assimilation of ecosystem carbonyl sulfide (COS) fluxes improved the model performance in gross primary productivity, evapotranspiration, and sensible heat, showing that COS provides constraints on parameters relevant to carbon-, water-, and energy-related processes.
Ye Liu, Huilin Huang, Sing-Chun Wang, Tao Zhang, Donghui Xu, and Yang Chen
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-151, https://doi.org/10.5194/gmd-2024-151, 2024
Revised manuscript accepted for GMD
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This study integrates machine learning with a land surface model to improve wildfire predictions in North America. Traditional models struggle with accurately simulating burned areas due to simplified processes. By combining the predictive power of machine learning with a land model, our hybrid framework better captures fire dynamics. This approach enhances our understanding of wildfire behavior and aids in developing more effective climate and fire management strategies.
Fang Li, Zhimin Zhou, Samuel Levis, Stephen Sitch, Felicity Hayes, Zhaozhong Feng, Peter B. Reich, Zhiyi Zhao, and Yanqing Zhou
Geosci. Model Dev., 17, 6173–6193, https://doi.org/10.5194/gmd-17-6173-2024, https://doi.org/10.5194/gmd-17-6173-2024, 2024
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A new scheme is developed to model the surface ozone damage to vegetation in regional and global process-based models. Based on 4210 data points from ozone experiments, it accurately reproduces statistically significant linear or nonlinear photosynthetic and stomatal responses to ozone in observations for all vegetation types. It also enables models to implicitly capture the variability in plant ozone tolerance and the shift among species within a vegetation type.
Alexander S. Brunmayr, Frank Hagedorn, Margaux Moreno Duborgel, Luisa I. Minich, and Heather D. Graven
Geosci. Model Dev., 17, 5961–5985, https://doi.org/10.5194/gmd-17-5961-2024, https://doi.org/10.5194/gmd-17-5961-2024, 2024
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A new generation of soil models promises to more accurately predict the carbon cycle in soils under climate change. However, measurements of 14C (the radioactive carbon isotope) in soils reveal that the new soil models face similar problems to the traditional models: they underestimate the residence time of carbon in soils and may therefore overestimate the net uptake of CO2 by the land ecosystem. Proposed solutions include restructuring the models and calibrating model parameters with 14C data.
Nina Raoult, Simon Beylat, James M. Salter, Frédéric Hourdin, Vladislav Bastrikov, Catherine Ottlé, and Philippe Peylin
Geosci. Model Dev., 17, 5779–5801, https://doi.org/10.5194/gmd-17-5779-2024, https://doi.org/10.5194/gmd-17-5779-2024, 2024
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We use computer models to predict how the land surface will respond to climate change. However, these complex models do not always simulate what we observe in real life, limiting their effectiveness. To improve their accuracy, we use sophisticated statistical and computational techniques. We test a technique called history matching against more common approaches. This method adapts well to these models, helping us better understand how they work and therefore how to make them more realistic.
Jorn Bruggeman, Karsten Bolding, Lars Nerger, Anna Teruzzi, Simone Spada, Jozef Skákala, and Stefano Ciavatta
Geosci. Model Dev., 17, 5619–5639, https://doi.org/10.5194/gmd-17-5619-2024, https://doi.org/10.5194/gmd-17-5619-2024, 2024
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To understand and predict the ocean’s capacity for carbon sequestration, its ability to supply food, and its response to climate change, we need the best possible estimate of its physical and biogeochemical properties. This is obtained through data assimilation which blends numerical models and observations. We present the Ensemble and Assimilation Tool (EAT), a flexible and efficient test bed that allows any scientist to explore and further develop the state of the art in data assimilation.
Dongyu Zheng, Andrew S. Merdith, Yves Goddéris, Yannick Donnadieu, Khushboo Gurung, and Benjamin J. W. Mills
Geosci. Model Dev., 17, 5413–5429, https://doi.org/10.5194/gmd-17-5413-2024, https://doi.org/10.5194/gmd-17-5413-2024, 2024
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This study uses a deep learning method to upscale the time resolution of paleoclimate simulations to 1 million years. This improved resolution allows a climate-biogeochemical model to more accurately predict climate shifts. The method may be critical in developing new fully continuous methods that are able to be applied over a moving continental surface in deep time with high resolution at reasonable computational expense.
Boris Ťupek, Aleksi Lehtonen, Alla Yurova, Rose Abramoff, Bertrand Guenet, Elisa Bruni, Samuli Launiainen, Mikko Peltoniemi, Shoji Hashimoto, Xianglin Tian, Juha Heikkinen, Kari Minkkinen, and Raisa Mäkipää
Geosci. Model Dev., 17, 5349–5367, https://doi.org/10.5194/gmd-17-5349-2024, https://doi.org/10.5194/gmd-17-5349-2024, 2024
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Updating the Yasso07 soil C model's dependency on decomposition with a hump-shaped Ricker moisture function improved modelled soil organic C (SOC) stocks in a catena of mineral and organic soils in boreal forest. The Ricker function, set to peak at a rate of 1 and calibrated against SOC and CO2 data using a Bayesian approach, showed a maximum in well-drained soils. Using SOC and CO2 data together with the moisture only from the topsoil humus was crucial for accurate model estimates.
Jacquelyn K. Shuman, Rosie A. Fisher, Charles Koven, Ryan Knox, Lara Kueppers, and Chonggang Xu
Geosci. Model Dev., 17, 4643–4671, https://doi.org/10.5194/gmd-17-4643-2024, https://doi.org/10.5194/gmd-17-4643-2024, 2024
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We adapt a fire behavior and effects module for use in a size-structured vegetation demographic model to test how climate, fire regime, and fire-tolerance plant traits interact to determine the distribution of tropical forests and grasslands. Our model captures the connection between fire disturbance and plant fire-tolerance strategies in determining plant distribution and provides a useful tool for understanding the vulnerability of these areas under changing conditions across the tropics.
Yoshiki Kanzaki, Isabella Chiaravalloti, Shuang Zhang, Noah J. Planavsky, and Christopher T. Reinhard
Geosci. Model Dev., 17, 4515–4532, https://doi.org/10.5194/gmd-17-4515-2024, https://doi.org/10.5194/gmd-17-4515-2024, 2024
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Soil pH is one of the most commonly measured agronomical and biogeochemical indices, mostly reflecting exchangeable acidity. Explicit simulation of both porewater and bulk soil pH is thus crucial to the accurate evaluation of alkalinity required to counteract soil acidification and the resulting capture of anthropogenic carbon dioxide through the enhanced weathering technique. This has been enabled by the updated reactive–transport SCEPTER code and newly developed framework to simulate soil pH.
David Sandoval, Iain Colin Prentice, and Rodolfo L. B. Nóbrega
Geosci. Model Dev., 17, 4229–4309, https://doi.org/10.5194/gmd-17-4229-2024, https://doi.org/10.5194/gmd-17-4229-2024, 2024
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Numerous estimates of water and energy balances depend on empirical equations requiring site-specific calibration, posing risks of "the right answers for the wrong reasons". We introduce novel first-principles formulations to calculate key quantities without requiring local calibration, matching predictions from complex land surface models.
Oliver Perkins, Matthew Kasoar, Apostolos Voulgarakis, Cathy Smith, Jay Mistry, and James D. A. Millington
Geosci. Model Dev., 17, 3993–4016, https://doi.org/10.5194/gmd-17-3993-2024, https://doi.org/10.5194/gmd-17-3993-2024, 2024
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Wildfire is often presented in the media as a danger to human life. Yet globally, millions of people’s livelihoods depend on using fire as a tool. So, patterns of fire emerge from interactions between humans, land use, and climate. This complexity means scientists cannot yet reliably say how fire will be impacted by climate change. So, we developed a new model that represents globally how people use and manage fire. The model reveals the extent and diversity of how humans live with and use fire.
Amos P. K. Tai, David H. Y. Yung, and Timothy Lam
Geosci. Model Dev., 17, 3733–3764, https://doi.org/10.5194/gmd-17-3733-2024, https://doi.org/10.5194/gmd-17-3733-2024, 2024
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We have developed the Terrestrial Ecosystem Model in R (TEMIR), which simulates plant carbon and pollutant uptake and predicts their response to varying atmospheric conditions. This model is designed to couple with an atmospheric chemistry model so that questions related to plant–atmosphere interactions, such as the effects of climate change, rising CO2, and ozone pollution on forest carbon uptake, can be addressed. The model has been well validated with both ground and satellite observations.
Fabian Stenzel, Johanna Braun, Jannes Breier, Karlheinz Erb, Dieter Gerten, Jens Heinke, Sarah Matej, Sebastian Ostberg, Sibyll Schaphoff, and Wolfgang Lucht
Geosci. Model Dev., 17, 3235–3258, https://doi.org/10.5194/gmd-17-3235-2024, https://doi.org/10.5194/gmd-17-3235-2024, 2024
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We provide an R package to compute two biosphere integrity metrics that can be applied to simulations of vegetation growth from the dynamic global vegetation model LPJmL. The pressure metric BioCol indicates that we humans modify and extract > 20 % of the potential preindustrial natural biomass production. The ecosystems state metric EcoRisk shows a high risk of ecosystem destabilization in many regions as a result of climate change and land, water, and fertilizer use.
Elin Ristorp Aas, Heleen A. de Wit, and Terje K. Berntsen
Geosci. Model Dev., 17, 2929–2959, https://doi.org/10.5194/gmd-17-2929-2024, https://doi.org/10.5194/gmd-17-2929-2024, 2024
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By including microbial processes in soil models, we learn how the soil system interacts with its environment and responds to climate change. We present a soil process model, MIMICS+, which is able to reproduce carbon stocks found in boreal forest soils better than a conventional land model. With the model we also find that when adding nitrogen, the relationship between soil microbes changes notably. Coupling the model to a vegetation model will allow for further study of these mechanisms.
Thomas Wutzler, Christian Reimers, Bernhard Ahrens, and Marion Schrumpf
Geosci. Model Dev., 17, 2705–2725, https://doi.org/10.5194/gmd-17-2705-2024, https://doi.org/10.5194/gmd-17-2705-2024, 2024
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Soil microbes provide a strong link for elemental fluxes in the earth system. The SESAM model applies an optimality assumption to model those linkages and their adaptation. We found that a previous heuristic description was a special case of a newly developed more rigorous description. The finding of new behaviour at low microbial biomass led us to formulate the constrained enzyme hypothesis. We now can better describe how microbially mediated linkages of elemental fluxes adapt across decades.
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Short summary
This study evaluates the performances of the new version (v.5.1) of 3D-CMCC Forest Ecosystem Model in simulating gross primary productivity (GPP), against eddy covariance GPP data for 10 FLUXNET forest sites across Europe. The model consistently reproduces both in timing and in magnitude daily and monthly GPP variability across all sites, with the exception of the two Mediterranean sites. Inclusion of forest structure within simulation ameliorate in some cases the model output.
This study evaluates the performances of the new version (v.5.1) of 3D-CMCC Forest Ecosystem...
