Articles | Volume 12, issue 2
https://doi.org/10.5194/essd-12-1295-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-12-1295-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
12 Jun 2020
Data description paper |
| 12 Jun 2020
| 12 Jun 2020
The PROFOUND Database for evaluating vegetation models and simulating climate impacts on European forests
Christopher P. O. Reyer
CORRESPONDING AUTHOR
Potsdam Institute for Climate Impact Research, Member of the Leibniz
Association, P.O. Box 601203, 14412 Potsdam, Germany
Ramiro Silveyra Gonzalez
Potsdam Institute for Climate Impact Research, Member of the Leibniz
Association, P.O. Box 601203, 14412 Potsdam, Germany
Klara Dolos
Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
Florian Hartig
Faculty of Biology and Pre-Clinical Medicine, University of Regensburg, Regensburg, Germany
Ylva Hauf
Potsdam Institute for Climate Impact Research, Member of the Leibniz
Association, P.O. Box 601203, 14412 Potsdam, Germany
Matthias Noack
Fachagentur Nachwachsende Rohstoffe e.V. (FNR), Gülzow-Prüzen, Germany
Petra Lasch-Born
Potsdam Institute for Climate Impact Research, Member of the Leibniz
Association, P.O. Box 601203, 14412 Potsdam, Germany
Thomas Rötzer
Department of Ecology and Ecosystem Management, Technical University of Munich, Munich, Germany
Hans Pretzsch
Department of Ecology and Ecosystem Management, Technical University of Munich, Munich, Germany
Henning Meesenburg
Northwest German Forest Research Institute, Göttingen, Germany
Stefan Fleck
Northwest German Forest Research Institute, Göttingen, Germany
Markus Wagner
Northwest German Forest Research Institute, Göttingen, Germany
Andreas Bolte
Thünen Institute of Forest Ecosystems, 16225 Eberswalde, Germany
Tanja G. M. Sanders
Thünen Institute of Forest Ecosystems, 16225 Eberswalde, Germany
Pasi Kolari
Department of Forest Sciences, University of Helsinki, Helsinki, Finland
Annikki Mäkelä
Department of Forest Sciences, University of Helsinki, Helsinki, Finland
Timo Vesala
Department of Forest Sciences, University of Helsinki, Helsinki, Finland
Ivan Mammarella
Department of Forest Sciences, University of Helsinki, Helsinki, Finland
Jukka Pumpanen
Biogeochemistry Research Group, University of Eastern Finland, Kuopio, Finland
Alessio Collalti
National Research Council of Italy, Institute for Agriculture and
Forestry Systems in the Mediterranean, Perugia (PG), Italy
Department of Innovation in Biological, Agro-food and Forest System,
University of Tuscia, 01100 Viterbo, Italy
Carlo Trotta
Department of Innovation in Biological, Agro-food and Forest System,
University of Tuscia, 01100 Viterbo, Italy
Giorgio Matteucci
National Research Council of Italy, Institute for Agriculture and
Forestry System in the Mediterranean, Ercolano (NA), Italy
Ettore D'Andrea
National Research Council of Italy, Institute for Agriculture and
Forestry System in the Mediterranean, Ercolano (NA), Italy
Lenka Foltýnová
Global Change Research Institute, Brno, Czech Republic
Jan Krejza
Global Change Research Institute, Brno, Czech Republic
Andreas Ibrom
Department of Environmental Engineering, Technical University of Denmark, Lyngby, Denmark
Kim Pilegaard
Department of Environmental Engineering, Technical University of Denmark, Lyngby, Denmark
Denis Loustau
French National Institute for Agricultural Research, Bordeaux, France
Jean-Marc Bonnefond
French National Institute for Agricultural Research, Bordeaux, France
Paul Berbigier
French National Institute for Agricultural Research, Bordeaux, France
Delphine Picart
French National Institute for Agricultural Research, Bordeaux, France
Sébastien Lafont
French National Institute for Agricultural Research, Bordeaux, France
Michael Dietze
Department of Earth & Environment, Boston University, Boston, USA
David Cameron
Centre for Ecology and Hydrology, Edinburgh, UK
Massimo Vieno
Centre for Ecology and Hydrology, Lancaster, UK
Hanqin Tian
School of Forestry and Wildlife Sciences, Auburn University, Auburn, USA
Alicia Palacios-Orueta
Departamento de Silvopascicultura, Technical University of Madrid, Madrid, Spain
Victor Cicuendez
Departamento de Silvopascicultura, Technical University of Madrid, Madrid, Spain
Laura Recuero
Departamento de Silvopascicultura, Technical University of Madrid, Madrid, Spain
Klaus Wiese
Departamento de Silvopascicultura, Technical University of Madrid, Madrid, Spain
Matthias Büchner
Potsdam Institute for Climate Impact Research, Member of the Leibniz
Association, P.O. Box 601203, 14412 Potsdam, Germany
Stefan Lange
Potsdam Institute for Climate Impact Research, Member of the Leibniz
Association, P.O. Box 601203, 14412 Potsdam, Germany
Jan Volkholz
Potsdam Institute for Climate Impact Research, Member of the Leibniz
Association, P.O. Box 601203, 14412 Potsdam, Germany
Hyungjun Kim
Department of Human and Social Systems, University of Tokyo, Tokyo, Japan
Joanna A. Horemans
Centre of Excellence PLECO, University of Antwerp, Antwerp,
Belgium
Friedrich Bohn
Helmholtz Centre for Environmental Research, Leipzig, Germany
Jörg Steinkamp
Senckenberg Biodiversity and Climate Research Centre, Senckenberg,
Germany
Alexander Chikalanov
University of Library Study and Information Technology, Sofia,
Bulgaria
Graham P. Weedon
Met Office, Wallingford, UK
Justin Sheffield
Dept. Civil & Environ. Eng., Princeton University, Princeton, NJ
08544, USA
Flurin Babst
W. Szafer Institute of Botany, Department of Ecology, Polish Academy
of Sciences, Cracow, Poland
Swiss Federal Research Institute WSL, Birmensdorf, Switzerland
Iliusi Vega del Valle
Potsdam Institute for Climate Impact Research, Member of the Leibniz
Association, P.O. Box 601203, 14412 Potsdam, Germany
Felicitas Suckow
Potsdam Institute for Climate Impact Research, Member of the Leibniz
Association, P.O. Box 601203, 14412 Potsdam, Germany
Simon Martel
Department of Earth & Environment, Boston University, Boston, USA
Mats Mahnken
Potsdam Institute for Climate Impact Research, Member of the Leibniz
Association, P.O. Box 601203, 14412 Potsdam, Germany
Martin Gutsch
Potsdam Institute for Climate Impact Research, Member of the Leibniz
Association, P.O. Box 601203, 14412 Potsdam, Germany
Katja Frieler
Potsdam Institute for Climate Impact Research, Member of the Leibniz
Association, P.O. Box 601203, 14412 Potsdam, Germany
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Our results showed substantially varied fertilizer-induced soil NOx emissions in 2019 from 0.84 to 2.2 Tg N yr-1 globally. Such variations further lead to 0.3 to 3.3 ppbv summertime ozone enhancement in agricultural hotspot regions and 7.1 ppbv to 16.6 ppbv reductions in global methane concentrations
Marielle Saunois, Adrien Martinez, Benjamin Poulter, Zhen Zhang, Peter A. Raymond, Pierre Regnier, Josep G. Canadell, Robert B. Jackson, Prabir K. Patra, Philippe Bousquet, Philippe Ciais, Edward J. Dlugokencky, Xin Lan, George H. Allen, David Bastviken, David J. Beerling, Dmitry A. Belikov, Donald R. Blake, Simona Castaldi, Monica Crippa, Bridget R. Deemer, Fraser Dennison, Giuseppe Etiope, Nicola Gedney, Lena Höglund-Isaksson, Meredith A. Holgerson, Peter O. Hopcroft, Gustaf Hugelius, Akihiko Ito, Atul K. Jain, Rajesh Janardanan, Matthew S. Johnson, Thomas Kleinen, Paul B. Krummel, Ronny Lauerwald, Tingting Li, Xiangyu Liu, Kyle C. McDonald, Joe R. Melton, Jens Mühle, Jurek Müller, Fabiola Murguia-Flores, Yosuke Niwa, Sergio Noce, Shufen Pan, Robert J. Parker, Changhui Peng, Michel Ramonet, William J. Riley, Gerard Rocher-Ros, Judith A. Rosentreter, Motoki Sasakawa, Arjo Segers, Steven J. Smith, Emily H. Stanley, Joël Thanwerdas, Hanqin Tian, Aki Tsuruta, Francesco N. Tubiello, Thomas S. Weber, Guido R. van der Werf, Douglas E. J. Worthy, Yi Xi, Yukio Yoshida, Wenxin Zhang, Bo Zheng, Qing Zhu, Qiuan Zhu, and Qianlai Zhuang
Earth Syst. Sci. Data, 17, 1873–1958, https://doi.org/10.5194/essd-17-1873-2025, https://doi.org/10.5194/essd-17-1873-2025, 2025
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Methane (CH4) is the second most important human-influenced greenhouse gas in terms of climate forcing after carbon dioxide (CO2). A consortium of multi-disciplinary scientists synthesise and update the budget of the sources and sinks of CH4. This edition benefits from important progress in estimating emissions from lakes and ponds, reservoirs, and streams and rivers. For the 2010s decade, global CH4 emissions are estimated at 575 Tg CH4 yr-1, including ~65 % from anthropogenic sources.
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.
Aki Vähä, Timo Vesala, Sofya Guseva, Anders Lindroth, Andreas Lorke, Sally MacIntyre, and Ivan Mammarella
Biogeosciences, 22, 1651–1671, https://doi.org/10.5194/bg-22-1651-2025, https://doi.org/10.5194/bg-22-1651-2025, 2025
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Boreal rivers are significant sources of carbon dioxide (CO2) and methane (CH4) for the atmosphere, but the controls of these emissions are uncertain. We measured 4 months of CO2 and CH4 exchanges between a regulated boreal river and the atmosphere with eddy covariance. We found statistical relationships between the gas exchange and several environmental variables, the most important of which were dissolved CO2 partial pressure in water, wind speed and water temperature.
Zhu Deng, Philippe Ciais, Liting Hu, Adrien Martinez, Marielle Saunois, Rona L. Thompson, Kushal Tibrewal, Wouter Peters, Brendan Byrne, Giacomo Grassi, Paul I. Palmer, Ingrid T. Luijkx, Zhu Liu, Junjie Liu, Xuekun Fang, Tengjiao Wang, Hanqin Tian, Katsumasa Tanaka, Ana Bastos, Stephen Sitch, Benjamin Poulter, Clément Albergel, Aki Tsuruta, Shamil Maksyutov, Rajesh Janardanan, Yosuke Niwa, Bo Zheng, Joël Thanwerdas, Dmitry Belikov, Arjo Segers, and Frédéric Chevallier
Earth Syst. Sci. Data, 17, 1121–1152, https://doi.org/10.5194/essd-17-1121-2025, https://doi.org/10.5194/essd-17-1121-2025, 2025
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This study reconciles national greenhouse gas (GHG) inventories with updated atmospheric inversion results to evaluate discrepancies for three principal GHG fluxes at the national level. Compared to our previous study, new satellite-based CO2 inversions were included and an updated mask of managed lands was used, improving agreement for Brazil and Canada. The proposed methodology can be regularly applied as a check to assess the gap between top-down inversions and bottom-up inventories.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Judith Hauck, Peter Landschützer, Corinne Le Quéré, Hongmei Li, Ingrid T. Luijkx, Are Olsen, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Almut Arneth, Vivek Arora, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Carla F. Berghoff, Henry C. Bittig, Laurent Bopp, Patricia Cadule, Katie Campbell, Matthew A. Chamberlain, Naveen Chandra, Frédéric Chevallier, Louise P. Chini, Thomas Colligan, Jeanne Decayeux, Laique M. Djeutchouang, Xinyu Dou, Carolina Duran Rojas, Kazutaka Enyo, Wiley Evans, Amanda R. Fay, Richard A. Feely, Daniel J. Ford, Adrianna Foster, Thomas Gasser, Marion Gehlen, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Jens Heinke, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Andrew R. Jacobson, Atul K. Jain, Tereza Jarníková, Annika Jersild, Fei Jiang, Zhe Jin, Etsushi Kato, Ralph F. Keeling, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Xin Lan, Siv K. Lauvset, Nathalie Lefèvre, Zhu Liu, Junjie Liu, Lei Ma, Shamil Maksyutov, Gregg Marland, Nicolas Mayot, Patrick C. McGuire, Nicolas Metzl, Natalie M. Monacci, Eric J. Morgan, Shin-Ichiro Nakaoka, Craig Neill, Yosuke Niwa, Tobias Nützel, Lea Olivier, Tsuneo Ono, Paul I. Palmer, Denis Pierrot, Zhangcai Qin, Laure Resplandy, Alizée Roobaert, Thais M. Rosan, Christian Rödenbeck, Jörg Schwinger, T. Luke Smallman, Stephen M. Smith, Reinel Sospedra-Alfonso, Tobias Steinhoff, Qing Sun, Adrienne J. Sutton, Roland Séférian, Shintaro Takao, Hiroaki Tatebe, Hanqin Tian, Bronte Tilbrook, Olivier Torres, Etienne Tourigny, Hiroyuki Tsujino, Francesco Tubiello, Guido van der Werf, Rik Wanninkhof, Xuhui Wang, Dongxu Yang, Xiaojuan Yang, Zhen Yu, Wenping Yuan, Xu Yue, Sönke Zaehle, Ning Zeng, and Jiye Zeng
Earth Syst. Sci. Data, 17, 965–1039, https://doi.org/10.5194/essd-17-965-2025, https://doi.org/10.5194/essd-17-965-2025, 2025
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The Global Carbon Budget 2024 describes the methodology, main results, and datasets used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, land ecosystems, and the ocean over the historical period (1750–2024). These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
José Ángel Callejas-Rodelas, Alexander Knohl, Ivan Mammarella, Timo Vesala, Olli Peltola, and Christian Markwitz
EGUsphere, https://doi.org/10.5194/egusphere-2025-810, https://doi.org/10.5194/egusphere-2025-810, 2025
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The spatial variability of CO2 and water vapour exchanges with the atmosphere was quantified above an agroforestry system, and further compared to a monocropping system, using a total of four eddy covariance stations. The variability of fluxes within the agroforestry was found to be as large as the variability between agroforestry and monocropping, induced by the heterogeneity of the site, which highlights the need for replicated measurements above such ecosystems.
Aloïs Tilloy, Dominik Paprotny, Stefania Grimaldi, Goncalo Gomes, Alessandra Bianchi, Stefan Lange, Hylke Beck, Cinzia Mazzetti, and Luc Feyen
Earth Syst. Sci. Data, 17, 293–316, https://doi.org/10.5194/essd-17-293-2025, https://doi.org/10.5194/essd-17-293-2025, 2025
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This article presents a reanalysis of Europe's river streamflow for the period 1951–2020. Streamflow is estimated through a state-of-the-art hydrological simulation framework benefitting from detailed information about the landscape, climate, and human activities. The resulting Hydrological European ReAnalysis (HERA) can be a valuable tool for studying hydrological dynamics, including the impacts of climate change and human activities on European water resources and flood and drought risks.
Binyuan Xu, Hanqin Tian, Shufen Pan, Xiaoyong Li, Ran Meng, Óscar Melo, Anne McDonald, María de los Ángeles Picone, Xiao-Peng Song, Edson Severnini, Katharine G. Young, and Feng Zhao
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-527, https://doi.org/10.5194/essd-2024-527, 2025
Revised manuscript under review for ESSD
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This study focuses on land use change in South America, reconstructing the historical dynamics of four major crops (soybean, maize, wheat, and rice) from 1950 to 2020 by integrating multiple data sources. The results reveal a significant expansion in cropland, particularly for soybean, leading to a substantial reduction in natural vegetation such as forests and grasslands. The datasets can be used to assess the impacts of cropland expansion on carbon and nitrogen cycles in South America.
Zhen Zhang, Benjamin Poulter, Joe R. Melton, William J. Riley, George H. Allen, David J. Beerling, Philippe Bousquet, Josep G. Canadell, Etienne Fluet-Chouinard, Philippe Ciais, Nicola Gedney, Peter O. Hopcroft, Akihiko Ito, Robert B. Jackson, Atul K. Jain, Katherine Jensen, Fortunat Joos, Thomas Kleinen, Sara H. Knox, Tingting Li, Xin Li, Xiangyu Liu, Kyle McDonald, Gavin McNicol, Paul A. Miller, Jurek Müller, Prabir K. Patra, Changhui Peng, Shushi Peng, Zhangcai Qin, Ryan M. Riggs, Marielle Saunois, Qing Sun, Hanqin Tian, Xiaoming Xu, Yuanzhi Yao, Yi Xi, Wenxin Zhang, Qing Zhu, Qiuan Zhu, and Qianlai Zhuang
Biogeosciences, 22, 305–321, https://doi.org/10.5194/bg-22-305-2025, https://doi.org/10.5194/bg-22-305-2025, 2025
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This study assesses global methane emissions from wetlands between 2000 and 2020 using multiple models. We found that wetland emissions increased by 6–7 Tg CH4 yr-1 in the 2010s compared to the 2000s. Rising temperatures primarily drove this increase, while changes in precipitation and CO2 levels also played roles. Our findings highlight the importance of wetlands in the global methane budget and the need for continuous monitoring to understand their impact on climate change.
Ekaterina Ezhova, Topi Laanti, Anna Lintunen, Pasi Kolari, Tuomo Nieminen, Ivan Mammarella, Keijo Heljanko, and Markku Kulmala
Biogeosciences, 22, 257–288, https://doi.org/10.5194/bg-22-257-2025, https://doi.org/10.5194/bg-22-257-2025, 2025
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Machine learning (ML) models are gaining popularity in biogeosciences. They are applied as gap-filling methods and used to upscale carbon fluxes to larger areas. Here we use explainable artificial intelligence (XAI) methods to elucidate the performance of machine learning models for carbon dioxide fluxes in boreal forests. We show that statistically equal models treat input variables differently. XAI methods can help scientists make informed decisions when applying ML models in their research.
Otso Peräkylä, Erkka Rinne, Ekaterina Ezhova, Anna Lintunen, Annalea Lohila, Juho Aalto, Mika Aurela, Pasi Kolari, and Markku Kulmala
Biogeosciences, 22, 153–179, https://doi.org/10.5194/bg-22-153-2025, https://doi.org/10.5194/bg-22-153-2025, 2025
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Forests are seen as good for climate. Yet, in areas with snow, trees break up the white snow surface and absorb more sunlight than open areas. This has a warming effect, negating some of the climate benefit of trees. We studied two site pairs in Finland, both with an open peatland and a forest. We found that the later the snow melts, the more extra energy the forest absorbs as compared to the peatland. This has implications for the future, as snow cover duration is affected by global warming.
Gab Abramowitz, Anna Ukkola, Sanaa Hobeichi, Jon Cranko Page, Mathew Lipson, Martin G. De Kauwe, Samuel Green, Claire Brenner, Jonathan Frame, Grey Nearing, Martyn Clark, Martin Best, Peter Anthoni, Gabriele Arduini, Souhail Boussetta, Silvia Caldararu, Kyeungwoo Cho, Matthias Cuntz, David Fairbairn, Craig R. Ferguson, Hyungjun Kim, Yeonjoo Kim, Jürgen Knauer, David Lawrence, Xiangzhong Luo, Sergey Malyshev, Tomoko Nitta, Jerome Ogee, Keith Oleson, Catherine Ottlé, Phillipe Peylin, Patricia de Rosnay, Heather Rumbold, Bob Su, Nicolas Vuichard, Anthony P. Walker, Xiaoni Wang-Faivre, Yunfei Wang, and Yijian Zeng
Biogeosciences, 21, 5517–5538, https://doi.org/10.5194/bg-21-5517-2024, https://doi.org/10.5194/bg-21-5517-2024, 2024
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This paper evaluates land models – computer-based models that simulate ecosystem dynamics; land carbon, water, and energy cycles; and the role of land in the climate system. It uses machine learning and AI approaches to show that, despite the complexity of land models, they do not perform nearly as well as they could given the amount of information they are provided with about the prediction problem.
Jacob A. Nelson, Sophia Walther, Fabian Gans, Basil Kraft, Ulrich Weber, Kimberly Novick, Nina Buchmann, Mirco Migliavacca, Georg Wohlfahrt, Ladislav Šigut, Andreas Ibrom, Dario Papale, Mathias Göckede, Gregory Duveiller, Alexander Knohl, Lukas Hörtnagl, Russell L. Scott, Jiří Dušek, Weijie Zhang, Zayd Mahmoud Hamdi, Markus Reichstein, Sergio Aranda-Barranco, Jonas Ardö, Maarten Op de Beeck, Dave Billesbach, David Bowling, Rosvel Bracho, Christian Brümmer, Gustau Camps-Valls, Shiping Chen, Jamie Rose Cleverly, Ankur Desai, Gang Dong, Tarek S. El-Madany, Eugenie Susanne Euskirchen, Iris Feigenwinter, Marta Galvagno, Giacomo A. Gerosa, Bert Gielen, Ignacio Goded, Sarah Goslee, Christopher Michael Gough, Bernard Heinesch, Kazuhito Ichii, Marcin Antoni Jackowicz-Korczynski, Anne Klosterhalfen, Sara Knox, Hideki Kobayashi, Kukka-Maaria Kohonen, Mika Korkiakoski, Ivan Mammarella, Mana Gharun, Riccardo Marzuoli, Roser Matamala, Stefan Metzger, Leonardo Montagnani, Giacomo Nicolini, Thomas O'Halloran, Jean-Marc Ourcival, Matthias Peichl, Elise Pendall, Borja Ruiz Reverter, Marilyn Roland, Simone Sabbatini, Torsten Sachs, Marius Schmidt, Christopher R. Schwalm, Ankit Shekhar, Richard Silberstein, Maria Lucia Silveira, Donatella Spano, Torbern Tagesson, Gianluca Tramontana, Carlo Trotta, Fabio Turco, Timo Vesala, Caroline Vincke, Domenico Vitale, Enrique R. Vivoni, Yi Wang, William Woodgate, Enrico A. Yepez, Junhui Zhang, Donatella Zona, and Martin Jung
Biogeosciences, 21, 5079–5115, https://doi.org/10.5194/bg-21-5079-2024, https://doi.org/10.5194/bg-21-5079-2024, 2024
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The movement of water, carbon, and energy from the Earth's surface to the atmosphere, or flux, is an important process to understand because it impacts our lives. Here, we outline a method called FLUXCOM-X to estimate global water and CO2 fluxes based on direct measurements from sites around the world. We go on to demonstrate how these new estimates of net CO2 uptake/loss, gross CO2 uptake, total water evaporation, and transpiration from plants compare to previous and independent estimates.
Liqing Peng, Justin Sheffield, Zhongwang Wei, Michael Ek, and Eric F. Wood
Earth Syst. Dynam., 15, 1277–1300, https://doi.org/10.5194/esd-15-1277-2024, https://doi.org/10.5194/esd-15-1277-2024, 2024
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Integrating evaporative demand into drought indicators is effective, but the choice of method and the effectiveness of surface features remain undocumented. We evaluate various methods and surface features for predicting soil moisture dynamics. Using minimal ancillary information alongside meteorological and vegetation data, we develop a simple land-cover-based method that improves soil moisture drought predictions, especially in forests, showing promise for better real-time drought forecasting.
Solomon H. Gebrechorkos, Julian Leyland, Simon J. Dadson, Sagy Cohen, Louise Slater, Michel Wortmann, Philip J. Ashworth, Georgina L. Bennett, Richard Boothroyd, Hannah Cloke, Pauline Delorme, Helen Griffith, Richard Hardy, Laurence Hawker, Stuart McLelland, Jeffrey Neal, Andrew Nicholas, Andrew J. Tatem, Ellie Vahidi, Yinxue Liu, Justin Sheffield, Daniel R. Parsons, and Stephen E. Darby
Hydrol. Earth Syst. Sci., 28, 3099–3118, https://doi.org/10.5194/hess-28-3099-2024, https://doi.org/10.5194/hess-28-3099-2024, 2024
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This study evaluated six high-resolution global precipitation datasets for hydrological modelling. MSWEP and ERA5 showed better performance, but spatial variability was high. The findings highlight the importance of careful dataset selection for river discharge modelling due to the lack of a universally superior dataset. Further improvements in global precipitation data products are needed.
Kim A. P. Faassen, Jordi Vilà-Guerau de Arellano, Raquel González-Armas, Bert G. Heusinkveld, Ivan Mammarella, Wouter Peters, and Ingrid T. Luijkx
Biogeosciences, 21, 3015–3039, https://doi.org/10.5194/bg-21-3015-2024, https://doi.org/10.5194/bg-21-3015-2024, 2024
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The ratio between atmospheric O2 and CO2 can be used to characterize the carbon balance at the surface. By combining a model and observations from the Hyytiälä forest (Finland), we show that using atmospheric O2 and CO2 measurements from a single height provides a weak constraint on the surface CO2 exchange because large-scale processes such as entrainment confound this signal. We therefore recommend always using multiple heights of O2 and CO2 measurements to study surface CO2 exchange.
Hanqin Tian, Naiqing Pan, Rona L. Thompson, Josep G. Canadell, Parvadha Suntharalingam, Pierre Regnier, Eric A. Davidson, Michael Prather, Philippe Ciais, Marilena Muntean, Shufen Pan, Wilfried Winiwarter, Sönke Zaehle, Feng Zhou, Robert B. Jackson, Hermann W. Bange, Sarah Berthet, Zihao Bian, Daniele Bianchi, Alexander F. Bouwman, Erik T. Buitenhuis, Geoffrey Dutton, Minpeng Hu, Akihiko Ito, Atul K. Jain, Aurich Jeltsch-Thömmes, Fortunat Joos, Sian Kou-Giesbrecht, Paul B. Krummel, Xin Lan, Angela Landolfi, Ronny Lauerwald, Ya Li, Chaoqun Lu, Taylor Maavara, Manfredi Manizza, Dylan B. Millet, Jens Mühle, Prabir K. Patra, Glen P. Peters, Xiaoyu Qin, Peter Raymond, Laure Resplandy, Judith A. Rosentreter, Hao Shi, Qing Sun, Daniele Tonina, Francesco N. Tubiello, Guido R. van der Werf, Nicolas Vuichard, Junjie Wang, Kelley C. Wells, Luke M. Western, Chris Wilson, Jia Yang, Yuanzhi Yao, Yongfa You, and Qing Zhu
Earth Syst. Sci. Data, 16, 2543–2604, https://doi.org/10.5194/essd-16-2543-2024, https://doi.org/10.5194/essd-16-2543-2024, 2024
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Atmospheric concentrations of nitrous oxide (N2O), a greenhouse gas 273 times more potent than carbon dioxide, have increased by 25 % since the preindustrial period, with the highest observed growth rate in 2020 and 2021. This rapid growth rate has primarily been due to a 40 % increase in anthropogenic emissions since 1980. Observed atmospheric N2O concentrations in recent years have exceeded the worst-case climate scenario, underscoring the importance of reducing anthropogenic N2O emissions.
Yannek Käber, Florian Hartig, and Harald Bugmann
Geosci. Model Dev., 17, 2727–2753, https://doi.org/10.5194/gmd-17-2727-2024, https://doi.org/10.5194/gmd-17-2727-2024, 2024
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Many forest models include detailed mechanisms of forest growth and mortality, but regeneration is often simplified. Testing and improving forest regeneration models is challenging. We address this issue by exploring how forest inventories from unmanaged European forests can be used to improve such models. We find that competition for light among trees is captured by the model, unknown model components can be informed by forest inventory data, and climatic effects are challenging to capture.
Lily Gouldsbrough, Ryan Hossaini, Emma Eastoe, Paul J. Young, and Massimo Vieno
Atmos. Chem. Phys., 24, 3163–3196, https://doi.org/10.5194/acp-24-3163-2024, https://doi.org/10.5194/acp-24-3163-2024, 2024
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High-resolution spatial fields of surface ozone are used to understand spikes in ozone concentration and predict their impact on public health. Such fields are routinely output from complex mathematical models for atmospheric conditions. These outputs are on a coarse spatial resolution and the highest concentrations tend to be biased. Using a novel data-driven machine learning methodology, we show how such output can be corrected to produce fields with both lower bias and higher resolution.
Jari-Pekka Nousu, Matthieu Lafaysse, Giulia Mazzotti, Pertti Ala-aho, Hannu Marttila, Bertrand Cluzet, Mika Aurela, Annalea Lohila, Pasi Kolari, Aaron Boone, Mathieu Fructus, and Samuli Launiainen
The Cryosphere, 18, 231–263, https://doi.org/10.5194/tc-18-231-2024, https://doi.org/10.5194/tc-18-231-2024, 2024
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The snowpack has a major impact on the land surface energy budget. Accurate simulation of the snowpack energy budget is difficult, and studies that evaluate models against energy budget observations are rare. We compared predictions from well-known models with observations of energy budgets, snow depths and soil temperatures in Finland. Our study identified contrasting strengths and limitations for the models. These results can be used for choosing the right models depending on the use cases.
Katja Frieler, Jan Volkholz, Stefan Lange, Jacob Schewe, Matthias Mengel, María del Rocío Rivas López, Christian Otto, Christopher P. O. Reyer, Dirk Nikolaus Karger, Johanna T. Malle, Simon Treu, Christoph Menz, Julia L. Blanchard, Cheryl S. Harrison, Colleen M. Petrik, Tyler D. Eddy, Kelly Ortega-Cisneros, Camilla Novaglio, Yannick Rousseau, Reg A. Watson, Charles Stock, Xiao Liu, Ryan Heneghan, Derek Tittensor, Olivier Maury, Matthias Büchner, Thomas Vogt, Tingting Wang, Fubao Sun, Inga J. Sauer, Johannes Koch, Inne Vanderkelen, Jonas Jägermeyr, Christoph Müller, Sam Rabin, Jochen Klar, Iliusi D. Vega del Valle, Gitta Lasslop, Sarah Chadburn, Eleanor Burke, Angela Gallego-Sala, Noah Smith, Jinfeng Chang, Stijn Hantson, Chantelle Burton, Anne Gädeke, Fang Li, Simon N. Gosling, Hannes Müller Schmied, Fred Hattermann, Jida Wang, Fangfang Yao, Thomas Hickler, Rafael Marcé, Don Pierson, Wim Thiery, Daniel Mercado-Bettín, Robert Ladwig, Ana Isabel Ayala-Zamora, Matthew Forrest, and Michel Bechtold
Geosci. Model Dev., 17, 1–51, https://doi.org/10.5194/gmd-17-1-2024, https://doi.org/10.5194/gmd-17-1-2024, 2024
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Our paper provides an overview of all observational climate-related and socioeconomic forcing data used as input for the impact model evaluation and impact attribution experiments within the third round of the Inter-Sectoral Impact Model Intercomparison Project. The experiments are designed to test our understanding of observed changes in natural and human systems and to quantify to what degree these changes have already been induced by climate change.
Willem E. van Caspel, David Simpson, Jan Eiof Jonson, Anna M. K. Benedictow, Yao Ge, Alcide di Sarra, Giandomenico Pace, Massimo Vieno, Hannah L. Walker, and Mathew R. Heal
Geosci. Model Dev., 16, 7433–7459, https://doi.org/10.5194/gmd-16-7433-2023, https://doi.org/10.5194/gmd-16-7433-2023, 2023
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Radiation coming from the sun is essential to atmospheric chemistry, driving the breakup, or photodissociation, of atmospheric molecules. This in turn affects the chemical composition and reactivity of the atmosphere. The representation of photodissociation effects is therefore essential in atmospheric chemistry modeling. One such model is the EMEP MSC-W model, for which a new way of calculating the photodissociation rates is tested and evaluated in this paper.
Markku Kulmala, Anna Lintunen, Hanna Lappalainen, Annele Virtanen, Chao Yan, Ekaterina Ezhova, Tuomo Nieminen, Ilona Riipinen, Risto Makkonen, Johanna Tamminen, Anu-Maija Sundström, Antti Arola, Armin Hansel, Kari Lehtinen, Timo Vesala, Tuukka Petäjä, Jaana Bäck, Tom Kokkonen, and Veli-Matti Kerminen
Atmos. Chem. Phys., 23, 14949–14971, https://doi.org/10.5194/acp-23-14949-2023, https://doi.org/10.5194/acp-23-14949-2023, 2023
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To be able to meet global grand challenges, we need comprehensive open data with proper metadata. In this opinion paper, we describe the SMEAR (Station for Measuring Earth surface – Atmosphere Relations) concept and include several examples (cases), such as new particle formation and growth, feedback loops and the effect of COVID-19, and what has been learned from these investigations. The future needs and the potential of comprehensive observations of the environment are summarized.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Dorothee C. E. Bakker, Judith Hauck, Peter Landschützer, Corinne Le Quéré, Ingrid T. Luijkx, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Peter Anthoni, Leticia Barbero, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Bertrand Decharme, Laurent Bopp, Ida Bagus Mandhara Brasika, Patricia Cadule, Matthew A. Chamberlain, Naveen Chandra, Thi-Tuyet-Trang Chau, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Xinyu Dou, Kazutaka Enyo, Wiley Evans, Stefanie Falk, Richard A. Feely, Liang Feng, Daniel J. Ford, Thomas Gasser, Josefine Ghattas, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Jens Heinke, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Andrew R. Jacobson, Atul Jain, Tereza Jarníková, Annika Jersild, Fei Jiang, Zhe Jin, Fortunat Joos, Etsushi Kato, Ralph F. Keeling, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Arne Körtzinger, Xin Lan, Nathalie Lefèvre, Hongmei Li, Junjie Liu, Zhiqiang Liu, Lei Ma, Greg Marland, Nicolas Mayot, Patrick C. McGuire, Galen A. McKinley, Gesa Meyer, Eric J. Morgan, David R. Munro, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin M. O'Brien, Are Olsen, Abdirahman M. Omar, Tsuneo Ono, Melf Paulsen, Denis Pierrot, Katie Pocock, Benjamin Poulter, Carter M. Powis, Gregor Rehder, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Thais M. Rosan, Jörg Schwinger, Roland Séférian, T. Luke Smallman, Stephen M. Smith, Reinel Sospedra-Alfonso, Qing Sun, Adrienne J. Sutton, Colm Sweeney, Shintaro Takao, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Hiroyuki Tsujino, Francesco Tubiello, Guido R. van der Werf, Erik van Ooijen, Rik Wanninkhof, Michio Watanabe, Cathy Wimart-Rousseau, Dongxu Yang, Xiaojuan Yang, Wenping Yuan, Xu Yue, Sönke Zaehle, Jiye Zeng, and Bo Zheng
Earth Syst. Sci. Data, 15, 5301–5369, https://doi.org/10.5194/essd-15-5301-2023, https://doi.org/10.5194/essd-15-5301-2023, 2023
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The Global Carbon Budget 2023 describes the methodology, main results, and data sets used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, land ecosystems, and the ocean over the historical period (1750–2023). These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Gemma Purser, Mathew R. Heal, Edward J. Carnell, Stephen Bathgate, Julia Drewer, James I. L. Morison, and Massimo Vieno
Atmos. Chem. Phys., 23, 13713–13733, https://doi.org/10.5194/acp-23-13713-2023, https://doi.org/10.5194/acp-23-13713-2023, 2023
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Forest expansion is a ″net-zero“ pathway, but change in land cover alters air quality in many ways. This study combines tree planting suitability data with UK measured emissions of biogenic volatile organic compounds to simulate spatial and temporal changes in atmospheric composition for planting scenarios of four species. Decreases in fine particulate matter are relatively larger than increases in ozone, which may indicate a net benefit of tree planting on human health aspects of air quality.
Matthew J. McGrath, Ana Maria Roxana Petrescu, Philippe Peylin, Robbie M. Andrew, Bradley Matthews, Frank Dentener, Juraj Balkovič, Vladislav Bastrikov, Meike Becker, Gregoire Broquet, Philippe Ciais, Audrey Fortems-Cheiney, Raphael Ganzenmüller, Giacomo Grassi, Ian Harris, Matthew Jones, Jürgen Knauer, Matthias Kuhnert, Guillaume Monteil, Saqr Munassar, Paul I. Palmer, Glen P. Peters, Chunjing Qiu, Mart-Jan Schelhaas, Oksana Tarasova, Matteo Vizzarri, Karina Winkler, Gianpaolo Balsamo, Antoine Berchet, Peter Briggs, Patrick Brockmann, Frédéric Chevallier, Giulia Conchedda, Monica Crippa, Stijn N. C. Dellaert, Hugo A. C. Denier van der Gon, Sara Filipek, Pierre Friedlingstein, Richard Fuchs, Michael Gauss, Christoph Gerbig, Diego Guizzardi, Dirk Günther, Richard A. Houghton, Greet Janssens-Maenhout, Ronny Lauerwald, Bas Lerink, Ingrid T. Luijkx, Géraud Moulas, Marilena Muntean, Gert-Jan Nabuurs, Aurélie Paquirissamy, Lucia Perugini, Wouter Peters, Roberto Pilli, Julia Pongratz, Pierre Regnier, Marko Scholze, Yusuf Serengil, Pete Smith, Efisio Solazzo, Rona L. Thompson, Francesco N. Tubiello, Timo Vesala, and Sophia Walther
Earth Syst. Sci. Data, 15, 4295–4370, https://doi.org/10.5194/essd-15-4295-2023, https://doi.org/10.5194/essd-15-4295-2023, 2023
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Accurate estimation of fluxes of carbon dioxide from the land surface is essential for understanding future impacts of greenhouse gas emissions on the climate system. A wide variety of methods currently exist to estimate these sources and sinks. We are continuing work to develop annual comparisons of these diverse methods in order to clarify what they all actually calculate and to resolve apparent disagreement, in addition to highlighting opportunities for increased understanding.
Olivia E. Clifton, Donna Schwede, Christian Hogrefe, Jesse O. Bash, Sam Bland, Philip Cheung, Mhairi Coyle, Lisa Emberson, Johannes Flemming, Erick Fredj, Stefano Galmarini, Laurens Ganzeveld, Orestis Gazetas, Ignacio Goded, Christopher D. Holmes, László Horváth, Vincent Huijnen, Qian Li, Paul A. Makar, Ivan Mammarella, Giovanni Manca, J. William Munger, Juan L. Pérez-Camanyo, Jonathan Pleim, Limei Ran, Roberto San Jose, Sam J. Silva, Ralf Staebler, Shihan Sun, Amos P. K. Tai, Eran Tas, Timo Vesala, Tamás Weidinger, Zhiyong Wu, and Leiming Zhang
Atmos. Chem. Phys., 23, 9911–9961, https://doi.org/10.5194/acp-23-9911-2023, https://doi.org/10.5194/acp-23-9911-2023, 2023
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A primary sink of air pollutants is dry deposition. Dry deposition estimates differ across the models used to simulate atmospheric chemistry. Here, we introduce an effort to examine dry deposition schemes from atmospheric chemistry models. We provide our approach’s rationale, document the schemes, and describe datasets used to drive and evaluate the schemes. We also launch the analysis of results by evaluating against observations and identifying the processes leading to model–model differences.
István Dunkl, Nicole Lovenduski, Alessio Collalti, Vivek K. Arora, Tatiana Ilyina, and Victor Brovkin
Biogeosciences, 20, 3523–3538, https://doi.org/10.5194/bg-20-3523-2023, https://doi.org/10.5194/bg-20-3523-2023, 2023
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Despite differences in the reproduction of gross primary productivity (GPP) by Earth system models (ESMs), ESMs have similar predictability of the global carbon cycle. We found that, although GPP variability originates from different regions and is driven by different climatic variables across the ESMs, the ESMs rely on the same mechanisms to predict their own GPP. This shows that the predictability of the carbon cycle is limited by our understanding of variability rather than predictability.
Alessandro Zanchetta, Linda M. J. Kooijmans, Steven van Heuven, Andrea Scifo, Hubertus A. Scheeren, Ivan Mammarella, Ute Karstens, Jin Ma, Maarten Krol, and Huilin Chen
Biogeosciences, 20, 3539–3553, https://doi.org/10.5194/bg-20-3539-2023, https://doi.org/10.5194/bg-20-3539-2023, 2023
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Carbonyl sulfide (COS) has been suggested as a tool to estimate carbon dioxide (CO2) uptake by plants during photosynthesis. However, understanding its sources and sinks is critical to preventing biases in this estimate. Combining observations and models, this study proves that regional sources occasionally influence the measurements at the 60 m tall Lutjewad tower (1 m a.s.l.; 53°24′ N, 6°21′ E) in the Netherlands. Moreover, it estimates nighttime COS fluxes to be −3.0 ± 2.6 pmol m−2 s−1.
Dirk Nikolaus Karger, Stefan Lange, Chantal Hari, Christopher P. O. Reyer, Olaf Conrad, Niklaus E. Zimmermann, and Katja Frieler
Earth Syst. Sci. Data, 15, 2445–2464, https://doi.org/10.5194/essd-15-2445-2023, https://doi.org/10.5194/essd-15-2445-2023, 2023
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We present the first 1 km, daily, global climate dataset for climate impact studies. We show that the high-resolution data have a decreased bias and higher correlation with measurements from meteorological stations than coarser data. The dataset will be of value for a wide range of climate change impact studies both at global and regional level that benefit from using a consistent global dataset.
Anton Rusanen, Kristo Hõrrak, Lauri R. Ahonen, Tuomo Nieminen, Pasi P. Aalto, Pasi Kolari, Markku Kulmala, Tuukka Petäjä, and Heikki Junninen
Atmos. Meas. Tech., 16, 2781–2793, https://doi.org/10.5194/amt-16-2781-2023, https://doi.org/10.5194/amt-16-2781-2023, 2023
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We present a framework for setting up SMEAR (Station for Measuring Ecosystem–Atmosphere Relations) type measurement station data flows. This framework, called SMEARcore, consists of modular open-source software components that can be chosen to suit various station configurations. The benefits of using this framework are automation of routine operations and real-time monitoring of measurement results.
Yao Ge, Massimo Vieno, David S. Stevenson, Peter Wind, and Mathew R. Heal
Atmos. Chem. Phys., 23, 6083–6112, https://doi.org/10.5194/acp-23-6083-2023, https://doi.org/10.5194/acp-23-6083-2023, 2023
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The sensitivity of fine particles and reactive N and S species to reductions in precursor emissions is investigated using the EMEP MSC-W (European Monitoring and Evaluation Programme Meteorological Synthesizing Centre – West) atmospheric chemistry transport model. This study reveals that the individual emissions reduction has multiple and geographically varying co-benefits and small disbenefits on different species, demonstrating the importance of prioritizing regional emissions controls.
Ana Maria Roxana Petrescu, Chunjing Qiu, Matthew J. McGrath, Philippe Peylin, Glen P. Peters, Philippe Ciais, Rona L. Thompson, Aki Tsuruta, Dominik Brunner, Matthias Kuhnert, Bradley Matthews, Paul I. Palmer, Oksana Tarasova, Pierre Regnier, Ronny Lauerwald, David Bastviken, Lena Höglund-Isaksson, Wilfried Winiwarter, Giuseppe Etiope, Tuula Aalto, Gianpaolo Balsamo, Vladislav Bastrikov, Antoine Berchet, Patrick Brockmann, Giancarlo Ciotoli, Giulia Conchedda, Monica Crippa, Frank Dentener, Christine D. Groot Zwaaftink, Diego Guizzardi, Dirk Günther, Jean-Matthieu Haussaire, Sander Houweling, Greet Janssens-Maenhout, Massaer Kouyate, Adrian Leip, Antti Leppänen, Emanuele Lugato, Manon Maisonnier, Alistair J. Manning, Tiina Markkanen, Joe McNorton, Marilena Muntean, Gabriel D. Oreggioni, Prabir K. Patra, Lucia Perugini, Isabelle Pison, Maarit T. Raivonen, Marielle Saunois, Arjo J. Segers, Pete Smith, Efisio Solazzo, Hanqin Tian, Francesco N. Tubiello, Timo Vesala, Guido R. van der Werf, Chris Wilson, and Sönke Zaehle
Earth Syst. Sci. Data, 15, 1197–1268, https://doi.org/10.5194/essd-15-1197-2023, https://doi.org/10.5194/essd-15-1197-2023, 2023
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This study updates the state-of-the-art scientific overview of CH4 and N2O emissions in the EU27 and UK in Petrescu et al. (2021a). Yearly updates are needed to improve the different respective approaches and to inform on the development of formal verification systems. It integrates the most recent emission inventories, process-based model and regional/global inversions, comparing them with UNFCCC national GHG inventories, in support to policy to facilitate real-time verification procedures.
Giacomo Grassi, Clemens Schwingshackl, Thomas Gasser, Richard A. Houghton, Stephen Sitch, Josep G. Canadell, Alessandro Cescatti, Philippe Ciais, Sandro Federici, Pierre Friedlingstein, Werner A. Kurz, Maria J. Sanz Sanchez, Raúl Abad Viñas, Ramdane Alkama, Selma Bultan, Guido Ceccherini, Stefanie Falk, Etsushi Kato, Daniel Kennedy, Jürgen Knauer, Anu Korosuo, Joana Melo, Matthew J. McGrath, Julia E. M. S. Nabel, Benjamin Poulter, Anna A. Romanovskaya, Simone Rossi, Hanqin Tian, Anthony P. Walker, Wenping Yuan, Xu Yue, and Julia Pongratz
Earth Syst. Sci. Data, 15, 1093–1114, https://doi.org/10.5194/essd-15-1093-2023, https://doi.org/10.5194/essd-15-1093-2023, 2023
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Striking differences exist in estimates of land-use CO2 fluxes between the national greenhouse gas inventories and the IPCC assessment reports. These differences hamper an accurate assessment of the collective progress under the Paris Agreement. By implementing an approach that conceptually reconciles land-use CO2 flux from national inventories and the global models used by the IPCC, our study is an important step forward for increasing confidence in land-use CO2 flux estimates.
Brendan Byrne, David F. Baker, Sourish Basu, Michael Bertolacci, Kevin W. Bowman, Dustin Carroll, Abhishek Chatterjee, Frédéric Chevallier, Philippe Ciais, Noel Cressie, David Crisp, Sean Crowell, Feng Deng, Zhu Deng, Nicholas M. Deutscher, Manvendra K. Dubey, Sha Feng, Omaira E. García, David W. T. Griffith, Benedikt Herkommer, Lei Hu, Andrew R. Jacobson, Rajesh Janardanan, Sujong Jeong, Matthew S. Johnson, Dylan B. A. Jones, Rigel Kivi, Junjie Liu, Zhiqiang Liu, Shamil Maksyutov, John B. Miller, Scot M. Miller, Isamu Morino, Justus Notholt, Tomohiro Oda, Christopher W. O'Dell, Young-Suk Oh, Hirofumi Ohyama, Prabir K. Patra, Hélène Peiro, Christof Petri, Sajeev Philip, David F. Pollard, Benjamin Poulter, Marine Remaud, Andrew Schuh, Mahesh K. Sha, Kei Shiomi, Kimberly Strong, Colm Sweeney, Yao Té, Hanqin Tian, Voltaire A. Velazco, Mihalis Vrekoussis, Thorsten Warneke, John R. Worden, Debra Wunch, Yuanzhi Yao, Jeongmin Yun, Andrew Zammit-Mangion, and Ning Zeng
Earth Syst. Sci. Data, 15, 963–1004, https://doi.org/10.5194/essd-15-963-2023, https://doi.org/10.5194/essd-15-963-2023, 2023
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Changes in the carbon stocks of terrestrial ecosystems result in emissions and removals of CO2. These can be driven by anthropogenic activities (e.g., deforestation), natural processes (e.g., fires) or in response to rising CO2 (e.g., CO2 fertilization). This paper describes a dataset of CO2 emissions and removals derived from atmospheric CO2 observations. This pilot dataset informs current capabilities and future developments towards top-down monitoring and verification systems.
Xiaoyong Li, Hanqin Tian, Chaoqun Lu, and Shufen Pan
Earth Syst. Sci. Data, 15, 1005–1035, https://doi.org/10.5194/essd-15-1005-2023, https://doi.org/10.5194/essd-15-1005-2023, 2023
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We reconstructed land use and land cover (LULC) history for the conterminous United States during 1630–2020 by integrating multi-source data. The results show the widespread expansion of cropland and urban land and the shrinking of natural vegetation in the past four centuries. Forest planting and regeneration accelerated forest recovery since the 1920s. The datasets can be used to assess the LULC impacts on the ecosystem's carbon, nitrogen, and water cycles.
Matti Kämäräinen, Juha-Pekka Tuovinen, Markku Kulmala, Ivan Mammarella, Juha Aalto, Henriikka Vekuri, Annalea Lohila, and Anna Lintunen
Biogeosciences, 20, 897–909, https://doi.org/10.5194/bg-20-897-2023, https://doi.org/10.5194/bg-20-897-2023, 2023
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In this study, we introduce a new method for modeling the exchange of carbon between the atmosphere and a study site located in a boreal forest in southern Finland. Our method yields more accurate results than previous approaches in this context. Accurately estimating carbon exchange is crucial for gaining a better understanding of the role of forests in regulating atmospheric carbon and addressing climate change.
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
Atmos. Chem. Phys., 23, 851–876, https://doi.org/10.5194/acp-23-851-2023, https://doi.org/10.5194/acp-23-851-2023, 2023
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The exchange ratio (ER) between atmospheric O2 and CO2 provides a useful tracer for separately estimating photosynthesis and respiration processes in the forest carbon balance. This is highly relevant to better understand the expected biosphere sink, which determines future atmospheric CO2 levels. We therefore measured O2, CO2, and their ER above a boreal forest in Finland and investigated their diurnal behaviour for a representative day, and we show the most suitable way to determine the ER.
Taija Saarela, Xudan Zhu, Helena Jäntti, Mizue Ohashi, Jun'ichiro Ide, Henri Siljanen, Aake Pesonen, Heidi Aaltonen, Anne Ojala, Hiroshi Nishimura, Timo Kekäläinen, Janne Jänis, Frank Berninger, and Jukka Pumpanen
Biogeosciences Discuss., https://doi.org/10.5194/bg-2022-225, https://doi.org/10.5194/bg-2022-225, 2022
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This study investigated the molecular composition and carbon dioxide production of water samples collected from two subarctic rivers that represent contrasting types of catchment characteristics. The results highlight the role of clearwater environments in microbial degradation and greenhouse gas dynamics of subarctic catchments.
Hanqin Tian, Zihao Bian, Hao Shi, Xiaoyu Qin, Naiqing Pan, Chaoqun Lu, Shufen Pan, Francesco N. Tubiello, Jinfeng Chang, Giulia Conchedda, Junguo Liu, Nathaniel Mueller, Kazuya Nishina, Rongting Xu, Jia Yang, Liangzhi You, and Bowen Zhang
Earth Syst. Sci. Data, 14, 4551–4568, https://doi.org/10.5194/essd-14-4551-2022, https://doi.org/10.5194/essd-14-4551-2022, 2022
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Nitrogen is one of the critical nutrients for growth. Evaluating the change in nitrogen inputs due to human activity is necessary for nutrient management and pollution control. In this study, we generated a historical dataset of nitrogen input to land at the global scale. This dataset consists of nitrogen fertilizer, manure, and atmospheric deposition inputs to cropland, pasture, and rangeland at high resolution from 1860 to 2019.
Kukka-Maaria Kohonen, Roderick Dewar, Gianluca Tramontana, Aleksanteri Mauranen, Pasi Kolari, Linda M. J. Kooijmans, Dario Papale, Timo Vesala, and Ivan Mammarella
Biogeosciences, 19, 4067–4088, https://doi.org/10.5194/bg-19-4067-2022, https://doi.org/10.5194/bg-19-4067-2022, 2022
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Four different methods for quantifying photosynthesis (GPP) at ecosystem scale were tested, of which two are based on carbon dioxide (CO2) and two on carbonyl sulfide (COS) flux measurements. CO2-based methods are traditional partitioning, and a new method uses machine learning. We introduce a novel method for calculating GPP from COS fluxes, with potentially better applicability than the former methods. Both COS-based methods gave on average higher GPP estimates than the CO2-based estimates.
Johannes Oberpriller, Christine Herschlein, Peter Anthoni, Almut Arneth, Andreas Krause, Anja Rammig, Mats Lindeskog, Stefan Olin, and Florian Hartig
Geosci. Model Dev., 15, 6495–6519, https://doi.org/10.5194/gmd-15-6495-2022, https://doi.org/10.5194/gmd-15-6495-2022, 2022
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Understanding uncertainties of projected ecosystem dynamics under environmental change is of immense value for research and climate change policy. Here, we analyzed these across European forests. We find that uncertainties are dominantly induced by parameters related to water, mortality, and climate, with an increasing importance of climate from north to south. These results highlight that climate not only contributes uncertainty but also modifies uncertainties in other ecosystem processes.
Kathrin Wehrli, Fei Luo, Mathias Hauser, Hideo Shiogama, Daisuke Tokuda, Hyungjun Kim, Dim Coumou, Wilhelm May, Philippe Le Sager, Frank Selten, Olivia Martius, Robert Vautard, and Sonia I. Seneviratne
Earth Syst. Dynam., 13, 1167–1196, https://doi.org/10.5194/esd-13-1167-2022, https://doi.org/10.5194/esd-13-1167-2022, 2022
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The ExtremeX experiment was designed to unravel the contribution of processes leading to the occurrence of recent weather and climate extremes. Global climate simulations are carried out with three models. The results show that in constrained experiments, temperature anomalies during heatwaves are well represented, although climatological model biases remain. Further, a substantial contribution of both atmospheric circulation and soil moisture to heat extremes is identified.
Fei Luo, Frank Selten, Kathrin Wehrli, Kai Kornhuber, Philippe Le Sager, Wilhelm May, Thomas Reerink, Sonia I. Seneviratne, Hideo Shiogama, Daisuke Tokuda, Hyungjun Kim, and Dim Coumou
Weather Clim. Dynam., 3, 905–935, https://doi.org/10.5194/wcd-3-905-2022, https://doi.org/10.5194/wcd-3-905-2022, 2022
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Recent studies have identified the weather systems in observational data, where wave patterns with high-magnitude values that circle around the whole globe in either wavenumber 5 or wavenumber 7 are responsible for the extreme events. In conclusion, we find that the climate models are able to reproduce the large-scale atmospheric circulation patterns as well as their associated surface variables such as temperature, precipitation, and sea level pressure.
Yao Ge, Massimo Vieno, David S. Stevenson, Peter Wind, and Mathew R. Heal
Atmos. Chem. Phys., 22, 8343–8368, https://doi.org/10.5194/acp-22-8343-2022, https://doi.org/10.5194/acp-22-8343-2022, 2022
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Reactive N and S gases and aerosols are critical determinants of air quality. We report a comprehensive analysis of the concentrations, wet and dry deposition, fluxes, and lifetimes of these species globally as well as for 10 world regions. We used the EMEP MSC-W model coupled with WRF meteorology and 2015 global emissions. Our work demonstrates the substantial regional variation in these quantities and the need for modelling to simulate atmospheric responses to precursor emissions.
Joonatan Ala-Könni, Kukka-Maaria Kohonen, Matti Leppäranta, and Ivan Mammarella
Geosci. Model Dev., 15, 4739–4755, https://doi.org/10.5194/gmd-15-4739-2022, https://doi.org/10.5194/gmd-15-4739-2022, 2022
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Properties of seasonally ice-covered lakes are not currently sufficiently included in global climate models. To fill this gap, this study evaluates three models that could be used to quantify the amount of heat that moves from and into the lake by the air above it and through evaporation of the ice cover. The results show that the complex nature of the surrounding environment as well as difficulties in accurately measuring the surface temperature of ice introduce errors to these models.
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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Lakes and reservoirs are warming across the globe. To better understand how lakes are changing and to project their future behavior amidst various sources of uncertainty, simulations with a range of lake models are required. This in turn requires international coordination across different lake modelling teams worldwide. Here we present a protocol for and results from coordinated simulations of climate change impacts on lakes worldwide.
M. G. Ziliani, M. U. Altaf, B. Aragon, R. Houborg, T. E. Franz, Y. Lu, J. Sheffield, I. Hoteit, and M. F. McCabe
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2022, 1045–1052, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-1045-2022, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-1045-2022, 2022
Shakirudeen Lawal, Stephen Sitch, Danica Lombardozzi, Julia E. M. S. Nabel, Hao-Wei Wey, Pierre Friedlingstein, Hanqin Tian, and Bruce Hewitson
Hydrol. Earth Syst. Sci., 26, 2045–2071, https://doi.org/10.5194/hess-26-2045-2022, https://doi.org/10.5194/hess-26-2045-2022, 2022
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To investigate the impacts of drought on vegetation, which few studies have done due to various limitations, we used the leaf area index as proxy and dynamic global vegetation models (DGVMs) to simulate drought impacts because the models use observationally derived climate. We found that the semi-desert biome responds strongly to drought in the summer season, while the tropical forest biome shows a weak response. This study could help target areas to improve drought monitoring and simulation.
Pierre Friedlingstein, Matthew W. Jones, Michael O'Sullivan, Robbie M. Andrew, Dorothee C. E. Bakker, Judith Hauck, Corinne Le Quéré, Glen P. Peters, Wouter Peters, Julia Pongratz, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Rob B. Jackson, Simone R. Alin, Peter Anthoni, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Laurent Bopp, Thi Tuyet Trang Chau, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Kim I. Currie, Bertrand Decharme, Laique M. Djeutchouang, Xinyu Dou, Wiley Evans, Richard A. Feely, Liang Feng, Thomas Gasser, Dennis Gilfillan, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Ingrid T. Luijkx, Atul Jain, Steve D. Jones, Etsushi Kato, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Arne Körtzinger, Peter Landschützer, Siv K. Lauvset, Nathalie Lefèvre, Sebastian Lienert, Junjie Liu, Gregg Marland, Patrick C. McGuire, Joe R. Melton, David R. Munro, Julia E. M. S. Nabel, Shin-Ichiro Nakaoka, Yosuke Niwa, Tsuneo Ono, Denis Pierrot, Benjamin Poulter, Gregor Rehder, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Thais M. Rosan, Jörg Schwinger, Clemens Schwingshackl, Roland Séférian, Adrienne J. Sutton, Colm Sweeney, Toste Tanhua, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Francesco Tubiello, Guido R. van der Werf, Nicolas Vuichard, Chisato Wada, Rik Wanninkhof, Andrew J. Watson, David Willis, Andrew J. Wiltshire, Wenping Yuan, Chao Yue, Xu Yue, Sönke Zaehle, and Jiye Zeng
Earth Syst. Sci. Data, 14, 1917–2005, https://doi.org/10.5194/essd-14-1917-2022, https://doi.org/10.5194/essd-14-1917-2022, 2022
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The Global Carbon Budget 2021 describes the data sets and methodology used to quantify the emissions of carbon dioxide and their partitioning among the atmosphere, land, and ocean. These living data are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Minttu Havu, Liisa Kulmala, Pasi Kolari, Timo Vesala, Anu Riikonen, and Leena Järvi
Biogeosciences, 19, 2121–2143, https://doi.org/10.5194/bg-19-2121-2022, https://doi.org/10.5194/bg-19-2121-2022, 2022
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The carbon sequestration potential of two street tree species and the soil beneath them was quantified with the urban land surface model SUEWS and the soil carbon model Yasso. The street tree plantings turned into a modest sink of carbon from the atmosphere after 14 years. Overall, the results indicate the importance of soil in urban carbon sequestration estimations, as soil respiration exceeded the carbon uptake in the early phase, due to the high initial carbon loss from the soil.
Hamze Dokoohaki, Bailey D. Morrison, Ann Raiho, Shawn P. Serbin, Katie Zarada, Luke Dramko, and Michael Dietze
Geosci. Model Dev., 15, 3233–3252, https://doi.org/10.5194/gmd-15-3233-2022, https://doi.org/10.5194/gmd-15-3233-2022, 2022
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We present a new terrestrial carbon cycle data assimilation system, built on the PEcAn model–data eco-informatics system, and its application for the development of a proof-of-concept carbon
reanalysisproduct that harmonizes carbon pools (leaf, wood, soil) and fluxes (GPP, Ra, Rh, NEE) across the contiguous United States from 1986–2019. Here, we build on a decade of work on uncertainty propagation to generate the most complete and robust uncertainty accounting available to date.
Ruqi Yang, Jun Wang, Ning Zeng, Stephen Sitch, Wenhan Tang, Matthew Joseph McGrath, Qixiang Cai, Di Liu, Danica Lombardozzi, Hanqin Tian, Atul K. Jain, and Pengfei Han
Earth Syst. Dynam., 13, 833–849, https://doi.org/10.5194/esd-13-833-2022, https://doi.org/10.5194/esd-13-833-2022, 2022
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We comprehensively investigate historical GPP trends based on five kinds of GPP datasets and analyze the causes for any discrepancies among them. Results show contrasting behaviors between modeled and satellite-based GPP trends, and their inconsistencies are likely caused by the contrasting performance between satellite-derived and modeled leaf area index (LAI). Thus, the uncertainty in satellite-based GPP induced by LAI undermines its role in assessing the performance of DGVM simulations.
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.
Zhu Deng, Philippe Ciais, Zitely A. Tzompa-Sosa, Marielle Saunois, Chunjing Qiu, Chang Tan, Taochun Sun, Piyu Ke, Yanan Cui, Katsumasa Tanaka, Xin Lin, Rona L. Thompson, Hanqin Tian, Yuanzhi Yao, Yuanyuan Huang, Ronny Lauerwald, Atul K. Jain, Xiaoming Xu, Ana Bastos, Stephen Sitch, Paul I. Palmer, Thomas Lauvaux, Alexandre d'Aspremont, Clément Giron, Antoine Benoit, Benjamin Poulter, Jinfeng Chang, Ana Maria Roxana Petrescu, Steven J. Davis, Zhu Liu, Giacomo Grassi, Clément Albergel, Francesco N. Tubiello, Lucia Perugini, Wouter Peters, and Frédéric Chevallier
Earth Syst. Sci. Data, 14, 1639–1675, https://doi.org/10.5194/essd-14-1639-2022, https://doi.org/10.5194/essd-14-1639-2022, 2022
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In support of the global stocktake of the Paris Agreement on climate change, we proposed a method for reconciling the results of global atmospheric inversions with data from UNFCCC national greenhouse gas inventories (NGHGIs). Here, based on a new global harmonized database that we compiled from the UNFCCC NGHGIs and a comprehensive framework presented in this study to process the results of inversions, we compared their results of carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O).
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.
Philippe Ciais, Ana Bastos, Frédéric Chevallier, Ronny Lauerwald, Ben Poulter, Josep G. Canadell, Gustaf Hugelius, Robert B. Jackson, Atul Jain, Matthew Jones, Masayuki Kondo, Ingrid T. Luijkx, Prabir K. Patra, Wouter Peters, Julia Pongratz, Ana Maria Roxana Petrescu, Shilong Piao, Chunjing Qiu, Celso Von Randow, Pierre Regnier, Marielle Saunois, Robert Scholes, Anatoly Shvidenko, Hanqin Tian, Hui Yang, Xuhui Wang, and Bo Zheng
Geosci. Model Dev., 15, 1289–1316, https://doi.org/10.5194/gmd-15-1289-2022, https://doi.org/10.5194/gmd-15-1289-2022, 2022
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The second phase of the Regional Carbon Cycle Assessment and Processes (RECCAP) will provide updated quantification and process understanding of CO2, CH4, and N2O emissions and sinks for ten regions of the globe. In this paper, we give definitions, review different methods, and make recommendations for estimating different components of the total land–atmosphere carbon exchange for each region in a consistent and complete approach.
J. Pacheco-Labrador, U. Weber, X. Ma, M. D. Mahecha, N. Carvalhais, C. Wirth, A. Huth, F. J. Bohn, G. Kraemer, U. Heiden, FunDivEUROPE members, and M. Migliavacca
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVI-1-W1-2021, 49–55, https://doi.org/10.5194/isprs-archives-XLVI-1-W1-2021-49-2022, https://doi.org/10.5194/isprs-archives-XLVI-1-W1-2021-49-2022, 2022
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.
Tom Gleeson, Thorsten Wagener, Petra Döll, Samuel C. Zipper, Charles West, Yoshihide Wada, Richard Taylor, Bridget Scanlon, Rafael Rosolem, Shams Rahman, Nurudeen Oshinlaja, Reed Maxwell, Min-Hui Lo, Hyungjun Kim, Mary Hill, Andreas Hartmann, Graham Fogg, James S. Famiglietti, Agnès Ducharne, Inge de Graaf, Mark Cuthbert, Laura Condon, Etienne Bresciani, and Marc F. P. Bierkens
Geosci. Model Dev., 14, 7545–7571, https://doi.org/10.5194/gmd-14-7545-2021, https://doi.org/10.5194/gmd-14-7545-2021, 2021
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Groundwater is increasingly being included in large-scale (continental to global) land surface and hydrologic simulations. However, it is challenging to evaluate these simulations because groundwater is
hiddenunderground and thus hard to measure. We suggest using multiple complementary strategies to assess the performance of a model (
model evaluation).
Seoung Soo Lee, Kyung-Ja Ha, Manguttathil Gopalakrishnan Manoj, Mohammad Kamruzzaman, Hyungjun Kim, Nobuyuki Utsumi, Youtong Zheng, Byung-Gon Kim, Chang Hoon Jung, Junshik Um, Jianping Guo, Kyoung Ock Choi, and Go-Un Kim
Atmos. Chem. Phys., 21, 16843–16868, https://doi.org/10.5194/acp-21-16843-2021, https://doi.org/10.5194/acp-21-16843-2021, 2021
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Using a modeling framework, a midlatitude stratocumulus cloud system is simulated. It is found that cloud mass in the system becomes very low due to interactions between ice and liquid particles compared to that in the absence of ice particles. It is also found that interactions between cloud mass and aerosols lead to a reduction in cloud mass in the system, and this is contrary to an aerosol-induced increase in cloud mass in the absence of ice particles.
Yao Ge, Mathew R. Heal, David S. Stevenson, Peter Wind, and Massimo Vieno
Geosci. Model Dev., 14, 7021–7046, https://doi.org/10.5194/gmd-14-7021-2021, https://doi.org/10.5194/gmd-14-7021-2021, 2021
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This study reports the first evaluation of the global EMEP MSC-W ACTM driven by WRF meteorology, with a focus on surface concentrations and wet deposition of reactive N and S species. The model–measurement comparison is conducted both spatially and temporally, covering 10 monitoring networks worldwide. The statistics from the comprehensive evaluations presented in this study support the application of this model framework for global analysis of the budgets and fluxes of reactive N and SIA.
Jan C. Minx, William F. Lamb, Robbie M. Andrew, Josep G. Canadell, Monica Crippa, Niklas Döbbeling, Piers M. Forster, Diego Guizzardi, Jos Olivier, Glen P. Peters, Julia Pongratz, Andy Reisinger, Matthew Rigby, Marielle Saunois, Steven J. Smith, Efisio Solazzo, and Hanqin Tian
Earth Syst. Sci. Data, 13, 5213–5252, https://doi.org/10.5194/essd-13-5213-2021, https://doi.org/10.5194/essd-13-5213-2021, 2021
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We provide a synthetic dataset on anthropogenic greenhouse gas (GHG) emissions for 1970–2018 with a fast-track extension to 2019. We show that GHG emissions continued to rise across all gases and sectors. Annual average GHG emissions growth slowed, but absolute decadal increases have never been higher in human history. We identify a number of data gaps and data quality issues in global inventories and highlight their importance for monitoring progress towards international climate goals.
John Zobitz, Heidi Aaltonen, Xuan Zhou, Frank Berninger, Jukka Pumpanen, and Kajar Köster
Geosci. Model Dev., 14, 6605–6622, https://doi.org/10.5194/gmd-14-6605-2021, https://doi.org/10.5194/gmd-14-6605-2021, 2021
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Forest fires heavily affect carbon stocks and fluxes of carbon in high-latitude forests. Long-term trends in soil respiration following forest fires are associated with recovery of aboveground biomass. We evaluated models for soil autotrophic and heterotrophic respiration with data from a chronosequence of stand-replacing forest fires in northern Canada. The best model that reproduced expected patterns in soil respiration components takes into account soil microbe carbon as a model variable.
Abhijeet Mishra, Florian Humpenöder, Jan Philipp Dietrich, Benjamin Leon Bodirsky, Brent Sohngen, Christopher P. O. Reyer, Hermann Lotze-Campen, and Alexander Popp
Geosci. Model Dev., 14, 6467–6494, https://doi.org/10.5194/gmd-14-6467-2021, https://doi.org/10.5194/gmd-14-6467-2021, 2021
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Timber plantations are an increasingly important source of roundwood production, next to harvest from natural forests. However, timber plantations are currently underrepresented in global land-use models. Here, we include timber production and plantations in the MAgPIE modeling framework. This allows one to capture the competition for land between agriculture and forestry. We show that increasing timber plantations in the coming decades partly compete with cropland for limited land resources.
Jina Jeong, Jonathan Barichivich, Philippe Peylin, Vanessa Haverd, Matthew Joseph McGrath, Nicolas Vuichard, Michael Neil Evans, Flurin Babst, and Sebastiaan Luyssaert
Geosci. Model Dev., 14, 5891–5913, https://doi.org/10.5194/gmd-14-5891-2021, https://doi.org/10.5194/gmd-14-5891-2021, 2021
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We have proposed and evaluated the use of four benchmarks that leverage tree-ring width observations to provide more nuanced verification targets for land-surface models (LSMs), which currently lack a long-term benchmark for forest ecosystem functioning. Using relatively unbiased European biomass network datasets, we identify the extent to which presumed biases in the much larger International Tree-Ring Data Bank might degrade the validation of LSMs.
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.
Daisuke Tokuda, Hyungjun Kim, Dai Yamazaki, and Taikan Oki
Geosci. Model Dev., 14, 5669–5693, https://doi.org/10.5194/gmd-14-5669-2021, https://doi.org/10.5194/gmd-14-5669-2021, 2021
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We developed TCHOIR, a hydrologic simulation framework, to solve fluvial- and thermodynamics of the river–lake continuum. This provides an algorithm for upscaling high-resolution topography as well, which enables the representation of those interactions at the global scale. Validation against in situ and satellite observations shows that the coupled mode outperforms river- or lake-only modes. TCHOIR will contribute to elucidating the role of surface hydrology in Earth’s energy and water cycle.
Alexander J. Winkler, Ranga B. Myneni, Alexis Hannart, Stephen Sitch, Vanessa Haverd, Danica Lombardozzi, Vivek K. Arora, Julia Pongratz, Julia E. M. S. Nabel, Daniel S. Goll, Etsushi Kato, Hanqin Tian, Almut Arneth, Pierre Friedlingstein, Atul K. Jain, Sönke Zaehle, and Victor Brovkin
Biogeosciences, 18, 4985–5010, https://doi.org/10.5194/bg-18-4985-2021, https://doi.org/10.5194/bg-18-4985-2021, 2021
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Satellite observations since the early 1980s show that Earth's greening trend is slowing down and that browning clusters have been emerging, especially in the last 2 decades. A collection of model simulations in conjunction with causal theory points at climatic changes as a key driver of vegetation changes in natural ecosystems. Most models underestimate the observed vegetation browning, especially in tropical rainforests, which could be due to an excessive CO2 fertilization effect in models.
Nahid Atashi, Dariush Rahimi, Victoria A. Sinclair, Martha A. Zaidan, Anton Rusanen, Henri Vuollekoski, Markku Kulmala, Timo Vesala, and Tareq Hussein
Hydrol. Earth Syst. Sci., 25, 4719–4740, https://doi.org/10.5194/hess-25-4719-2021, https://doi.org/10.5194/hess-25-4719-2021, 2021
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Dew formation potential during a long-term period (1979–2018) was assessed in Iran to identify dew formation zones and to investigate the impacts of long-term variation in meteorological parameters on dew formation. Six dew formation zones were identified based on cluster analysis of the time series of the simulated dew yield. The distribution of dew formation zones in Iran was closely aligned with topography and sources of moisture. The dew formation trend was significantly negative.
Matthias Mengel, Simon Treu, Stefan Lange, and Katja Frieler
Geosci. Model Dev., 14, 5269–5284, https://doi.org/10.5194/gmd-14-5269-2021, https://doi.org/10.5194/gmd-14-5269-2021, 2021
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To identify the impacts of historical climate change it is necessary to separate the effect of the different impact drivers. To address this, one needs to compare historical impacts to a counterfactual world with impacts that would have been without climate change. We here present an approach that produces counterfactual climate data and can be used in climate impact models to simulate counterfactual impacts. We make these data available through the ISIMIP project.
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.
Rainer Brumme, Bernd Ahrends, Joachim Block, Christoph Schulz, Henning Meesenburg, Uwe Klinck, Markus Wagner, and Partap K. Khanna
Biogeosciences, 18, 3763–3779, https://doi.org/10.5194/bg-18-3763-2021, https://doi.org/10.5194/bg-18-3763-2021, 2021
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In order to study the fate of litter nitrogen in forest soils, we combined a leaf litterfall exchange experiment using 15N-labeled leaf litter with long-term element budgets at seven European beech sites in Germany. It appears that fructification intensity, which has increased in recent decades, has a distinct impact on N retention in forest soils. Despite reduced nitrogen deposition, about 6 and 10 kg ha−1 of nitrogen were retained annually in the soils and in the forest stands, respectively.
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.
Ana Maria Roxana Petrescu, Chunjing Qiu, Philippe Ciais, Rona L. Thompson, Philippe Peylin, Matthew J. McGrath, Efisio Solazzo, Greet Janssens-Maenhout, Francesco N. Tubiello, Peter Bergamaschi, Dominik Brunner, Glen P. Peters, Lena Höglund-Isaksson, Pierre Regnier, Ronny Lauerwald, David Bastviken, Aki Tsuruta, Wilfried Winiwarter, Prabir K. Patra, Matthias Kuhnert, Gabriel D. Oreggioni, Monica Crippa, Marielle Saunois, Lucia Perugini, Tiina Markkanen, Tuula Aalto, Christine D. Groot Zwaaftink, Hanqin Tian, Yuanzhi Yao, Chris Wilson, Giulia Conchedda, Dirk Günther, Adrian Leip, Pete Smith, Jean-Matthieu Haussaire, Antti Leppänen, Alistair J. Manning, Joe McNorton, Patrick Brockmann, and Albertus Johannes Dolman
Earth Syst. Sci. Data, 13, 2307–2362, https://doi.org/10.5194/essd-13-2307-2021, https://doi.org/10.5194/essd-13-2307-2021, 2021
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This study is topical and provides a state-of-the-art scientific overview of data availability from bottom-up and top-down CH4 and N2O emissions in the EU27 and UK. The data integrate recent emission inventories with process-based model data and regional/global inversions for the European domain, aiming at reconciling them with official country-level UNFCCC national GHG inventories in support to policy and to facilitate real-time verification procedures.
Wolfgang A. Obermeier, Julia E. M. S. Nabel, Tammas Loughran, Kerstin Hartung, Ana Bastos, Felix Havermann, Peter Anthoni, Almut Arneth, Daniel S. Goll, Sebastian Lienert, Danica Lombardozzi, Sebastiaan Luyssaert, Patrick C. McGuire, Joe R. Melton, Benjamin Poulter, Stephen Sitch, Michael O. Sullivan, Hanqin Tian, Anthony P. Walker, Andrew J. Wiltshire, Soenke Zaehle, and Julia Pongratz
Earth Syst. Dynam., 12, 635–670, https://doi.org/10.5194/esd-12-635-2021, https://doi.org/10.5194/esd-12-635-2021, 2021
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We provide the first spatio-temporally explicit comparison of different model-derived fluxes from land use and land cover changes (fLULCCs) by using the TRENDY v8 dynamic global vegetation models used in the 2019 global carbon budget. We find huge regional fLULCC differences resulting from environmental assumptions, simulated periods, and the timing of land use and land cover changes, and we argue for a method consistent across time and space and for carefully choosing the accounting period.
Alexey N. Shiklomanov, Michael C. Dietze, Istem Fer, Toni Viskari, and Shawn P. Serbin
Geosci. Model Dev., 14, 2603–2633, https://doi.org/10.5194/gmd-14-2603-2021, https://doi.org/10.5194/gmd-14-2603-2021, 2021
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Airborne and satellite images are a great resource for calibrating and evaluating computer models of ecosystems. Typically, researchers derive ecosystem properties from these images and then compare models against these derived properties. Here, we present an alternative approach where we modify a model to predict what the satellite would see more directly. We then show how this approach can be used to calibrate model parameters using airborne data from forest sites in the northeastern US.
Zichong Chen, Junjie Liu, Daven K. Henze, Deborah N. Huntzinger, Kelley C. Wells, Stephen Sitch, Pierre Friedlingstein, Emilie Joetzjer, Vladislav Bastrikov, Daniel S. Goll, Vanessa Haverd, Atul K. Jain, Etsushi Kato, Sebastian Lienert, Danica L. Lombardozzi, Patrick C. McGuire, Joe R. Melton, Julia E. M. S. Nabel, Benjamin Poulter, Hanqin Tian, Andrew J. Wiltshire, Sönke Zaehle, and Scot M. Miller
Atmos. Chem. Phys., 21, 6663–6680, https://doi.org/10.5194/acp-21-6663-2021, https://doi.org/10.5194/acp-21-6663-2021, 2021
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NASA's Orbiting Carbon Observatory 2 (OCO-2) satellite observes atmospheric CO2 globally. We use a multiple regression and inverse model to quantify the relationships between OCO-2 and environmental drivers within individual years for 2015–2018 and within seven global biomes. Our results point to limitations of current space-based observations for inferring environmental relationships but also indicate the potential to inform key relationships that are very uncertain in process-based models.
Noemi Vergopolan, Sitian Xiong, Lyndon Estes, Niko Wanders, Nathaniel W. Chaney, Eric F. Wood, Megan Konar, Kelly Caylor, Hylke E. Beck, Nicolas Gatti, Tom Evans, and Justin Sheffield
Hydrol. Earth Syst. Sci., 25, 1827–1847, https://doi.org/10.5194/hess-25-1827-2021, https://doi.org/10.5194/hess-25-1827-2021, 2021
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Drought monitoring and yield prediction often rely on coarse-scale hydroclimate data or (infrequent) vegetation indexes that do not always indicate the conditions farmers face in the field. Consequently, decision-making based on these indices can often be disconnected from the farmer reality. Our study focuses on smallholder farming systems in data-sparse developing countries, and it shows how field-scale soil moisture can leverage and improve crop yield prediction and drought impact assessment.
Olli Peltola, Karl Lapo, Ilkka Martinkauppi, Ewan O'Connor, Christoph K. Thomas, and Timo Vesala
Atmos. Meas. Tech., 14, 2409–2427, https://doi.org/10.5194/amt-14-2409-2021, https://doi.org/10.5194/amt-14-2409-2021, 2021
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We evaluated the suitability of fiber-optic distributed temperature sensing (DTS) for observing spatial (>25 cm) and temporal (>1 s) details of airflow within and above forests. The DTS measurements could discern up to third-order moments of the flow and observe spatial details of coherent flow motions. Similar measurements are not possible with more conventional measurement techniques. Hence, the DTS measurements will provide key insights into flows close to roughness elements, e.g. trees.
Kathryn I. Wheeler and Michael C. Dietze
Biogeosciences, 18, 1971–1985, https://doi.org/10.5194/bg-18-1971-2021, https://doi.org/10.5194/bg-18-1971-2021, 2021
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Monitoring leaf phenology (i.e., seasonality) allows for tracking the progression of climate change and seasonal variations in a variety of organismal and ecosystem processes. Recent versions of the Geostationary Operational Environmental Satellites allow for the monitoring of a phenological-sensitive index at a high temporal frequency (5–10 min) throughout most of the western hemisphere. Here we show the high potential of these new data to measure the phenology of deciduous forests.
Zihao Bian, Hanqin Tian, Qichun Yang, Rongting Xu, Shufen Pan, and Bowen Zhang
Earth Syst. Sci. Data, 13, 515–527, https://doi.org/10.5194/essd-13-515-2021, https://doi.org/10.5194/essd-13-515-2021, 2021
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The estimation of manure nutrient production and application is critical for the efficient use of manure nutrients. This study developed four manure nitrogen and phosphorus datasets with high spatial resolution and a long time period (1860–2017) in the US. The datasets can provide useful information for stakeholders and scientists who focus on agriculture, nutrient budget, and biogeochemical cycle.
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.
Hylke E. Beck, Ming Pan, Diego G. Miralles, Rolf H. Reichle, Wouter A. Dorigo, Sebastian Hahn, Justin Sheffield, Lanka Karthikeyan, Gianpaolo Balsamo, Robert M. Parinussa, Albert I. J. M. van Dijk, Jinyang Du, John S. Kimball, Noemi Vergopolan, and Eric F. Wood
Hydrol. Earth Syst. Sci., 25, 17–40, https://doi.org/10.5194/hess-25-17-2021, https://doi.org/10.5194/hess-25-17-2021, 2021
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We evaluated the largest and most diverse set of surface soil moisture products ever evaluated in a single study. We found pronounced differences in performance among individual products and product groups. Our results provide guidance to choose the most suitable product for a particular application.
Richard Essery, Hyungjun Kim, Libo Wang, Paul Bartlett, Aaron Boone, Claire Brutel-Vuilmet, Eleanor Burke, Matthias Cuntz, Bertrand Decharme, Emanuel Dutra, Xing Fang, Yeugeniy Gusev, Stefan Hagemann, Vanessa Haverd, Anna Kontu, Gerhard Krinner, Matthieu Lafaysse, Yves Lejeune, Thomas Marke, Danny Marks, Christoph Marty, Cecile B. Menard, Olga Nasonova, Tomoko Nitta, John Pomeroy, Gerd Schädler, Vladimir Semenov, Tatiana Smirnova, Sean Swenson, Dmitry Turkov, Nander Wever, and Hua Yuan
The Cryosphere, 14, 4687–4698, https://doi.org/10.5194/tc-14-4687-2020, https://doi.org/10.5194/tc-14-4687-2020, 2020
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Climate models are uncertain in predicting how warming changes snow cover. This paper compares 22 snow models with the same meteorological inputs. Predicted trends agree with observations at four snow research sites: winter snow cover does not start later, but snow now melts earlier in spring than in the 1980s at two of the sites. Cold regions where snow can last until late summer are predicted to be particularly sensitive to warming because the snow then melts faster at warmer times of year.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Judith Hauck, Are Olsen, Glen P. Peters, Wouter Peters, Julia Pongratz, Stephen Sitch, Corinne Le Quéré, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone Alin, Luiz E. O. C. Aragão, Almut Arneth, Vivek Arora, Nicholas R. Bates, Meike Becker, Alice Benoit-Cattin, Henry C. Bittig, Laurent Bopp, Selma Bultan, Naveen Chandra, Frédéric Chevallier, Louise P. Chini, Wiley Evans, Liesbeth Florentie, Piers M. Forster, Thomas Gasser, Marion Gehlen, Dennis Gilfillan, Thanos Gkritzalis, Luke Gregor, Nicolas Gruber, Ian Harris, Kerstin Hartung, Vanessa Haverd, Richard A. Houghton, Tatiana Ilyina, Atul K. Jain, Emilie Joetzjer, Koji Kadono, Etsushi Kato, Vassilis Kitidis, Jan Ivar Korsbakken, Peter Landschützer, Nathalie Lefèvre, Andrew Lenton, Sebastian Lienert, Zhu Liu, Danica Lombardozzi, Gregg Marland, Nicolas Metzl, David R. Munro, Julia E. M. S. Nabel, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin O'Brien, Tsuneo Ono, Paul I. Palmer, Denis Pierrot, Benjamin Poulter, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Jörg Schwinger, Roland Séférian, Ingunn Skjelvan, Adam J. P. Smith, Adrienne J. Sutton, Toste Tanhua, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Guido van der Werf, Nicolas Vuichard, Anthony P. Walker, Rik Wanninkhof, Andrew J. Watson, David Willis, Andrew J. Wiltshire, Wenping Yuan, Xu Yue, and Sönke Zaehle
Earth Syst. Sci. Data, 12, 3269–3340, https://doi.org/10.5194/essd-12-3269-2020, https://doi.org/10.5194/essd-12-3269-2020, 2020
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The Global Carbon Budget 2020 describes the data sets and methodology used to quantify the emissions of carbon dioxide and their partitioning among the atmosphere, land, and ocean. These living data are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Virginie Moreaux, Simon Martel, Alexandre Bosc, Delphine Picart, David Achat, Christophe Moisy, Raphael Aussenac, Christophe Chipeaux, Jean-Marc Bonnefond, Soisick Figuères, Pierre Trichet, Rémi Vezy, Vincent Badeau, Bernard Longdoz, André Granier, Olivier Roupsard, Manuel Nicolas, Kim Pilegaard, Giorgio Matteucci, Claudy Jolivet, Andrew T. Black, Olivier Picard, and Denis Loustau
Geosci. Model Dev., 13, 5973–6009, https://doi.org/10.5194/gmd-13-5973-2020, https://doi.org/10.5194/gmd-13-5973-2020, 2020
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The model GO+ describes the functioning of managed forests based upon biophysical and biogeochemical processes. It accounts for the impacts of forest operations on energy, water and carbon exchanges within the soil–vegetation–atmosphere continuum. It includes versatile descriptions of management operations. Its sensitivity and uncertainty are detailed and predictions are compared with observations about mass and energy exchanges, hydrological data, and tree growth variables from different sites.
Yuan Zhang, Ana Bastos, Fabienne Maignan, Daniel Goll, Olivier Boucher, Laurent Li, Alessandro Cescatti, Nicolas Vuichard, Xiuzhi Chen, Christof Ammann, M. Altaf Arain, T. Andrew Black, Bogdan Chojnicki, Tomomichi Kato, Ivan Mammarella, Leonardo Montagnani, Olivier Roupsard, Maria J. Sanz, Lukas Siebicke, Marek Urbaniak, Francesco Primo Vaccari, Georg Wohlfahrt, Will Woodgate, and Philippe Ciais
Geosci. Model Dev., 13, 5401–5423, https://doi.org/10.5194/gmd-13-5401-2020, https://doi.org/10.5194/gmd-13-5401-2020, 2020
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We improved the ORCHIDEE LSM by distinguishing diffuse and direct light in canopy and evaluated the new model with observations from 159 sites. Compared with the old model, the new model has better sunny GPP and reproduced the diffuse light fertilization effect observed at flux sites. Our simulations also indicate different mechanisms causing the observed GPP enhancement under cloudy conditions at different times. The new model has the potential to study large-scale impacts of aerosol changes.
Petra Lasch-Born, Felicitas Suckow, Christopher P. O. Reyer, Martin Gutsch, Chris Kollas, Franz-Werner Badeck, Harald K. M. Bugmann, Rüdiger Grote, Cornelia Fürstenau, Marcus Lindner, and Jörg Schaber
Geosci. Model Dev., 13, 5311–5343, https://doi.org/10.5194/gmd-13-5311-2020, https://doi.org/10.5194/gmd-13-5311-2020, 2020
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The process-based model 4C has been developed to study climate impacts on forests and is now freely available as an open-source tool. This paper provides a comprehensive description of the 4C version (v2.2) for scientific users of the model and presents an evaluation of 4C. The evaluation focused on forest growth, carbon water, and heat fluxes. We conclude that 4C is widely applicable, reliable, and ready to be released to the scientific community to use and further develop the model.
Marco Cucchi, Graham P. Weedon, Alessandro Amici, Nicolas Bellouin, Stefan Lange, Hannes Müller Schmied, Hans Hersbach, and Carlo Buontempo
Earth Syst. Sci. Data, 12, 2097–2120, https://doi.org/10.5194/essd-12-2097-2020, https://doi.org/10.5194/essd-12-2097-2020, 2020
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WFDE5 is a novel meteorological forcing dataset for running land surface and global hydrological models. It has been generated using the WATCH Forcing Data methodology applied to surface meteorological variables from the ERA5 reanalysis. It is publicly available, along with its source code, through the C3S Climate Data Store at ECMWF. Results of the evaluations described in the paper highlight the benefits of using WFDE5 compared to both ERA5 and its predecessor WFDEI.
Tom Gleeson, Thorsten Wagener, Petra Döll, Samuel C. Zipper, Charles West, Yoshihide Wada, Richard Taylor, Bridget Scanlon, Rafael Rosolem, Shams Rahman, Nurudeen Oshinlaja, Reed Maxwell, Min-Hui Lo, Hyungjun Kim, Mary Hill, Andreas Hartmann, Graham Fogg, James S. Famiglietti, Agnès Ducharne, Inge de Graaf, Mark Cuthbert, Laura Condon, Etienne Bresciani, and Marc F. P. Bierkens
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2020-378, https://doi.org/10.5194/hess-2020-378, 2020
Revised manuscript not accepted
Cited articles
Babst, F., Bouriaud, O., Papale, P., Gielen, B., Janssens, IA., Nikinmaa,
E., Ibrom, A., Wu, J., Bernhofer, C., Köstner, B., Grünwald, T.,
Seufert, G., Ciais, P., and Frank, D.: Above-ground woody carbon
sequestration measured from tree rings is coherent with net ecosystem
productivity at five eddy-covariance sites, New Phytologist, 201,
1289–1303, https://doi.org/10.1111/nph.12589, 2014
Bagnara, M., Silveyra Gonzalez, R., Reifenberg, S., Steinkamp, J., Hickler,
T., Werner, C., Dormann, C. F., and Hartig, F.: An R package facilitating
sensitivity analysis, calibration and forward simulations with the LPJ-GUESS
dynamic vegetation model, Environ. Model. Softw., 111,
55–60, https://doi.org/10.1016/j.envsoft.2018.09.004, 2019
Banos, V., Deuffic, P., Hautdidier, B., and Sergent, A.: A forward-looking
approach to foster integrated forest development, A case study in the
forests of the landes de gascogne, Rev. For. Française, 68, 231–243,
https://doi.org/10.4267/2042/62005, 2016.
Barr, A. G., Richardson, A., Hollinger, D., Papale, D., Arain, M. A., Black,
T. A., Bohrer, G., Dragoni, D., Fischer, M. L., Gu, L., Law, B., Margolis,
H., McCaughey, H., Munger, J., Oechel, W., and Schaeffer, K.: Use of
change-point detection for friction-velocity threshold evaluation in
eddy-covariance studies, Agr. For. Meteorol., 171, 31–45, https://doi.org/10.1016/j.agrformet.2012.11.023, 2013.
Berbigier, P., Bonnefond, J. M., and Mellmann, P.: CO2 and water vapour
fluxes for 2 years above Euroflux forest site, Agr. For. Meteorol.,
108, 183–197, https://doi.org/10.1016/S0168-1923(01)00240-4, 2001.
Bolte, A., Lambertz, B., Steinmeyer, A., Kallweit, R., and Meesenburg, H.:
Zur Funktion der Bodenvegetation im Stoffhaushalt von Wäldern – Studien
auf Dauerbeobachtungsflächen des EU Level II-Programms in
Norddeutschland, Forstarchiv, 75, 207–220, 2004.
Bonten, L. T. C., Groenenberg, J. E., Meesenburg, H., and de Vries, W.: Using
advanced surface complexation models for modelling soil chemistry under
forests: Solling forest, Germany, Environ. Pollut., 159, 2831–2839,
https://doi.org/10.1016/j.envpol.2011.05.002, 2011.
Bosc, A., de Grandcourt, A., and Loustau, D.: Variability of stem and branch
maintenance respiration in a Pinus pinaster tree, Tree Physiol., 23,
227–236, https://doi.org/10.1093/treephys/23.4.227, 2003.
Brus, D., Hengeveld, G., Walvoort, D. J. J., Goedhart, P. W., Heidema, A.
H., Nabuurs, G.-J., and Gunia, K.: Statistical mapping of tree species over
Europe, Eur. J. For. Res., 131, 145–157, https://doi.org/10.1007/s10342-011-0513-5,
2012.
Bugmann, H. M., Yan, X., Sykes, M., Martin, P., Lindner, M., Desanker, P.,
and Cumming, S.: A comparison of forest gap models: Model structure and
behaviour, Clim. Change, 34, 289–313, https://doi.org/10.1007/BF00224640, 1996.
Cescatti, A. and Piutti, E.: Silvicultural alternatives, competition regime
and sensitivity to climate in a European beech forest, For. Ecol. Manage.,
102, 213–223, https://doi.org/10.1016/S0378-1127(97)00163-1, 1998.
Chang, J., Ciais, P., Wang, X., Piao, S., Asrar, G., Betts, R., Chevallier,
F., Dury, M., François, L., Frieler, K., and Steinkamp, J.: Benchmarking
carbon fluxes of the ISIMIP2a biome models, Environ. Res. Lett., 12, 45002,
https://doi.org/10.1088/1748-9326/aa63fa, 2017.
Chiti, T., Papale, D., Smith, P., Dalmonech, D., Matteucci, G., Yeluripati,
J., Rodeghiero, M., and Valentini, R.: Predicting changes in soil organic
carbon in mediterranean and alpine forests during the Kyoto Protocol
commitment periods using the CENTURY model, Soil Use Manag., 26,
475–484, https://doi.org/10.1111/j.1475-2743.2010.00300.x, 2010.
Collalti, A., Marconi, S., Ibrom, A., Trotta, C., Anav, A., D'Andrea, E., Matteucci, G., Montagnani, L., Gielen, B., Mammarella, I., Grünwald, T., Knohl, A., Berninger, F., Zhao, Y., Valentini, R., and Santini, M.: Validation of 3D-CMCC Forest Ecosystem Model (v.5.1) against eddy covariance data for 10 European forest sites, Geosci. Model Dev., 9, 479–504, https://doi.org/10.5194/gmd-9-479-2016, 2016.
Collalti, A., Trotta, C., Keenan, T., Ibrom, A., Bond-Lamberty, B., Grote,
R., Vicca, S., Reyer, C.P.O., Migliavacca, M., Veroustraete, F., Anav, A.,
Campioli, M., Scoccimarro, E., Šigut, L., Grieco, E., Cescatti, A., and
Matteucci G.: Thinning can reduce losses in carbon use efficiency and carbon
stocks in managed forests under warmer climate, J. Adv. Model. Earth Sy., 10, 2427–2452,
https://doi.org/10.1029/2018MS001275, 2018.
Collalti, A., Thornton, P. E., Cescatti, A., Rita, A., Nolè, A.,
Borghetti, M., Trotta, C., Ciais, P., and Matteucci, G.: The sensitivity of the
forest carbon budget shifts between different parameters and processes along
stand development and climate change, Ecol. Appl., 29, 1–18,
https://doi.org/10.1002/eap.1837, 2019.
Collier, N., Hoffman,F.M., Lawrence, D. M., Keppel-Aleks, G., Koven, C. D.,
Riley, W. J., Mu, M., and Randerson, J. T.: The International Land Model
Benchmarking (ILAMB) system: Design, theory, and implementation, J. Adv.
Model. Earth Sy., 10, 2731–2754, https://doi.org/10.1029/2018MS001354, 2018.
Cramer, W., Kicklighter, D. W., Bondeau, A., Iii, B. M., Churkina, G.,
Nemry, B., Ruimy, A., Schloss, A. L., and the participants of the Potsdam NPP
Model Intercomparison: Comparing global models of terrestrial net primary
productivity (NPP): overview and key results, Glob. Chang. Biol., 5,
1–15, https://doi.org/10.1046/j.1365-2486.1999.00009.x, 1999.
Cramer, W., Bondeau, A., Woodward, F. I., Prentice, I. C., Betts, R. A.,
Brovkin, V., Cox, P. M., Fisher, V., Foley, J. A., Friend, A. D., Kucharik,
C., Lomas, M. R., Ramankutty, N., Sitch, S., Smith, B., White, A., and
Young-Molling, C.: Global response of terrestrial ecosystem structure and
function to CO2 and climate change: Results from six dynamic global
vegetation models, Glob. Chang. Biol., 7, 357–373,
https://doi.org/10.1046/j.1365-2486.2001.00383.x, 2001.
D'Andrea, E., Rezaie, N., Battistelli, A., Gravichkova, O., Kuhlmann, I.,
Matteucci, G., Moscatello, S., Proietti, S., Scartazza, A., Trumbore, S., and Muhr, J.: Winter's bite: Beech trees survive complete defoliation due to spring
late frost damage by mobilizing old C reserves, New Phyt., 224, 625–631, 2019.
De Lary, R.: Massif des Landes de Gascogne, II – ETAT DES CONNAISSANCES
Tech. Bordeaux: CRPF Aquitaine, 2015.
Didan, K., Munoz, A. B., Solano, R., and Huete, A.: MODIS Vegetation Index
User's Guide (MOD13 Series), available at:
https://vip.arizona.edu/documents/MODIS/MODIS_VI_UsersGuide_June_2015_C6.pdf (last access: 5 June 2020), 2015.
Dietze, M. C.: Prediction in ecology: a first-principles framework, Ecol.
Appl., 27, 2048–2060, https://doi.org/10.1002/eap.1589, 2017.
Dietze, M. C., Lebauer, D. S., and Kooper, R.: On improving the communication
between models and data, Plant, Cell Environ., 36, 1575–1585,
https://doi.org/10.1111/pce.12043, 2013.
Dlugokencky, E. and Tans, P.: Trends in Atmospheric Carbon Dioxide, Natl.
Ocean. Atmos. Adm. Earth Syst. Res. Lab., available at:
https://www.esrl.noaa.gov/gmd/ccgg/trends/ (last access: 5 June 2020), 2014.
Duncker, P. S., Barreiro, S. M., Hengeveld, G. M., Lind, T., Mason, W. L.,
and Ambrozy, S.: Classification of Forest Management Approaches?: A New
Conceptual Framework and Its Applicability to European Forestry, Ecol. Soc.,
17, 51, https://doi.org/10.5751/ES-05262-170451, 2012.
Eastaugh, C., Pötzelsberger, E., and Hasenauer, H.: Assessing the impacts
of climate change and nitrogen deposition on Norway spruce (Picea abies L.
Karst) growth in Austria with BIOME-BGC, Tree Physiol., 31, 262–274,
https://doi.org/10.1093/treephys/tpr033, 2011.
EMEP/CEIP: Present state Emissision data, available at:
http://www.ceip.at/webdab_emepdatabase/reported_emissiondata/ (last access: 5 June 2020), 2014a.
EMEP/CEIP: Present state Emissision data, available at:
http://www.ceip.at/status_reporting/2014_submissions/ (last access: 5 June 2020), 2014b.
Feoli, E. and Lagonegro, M.: Syntaxonomical analysis of beech woods in the
Apennines (Italy) using the program package IAHOPA, Plant Ecol., 50,
129–173, 1982.
Fleck, S., Cools, N., De Vos, B., Meesenburg, H., and Fischer, R.: The Level
II aggregated forest soil condition database links soil physicochemical and
hydraulic properties with long-term observations of forest condition in
Europe, Ann. For. Sci., 73, 945–957, https://doi.org/10.1007/s13595-016-0571-4,
2016.
FLUXNET 2015: FLUXNET2015 Release – Processing Pipeline document –
Last revision 20170512, available at:
http://fluxnet.fluxdata.org/data/fluxnet2015-dataset/data-processing/ (last access: 5 June 2020), 2017.
Fontes, L., Bontemps, J. D., Bugmann, H., Oijen, M. V., Gracia, C., Kramer,
K., Lindner, M., Rötzer, T., and Skovsgaard, J. P.: Models for supporting
forest management in a changing environment, For. Syst., 3, 8–29,
https://doi.org/10.5424/fs/201019S-9315, 2010.
Frieler, K., Lange, S., Piontek, F., Reyer, C. P. O., Schewe, J., Warszawski, L., Zhao, F., Chini, L., Denvil, S., Emanuel, K., Geiger, T., Halladay, K., Hurtt, G., Mengel, M., Murakami, D., Ostberg, S., Popp, A., Riva, R., Stevanovic, M., Suzuki, T., Volkholz, J., Burke, E., Ciais, P., Ebi, K., Eddy, T. D., Elliott, J., Galbraith, E., Gosling, S. N., Hattermann, F., Hickler, T., Hinkel, J., Hof, C., Huber, V., Jägermeyr, J., Krysanova, V., Marcé, R., Müller Schmied, H., Mouratiadou, I., Pierson, D., Tittensor, D. P., Vautard, R., van Vliet, M., Biber, M. F., Betts, R. A., Bodirsky, B. L., Deryng, D., Frolking, S., Jones, C. D., Lotze, H. K., Lotze-Campen, H., Sahajpal, R., Thonicke, K., Tian, H., and Yamagata, Y.: Assessing the impacts of 1.5 ∘C global warming – simulation protocol of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP2b), Geosci. Model Dev., 10, 4321–4345, https://doi.org/10.5194/gmd-10-4321-2017, 2017.
Fürstenau, C., Badeck, F. W., Lasch, P., Lexer, M. J., Lindner, M.,
Mohr, P., and Suckow, F.: Multiple-use forest management in consideration of
climate change and the interests of stakeholder groups, Eur. J. For. Res.,
126, 225–239, https://doi.org/10.1007/s10342-006-0114-x, 2007.
Gerstengarbe, F., Hoffmann, P., Österle, H., and Werner, C.: Ensemble
simulations for the RCP8.5-Scenario, Meteorol. Z., 24, 147–156,
https://doi.org/10.1127/metz/2014/0523, 2015.
González, J. R., Pukkala, T., and Palahí, M.: Optimising the
management of Pinus sylvestris L. stand under risk of fire in Catalonia
(north-east of Spain), Ann. For. Sci. Springer Verlag/EDP Sci., 62,
493–501, 2005.
Grimm, V. and Railsback, S. F.: Pattern-oriented modelling: a “multi-scope”
for predictive systems ecology, Philos. T. Roy. Soc. B, 367, 298–310, https://doi.org/10.1098/rstb.2011.0180, 2012.
Gutsch, M., Lasch, P., Suckow, F., and Reyer, C.: Management of mixed
oak-pine forests under climate scenario uncertainty, For. Syst., 20,
453–463, https://doi.org/10.5424/fs/20112003-11073, 2011.
Haataja, J. and Vesala, T.: SMEAR II. Station for Measuring Forest
Ecosystem–Atmosphere Relation, Univ. Helsinki Dep. For. Ecol. Publ., Vol. 17,
1997.
Hanewinkel, M. and Pretzsch, H.: Modelling the conversion from even-aged to
uneven-aged stands of Norway spruce (Picea abies L. Karst.) with a
distance-dependent growth simulator, For. Ecol. Manage., 134, 55–70,
https://doi.org/10.1016/S0378-1127(99)00245-5, 2000.
Hartig, F., Dyke, J., Hickler, T., Higgins, S. I., O'Hara, R. B., Scheiter,
S., and Huth, A.: Connecting dynamic vegetation models to data – an inverse
perspective, J. Biogeogr., 39, 2240–2252,
https://doi.org/10.1111/j.1365-2699.2012.02745.x, 2012.
Hein, S. and Dhôte, J.-F.: Effect of species composition, stand density
and site index on the basal area increment of oak trees (Quercus sp.) in
mixed stands with beech (Fagus sylvatica L.) in northern France, Ann. For.
Sci., 63, 457–467, https://doi.org/10.1051/forest:2006026, 2006.
Hempel, S., Frieler, K., Warszawski, L., Schewe, J., and Piontek, F.: A trend-preserving bias correction – the ISI-MIP approach, Earth Syst. Dynam., 4, 219–236, https://doi.org/10.5194/esd-4-219-2013, 2013.
Huntzinger, D. N., Schwalm, C., Michalak, A. M., Schaefer, K., King, A. W., Wei, Y., Jacobson, A., Liu, S., Cook, R. B., Post, W. M., Berthier, G., Hayes, D., Huang, M., Ito, A., Lei, H., Lu, C., Mao, J., Peng, C. H., Peng, S., Poulter, B., Riccuito, D., Shi, X., Tian, H., Wang, W., Zeng, N., Zhao, F., and Zhu, Q.: The North American Carbon Program Multi-Scale Synthesis and Terrestrial Model Intercomparison Project – Part 1: Overview and experimental design, Geosci. Model Dev., 6, 2121–2133, https://doi.org/10.5194/gmd-6-2121-2013, 2013.
Ilvesniemi, H., Levula, J., Ojansuu, R., Kolari, P., Kulmala, L., Pumpanen,
J., Launiainen, S., Vesala, T., and Nikinmaa, E.: Long-term measurements of
the carbon balance of a boreal Scots pine dominated forest ecosystem, Boreal
Environ. Res., 14, 731–753, 2009.
Ilvesniemi, H., Pumpanen, J., and Duursma, R.: Water balance of a boreal
Scots pine forest, Boreal Environ. Res., 15, 375–396, 2010.
ISSS-ISRIC-FAO: World Reference Base For Soil Resources World Soil Resource
Reports 84, FAO, Rome, 1998.
Ito, A., Nishina, K., Reyer, C., François, L., Henrot, A.-J., Munhoven,
G., Jacquemin, I., Tian, H., Yang, J., Pan, S., Morfopoulos, C., Betts, R.,
Hickler, T., Steinkamp, J., Ostberg, S., Schaphoff, S., Ciais, P., Chang,
J., Rafique, R., and Zhao, F.: Photosynthetic productivity and its
efficiencies in ISIMIP2a biome models: Benchmarking for impact assessment
studies, Environ. Res. Lett., 12, 85001, https://doi.org/10.1088/1748-9326/aa7a19, 2017.
Kelley, D. I., Prentice, I. C., Harrison, S. P., Wang, H., Simard, M., Fisher, J. B., and Willis, K. O.: A comprehensive benchmarking system for evaluating global vegetation models, Biogeosciences, 10, 3313–3340, https://doi.org/10.5194/bg-10-3313-2013, 2013.
Kerr, G.: The effect of heavy or “free growth” thinning on oak (Quercus
petraea and Q-robur), Forestry, 69, 303–317,
https://doi.org/10.1093/forestry/69.4.303, 1996.
Khanna, S., Palacios-Orueta, A., Whiting, M., Ustin, S., Riaño, D., and
Litago, J.: Development of Angle Indexes for Soil Moisture Estimation, Dry
Matter Detection and Land-cover Discrimination, Remote Sens. Environ., 109,
154–165, https://doi.org/10.1016/j.rse.2006.12.018, 2007.
Kratochvilova, I., Janous, D., Marek, M., Bartak, M., and Riha, L.:
Production activity of mountain cultivated Norway spruce stands under the
impact of air pollution. I. General description of problems, Ekológia
(CSSR), 8, 407–419, 1989.
Ladekarl, U. L.: Soil moisture, evapotranspiration and groundwater recharge
in forest and heathland, University of Aarhus, Denmark, 2001.
Lähde, E., Laiho, O., and Lin, C. J.: Silvicultural alternatives in an
uneven-sized forest dominated by Picea abies, J. For. Res., 15, 14–20,
https://doi.org/10.1007/s10310-009-0154-4, 2010.
Lamarque, J.-F., Dentener, F., McConnell, J., Ro, C.-U., Shaw, M., Vet, R., Bergmann, D., Cameron-Smith, P., Dalsoren, S., Doherty, R., Faluvegi, G., Ghan, S. J., Josse, B., Lee, Y. H., MacKenzie, I. A., Plummer, D., Shindell, D. T., Skeie, R. B., Stevenson, D. S., Strode, S., Zeng, G., Curran, M., Dahl-Jensen, D., Das, S., Fritzsche, D., and Nolan, M.: Multi-model mean nitrogen and sulfur deposition from the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP): evaluation of historical and projected future changes, Atmos. Chem. Phys., 13, 7997–8018, https://doi.org/10.5194/acp-13-7997-2013, 2013a.
Lamarque, J.-F., Shindell, D. T., Josse, B., Young, P. J., Cionni, I., Eyring, V., Bergmann, D., Cameron-Smith, P., Collins, W. J., Doherty, R., Dalsoren, S., Faluvegi, G., Folberth, G., Ghan, S. J., Horowitz, L. W., Lee, Y. H., MacKenzie, I. A., Nagashima, T., Naik, V., Plummer, D., Righi, M., Rumbold, S. T., Schulz, M., Skeie, R. B., Stevenson, D. S., Strode, S., Sudo, K., Szopa, S., Voulgarakis, A., and Zeng, G.: The Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP): overview and description of models, simulations and climate diagnostics, Geosci. Model Dev., 6, 179–206, https://doi.org/10.5194/gmd-6-179-2013, 2013b.
Lange, S.: Bias correction of surface downwelling longwave and shortwave radiation for the EWEMBI dataset, Earth Syst. Dynam., 9, 627–645, https://doi.org/10.5194/esd-9-627-2018, 2018.
Lasch, P., Badeck, F. W., Suckow, F., Lindner, M., and Mohr, P.: Model-based
analysis of management alternatives at stand and regional level in
Brandenburg (Germany), For. Ecol. Manage., 207, 59–74,
https://doi.org/10.1016/j.foreco.2004.10.034, 2005.
Lasslop, G., Reichstein, M., Papale, D., Richardson, A., Arneth, A., Barr,
A., Stoy, P., and Wohlfahrt, G.: Separation of net ecosystem exchange into
assimilation and respiration using a light response curve approach: critical
issues and global evaluation, Glob. Change Biol., 16, 187–208, https://doi.org/10.1111/j.1365-2486.2009.02041.x, 2010.
Lasslop, G., Migliavacca, M., Bohrer, G., Reichstein, M., Bahn, M., Ibrom, A., Jacobs, C., Kolari, P., Papale, D., Vesala, T., Wohlfahrt, G., and Cescatti, A.: On the choice of the driving temperature for eddy-covariance carbon dioxide flux partitioning, Biogeosciences, 9, 5243–5259, https://doi.org/10.5194/bg-9-5243-2012, 2012.
Le Mellec, A., Meesenburg, H., and Michalzik, B.: The importance of
canopy-derived dissolved and particulate organic matter (DOM and POM) –
comparing throughfall solution from broadleaved and coniferous forests, Ann.
For. Sci., 67, 411, https://doi.org/10.1051/forest/2009130, 2010.
Lindner, M., Fitzgerald, J. B., Zimmermann, N. E., Reyer, C., Delzon, S.,
van der Maaten, E., Schelhaas, M. J., Lasch, P., Eggers, J., van der
Maaten-Theunissen, M., Suckow, F., Psomas, A., Poulter, B., and Hanewinkel,
M.: Climate change and European forests: What do we know, what are the
uncertainties, and what are the implications for forest management?, J.
Environ. Manage., 146, 69–83, https://doi.org/10.1016/j.jenvman.2014.07.030, 2014.
Loustau, D., Bosc, A., Colin, A., Ogée, J., Davi, H., François, C.,
Dufrêne, E., Déqué, M., Cloppet, E., Arrouays, D., Le Bas, C.,
Saby, N., Pignard, G., Hamza, N., Granier, A., Bréda, N., Ciais, P.,
Viovy, N., Delage, F., and Bas, C. L. E.: Modeling climate change effects on
the potential production of French plains forests at the sub-regional
level., Tree Physiol., 25, 813–23, https://doi.org/10.1093/treephys/25.7.813, 2005.
Mammarella, I., Launiainen, S., Gronholm, T., Keronen, P., Pumpanen, J.,
Rannik, Ü., and Vesala, T.: Relative humidity effect on the
high-frequency attenuation of water vapor flux measured by a closed-path
eddy covariance system, J. Atmos. Ocean. Tech., 26, 1856–1866,
https://doi.org/10.1175/2009JTECHA1179.1, 2009.
Marchetto, A., Rogora, M., Waldner, P., Thimonier, A., Hansen, K., Karlsson,
G. P., Simpson,D., Fagerli, H., Sanders, T. G. M., Schmitz, A., and de Vries, W.: How close are model estimates and field measurements of sulphur and
nitrogen deposition to the European forests?, in preparation, 2020.
Matyssek, R., Schnyder, H., Oßwald, W., Ernst, D., Munch, J., and
Pretzsch, H.: Growth and Defence in Plants Resource Allocation at Multiple
Scales, Ecological, Springer, https://doi.org/10.1007/978-3-642-30645-7,
2012.
Meesenburg, H., Brumme, R., Jacobsen, C., Meiwes, K. J., and Eichhorn, J.:
Soil properties, in: Functioning and Management of European Beech Ecosystems,
edited by: Brumme, R. and Khanna, P. K., Ecol. Studies, Springer, Berlin, Germany, 208, 49–63, 2009.
Meesenburg, H., Ahrends, B., Fleck, S., Wagner, M., Fortmann, H., Scheler,
B., Klinck, U., Dammann, I., Eichhorn, J., Mindrup, M., and Meiwes, K. J.:
Long-term changes of ecosystem services at Solling, Germany: Recovery from
acidification, but increasing nitrogen saturation?, Ecol. Indic., 65,
103–112, https://doi.org/10.1016/j.ecolind.2015.12.013, 2016.
Meinshausen, M., Smith, S. J., Calvin, K., Daniel, J. S., Kainuma, M. L. T.,
Lamarque, J.-F., Matsumoto, K., Montzka, S. A., Raper, S. C. B., Riahi, K.,
Thomson, A., Velders, G. J. M., and van Vuuren, D. P. P.: The RCP greenhouse
gas concentrations and their extensions from 1765 to 2300, Clim. Change,
109, 213, https://doi.org/10.1007/s10584-011-0156-z, 2011.
Meiwes, K. J., Meesenburg, H., Eichhorn, J., Jacobsen, C., and Khanna, P. K.:
Changes in C and N contents of soil under beech forests over a period of 35
years, Functioning and Management of European Beech Ecosystems, edited by:
Brumme, R. and Khanna, P. K., Ecol. Studies, Springer, Berlin, Germany, 208, 49–63,
2009.
Meteorological Yearbook 2012: experimentální ekologické
pracoviště Bílý Kříž (Moravskoslezské
Beskydy), Ekosystémová stanice Štítná nad
Vláří (Bíle Karpaty), Ekosystémová stanice
Rájec (Drahanská vrchovina), Brno: Centrum výzkumu
globální změny AV ČR, 2015.
Monteith, J. L.: Solar Radiation and Productivity in Tropical Ecosystems, J.
Appl. Ecol., 9, 747–766, https://doi.org/10.2307/2401901, 1972.
Morales, P., Sykes, M. T., Prentice, I. C., Smith, P., Smith, B., Bugmann,
H., Zierl, B., Friedlingstein, P., Viovy, N., Sabaté, S., Sánchez,
A., Pla, E., Gracia, C. A., Sitch, S., Arneth, A., and Ogee, J.: Comparing
and evaluating process-based ecosystem model predictions of carbon and water
fluxes in major European forest biomes, Glob. Chang. Biol., 11,
2211–2233, https://doi.org/10.1111/j.1365-2486.2005.01036.x, 2005.
Mund, M.: Carbon pools of European beech forests (Fagus sylvatica) under
different silvicultural management, Georg-August-Universität
Göttingen, 2004.
Myneni, R.: MODIS Collection 6 (C6) LAI/FPAR Product User's Guide, available at:
https://lpdaac.usgs.gov/documents/2/mod15_user_guide.pdf (last access: 5 June 2020), 2015.
Noack, M.: Forstliche Langfristforschung für den Zukunftswald – welche
Entwicklung vollzogen WIEDEMANN's schlechteste
Kiefernbestände Ostdeutschlands, 2011.
Noack, M.: Der langfristige Durchforstungsversuch “PEITZ 150”:
Forschungsbeitrag zum Wachstum der Gemeinen Kiefer auf
nährkraftschwachen Böden im Land Brandenburg unter dem Einfluss von
Standortswandel und Durchforstung, Eberswalder Forstl. Schriftenr., 49,
56–72, 2012.
ORNL DAAC: MODIS Collection 5 Land Products Global Subsetting and
Visualization Tool, ORNL DAAC, Oak Ridge, Tennessee, USA, Subset obtained for MOD09A1 product at various sites in Spatial Range:
N = 70.00N, S = 35.00N, E = 50.00E, W = 10.00W, time period: 2000-02-18 to
2015-12-27, and subset size: 0.5 × 0.5 km,
https://doi.org/10.3334/ORNLDAAC/1241, 2008a.
ORNL DAAC: MODIS Collection 5 Land Products Global Subsetting and
Visualization Tool, ORNL DAAC, Oak Ridge, Tennessee, USA, Subset obtained for MOD11A2 product at various sites in Spatial Range:
N = 70.00N, S = 35.00N, E = 50.00E, W = 10.00W, time period: 2000-03-05 to 2015-12-27, and subset size: 1 × 1 km,
https://doi.org/10.3334/ORNLDAAC/1241, 2008b.
ORNL DAAC: MODIS Collection 5 Land Products Global Subsetting and
Visualization Tool, ORNL DAAC, Oak Ridge, Tennessee, USA, Subset obtained for MOD13Q1 product at various sites in Spatial Range:
N = 70.00N, S = 35.00N, E = 50.00E, W = 10.00W, time period: 2000-02-18 to
2015-12-19, and subset size: 0.25 × 0.25 km,
https://doi.org/10.3334/ORNLDAAC/1241, 2008c.
ORNL DAAC: MODIS Collection 5 Land Products Global Subsetting and
Visualization Tool, ORNL DAAC, Oak Ridge, Tennessee, USA, Subset obtained for MOD15A2 product at various sites in Spatial Range:
N = 70.00N, S = 35.00N, E = 50.00E, W = 10.00W, time period: 2000-02-18 to
2015-12-27, and subset size: 1 × 1 km,
https://doi.org/10.3334/ORNLDAAC/1241, 2008d.
ORNL DAAC: MODIS Collection 5 Land Products Global Subsetting and
Visualization Tool, ORNL DAAC, Oak Ridge, Tennessee, USA, Subset obtained for MOD17A2 product at various sites in Spatial Range:
N = 70.00N, S = 35.00N, E = 50.00E, W = 10.00W, time period: 2000-01-01 to
2014-12-27, and subset size: 1 × 1 km,
https://doi.org/10.3334/ORNLDAAC/1241, 2008e.
Palacios-Orueta, A., Khanna, S., Litago, J., Whiting, M., and Ustin, S.:
Assessment of NDVI and NDWI spectral indices using MODIS time series
analysis and development of a new spectral index based on MODIS shortwave
infrared bands, in: 1st International Conference on Remote sensing and
geoinformation processing in the assessment and monitoring of land
degradation and desertification, Trier, 7–9 September, 2005.
Palacios-Orueta, A., Huesca, M., Whiting, M., Litago, J., Khanna, S.,
Garcia, M., and Ustin, S.: Derivation of phenological metrics by function
fitting to time-series of Spectral Shape Indexes AS1 and AS2: Mapping cotton
phenological stages using MODIS time series, Remote Sens. Environ., 126,
148–159, https://doi.org/10.1016/j.rse.2012.08.002, 2012.
Panferov, O., Kreilein, H., Meesenburg, H., Eichhorn, J., and Gravenhorst,
G.: Climatic condition at the three beech forest sites in Central Germany, in: Functioning and Management of European Beech Ecosystems, edited by:
Brumme, R. and Khanna, P. K., Ecol. Studies, 208, 13–32, https://doi.org/10.1007/b82392_3, 2009.
Papale, D., Reichstein, M., Aubinet, M., Canfora, E., Bernhofer, C., Kutsch, W., Longdoz, B., Rambal, S., Valentini, R., Vesala, T., and Yakir, D.: Towards a standardized processing of Net Ecosystem Exchange measured with eddy covariance technique: algorithms and uncertainty estimation, Biogeosciences, 3, 571–583, https://doi.org/10.5194/bg-3-571-2006, 2006.
Pape, R.: Influence of Thinning and Tree Diameter Class on the Development
of Basic Density and Annual Ring Width in Picea abies, Scand. J. For. Res.,
14, 27–37, https://doi.org/10.1080/02827589950152269, 1999.
Pilegaard, K., Mikkelsen, T. N., Beier, C., Jensen, N. O., Ambus, P., and
Ro-Poulsen, H.: Field measurements of atmosphere – biosphere interactions
in a Danish beech forest, Boreal Environ. Res., 8, 315–333
available at: http://www.borenv.net/BER/pdfs/ber8/ber8-315.pdf (last access: 5 June 2020),
2003.
Pilegaard, K., Ibrom, A., Courtney, M. S., Hummelshøj, P., and Jensen, N.
O.: Increasing net CO2 uptake by a Danish beech forest during the period
from 1996 to 2009, Agr. For. Meteorol., 151, 934–946,
https://doi.org/10.1016/j.agrformet.2011.02.013, 2011.
Porté, A. and Loustau, D.: Variability of the photosynthetic
characteristics of mature needles within the crown of a 25-year-old Pinus
pinaster, Tree Physiol., 18, 223–232,
https://doi.org/10.1093/treephys/18.4.223, 1998.
Pretzsch, H., Kahn, M., and Grote, R.: The mixed spruce-beech forest stands
of the “Sonderforschungsbereich” “Growth or Parasite Defence?” in the
forest district Kranzberger Forst, Forstwissenschaftliches Cent. Ver.
Tharandter Forstl. Jahrb., 117, 241–257, https://doi.org/10.1007/bf02832979, 1998.
Pretzsch, H., Rötzer, T., Matyssek, R., Grams, T. E. E., Häberle, K.
H., Pritsch, K., Kerner, R., and Munch, J. C.: Mixed Norway spruce (Picea
abies [L.] Karst) and European beech (Fagus sylvatica [L.]) stands under
drought: from reaction pattern to mechanism, Trees – Struct. Funct., 28,
1305–1321, https://doi.org/10.1007/s00468-014-1035-9, 2014.
Pretzsch, H., Forrester, D., and Rötzer, T.: Representation of species
mixing in forest growth models, A review and perspective, Ecol. Modelling,
313, 276–292, https://doi.org/10.1016/j.ecolmodel.2015.06.044, 2015.
Pukkala, T., Miina, J., Kurttila, M., and Kolstrom, T.: A spatial yield model
for optimizing the thinning regime of mixed stands of Pinus sylvestris and
Picea abies, Scand. J. For. Res., 13, 31–42,
https://doi.org/10.1080/02827589809382959, 1998.
R Core Team: R: A language and environment for statistical computing. R
Foundation for Statistical Computing, Vienna, Austria, available at:
https://www.R-project.org/ (last access: 5 June 2020), 2016.
Rannik, Ü., Keronen, P., Hari, P., and Vesala, T.: Estimation of
forest-atmosphere CO2 exchange by eddy covariance and profile techniques, Agr. For. Meteorol., 126, 141–155,
https://doi.org/10.1016/j.agrformet.2004.06.010, 2004.
Reichstein, M., Falge, E., Baldocchi, D., Papale, D., Aubinet, M.,
Berbigier, P., Bernhofer, C., Buchmann, N., Gilmanov, T., Granier, A.,
Grünwald, T., Havránková, K., Ilvesniemi, H., Janous, D., Knohl,
A., Laurila, T., Lohila, A., Loustau, D., Matteucci, G., and Valentini, R.:
On the Separation of Net Ecosystem Exchange into Assimilation and Ecosystem
Respiration: Review and Improved Algorithm, Glob. Chang. Biol., 11,
1424–1439, https://doi.org/10.1111/j.1365-2486.2005.001002.x, 2005.
Reyer, C. P. O., Silveyra Gonzalez, R., Dolos, K., Hartig, F., Hauf, Y., Noack,
M., Lasch-Born, P., Rötzer, T., Pretzsch, H., Meesenburg, H., Fleck, S.,
Wagner, M., Bolte, A., Sanders, T., Kolari, P., Mäkelä, A., Vesala,
T., Mammarella, I., Pumpanen, J., Matteucci, G., Collalti, A., D'Andrea, E.,
Foltýnová, L., Krejza, J., Ibrom, A., Pilegaard, K., Loustau, D.,
Bonnefond, J.-M., Berbigier, P., Picart, D., Lafont, S., Dietze, M., Cameron,
D., Vieno, M., Tian, H., Palacios, A., Cicuendez, V., Recuero, L., Wieze,
K., Büchner, M., Lange, S., Volkholz, J., Kim, H., Weedon, G. P.,
Sheffield, J., Vega del Valle, I., Suckow, F., Horemans, J., Martel, S.,
Bohn, F., Steinkamp, J., Chikalanov A., and Frieler, K.: The PROFOUND
database for evaluating vegetation models and simulating climate impacts on
forests, V.0.1.12, GFZ Data Services, https://doi.org/10.5880/PIK.2019.008, 2019.
Reyer, C. P. O., Silveyra Gonzalez, R., Dolos, K., Hartig, F., Hauf, Y., Noack,
M., Lasch-Born, P., Rötzer, T., Pretzsch, H., Meesenburg, H., Fleck, S.,
Wagner, M., Bolte, A., Sanders, T., Kolari, P., Mäkelä, A., Vesala,
T., Mammarella, I., Pumpanen, J., Matteucci, G., Collalti, A., D'Andrea, E.,
Foltýnová, L., Krejza, J., Ibrom, A., Pilegaard, K., Loustau, D.,
Bonnefond, J.-M., Berbigier, P., Picart, D., Lafont, S., Dietze, M., Cameron,
D., Vieno, M., Tian, H., Palacios, A., Cicuendez, V., Recuero, L., Wieze,
K., Büchner, M., Lange, S., Volkholz, J., Kim, H., Weedon, G. P.,
Sheffield, J., Babst F., Vega del Valle, I., Suckow, F., Horemans, J.,
Martel, S., Bohn, F., Steinkamp, J., Chikalanov A., Mahnken M., Gutsch M.,
and Frieler, K.: The PROFOUND database for evaluating vegetation models and
simulating climate impacts on forests, V.0.3.0, GFZ Data Services,
https://doi.org/10.5880/PIK.2020.006/, 2020.
Reyer, C.: Forest Productivity under Environmental Change – a Review of
Stand-Scale Modeling Studies, Curr. For. Reports, 53–68,
https://doi.org/10.1007/s40725-015-0009-5, 2015.
Riek, W. and Stähr, F.: Eigenschaften typischer Waldböden im
Nordostdeutschen Tiefland unter besonderer Berücksichtigung des Landes
Brandenburg: Hinweise für die Waldbewirtschaftung, Eberswalder Forstl.
Schriftenr., 19, 180 pp., 2004.
Rötzer, T. and Goergen, K.: Modelling the impact of climate change on
the productivity and water-use efficiency of a central European beech
forest, Clim. Res., 58, 81–95, https://doi.org/10.3354/cr01179, 2013.
Running, S. W. and Zhao, M.: Daily GPP and Annual NPP (MOD17A2/A3) products
NASA Earth Observing System MODIS Land Algorithm – User's guide V3,
available at:
https://www.ntsg.umt.edu/files/modis/MOD17UsersGuide2015_v3.pdf (last access: 5 June 2020), 2015.
Santhana-Vannan, S.-K., Cook, B., Pan, J. Y., and Wilson, B. E.: A SOAP Web
Service for accessing MODIS land product subsets, Earth Sci. Informatics, 4,
97–106, https://doi.org/10.1007/s12145-011-0079-2, 2011.
Schellnhuber, H.: “Earth system” analysis and the second Copernican
revolution, Nature, 402, C19–C23, https://doi.org/10.1038/35011515, 1999.
Schütz, J.-P.: Modelling the demographic sustainability of pure beech
plenter forests in Eastern Germany, Ann. For. Sci., 63, 93–100,
https://doi.org/10.1051/forest:2005101, 2006.
Sheffield, J., Goteti, G., and Wood, E. F.: Development of a 50-year
high-resolution global dataset of meteorological forcings for land surface
modeling, J. Clim., 19, 3088–3111, https://doi.org/10.1175/JCLI3790.1, 2006.
Silveyra Gonzalez, R., Reyer, C. P. O., Bohn, F., Mahnken, M., Hartig, F.:
ProfoundData: Downloading and Exploring Data from the PROFOUND Database,
available at: https://CRAN.R-project.org/package=ProfoundData, last access: 5 June 2020.
Simpson, D., Benedictow, A., Berge, H., Bergström, R., Emberson, L. D., Fagerli, H., Flechard, C. R., Hayman, G. D., Gauss, M., Jonson, J. E., Jenkin, M. E., Nyíri, A., Richter, C., Semeena, V. S., Tsyro, S., Tuovinen, J.-P., Valdebenito, Á., and Wind, P.: The EMEP MSC-W chemical transport model – technical description, Atmos. Chem. Phys., 12, 7825–7865, https://doi.org/10.5194/acp-12-7825-2012, 2012.
Sitch, S., Friedlingstein, P., Gruber, N., Jones, S. D., Murray-Tortarolo, G., Ahlström, A., Doney, S. C., Graven, H., Heinze, C., Huntingford, C., Levis, S., Levy, P. E., Lomas, M., Poulter, B., Viovy, N., Zaehle, S., Zeng, N., Arneth, A., Bonan, G., Bopp, L., Canadell, J. G., Chevallier, F., Ciais, P., Ellis, R., Gloor, M., Peylin, P., Piao, S. L., Le Quéré, C., Smith, B., Zhu, Z., and Myneni, R.: Recent trends and drivers of regional sources and sinks of carbon dioxide, Biogeosciences, 12, 653–679, https://doi.org/10.5194/bg-12-653-2015, 2015.
Štefančík, I.: Growth characteristics of oak (Quercus petraea
[Mattusch.] liebl.) stand under diferent thinning regimes, J. For. Sci., 58,
67–78, 2012.
Sterba, H.: Estimating Potential Density from Thinning Experiments and
Inventory Data, For. Sci., 33, 1022–1034, 1987.
Tiktak, A. and Grinsven, H.: Review of Sixteen Forest-Soil-Atmosphere
Models, Ecol. Model., 83, 35–53, https://doi.org/10.1016/0304-3800(95)00081-6, 1995.
Ulrich, B.: Nutrient and acid-base budget of central European forest
ecosystems, in: Effects of Acid Rain
on Forest Processes, edited by: Godbold, D. L. and Hüttermann, A., Wiley-Liss New York, USA, 1–50, 1994.
Vermote, E. F., Roger, J. C., and Ray, J. P.: MODIS Surface Reflectance
User's Guide, Collection 6, available at:
http://modis-sr.ltdri.org/guide/MOD09_UserGuide_v1.4.pdf (last access: 5 June 2020),
2015.
Vesala, T., Suni, T., Rannik, Ü., Keronen, P., Markkanen, T., Sevanto.,
S., Grönholm, T., Smolander, S., Kulmala, M., Ilvesniemi, H., Ojansuu,
R., Uotila, A., Levula, J., Mäkelä, A., Pumpanen, J., Kolari, P.,
Kulmala, L., Altimir, N., Berninger, F., Nikinmaa, E., and Hari, P.: Effect
of thinning on surface fluxes in a boreal forest, Global Biogeochem. Cy.,
19, 1–11, https://doi.org/10.1029/2004GB002316, 2005.
Warszawski, L., Frieler, K., Huber, V., Piontek, F., Serdeczny, O., and
Schewe, J.: The Inter-Sectoral Impact Model Intercomparison Project
(ISI–MIP): Project framework, P. Natl. Acad. Sci. USA, 111, 3228–3232,
https://doi.org/10.1073/pnas.1312330110, 2014.
Weedon, G. P., Gomes, S., Viterbo, P., Shuttleworth, W. J., Blyth, E.,
Österle, H., Adam, J. C., Bellouin, N., Boucher, O., and Best, M.:
Creation of the WATCH Forcing Data and Its Use to Assess Global and Regional
Reference Crop Evaporation over Land during the Twentieth Century, J.
Hydrometeorol., 12, 823–848, https://doi.org/10.1175/2011JHM1369.1, 2011.
Weedon, G. P., Balsamo, G., Bellouin, N., Gomes, S., Best, M. J., and
Viterbo, P.: The WFDEI meteorological forcing data set: WATCH Forcing Data
methodology applied to ERA-Interim reanalysis data, Water Resour. Res., 50,
7505–7514, https://doi.org/10.1002/2014WR015638, 2014.
Wegehenkel, M., Wagner, A., Tiziana, A., Fleck, S., Meesenburg, H., and
Raspe, S.: Impact of stoniness correction of soil hydraulic parameters on
water balance simulations of forest plots, J. Plant Nutr. Soil Sci., 180,
71–86, https://doi.org/10.1002/jpln.201600244, 2016.
Wu, J., Larsen, K. S., van der Linden, L., Beier, C., Pilegaard, K., and
Ibrom, A.: Synthesis on the carbon budget and cycling in a Danish, temperate
deciduous forest, Agr. For. Meteorol., 181, 94–107,
https://doi.org/10.1016/j.agrformet.2013.07.012, 2013.
Zhu, Z., Piao, S., Myneni, R. B., Huang, M., Zeng, Z., Canadell, J. G., Ciais,
P., Sitch, S., Friedlingstein, P., Arneth, A., Cao, C., Cheng, L., Kato, E.,
Koven, C., Li, Y., Lian, X., Liu, Y., Liu, R., Mao, J., and Zeng, N.:
Greening of the Earth and its drivers, Nat. Clim. Chang., 6, 791–795,
https://doi.org/10.1038/nclimate3004, 2016.
Short summary
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.
Process-based vegetation models are widely used to predict local and global ecosystem dynamics...
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