Articles | Volume 17, issue 6
https://doi.org/10.5194/gmd-17-2299-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-17-2299-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
20 Mar 2024
Development and technical paper |
| 20 Mar 2024
| 20 Mar 2024
Optimising CH4 simulations from the LPJ-GUESS model v4.1 using an adaptive Markov chain Monte Carlo algorithm
Jalisha T. Kallingal
CORRESPONDING AUTHOR
Department of Physical Geography and Ecosystem Science, Lund University, 223 62 Lund, Sweden
Johan Lindström
Centre for Mathematical Sciences, Lund University, 223 62 Lund, Sweden
Paul A. Miller
Department of Physical Geography and Ecosystem Science, Lund University, 223 62 Lund, Sweden
Janne Rinne
Natural Resources Institute Finland, 00790 Helsinki, Finland
Maarit Raivonen
Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, 00014 Helsinki, Finland
Marko Scholze
Department of Physical Geography and Ecosystem Science, Lund University, 223 62 Lund, Sweden
Related authors
Guillaume Monteil, Jalisha Theanutti Kallingal, and Marko Scholze
EGUsphere, https://doi.org/10.5194/egusphere-2024-3122, https://doi.org/10.5194/egusphere-2024-3122, 2024
Short summary
Short summary
Methane is a potent greenhouse gas, emitted both from natural and anthropogenic processes. Large uncertainties remain on its emission budget. Our study compares and combines two approaches to estimate European methane emissions, with a focus on wetlands, based on observed atmospheric CH4 concentrations and in-situ flux measurements. We find a good agreement and complementarity between the approaches, and identify obstacles towards a more integrated data-informed emission estimation system.
Jalisha Theanutti Kallingal, Marko Scholze, Paul Anthony Miller, Johan Lindström, Janne Rinne, Mika Aurela, Patrik Vestin, and Per Weslien
EGUsphere, https://doi.org/10.5194/egusphere-2024-3305, https://doi.org/10.5194/egusphere-2024-3305, 2024
Short summary
Short summary
We explored the possibilities of a Bayesian-based data assimilation algorithm to improve the wetland CH4 flux estimates by a dynamic vegetation model. By assimilating CH4 observations from 14 wetland sites we calibrated model parameters and estimated large-scale annual emissions from northern wetlands. Our findings indicate that this approach leads to more reliable estimates of CH4 dynamics, which will improve our understanding of the climate change feedback from wetland CH4 emissions.
Jalisha Theanutti Kallingal, Marko Scholze, Paul Anthony Miller, Johan Lindström, Janne Rinne, Mika Aurela, Patrik Vestin, and Per Weslien
EGUsphere, https://doi.org/10.5194/egusphere-2024-373, https://doi.org/10.5194/egusphere-2024-373, 2024
Preprint archived
Short summary
Short summary
Our study employs an Adaptive MCMC algorithm (GRaB-AM) to constrain process parameters in the wetlands emission module of the LPJ-GUESS model, using CH4 EC flux observations from 14 diverse wetlands. We aim to derive a single set of parameters capable of representing the diversity of northern wetlands. By reducing uncertainties in model parameters and improving simulation accuracy, our research contributes to more reliable projections of future wetland CH4 emissions and their climate impact.
Nikolina Mileva, Julia Pongratz, Vivek K. Arora, Akihiko Ito, Sebastiaan Luyssaert, Sonali S. McDermid, Paul A. Miller, Daniele Peano, Roland Séférian, Yanwu Zhang, and Wolfgang Buermann
EGUsphere, https://doi.org/10.5194/egusphere-2025-979, https://doi.org/10.5194/egusphere-2025-979, 2025
This preprint is open for discussion and under review for Earth System Dynamics (ESD).
Short summary
Short summary
Despite forests being so important for mitigating climate change, there are still uncertainties about how much the changes in forest cover contribute to the cooling/warming of the climate. Climate models and real-world observations often disagree about the magnitude and even the direction of these changes. We constrain climate models scenarios of widespread deforestation with satellite and in-situ data and show that models still have difficulties representing the movement of heat and water.
Maria K. Tenkanen, Aki Tsuruta, Hugo Denier van der Gon, Lena Höglund-Isaksson, Antti Leppänen, Tiina Markkanen, Ana Maria Roxana Petrescu, Maarit Raivonen, Hermanni Aaltonen, and Tuula Aalto
Atmos. Chem. Phys., 25, 2181–2206, https://doi.org/10.5194/acp-25-2181-2025, https://doi.org/10.5194/acp-25-2181-2025, 2025
Short summary
Short summary
Accurate national methane (CH4) emission estimates are essential for tracking progress towards climate goals. This study compares estimates from Finland, which use different methods and scales, and shows how well a global model estimates emissions within a country. The bottom-up estimates vary a lot, but constraining them with atmospheric CH4 measurements brought the estimates closer together. We also highlight the importance of quantifying natural emissions alongside anthropogenic emissions.
Tuula Aalto, Aki Tsuruta, Jarmo Mäkelä, Jurek Müller, Maria Tenkanen, Eleanor Burke, Sarah Chadburn, Yao Gao, Vilma Mannisenaho, Thomas Kleinen, Hanna Lee, Antti Leppänen, Tiina Markkanen, Stefano Materia, Paul A. Miller, Daniele Peano, Olli Peltola, Benjamin Poulter, Maarit Raivonen, Marielle Saunois, David Wårlind, and Sönke Zaehle
Biogeosciences, 22, 323–340, https://doi.org/10.5194/bg-22-323-2025, https://doi.org/10.5194/bg-22-323-2025, 2025
Short summary
Short summary
Wetland methane responses to temperature and precipitation were studied in a boreal wetland-rich region in northern Europe using ecosystem models, atmospheric inversions, and upscaled flux observations. The ecosystem models differed in their responses to temperature and precipitation and in their seasonality. However, multi-model means, inversions, and upscaled fluxes had similar seasonality, and they suggested co-limitation by temperature and precipitation.
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
Short summary
Short summary
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.
Carlos Gómez-Ortiz, Guillaume Monteil, Sourish Basu, and Marko Scholze
Atmos. Chem. Phys., 25, 397–424, https://doi.org/10.5194/acp-25-397-2025, https://doi.org/10.5194/acp-25-397-2025, 2025
Short summary
Short summary
In this paper, we test new implementations of our inverse modeling tool to estimate the weekly and regional CO2 emissions from fossil fuels in Europe. We use synthetic atmospheric observations of CO2 and radiocarbon (14CO2) to trace emissions to their sources, while separating the natural and fossil CO2. Our tool accurately estimates fossil CO2 emissions in densely monitored regions like western/central Europe. This approach aids in developing strategies for reducing CO2 emissions.
Carlos Gómez-Ortiz, Guillaume Monteil, Ute Karstens, and Marko Scholze
EGUsphere, https://doi.org/10.5194/egusphere-2024-3013, https://doi.org/10.5194/egusphere-2024-3013, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
In 2024, an intensive sampling campaign is being conducted to improve fossil CO₂ emission estimates in Europe using 14C measurements. By testing different strategies for selecting air samples, this study shows that increasing sample frequency and carefully choosing samples based on their fossil fuel and nuclear content leads to more accurate results, reducing the uncertainty and bias of the estimates.
Vilna Tyystjärvi, Tiina Markkanen, Leif Backman, Maarit Raivonen, Antti Leppänen, Xuefei Li, Paavo Ojanen, Kari Minkkinen, Roosa Hautala, Mikko Peltoniemi, Jani Anttila, Raija Laiho, Annalea Lohila, Raisa Mäkipää, and Tuula Aalto
Biogeosciences, 21, 5745–5771, https://doi.org/10.5194/bg-21-5745-2024, https://doi.org/10.5194/bg-21-5745-2024, 2024
Short summary
Short summary
Drainage of boreal peatlands strongly influences soil methane fluxes, with important implications for climatic impacts. Here we simulate methane fluxes in forestry-drained and restored peatlands during the 21st century. We found that restoration turned peatlands into a source of methane, but the magnitude varied regionally. In forests, changes in the water table level influenced methane fluxes, and in general, the sink was weaker under rotational forestry compared to continuous cover forestry.
Guillaume Monteil, Jalisha Theanutti Kallingal, and Marko Scholze
EGUsphere, https://doi.org/10.5194/egusphere-2024-3122, https://doi.org/10.5194/egusphere-2024-3122, 2024
Short summary
Short summary
Methane is a potent greenhouse gas, emitted both from natural and anthropogenic processes. Large uncertainties remain on its emission budget. Our study compares and combines two approaches to estimate European methane emissions, with a focus on wetlands, based on observed atmospheric CH4 concentrations and in-situ flux measurements. We find a good agreement and complementarity between the approaches, and identify obstacles towards a more integrated data-informed emission estimation system.
Ross Charles Petersen, Thomas Holst, Cheng Wu, Radovan Krejci, Jeremy Chan, Claudia Mohr, and Janne Rinne
EGUsphere, https://doi.org/10.5194/egusphere-2024-3410, https://doi.org/10.5194/egusphere-2024-3410, 2024
Short summary
Short summary
Ecosystem-scale emissions of biogenic volatile organic compounds (BVOCs) are important for atmospheric chemistry. Here we investigate boreal BVOC fluxes from a forest in central Sweden. BVOC fluxes were measured above-canopy using proton-transfer-reaction mass spectrometry, while compound-specific monoterpene (MT) fluxes were assessed using a concentration gradient method. We also evaluate the impact of chemical degradation on observed sesquiterpene (SQT) and nighttime MT fluxes.
Jalisha Theanutti Kallingal, Marko Scholze, Paul Anthony Miller, Johan Lindström, Janne Rinne, Mika Aurela, Patrik Vestin, and Per Weslien
EGUsphere, https://doi.org/10.5194/egusphere-2024-3305, https://doi.org/10.5194/egusphere-2024-3305, 2024
Short summary
Short summary
We explored the possibilities of a Bayesian-based data assimilation algorithm to improve the wetland CH4 flux estimates by a dynamic vegetation model. By assimilating CH4 observations from 14 wetland sites we calibrated model parameters and estimated large-scale annual emissions from northern wetlands. Our findings indicate that this approach leads to more reliable estimates of CH4 dynamics, which will improve our understanding of the climate change feedback from wetland CH4 emissions.
Ana Maria Roxana Petrescu, Glen P. Peters, Richard Engelen, Sander Houweling, Dominik Brunner, Aki Tsuruta, Bradley Matthews, Prabir K. Patra, Dmitry Belikov, Rona L. Thompson, Lena Höglund-Isaksson, Wenxin Zhang, Arjo J. Segers, Giuseppe Etiope, Giancarlo Ciotoli, Philippe Peylin, Frédéric Chevallier, Tuula Aalto, Robbie M. Andrew, David Bastviken, Antoine Berchet, Grégoire Broquet, Giulia Conchedda, Stijn N. C. Dellaert, Hugo Denier van der Gon, Johannes Gütschow, Jean-Matthieu Haussaire, Ronny Lauerwald, Tiina Markkanen, Jacob C. A. van Peet, Isabelle Pison, Pierre Regnier, Espen Solum, Marko Scholze, Maria Tenkanen, Francesco N. Tubiello, Guido R. van der Werf, and John R. Worden
Earth Syst. Sci. Data, 16, 4325–4350, https://doi.org/10.5194/essd-16-4325-2024, https://doi.org/10.5194/essd-16-4325-2024, 2024
Short summary
Short summary
This study provides an overview of data availability from observation- and inventory-based CH4 emission estimates. It systematically compares them and provides recommendations for robust comparisons, aiming to steadily engage more parties in using observational methods to complement their UNFCCC submissions. Anticipating improvements in atmospheric modelling and observations, future developments need to resolve knowledge gaps in both approaches and to better quantify remaining uncertainty.
Amali A. Amali, Clemens Schwingshackl, Akihiko Ito, Alina Barbu, Christine Delire, Daniele Peano, David M. Lawrence, David Wårlind, Eddy Robertson, Edouard L. Davin, Elena Shevliakova, Ian N. Harman, Nicolas Vuichard, Paul A. Miller, Peter J. Lawrence, Tilo Ziehn, Tomohiro Hajima, Victor Brovkin, Yanwu Zhang, Vivek K. Arora, and Julia Pongratz
EGUsphere, https://doi.org/10.5194/egusphere-2024-2460, https://doi.org/10.5194/egusphere-2024-2460, 2024
Short summary
Short summary
Our study explored the impact of anthropogenic land-use change (LUC) on climate dynamics, focusing on biogeophysical (BGP) and biogeochemical (BGC) effects using data from the CMIP6-LUMIP project. We found that LUC-induced carbon emissions contribute to a BGC warming of 0.20 °C, with BGC effects dominating globally over BGP effects, which show regional variability. Our findings highlight discrepancies in model simulations and emphasise the need for improved representations of LUC processes.
Wolfgang Knorr, Matthew Williams, Tea Thum, Thomas Kaminski, Michael Voßbeck, Marko Scholze, Tristan Quaife, Luke Smallmann, Susan Steele-Dunne, Mariette Vreugdenhil, Tim Green, Sönke Zähle, Mika Aurela, Alexandre Bouvet, Emanuel Bueechi, Wouter Dorigo, Tarek El-Madany, Mirco Migliavacca, Marika Honkanen, Yann Kerr, Anna Kontu, Juha Lemmetyinen, Hannakaisa Lindqvist, Arnaud Mialon, Tuuli Miinalainen, Gaetan Pique, Amanda Ojasalo, Shaun Quegan, Peter Rayner, Pablo Reyes-Muñoz, Nemesio Rodríguez-Fernández, Mike Schwank, Jochem Verrelst, Songyan Zhu, Dirk Schüttemeyer, and Matthias Drusch
EGUsphere, https://doi.org/10.5194/egusphere-2024-1534, https://doi.org/10.5194/egusphere-2024-1534, 2024
Short summary
Short summary
When it comes to climate change, the land surfaces are where the vast majority of impacts happen. The task of monitoring those across the globe is formidable and must necessarily rely on satellites – at a significant cost: the measurements are only indirect and require comprehensive physical understanding. We have created a comprehensive modelling system that we offer to the research community to explore how satellite data can be better exploited to help us see what changes on our lands.
Lukas Kohl, Petri Kiuru, Marjo Palviainen, Maarit Raivonen, Markku Koskinen, Mari Pihlatie, and Annamari Lauren
EGUsphere, https://doi.org/10.5194/egusphere-2024-1280, https://doi.org/10.5194/egusphere-2024-1280, 2024
Short summary
Short summary
We present an assay to illuminate heterogeneity of biogeochemical transformations within peat samples. For this, we injected isotope labelled acetate into peat cores and monitoring the release of label-derived gases, which we compared to microtomography images. The fraction of label converted to CO2 and the rapidness of this conversion was linked to injection depth as well as air-filled porosity. Pore network metric did not provide predictive power over compared to porosity alone.
Fredrik Lagergren, Robert G. Björk, Camilla Andersson, Danijel Belušić, Mats P. Björkman, Erik Kjellström, Petter Lind, David Lindstedt, Tinja Olenius, Håkan Pleijel, Gunhild Rosqvist, and Paul A. Miller
Biogeosciences, 21, 1093–1116, https://doi.org/10.5194/bg-21-1093-2024, https://doi.org/10.5194/bg-21-1093-2024, 2024
Short summary
Short summary
The Fennoscandian boreal and mountain regions harbour a wide range of ecosystems sensitive to climate change. A new, highly resolved high-emission climate scenario enabled modelling of the vegetation development in this region at high resolution for the 21st century. The results show dramatic south to north and low- to high-altitude shifts of vegetation zones, especially for the open tundra environments, which will have large implications for nature conservation, reindeer husbandry and forestry.
Jalisha Theanutti Kallingal, Marko Scholze, Paul Anthony Miller, Johan Lindström, Janne Rinne, Mika Aurela, Patrik Vestin, and Per Weslien
EGUsphere, https://doi.org/10.5194/egusphere-2024-373, https://doi.org/10.5194/egusphere-2024-373, 2024
Preprint archived
Short summary
Short summary
Our study employs an Adaptive MCMC algorithm (GRaB-AM) to constrain process parameters in the wetlands emission module of the LPJ-GUESS model, using CH4 EC flux observations from 14 diverse wetlands. We aim to derive a single set of parameters capable of representing the diversity of northern wetlands. By reducing uncertainties in model parameters and improving simulation accuracy, our research contributes to more reliable projections of future wetland CH4 emissions and their climate impact.
Andria Dawson, John W. Williams, Marie-José Gaillard, Simon J. Goring, Behnaz Pirzamanbein, Johan Lindstrom, R. Scott Anderson, Andrea Brunelle, David Foster, Konrad Gajewski, Dan G. Gavin, Terri Lacourse, Thomas A. Minckley, Wyatt Oswald, Bryan Shuman, and Cathy Whitlock
Clim. Past Discuss., https://doi.org/10.5194/cp-2024-6, https://doi.org/10.5194/cp-2024-6, 2024
Revised manuscript accepted for CP
Short summary
Short summary
Holocene vegetation-atmosphere interactions provide insight into intensifying land use impacts and the Holocene Conundrum- a mismatch between data- and model- inferred temperature. Using pollen records and statistical modeling, we reconstruct Holocene land cover for North America. We determine patterns and magnitudes of land cover changes across scales. We attribute land cover changes to ecological, climatic, and human drivers. These reconstructions provide benchmarks for Earth System Models.
Anna-Maria Virkkala, Pekka Niittynen, Julia Kemppinen, Maija E. Marushchak, Carolina Voigt, Geert Hensgens, Johanna Kerttula, Konsta Happonen, Vilna Tyystjärvi, Christina Biasi, Jenni Hultman, Janne Rinne, and Miska Luoto
Biogeosciences, 21, 335–355, https://doi.org/10.5194/bg-21-335-2024, https://doi.org/10.5194/bg-21-335-2024, 2024
Short summary
Short summary
Arctic greenhouse gas (GHG) fluxes of CO2, CH4, and N2O are important for climate feedbacks. We combined extensive in situ measurements and remote sensing data to develop machine-learning models to predict GHG fluxes at a 2 m resolution across a tundra landscape. The analysis revealed that the system was a net GHG sink and showed widespread CH4 uptake in upland vegetation types, almost surpassing the high wetland CH4 emissions at the landscape scale.
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
Short summary
Short summary
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.
Matti Räsänen, Risto Vesala, Petri Rönnholm, Laura Arppe, Petra Manninen, Markus Jylhä, Jouko Rikkinen, Petri Pellikka, and Janne Rinne
Biogeosciences, 20, 4029–4042, https://doi.org/10.5194/bg-20-4029-2023, https://doi.org/10.5194/bg-20-4029-2023, 2023
Short summary
Short summary
Fungus-growing termites recycle large parts of dead plant material in African savannas and are significant sources of greenhouse gases. We measured CO2 and CH4 fluxes from their mounds and surrounding soils in open and closed habitats. The fluxes scale with mound volume. The results show that emissions from mounds of fungus-growing termites are more stable than those from other termites. The soil fluxes around the mound are affected by the termite colonies at up to 2 m distance from the mound.
Gustav Strandberg, Jie Chen, Ralph Fyfe, Erik Kjellström, Johan Lindström, Anneli Poska, Qiong Zhang, and Marie-José Gaillard
Clim. Past, 19, 1507–1530, https://doi.org/10.5194/cp-19-1507-2023, https://doi.org/10.5194/cp-19-1507-2023, 2023
Short summary
Short summary
The impact of land use and land cover change (LULCC) on the climate around 2500 years ago is studied using reconstructions and models. The results suggest that LULCC impacted the climate in parts of Europe. Reconstructed LULCC shows up to 1.5 °C higher temperature in parts of Europe in some seasons. This relatively strong response implies that anthropogenic LULCC that had occurred by the late prehistoric period may have already affected the European climate by 2500 years ago.
Ross Petersen, Thomas Holst, Meelis Mölder, Natascha Kljun, and Janne Rinne
Atmos. Chem. Phys., 23, 7839–7858, https://doi.org/10.5194/acp-23-7839-2023, https://doi.org/10.5194/acp-23-7839-2023, 2023
Short summary
Short summary
We investigate variability in the vertical distribution of volatile organic compounds (VOCs) in boreal forest, determined through multiyear measurements at several heights in a boreal forest in Sweden. VOC source/sink seasonality in canopy was explored using these vertical profiles and with measurements from a collection of sonic anemometers on the station flux tower. Our results show seasonality in the source/sink distribution for several VOCs, such as monoterpenes and water-soluble compounds.
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
Short summary
Short summary
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.
Saqr Munassar, Guillaume Monteil, Marko Scholze, Ute Karstens, Christian Rödenbeck, Frank-Thomas Koch, Kai U. Totsche, and Christoph Gerbig
Atmos. Chem. Phys., 23, 2813–2828, https://doi.org/10.5194/acp-23-2813-2023, https://doi.org/10.5194/acp-23-2813-2023, 2023
Short summary
Short summary
Using different transport models results in large errors in optimized fluxes in the atmospheric inversions. Boundary conditions and inversion system configurations lead to a smaller but non-negligible impact. The findings highlight the importance to validate transport models for further developments but also to properly account for such errors in inverse modelling. This will help narrow the convergence of gas estimates reported in the scientific literature from different inversion frameworks.
Yao Gao, Eleanor J. Burke, Sarah E. Chadburn, Maarit Raivonen, Mika Aurela, Lawrence B. Flanagan, Krzysztof Fortuniak, Elyn Humphreys, Annalea Lohila, Tingting Li, Tiina Markkanen, Olli Nevalainen, Mats B. Nilsson, Włodzimierz Pawlak, Aki Tsuruta, Huiyi Yang, and Tuula Aalto
Biogeosciences Discuss., https://doi.org/10.5194/bg-2022-229, https://doi.org/10.5194/bg-2022-229, 2022
Manuscript not accepted for further review
Short summary
Short summary
We coupled a process-based peatland CH4 emission model HIMMELI with a state-of-art land surface model JULES. The performance of the coupled model was evaluated at six northern wetland sites. The coupled model is considered to be more appropriate in simulating wetland CH4 emission. In order to improve the simulated CH4 emission, the model requires better representation of the peat soil carbon and hydrologic processes in JULES and the methane production and transportation processes in HIMMELI.
Matti Räsänen, Mika Aurela, Ville Vakkari, Johan P. Beukes, Juha-Pekka Tuovinen, Pieter G. Van Zyl, Miroslav Josipovic, Stefan J. Siebert, Tuomas Laurila, Markku Kulmala, Lauri Laakso, Janne Rinne, Ram Oren, and Gabriel Katul
Hydrol. Earth Syst. Sci., 26, 5773–5791, https://doi.org/10.5194/hess-26-5773-2022, https://doi.org/10.5194/hess-26-5773-2022, 2022
Short summary
Short summary
The productivity of semiarid grazed grasslands is linked to the variation in rainfall and transpiration. By combining carbon dioxide and water flux measurements, we show that the annual transpiration is nearly constant during wet years while grasses react quickly to dry spells and drought, which reduce transpiration. The planning of annual grazing strategies could consider the early-season rainfall frequency that was linked to the portion of annual transpiration.
Petri Kiuru, Marjo Palviainen, Arianna Marchionne, Tiia Grönholm, Maarit Raivonen, Lukas Kohl, and Annamari Laurén
Biogeosciences, 19, 5041–5058, https://doi.org/10.5194/bg-19-5041-2022, https://doi.org/10.5194/bg-19-5041-2022, 2022
Short summary
Short summary
Peatlands are large carbon stocks. Emissions of carbon dioxide and methane from peatlands may increase due to changes in management and climate. We studied the variation in the gas diffusivity of peat with depth using pore network simulations and laboratory experiments. Gas diffusivity was found to be lower in deeper peat with smaller pores and lower pore connectivity. However, gas diffusivity was not extremely low in wet conditions, which may reflect the distinctive structure of peat.
Malika Menoud, Carina van der Veen, Dave Lowry, Julianne M. Fernandez, Semra Bakkaloglu, James L. France, Rebecca E. Fisher, Hossein Maazallahi, Mila Stanisavljević, Jarosław Nęcki, Katarina Vinkovic, Patryk Łakomiec, Janne Rinne, Piotr Korbeń, Martina Schmidt, Sara Defratyka, Camille Yver-Kwok, Truls Andersen, Huilin Chen, and Thomas Röckmann
Earth Syst. Sci. Data, 14, 4365–4386, https://doi.org/10.5194/essd-14-4365-2022, https://doi.org/10.5194/essd-14-4365-2022, 2022
Short summary
Short summary
Emission sources of methane (CH4) can be distinguished with measurements of CH4 stable isotopes. We present new measurements of isotope signatures of various CH4 sources in Europe, mainly anthropogenic, sampled from 2017 to 2020. The present database also contains the most recent update of the global signature dataset from the literature. The dataset improves CH4 source attribution and the understanding of the global CH4 budget.
Janne Rinne, Patryk Łakomiec, Patrik Vestin, Joel D. White, Per Weslien, Julia Kelly, Natascha Kljun, Lena Ström, and Leif Klemedtsson
Biogeosciences, 19, 4331–4349, https://doi.org/10.5194/bg-19-4331-2022, https://doi.org/10.5194/bg-19-4331-2022, 2022
Short summary
Short summary
The study uses the stable isotope 13C of carbon in methane to investigate the origins of spatial and temporal variation in methane emitted by a temperate wetland ecosystem. The results indicate that methane production is more important for spatial variation than methane consumption by micro-organisms. Temporal variation on a seasonal timescale is most likely affected by more than one driver simultaneously.
Ralf Döscher, Mario Acosta, Andrea Alessandri, Peter Anthoni, Thomas Arsouze, Tommi Bergman, Raffaele Bernardello, Souhail Boussetta, Louis-Philippe Caron, Glenn Carver, Miguel Castrillo, Franco Catalano, Ivana Cvijanovic, Paolo Davini, Evelien Dekker, Francisco J. Doblas-Reyes, David Docquier, Pablo Echevarria, Uwe Fladrich, Ramon Fuentes-Franco, Matthias Gröger, Jost v. Hardenberg, Jenny Hieronymus, M. Pasha Karami, Jukka-Pekka Keskinen, Torben Koenigk, Risto Makkonen, François Massonnet, Martin Ménégoz, Paul A. Miller, Eduardo Moreno-Chamarro, Lars Nieradzik, Twan van Noije, Paul Nolan, Declan O'Donnell, Pirkka Ollinaho, Gijs van den Oord, Pablo Ortega, Oriol Tintó Prims, Arthur Ramos, Thomas Reerink, Clement Rousset, Yohan Ruprich-Robert, Philippe Le Sager, Torben Schmith, Roland Schrödner, Federico Serva, Valentina Sicardi, Marianne Sloth Madsen, Benjamin Smith, Tian Tian, Etienne Tourigny, Petteri Uotila, Martin Vancoppenolle, Shiyu Wang, David Wårlind, Ulrika Willén, Klaus Wyser, Shuting Yang, Xavier Yepes-Arbós, and Qiong Zhang
Geosci. Model Dev., 15, 2973–3020, https://doi.org/10.5194/gmd-15-2973-2022, https://doi.org/10.5194/gmd-15-2973-2022, 2022
Short summary
Short summary
The Earth system model EC-Earth3 is documented here. Key performance metrics show physical behavior and biases well within the frame known from recent models. With improved physical and dynamic features, new ESM components, community tools, and largely improved physical performance compared to the CMIP5 version, EC-Earth3 represents a clear step forward for the only European community ESM. We demonstrate here that EC-Earth3 is suited for a range of tasks in CMIP6 and beyond.
Petri Kiuru, Marjo Palviainen, Tiia Grönholm, Maarit Raivonen, Lukas Kohl, Vincent Gauci, Iñaki Urzainki, and Annamari Laurén
Biogeosciences, 19, 1959–1977, https://doi.org/10.5194/bg-19-1959-2022, https://doi.org/10.5194/bg-19-1959-2022, 2022
Short summary
Short summary
Peatlands are large sources of methane (CH4), and peat structure controls CH4 production and emissions. We used X-ray microtomography imaging, complex network theory methods, and pore network modeling to describe the properties of peat macropore networks and the role of macropores in CH4-related processes. We show that conditions for gas transport and CH4 production vary with depth and are affected by hysteresis, which may explain the hotspots and episodic spikes in peatland CH4 emissions.
H. E. Markus Meier, Madline Kniebusch, Christian Dieterich, Matthias Gröger, Eduardo Zorita, Ragnar Elmgren, Kai Myrberg, Markus P. Ahola, Alena Bartosova, Erik Bonsdorff, Florian Börgel, Rene Capell, Ida Carlén, Thomas Carlund, Jacob Carstensen, Ole B. Christensen, Volker Dierschke, Claudia Frauen, Morten Frederiksen, Elie Gaget, Anders Galatius, Jari J. Haapala, Antti Halkka, Gustaf Hugelius, Birgit Hünicke, Jaak Jaagus, Mart Jüssi, Jukka Käyhkö, Nina Kirchner, Erik Kjellström, Karol Kulinski, Andreas Lehmann, Göran Lindström, Wilhelm May, Paul A. Miller, Volker Mohrholz, Bärbel Müller-Karulis, Diego Pavón-Jordán, Markus Quante, Marcus Reckermann, Anna Rutgersson, Oleg P. Savchuk, Martin Stendel, Laura Tuomi, Markku Viitasalo, Ralf Weisse, and Wenyan Zhang
Earth Syst. Dynam., 13, 457–593, https://doi.org/10.5194/esd-13-457-2022, https://doi.org/10.5194/esd-13-457-2022, 2022
Short summary
Short summary
Based on the Baltic Earth Assessment Reports of this thematic issue in Earth System Dynamics and recent peer-reviewed literature, current knowledge about the effects of global warming on past and future changes in the climate of the Baltic Sea region is summarised and assessed. The study is an update of the Second Assessment of Climate Change (BACC II) published in 2015 and focuses on the atmosphere, land, cryosphere, ocean, sediments, and the terrestrial and marine biosphere.
Joel Dawson White, Lena Ström, Veiko Lehsten, Janne Rinne, and Dag Ahrén
Biogeosciences Discuss., https://doi.org/10.5194/bg-2021-353, https://doi.org/10.5194/bg-2021-353, 2022
Revised manuscript not accepted
Short summary
Short summary
Microbes that produce CH4 play an important role to climate. Microbes which emit CH4 from wetlands is poorly understood. We observed that microbial community was of importance in explaining CH4 emission. We found, that microbes that produce CH4 hold the ability to produce and consume CH4 in multiple ways. This is important in terms of future climate scenarios, where wetlands are expected to shift. Therefore, we expect the community to be highly adaptive to future climate scenarios.
Adrian Gustafson, Paul A. Miller, Robert G. Björk, Stefan Olin, and Benjamin Smith
Biogeosciences, 18, 6329–6347, https://doi.org/10.5194/bg-18-6329-2021, https://doi.org/10.5194/bg-18-6329-2021, 2021
Short summary
Short summary
We performed model simulations of vegetation change for a historic period and a range of climate change scenarios at a high spatial resolution. Projected treeline advance continued at the same or increased rates compared to our historic simulation. Temperature isotherms advanced faster than treelines, revealing a lag in potential vegetation shifts that was modulated by nitrogen availability. At the year 2100 projected treelines had advanced by 45–195 elevational metres depending on the scenario.
Patryk Łakomiec, Jutta Holst, Thomas Friborg, Patrick Crill, Niklas Rakos, Natascha Kljun, Per-Ola Olsson, Lars Eklundh, Andreas Persson, and Janne Rinne
Biogeosciences, 18, 5811–5830, https://doi.org/10.5194/bg-18-5811-2021, https://doi.org/10.5194/bg-18-5811-2021, 2021
Short summary
Short summary
Methane emission from the subarctic mire with heterogeneous permafrost status was measured for the years 2014–2016. Lower methane emission was measured from the palsa mire sector while the thawing wet sector emitted more. Both sectors have a similar annual pattern with a gentle rise during spring and a decrease during autumn. The highest emission was observed in the late summer. Winter emissions were positive during the measurement period and have a significant impact on the annual budgets.
Alexandra Pongracz, David Wårlind, Paul A. Miller, and Frans-Jan W. Parmentier
Biogeosciences, 18, 5767–5787, https://doi.org/10.5194/bg-18-5767-2021, https://doi.org/10.5194/bg-18-5767-2021, 2021
Short summary
Short summary
This study shows that the introduction of a multi-layer snow scheme in the LPJ-GUESS DGVM improved simulations of high-latitude soil temperature dynamics and permafrost extent compared to observations. In addition, these improvements led to shifts in carbon fluxes that contrasted within and outside of the permafrost region. Our results show that a realistic snow scheme is essential to accurately simulate snow–soil–vegetation relationships and carbon–climate feedbacks.
Matthias Gröger, Christian Dieterich, Jari Haapala, Ha Thi Minh Ho-Hagemann, Stefan Hagemann, Jaromir Jakacki, Wilhelm May, H. E. Markus Meier, Paul A. Miller, Anna Rutgersson, and Lichuan Wu
Earth Syst. Dynam., 12, 939–973, https://doi.org/10.5194/esd-12-939-2021, https://doi.org/10.5194/esd-12-939-2021, 2021
Short summary
Short summary
Regional climate studies are typically pursued by single Earth system component models (e.g., ocean models and atmosphere models). These models are driven by prescribed data which hamper the simulation of feedbacks between Earth system components. To overcome this, models were developed that interactively couple model components and allow an adequate simulation of Earth system interactions important for climate. This article reviews recent developments of such models for the Baltic Sea region.
Antoine Berchet, Espen Sollum, Rona L. Thompson, Isabelle Pison, Joël Thanwerdas, Grégoire Broquet, Frédéric Chevallier, Tuula Aalto, Adrien Berchet, Peter Bergamaschi, Dominik Brunner, Richard Engelen, Audrey Fortems-Cheiney, Christoph Gerbig, Christine D. Groot Zwaaftink, Jean-Matthieu Haussaire, Stephan Henne, Sander Houweling, Ute Karstens, Werner L. Kutsch, Ingrid T. Luijkx, Guillaume Monteil, Paul I. Palmer, Jacob C. A. van Peet, Wouter Peters, Philippe Peylin, Elise Potier, Christian Rödenbeck, Marielle Saunois, Marko Scholze, Aki Tsuruta, and Yuanhong Zhao
Geosci. Model Dev., 14, 5331–5354, https://doi.org/10.5194/gmd-14-5331-2021, https://doi.org/10.5194/gmd-14-5331-2021, 2021
Short summary
Short summary
We present here the Community Inversion Framework (CIF) to help rationalize development efforts and leverage the strengths of individual inversion systems into a comprehensive framework. The CIF is a programming protocol to allow various inversion bricks to be exchanged among researchers.
The ensemble of bricks makes a flexible, transparent and open-source Python-based tool. We describe the main structure and functionalities and demonstrate it in a simple academic case.
Guillaume Monteil and Marko Scholze
Geosci. Model Dev., 14, 3383–3406, https://doi.org/10.5194/gmd-14-3383-2021, https://doi.org/10.5194/gmd-14-3383-2021, 2021
Short summary
Short summary
LUMIA is a Python library for atmospheric inversions, originally developed at Lund University to perform regional atmospheric CO2 inversions. The inversions rely on coupling the regional transport model FLEXPART and the global transport model TM5. The paper presents the modeling setup and some first results, and it introduces the LUMIA Python package as a toolbox for inversions beyond the use case presented in the paper.
Ana Maria Roxana Petrescu, Matthew J. McGrath, Robbie M. Andrew, Philippe Peylin, Glen P. Peters, Philippe Ciais, Gregoire Broquet, Francesco N. Tubiello, Christoph Gerbig, Julia Pongratz, Greet Janssens-Maenhout, Giacomo Grassi, Gert-Jan Nabuurs, Pierre Regnier, Ronny Lauerwald, Matthias Kuhnert, Juraj Balkovič, Mart-Jan Schelhaas, Hugo A. C. Denier van der
Gon, Efisio Solazzo, Chunjing Qiu, Roberto Pilli, Igor B. Konovalov, Richard A. Houghton, Dirk Günther, Lucia Perugini, Monica Crippa, Raphael Ganzenmüller, Ingrid T. Luijkx, Pete Smith, Saqr Munassar, Rona L. Thompson, Giulia Conchedda, Guillaume Monteil, Marko Scholze, Ute Karstens, Patrick Brockmann, and Albertus Johannes Dolman
Earth Syst. Sci. Data, 13, 2363–2406, https://doi.org/10.5194/essd-13-2363-2021, https://doi.org/10.5194/essd-13-2363-2021, 2021
Short summary
Short summary
This study is topical and provides a state-of-the-art scientific overview of data availability from bottom-up and top-down CO2 fossil emissions and CO2 land fluxes in the EU27+UK. The data integrate recent emission inventories with ecosystem data, land carbon models and regional/global inversions for the European domain, aiming at reconciling CO2 estimates with official country-level UNFCCC national GHG inventories in support to policy and facilitating real-time verification procedures.
Roger Seco, Thomas Holst, Mikkel Sillesen Matzen, Andreas Westergaard-Nielsen, Tao Li, Tihomir Simin, Joachim Jansen, Patrick Crill, Thomas Friborg, Janne Rinne, and Riikka Rinnan
Atmos. Chem. Phys., 20, 13399–13416, https://doi.org/10.5194/acp-20-13399-2020, https://doi.org/10.5194/acp-20-13399-2020, 2020
Short summary
Short summary
Northern ecosystems exchange climate-relevant trace gases with the atmosphere, including volatile organic compounds (VOCs). We measured VOC fluxes from a subarctic permafrost-free fen and its adjacent lake in northern Sweden. The graminoid-dominated fen emitted mainly isoprene during the peak of the growing season, with a pronounced response to increasing temperatures stronger than assumed by biogenic emission models. The lake was a sink of acetone and acetaldehyde during both periods measured.
Guillaume Monteil, Grégoire Broquet, Marko Scholze, Matthew Lang, Ute Karstens, Christoph Gerbig, Frank-Thomas Koch, Naomi E. Smith, Rona L. Thompson, Ingrid T. Luijkx, Emily White, Antoon Meesters, Philippe Ciais, Anita L. Ganesan, Alistair Manning, Michael Mischurow, Wouter Peters, Philippe Peylin, Jerôme Tarniewicz, Matt Rigby, Christian Rödenbeck, Alex Vermeulen, and Evie M. Walton
Atmos. Chem. Phys., 20, 12063–12091, https://doi.org/10.5194/acp-20-12063-2020, https://doi.org/10.5194/acp-20-12063-2020, 2020
Short summary
Short summary
The paper presents the first results from the EUROCOM project, a regional atmospheric inversion intercomparison exercise involving six European research groups. It aims to produce an estimate of the net carbon flux between the European terrestrial ecosystems and the atmosphere for the period 2006–2015, based on constraints provided by observed CO2 concentrations and using inverse modelling techniques. The use of six different models enables us to investigate the robustness of the results.
Marielle Saunois, Ann R. Stavert, Ben Poulter, Philippe Bousquet, Josep G. Canadell, Robert B. Jackson, Peter A. Raymond, Edward J. Dlugokencky, Sander Houweling, Prabir K. Patra, Philippe Ciais, Vivek K. Arora, David Bastviken, Peter Bergamaschi, Donald R. Blake, Gordon Brailsford, Lori Bruhwiler, Kimberly M. Carlson, Mark Carrol, Simona Castaldi, Naveen Chandra, Cyril Crevoisier, Patrick M. Crill, Kristofer Covey, Charles L. Curry, Giuseppe Etiope, Christian Frankenberg, Nicola Gedney, Michaela I. Hegglin, Lena Höglund-Isaksson, Gustaf Hugelius, Misa Ishizawa, Akihiko Ito, Greet Janssens-Maenhout, Katherine M. Jensen, Fortunat Joos, Thomas Kleinen, Paul B. Krummel, Ray L. Langenfelds, Goulven G. Laruelle, Licheng Liu, Toshinobu Machida, Shamil Maksyutov, Kyle C. McDonald, Joe McNorton, Paul A. Miller, Joe R. Melton, Isamu Morino, Jurek Müller, Fabiola Murguia-Flores, Vaishali Naik, Yosuke Niwa, Sergio Noce, Simon O'Doherty, Robert J. Parker, Changhui Peng, Shushi Peng, Glen P. Peters, Catherine Prigent, Ronald Prinn, Michel Ramonet, Pierre Regnier, William J. Riley, Judith A. Rosentreter, Arjo Segers, Isobel J. Simpson, Hao Shi, Steven J. Smith, L. Paul Steele, Brett F. Thornton, Hanqin Tian, Yasunori Tohjima, Francesco N. Tubiello, Aki Tsuruta, Nicolas Viovy, Apostolos Voulgarakis, Thomas S. Weber, Michiel van Weele, Guido R. van der Werf, Ray F. Weiss, Doug Worthy, Debra Wunch, Yi Yin, Yukio Yoshida, Wenxin Zhang, Zhen Zhang, Yuanhong Zhao, Bo Zheng, Qing Zhu, Qiuan Zhu, and Qianlai Zhuang
Earth Syst. Sci. Data, 12, 1561–1623, https://doi.org/10.5194/essd-12-1561-2020, https://doi.org/10.5194/essd-12-1561-2020, 2020
Short summary
Short summary
Understanding and quantifying the global methane (CH4) budget is important for assessing realistic pathways to mitigate climate change. We have established a consortium of multidisciplinary scientists under the umbrella of the Global Carbon Project to synthesize and stimulate new research aimed at improving and regularly updating the global methane budget. This is the second version of the review dedicated to the decadal methane budget, integrating results of top-down and bottom-up estimates.
Sheila Wachiye, Lutz Merbold, Timo Vesala, Janne Rinne, Matti Räsänen, Sonja Leitner, and Petri Pellikka
Biogeosciences, 17, 2149–2167, https://doi.org/10.5194/bg-17-2149-2020, https://doi.org/10.5194/bg-17-2149-2020, 2020
Short summary
Short summary
Limited data on emissions in Africa translate into uncertainty during GHG budgeting. We studied annual CO2, N2O, and CH4 emissions in four land-use types in Kenyan savanna using static chambers and gas chromatography. CO2 emissions varied between seasons and land-use types. Soil moisture and vegetation explained the seasonal variation, while soil temperature was insignificant. N2O and CH4 emissions did not vary at all sites. Our results are useful in climate change mitigation interventions.
Matti Räsänen, Mika Aurela, Ville Vakkari, Johan P. Beukes, Juha-Pekka Tuovinen, Pieter G. Van Zyl, Miroslav Josipovic, Stefan J. Siebert, Tuomas Laurila, Markku Kulmala, Lauri Laakso, Janne Rinne, Ram Oren, and Gabriel Katul
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2019-651, https://doi.org/10.5194/hess-2019-651, 2020
Revised manuscript not accepted
Short summary
Short summary
The annual ET is approximately equal to precipitation during six measured years for grazed savanna grassland. The computed annual transpiration was highly constrained when rainfall was near or above the long-term mean but was reduced during severe drought year. The developed methodologies can be used in a wide range of arid and semi-arid ecosystems.
Olli Peltola, Timo Vesala, Yao Gao, Olle Räty, Pavel Alekseychik, Mika Aurela, Bogdan Chojnicki, Ankur R. Desai, Albertus J. Dolman, Eugenie S. Euskirchen, Thomas Friborg, Mathias Göckede, Manuel Helbig, Elyn Humphreys, Robert B. Jackson, Georg Jocher, Fortunat Joos, Janina Klatt, Sara H. Knox, Natalia Kowalska, Lars Kutzbach, Sebastian Lienert, Annalea Lohila, Ivan Mammarella, Daniel F. Nadeau, Mats B. Nilsson, Walter C. Oechel, Matthias Peichl, Thomas Pypker, William Quinton, Janne Rinne, Torsten Sachs, Mateusz Samson, Hans Peter Schmid, Oliver Sonnentag, Christian Wille, Donatella Zona, and Tuula Aalto
Earth Syst. Sci. Data, 11, 1263–1289, https://doi.org/10.5194/essd-11-1263-2019, https://doi.org/10.5194/essd-11-1263-2019, 2019
Short summary
Short summary
Here we develop a monthly gridded dataset of northern (> 45 N) wetland methane (CH4) emissions. The data product is derived using a random forest machine-learning technique and eddy covariance CH4 fluxes from 25 wetland sites. Annual CH4 emissions from these wetlands calculated from the derived data product are comparable to prior studies focusing on these areas. This product is an independent estimate of northern wetland CH4 emissions and hence could be used, e.g. for process model evaluation.
Alexander J. Norton, Peter J. Rayner, Ernest N. Koffi, Marko Scholze, Jeremy D. Silver, and Ying-Ping Wang
Biogeosciences, 16, 3069–3093, https://doi.org/10.5194/bg-16-3069-2019, https://doi.org/10.5194/bg-16-3069-2019, 2019
Short summary
Short summary
This study presents an estimate of global terrestrial photosynthesis. We make use of satellite chlorophyll fluorescence measurements, a visible indicator of photosynthesis, to optimize model parameters and estimate photosynthetic carbon uptake. This new framework incorporates nonlinear, process-based understanding of the link between fluorescence and photosynthesis, an advance on past approaches. This will aid in the utility of fluorescence to quantify terrestrial carbon cycle feedbacks.
Alexander J. Norton, Peter J. Rayner, Ernest N. Koffi, Marko Scholze, Jeremy D. Silver, and Ying-Ping Wang
Biogeosciences Discuss., https://doi.org/10.5194/bg-2018-270, https://doi.org/10.5194/bg-2018-270, 2018
Revised manuscript has not been submitted
Short summary
Short summary
This study presents a global estimate of land carbon uptake through photosynthesis. We make use satellite chlorophyll fluorescence measurements, a visible indicator of photosynthesis, to optimize model parameters and then use the optimized model to estimate photosynthetic carbon uptake. This provides a new tool that can combine measurements and observations in a systematic way and maximise the use of chlorophyll fluorescence to improve our understanding of the land carbon cycle.
Alexander J. Norton, Peter J. Rayner, Ernest N. Koffi, and Marko Scholze
Geosci. Model Dev., 11, 1517–1536, https://doi.org/10.5194/gmd-11-1517-2018, https://doi.org/10.5194/gmd-11-1517-2018, 2018
Short summary
Short summary
It is difficult to estimate how much CO2 plants absorb via photosynthesis and even more difficult to model this for the whole globe. Here, we present a framework to combine a new satellite measurement "solar-induced chlorophyll fluorescence" with a global photosynthesis model. We then quantify how this new measurement constrains model uncertainties and find highly effective constraint. These results pave a novel pathway for improving estimates and modelling abilities of photosynthesis globally.
Jouni Susiluoto, Maarit Raivonen, Leif Backman, Marko Laine, Jarmo Makela, Olli Peltola, Timo Vesala, and Tuula Aalto
Geosci. Model Dev., 11, 1199–1228, https://doi.org/10.5194/gmd-11-1199-2018, https://doi.org/10.5194/gmd-11-1199-2018, 2018
Short summary
Short summary
Methane is an important greenhouse gas and methane emissions from wetlands contribute to the warming of the climate. Wetland methane emissions are also challenging to estimate. We analyze the performance of a new wetland emission computer model utilizing mathematical methods and using data from a wetland in southern Finland. The analysis helps to explain how wetlands produce methane and how emission modeling can be improved and uncertainties in the emission estimates reduced in future studies.
Aino Korrensalo, Elisa Männistö, Pavel Alekseychik, Ivan Mammarella, Janne Rinne, Timo Vesala, and Eeva-Stiina Tuittila
Biogeosciences, 15, 1749–1761, https://doi.org/10.5194/bg-15-1749-2018, https://doi.org/10.5194/bg-15-1749-2018, 2018
Short summary
Short summary
We measured methane fluxes of a boreal bog from six different plant community types in 2012–2014. We found only little variation in methane fluxes among plant community types. Peat temperature as well as both leaf area of plant species with air channels and of all vegetation are important factors controlling the fluxes. We also detected negative net fluxes indicating methane consumption each year. Our results can be used to improve the models of peatland methane dynamics under climate change.
Olli Peltola, Maarit Raivonen, Xuefei Li, and Timo Vesala
Biogeosciences, 15, 937–951, https://doi.org/10.5194/bg-15-937-2018, https://doi.org/10.5194/bg-15-937-2018, 2018
Short summary
Short summary
Emission via bubbling, i.e. ebullition, is one of the main CH4 emission pathways from wetlands to the atmosphere, yet it is still coarsely represented in wetland CH4 models. In this study three ebullition modelling approaches are evaluated. Modeled annual CH4 emissions were similar, whereas temporal variability in CH4 emissions varied an order of magnitude between the approaches. Hence realistic description of ebullition is needed when models are compared to and calibrated against measurements.
Chunjing Qiu, Dan Zhu, Philippe Ciais, Bertrand Guenet, Gerhard Krinner, Shushi Peng, Mika Aurela, Christian Bernhofer, Christian Brümmer, Syndonia Bret-Harte, Housen Chu, Jiquan Chen, Ankur R. Desai, Jiří Dušek, Eugénie S. Euskirchen, Krzysztof Fortuniak, Lawrence B. Flanagan, Thomas Friborg, Mateusz Grygoruk, Sébastien Gogo, Thomas Grünwald, Birger U. Hansen, David Holl, Elyn Humphreys, Miriam Hurkuck, Gerard Kiely, Janina Klatt, Lars Kutzbach, Chloé Largeron, Fatima Laggoun-Défarge, Magnus Lund, Peter M. Lafleur, Xuefei Li, Ivan Mammarella, Lutz Merbold, Mats B. Nilsson, Janusz Olejnik, Mikaell Ottosson-Löfvenius, Walter Oechel, Frans-Jan W. Parmentier, Matthias Peichl, Norbert Pirk, Olli Peltola, Włodzimierz Pawlak, Daniel Rasse, Janne Rinne, Gaius Shaver, Hans Peter Schmid, Matteo Sottocornola, Rainer Steinbrecher, Torsten Sachs, Marek Urbaniak, Donatella Zona, and Klaudia Ziemblinska
Geosci. Model Dev., 11, 497–519, https://doi.org/10.5194/gmd-11-497-2018, https://doi.org/10.5194/gmd-11-497-2018, 2018
Short summary
Short summary
Northern peatlands store large amount of soil carbon and are vulnerable to climate change. We implemented peatland hydrological and carbon accumulation processes into the ORCHIDEE land surface model. The model was evaluated against EC measurements from 30 northern peatland sites. The model generally well reproduced the spatial gradient and temporal variations in GPP and NEE at these sites. Water table depth was not well predicted but had only small influence on simulated NEE.
Maarit Raivonen, Sampo Smolander, Leif Backman, Jouni Susiluoto, Tuula Aalto, Tiina Markkanen, Jarmo Mäkelä, Janne Rinne, Olli Peltola, Mika Aurela, Annalea Lohila, Marin Tomasic, Xuefei Li, Tuula Larmola, Sari Juutinen, Eeva-Stiina Tuittila, Martin Heimann, Sanna Sevanto, Thomas Kleinen, Victor Brovkin, and Timo Vesala
Geosci. Model Dev., 10, 4665–4691, https://doi.org/10.5194/gmd-10-4665-2017, https://doi.org/10.5194/gmd-10-4665-2017, 2017
Short summary
Short summary
Wetlands are one of the most significant natural sources of the strong greenhouse gas methane. We developed a model that can be used within a larger wetland carbon model to simulate the methane emissions. In this study, we present the model and results of its testing. We found that the model works well with different settings and that the results depend primarily on the rate of input anoxic soil respiration and also on factors that affect the simulated oxygen concentrations in the wetland soil.
Nitin Chaudhary, Paul A. Miller, and Benjamin Smith
Biogeosciences, 14, 4023–4044, https://doi.org/10.5194/bg-14-4023-2017, https://doi.org/10.5194/bg-14-4023-2017, 2017
Short summary
Short summary
We employed an individual- and patch-based dynamic global ecosystem model to quantify long-term C accumulation rates and to assess the effects of historical and projected climate change on peatland C balances across the pan-Arctic. We found that peatlands in Scandinavia, Europe, Russia and central and eastern Canada will become C sources, while Siberia, far eastern Russia, Alaska and western and northern Canada will increase their sink capacity by the end of the 21st century.
Marko Scholze, Michael Buchwitz, Wouter Dorigo, Luis Guanter, and Shaun Quegan
Biogeosciences, 14, 3401–3429, https://doi.org/10.5194/bg-14-3401-2017, https://doi.org/10.5194/bg-14-3401-2017, 2017
Short summary
Short summary
This paper briefly reviews data assimilation techniques in carbon cycle data assimilation and the requirements of data assimilation systems on observations. We provide a non-exhaustive overview of current observations and their uncertainties for use in terrestrial carbon cycle data assimilation, focussing on relevant space-based observations.
Nitin Chaudhary, Paul A. Miller, and Benjamin Smith
Biogeosciences, 14, 2571–2596, https://doi.org/10.5194/bg-14-2571-2017, https://doi.org/10.5194/bg-14-2571-2017, 2017
Short summary
Short summary
We incorporated peatland dynamics into
Arcticversion of dynamic vegetation model LPJ-GUESS to understand the long-term evolution of northern peatlands and effects of climate change on peatland carbon balance. We found that the Stordalen mire may be expected to sequester more carbon before 2050 due to milder and wetter climate conditions, a longer growing season and CO2 fertilization effect, turning into a C source after 2050 because of higher decomposition rates in response to warming soils.
Matti Räsänen, Mika Aurela, Ville Vakkari, Johan P. Beukes, Juha-Pekka Tuovinen, Pieter G. Van Zyl, Miroslav Josipovic, Andrew D. Venter, Kerneels Jaars, Stefan J. Siebert, Tuomas Laurila, Janne Rinne, and Lauri Laakso
Biogeosciences, 14, 1039–1054, https://doi.org/10.5194/bg-14-1039-2017, https://doi.org/10.5194/bg-14-1039-2017, 2017
Short summary
Short summary
This study presents measurements of carbon dioxide exchange between the atmosphere and a grazed savanna grassland ecosystem for 3 years. We find that the yearly variation in carbon dioxide balance is largely determined by the changes in the early wet season balance (September to November) and in the mid-growing season balance (December to January).
Aino Korrensalo, Pavel Alekseychik, Tomáš Hájek, Janne Rinne, Timo Vesala, Lauri Mehtätalo, Ivan Mammarella, and Eeva-Stiina Tuittila
Biogeosciences, 14, 257–269, https://doi.org/10.5194/bg-14-257-2017, https://doi.org/10.5194/bg-14-257-2017, 2017
Short summary
Short summary
Photosynthetic parameters of peatland plant species were measured over one growing season in an ombrotrophic bog. Based on these measurements, ecosystem-level photosynthesis was calculated for the whole growing season and compared with an estimate derived from micrometeorological measurements. These two estimates corresponded well. Species with low areal cover at the site but high photosynthetic efficiency appeared to be potentially important for the ecosystem-level carbon balance.
Kerneels Jaars, Pieter G. van Zyl, Johan P. Beukes, Heidi Hellén, Ville Vakkari, Micky Josipovic, Andrew D. Venter, Matti Räsänen, Leandra Knoetze, Dirk P. Cilliers, Stefan J. Siebert, Markku Kulmala, Janne Rinne, Alex Guenther, Lauri Laakso, and Hannele Hakola
Atmos. Chem. Phys., 16, 15665–15688, https://doi.org/10.5194/acp-16-15665-2016, https://doi.org/10.5194/acp-16-15665-2016, 2016
Short summary
Short summary
Biogenic volatile organic compounds (BVOCs) – important in tropospheric ozone and secondary organic aerosol formation – were measured at a savannah grassland in South Africa. Results presented are the most extensive for this type of landscape. Compared to other parts of the world, monoterpene levels were similar, while very low isoprene levels led to significantly lower total BVOC levels. BVOC levels were an order of magnitude lower compared to anthropogenic VOC levels measured at Welgegund.
Natasha MacBean, Philippe Peylin, Frédéric Chevallier, Marko Scholze, and Gregor Schürmann
Geosci. Model Dev., 9, 3569–3588, https://doi.org/10.5194/gmd-9-3569-2016, https://doi.org/10.5194/gmd-9-3569-2016, 2016
Short summary
Short summary
Model projections of the response of the terrestrial biosphere to anthropogenic emissions are uncertain, in part due to unknown fixed parameters in a model. Data assimilation can address this by using observations to optimise these parameter values. Using multiple types of data is beneficial for constraining different model processes, but it can also pose challenges in a DA context. This paper demonstrates and discusses the issues involved using toy models and examples from existing literature.
Wenli Wang, Annette Rinke, John C. Moore, Duoying Ji, Xuefeng Cui, Shushi Peng, David M. Lawrence, A. David McGuire, Eleanor J. Burke, Xiaodong Chen, Bertrand Decharme, Charles Koven, Andrew MacDougall, Kazuyuki Saito, Wenxin Zhang, Ramdane Alkama, Theodore J. Bohn, Philippe Ciais, Christine Delire, Isabelle Gouttevin, Tomohiro Hajima, Gerhard Krinner, Dennis P. Lettenmaier, Paul A. Miller, Benjamin Smith, Tetsuo Sueyoshi, and Artem B. Sherstiukov
The Cryosphere, 10, 1721–1737, https://doi.org/10.5194/tc-10-1721-2016, https://doi.org/10.5194/tc-10-1721-2016, 2016
Short summary
Short summary
The winter snow insulation is a key process for air–soil temperature coupling and is relevant for permafrost simulations. Differences in simulated air–soil temperature relationships and their modulation by climate conditions are found to be related to the snow model physics. Generally, models with better performance apply multilayer snow schemes.
Pekka Rantala, Leena Järvi, Risto Taipale, Terhi K. Laurila, Johanna Patokoski, Maija K. Kajos, Mona Kurppa, Sami Haapanala, Erkki Siivola, Tuukka Petäjä, Taina M. Ruuskanen, and Janne Rinne
Atmos. Chem. Phys., 16, 7981–8007, https://doi.org/10.5194/acp-16-7981-2016, https://doi.org/10.5194/acp-16-7981-2016, 2016
Short summary
Short summary
Fluxes of volatile organic compounds (VOCs) were measured above an urban landscape in Helsinki, northern Europe. We found that traffic was a major source for many oxygenated and aromatic VOCs, whereas isoprene originated mostly from the urban vegetation. Overall, the VOC fluxes were quite small in comparison with the earlier urban VOC flux measurements.
Johanna Joensuu, Nuria Altimir, Hannele Hakola, Michael Rostás, Maarit Raivonen, Mika Vestenius, Hermanni Aaltonen, Markus Riederer, and Jaana Bäck
Atmos. Chem. Phys., 16, 7813–7823, https://doi.org/10.5194/acp-16-7813-2016, https://doi.org/10.5194/acp-16-7813-2016, 2016
Short summary
Short summary
Plants produce volatile compounds (BVOCs) that have a major role in atmospheric chemistry. Our aim was to see if terpenes, a key group of BVOCs, can be found on surfaces of pine needles and, if so, how they compare with the emissions of the same tree. Both emissions and wax extracts were clearly dominated by monoterpenes, but there were also differences in the emission and wax spectra. The results support the existence of BVOCs on needle surfaces, with possible implications for air chemistry.
Simon Schallhart, Pekka Rantala, Eiko Nemitz, Ditte Taipale, Ralf Tillmann, Thomas F. Mentel, Benjamin Loubet, Giacomo Gerosa, Angelo Finco, Janne Rinne, and Taina M. Ruuskanen
Atmos. Chem. Phys., 16, 7171–7194, https://doi.org/10.5194/acp-16-7171-2016, https://doi.org/10.5194/acp-16-7171-2016, 2016
Short summary
Short summary
We present ecosystem exchange fluxes from a mixed oak–hornbeam forest in the Po Valley, Italy. Detectable fluxes were observed for 29 compounds, dominated by isoprene, which comprised over 60 % of the upward flux. Methanol seemed to be deposited to dew, as the deposition happened in the early morning. We estimated that up to 30 % of the upward flux of methyl vinyl ketone and methacrolein originated from atmospheric oxidation of isoprene.
Almut Arneth, Risto Makkonen, Stefan Olin, Pauli Paasonen, Thomas Holst, Maija K. Kajos, Markku Kulmala, Trofim Maximov, Paul A. Miller, and Guy Schurgers
Atmos. Chem. Phys., 16, 5243–5262, https://doi.org/10.5194/acp-16-5243-2016, https://doi.org/10.5194/acp-16-5243-2016, 2016
Short summary
Short summary
We study the potentially contrasting effects of enhanced ecosystem CO2 release in response to warmer temperatures vs. emissions of biogenic volatile organic compounds and their formation of secondary organic aerosol through a combination of measurements and modelling at a remote location in Eastern Siberia. The study aims to highlight the number of potentially opposing processes and complex interactions between vegetation physiology, soil processes and trace-gas exchanges in the climate system.
S. Osterwalder, J. Fritsche, C. Alewell, M. Schmutz, M. B. Nilsson, G. Jocher, J. Sommar, J. Rinne, and K. Bishop
Atmos. Meas. Tech., 9, 509–524, https://doi.org/10.5194/amt-9-509-2016, https://doi.org/10.5194/amt-9-509-2016, 2016
Short summary
Short summary
Human activities have increased mercury (Hg) cycling between land and atmosphere. To define landscapes as sinks or sources of Hg we have developed an advanced REA system for long-term measurements of gaseous elemental Hg exchange. It was tested in two contrasting environments: above Basel, Switzerland, and a peatland in Sweden. Both landscapes showed net Hg emission (15 and 3 ng m−2 h−1, respectively). The novel system will help to advance our understanding of Hg exchange on an ecosystem scale.
S. Peng, P. Ciais, G. Krinner, T. Wang, I. Gouttevin, A. D. McGuire, D. Lawrence, E. Burke, X. Chen, B. Decharme, C. Koven, A. MacDougall, A. Rinke, K. Saito, W. Zhang, R. Alkama, T. J. Bohn, C. Delire, T. Hajima, D. Ji, D. P. Lettenmaier, P. A. Miller, J. C. Moore, B. Smith, and T. Sueyoshi
The Cryosphere, 10, 179–192, https://doi.org/10.5194/tc-10-179-2016, https://doi.org/10.5194/tc-10-179-2016, 2016
Short summary
Short summary
Soil temperature change is a key indicator of the dynamics of permafrost. Using nine process-based ecosystem models with permafrost processes, a large spread of soil temperature trends across the models. Air temperature and longwave downward radiation are the main drivers of soil temperature trends. Based on an emerging observation constraint method, the total boreal near-surface permafrost area decrease comprised between 39 ± 14 × 103 and 75 ± 14 × 103 km2 yr−1 from 1960 to 2000.
J. Patokoski, T. M. Ruuskanen, M. K. Kajos, R. Taipale, P. Rantala, J. Aalto, T. Ryyppö, T. Nieminen, H. Hakola, and J. Rinne
Atmos. Chem. Phys., 15, 13413–13432, https://doi.org/10.5194/acp-15-13413-2015, https://doi.org/10.5194/acp-15-13413-2015, 2015
Short summary
Short summary
In this study, main source areas for long-lived VOCs at the boreal forest in SMEAR II were determined. Air masses arriving from eastern and western directions were more polluted than those arriving from the northern direction. The biogenic and anthropogenic influences of three different source profiles were determined. The elevated trace gas concentrations from forest fire episodes were observed clearly in the trajectory analysis.
T. Li, W. Zhang, Q. Zhang, Y. Lu, G. Wang, Z. Niu, M. Raivonen, and T. Vesala
Biogeosciences, 12, 6853–6868, https://doi.org/10.5194/bg-12-6853-2015, https://doi.org/10.5194/bg-12-6853-2015, 2015
Short summary
Short summary
Natural wetlands in China have experienced extensive conversion and climate warming, which makes the estimation of methane emission from wetlands highly uncertain. In this paper, we simulated an increase of 25.5% in national CH4 fluxes from 1950 to 2010, which was mainly induced by climate warming. Although climate warming has accelerated CH4 fluxes, the total amount of national CH4 emissions decreased by approximately 2.35 Tg (1.91－2.81 Tg), due to a large wetland loss of 17.0 million ha.
M. K. Kajos, P. Rantala, M. Hill, H. Hellén, J. Aalto, J. Patokoski, R. Taipale, C. C. Hoerger, S. Reimann, T. M. Ruuskanen, J. Rinne, and T. Petäjä
Atmos. Meas. Tech., 8, 4453–4473, https://doi.org/10.5194/amt-8-4453-2015, https://doi.org/10.5194/amt-8-4453-2015, 2015
P. Rantala, J. Aalto, R. Taipale, T. M. Ruuskanen, and J. Rinne
Biogeosciences, 12, 5753–5770, https://doi.org/10.5194/bg-12-5753-2015, https://doi.org/10.5194/bg-12-5753-2015, 2015
M. A. Rawlins, A. D. McGuire, J. S. Kimball, P. Dass, D. Lawrence, E. Burke, X. Chen, C. Delire, C. Koven, A. MacDougall, S. Peng, A. Rinke, K. Saito, W. Zhang, R. Alkama, T. J. Bohn, P. Ciais, B. Decharme, I. Gouttevin, T. Hajima, D. Ji, G. Krinner, D. P. Lettenmaier, P. Miller, J. C. Moore, B. Smith, and T. Sueyoshi
Biogeosciences, 12, 4385–4405, https://doi.org/10.5194/bg-12-4385-2015, https://doi.org/10.5194/bg-12-4385-2015, 2015
Short summary
Short summary
We used outputs from nine models to better understand land-atmosphere CO2 exchanges across Northern Eurasia over the period 1960-1990. Model estimates were assessed against independent ground and satellite measurements. We find that the models show a weakening of the CO2 sink over time; the models tend to overestimate respiration, causing an underestimate in NEP; the model range in regional NEP is twice the multimodel mean. Residence time for soil carbon decreased, amid a gain in carbon storage.
A. Ekici, S. Chadburn, N. Chaudhary, L. H. Hajdu, A. Marmy, S. Peng, J. Boike, E. Burke, A. D. Friend, C. Hauck, G. Krinner, M. Langer, P. A. Miller, and C. Beer
The Cryosphere, 9, 1343–1361, https://doi.org/10.5194/tc-9-1343-2015, https://doi.org/10.5194/tc-9-1343-2015, 2015
Short summary
Short summary
This paper compares the performance of different land models in estimating soil thermal regimes at distinct cold region landscape types. Comparing models with different processes reveal the importance of surface insulation (snow/moss layer) and soil internal processes (heat/water transfer). The importance of model processes also depend on site conditions such as high/low snow cover, dry/wet soil types.
E. N. Koffi, P. J. Rayner, A. J. Norton, C. Frankenberg, and M. Scholze
Biogeosciences, 12, 4067–4084, https://doi.org/10.5194/bg-12-4067-2015, https://doi.org/10.5194/bg-12-4067-2015, 2015
Short summary
Short summary
We investigate the utility of satellite measurements of solar-induced chlorophyll fluorescence (SIF) in constraining gross primary productivity (GPP). We simulate SIF with the biosphere model BETHY coupled with the fluorescence model SCOPE. The model simulates well the patterns of SIF. SIF is sensitive to leaf chlorophyll and incoming radiation but not to the key physiological parameter Vcmax controlling GPP. Thus, further model development is necessary before SIF can be used to constrain GPP.
J. Tang, P. A. Miller, A. Persson, D. Olefeldt, P. Pilesjö, M. Heliasz, M. Jackowicz-Korczynski, Z. Yang, B. Smith, T. V. Callaghan, and T. R. Christensen
Biogeosciences, 12, 2791–2808, https://doi.org/10.5194/bg-12-2791-2015, https://doi.org/10.5194/bg-12-2791-2015, 2015
P. J. Rayner, A. Stavert, M. Scholze, A. Ahlström, C. E. Allison, and R. M. Law
Biogeosciences, 12, 835–844, https://doi.org/10.5194/bg-12-835-2015, https://doi.org/10.5194/bg-12-835-2015, 2015
Short summary
Short summary
Recent papers suggest a slow-down in the natural uptake of
anthropogenic CO2. We analyse recent trends in atmospheric concentration and
known inputs to test for such a slow-down. We see, rather, an increase
in uptake compared to a simple response to changing CO2 concentration. Using atmospheric models and statistical techniques we isolate this increased uptake to the northern temperate and boreal continents during summer, suggesting a stronger growing season.
W. Zhang, C. Jansson, P. A. Miller, B. Smith, and P. Samuelsson
Biogeosciences, 11, 5503–5519, https://doi.org/10.5194/bg-11-5503-2014, https://doi.org/10.5194/bg-11-5503-2014, 2014
S. Kemp, M. Scholze, T. Ziehn, and T. Kaminski
Geosci. Model Dev., 7, 1609–1619, https://doi.org/10.5194/gmd-7-1609-2014, https://doi.org/10.5194/gmd-7-1609-2014, 2014
A. Arneth, S. Olin, R. Makkonen, P. Paasonen, T. Holst, M. Kajos, M. Kulmala, T. Maximov, P. A. Miller, and G. Schurgers
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acpd-14-19149-2014, https://doi.org/10.5194/acpd-14-19149-2014, 2014
Revised manuscript not accepted
A. Virkkula, J. Levula, T. Pohja, P. P. Aalto, P. Keronen, S. Schobesberger, C. B. Clements, L. Pirjola, A.-J. Kieloaho, L. Kulmala, H. Aaltonen, J. Patokoski, J. Pumpanen, J. Rinne, T. Ruuskanen, M. Pihlatie, H. E. Manninen, V. Aaltonen, H. Junninen, T. Petäjä, J. Backman, M. Dal Maso, T. Nieminen, T. Olsson, T. Grönholm, J. Aalto, T. H. Virtanen, M. Kajos, V.-M. Kerminen, D. M. Schultz, J. Kukkonen, M. Sofiev, G. De Leeuw, J. Bäck, P. Hari, and M. Kulmala
Atmos. Chem. Phys., 14, 4473–4502, https://doi.org/10.5194/acp-14-4473-2014, https://doi.org/10.5194/acp-14-4473-2014, 2014
J. D. Watts, J. S. Kimball, F. J. W. Parmentier, T. Sachs, J. Rinne, D. Zona, W. Oechel, T. Tagesson, M. Jackowicz-Korczyński, and M. Aurela
Biogeosciences, 11, 1961–1980, https://doi.org/10.5194/bg-11-1961-2014, https://doi.org/10.5194/bg-11-1961-2014, 2014
A. L. Corrigan, L. M. Russell, S. Takahama, M. Äijälä, M. Ehn, H. Junninen, J. Rinne, T. Petäjä, M. Kulmala, A. L. Vogel, T. Hoffmann, C. J. Ebben, F. M. Geiger, P. Chhabra, J. H. Seinfeld, D. R. Worsnop, W. Song, J. Auld, and J. Williams
Atmos. Chem. Phys., 13, 12233–12256, https://doi.org/10.5194/acp-13-12233-2013, https://doi.org/10.5194/acp-13-12233-2013, 2013
N. Unger, K. Harper, Y. Zheng, N. Y. Kiang, I. Aleinov, A. Arneth, G. Schurgers, C. Amelynck, A. Goldstein, A. Guenther, B. Heinesch, C. N. Hewitt, T. Karl, Q. Laffineur, B. Langford, K. A. McKinney, P. Misztal, M. Potosnak, J. Rinne, S. Pressley, N. Schoon, and D. Serça
Atmos. Chem. Phys., 13, 10243–10269, https://doi.org/10.5194/acp-13-10243-2013, https://doi.org/10.5194/acp-13-10243-2013, 2013
M. K. Kajos, H. Hakola, T. Holst, T. Nieminen, V. Tarvainen, T. Maximov, T. Petäjä, A. Arneth, and J. Rinne
Biogeosciences, 10, 4705–4719, https://doi.org/10.5194/bg-10-4705-2013, https://doi.org/10.5194/bg-10-4705-2013, 2013
H. Hakola, H. Hellén, M. Hemmilä, J. Rinne, and M. Kulmala
Atmos. Chem. Phys., 12, 11665–11678, https://doi.org/10.5194/acp-12-11665-2012, https://doi.org/10.5194/acp-12-11665-2012, 2012
Related subject area
Biogeosciences
FESOM2.1-REcoM3-MEDUSA2: an ocean–sea ice–biogeochemistry model coupled to a sediment model
Satellite-based modeling of wetland methane emissions on a global scale (SatWetCH4 1.0)
Systematic underestimation of type-specific ecosystem process variability in the Community Land Model v5 over Europe
Soil nitrous oxide emissions from global land ecosystems and their drivers within the LPJ-GUESS model (v4.1)
Lambda-PFLOTRAN 1.0: a workflow for incorporating organic matter chemistry informed by ultra high resolution mass spectrometry into biogeochemical modeling
An improved model for air–sea exchange of elemental mercury in MITgcm-ECCOv4-Hg: the role of surfactants and waves
BOATSv2: new ecological and economic features improve simulations of high seas catch and effort
A dynamical process-based model for quantifying global agricultural ammonia emissions – AMmonia–CLIMate v1.0 (AMCLIM v1.0) – Part 1: Land module for simulating emissions from synthetic fertilizer use
Simulating Ips typographus L. outbreak dynamics and their influence on carbon balance estimates with ORCHIDEE r8627
Biological nitrogen fixation of natural and agricultural vegetation simulated with LPJmL 5.7.9
Learning from conceptual models – a study of the emergence of cooperation towards resource protection in a social–ecological system
The biogeochemical model Biome-BGCMuSo v6.2 provides plausible and accurate simulations of the carbon cycle in central European beech forests
Parameterisation toolbox for physical-biogeochemical model compatible with FABM. Case study: the coupled 1D GOTM-ECOSMO E2E for the Sylt-Romo Bight, North Sea
China Wildfire Emission (ChinaWED v1) for the period 2012–2022
H2MV (v1.0): Global Physically-Constrained Deep Learning Water Cycle Model with Vegetation
DeepPhenoMem V1.0: deep learning modelling of canopy greenness dynamics accounting for multi-variate meteorological memory effects on vegetation phenology
Impacts of land-use change on biospheric carbon: an oriented benchmark using the ORCHIDEE land surface model
Including the Phosphorus cycle into the LPJ-GUESS Dynamic Global Vegetation Model (v4.1, r10994) – Global patterns and temporal trends of N and P primary production limitation
Implementing the iCORAL (version 1.0) coral reef CaCO3 production module in the iLOVECLIM climate model
Assimilation of carbonyl sulfide (COS) fluxes within the adjoint-based data assimilation system – Nanjing University Carbon Assimilation System (NUCAS v1.0)
Alquimia v1.0: A generic interface to biogeochemical codes – A tool for interoperable development, prototyping and benchmarking for multiphysics simulators
Quantifying the role of ozone-caused damage to vegetation in the Earth system: a new parameterization scheme for photosynthetic and stomatal responses
Sources of Uncertainty in the Global Fire Model SPITFIRE: Development of LPJmL-SPITFIRE1.9 and Directions for Future Improvements
Radiocarbon analysis reveals underestimation of soil organic carbon persistence in new-generation soil models
Exploring the potential of history matching for land surface model calibration
EAT v1.0.0: a 1D test bed for physical–biogeochemical data assimilation in natural waters
Using deep learning to integrate paleoclimate and global biogeochemistry over the Phanerozoic Eon
A comprehensive land surface vegetation model for multi-stream data assimilation, D&B v1.0
Modelling boreal forest's mineral soil and peat C dynamics with the Yasso07 model coupled with the Ricker moisture modifier
Process-based Modeling of Solar-induced Chlorophyll Fluorescence with VISIT-SIF version 1.0
The unicellular NUM v.0.91: A trait-based plankton model evaluated in two contrasting biogeographic provinces
Dynamic ecosystem assembly and escaping the “fire trap” in the tropics: insights from FATES_15.0.0
NN-TOC v1: global prediction of total organic carbon in marine sediments using deep neural networks
In silico calculation of soil pH by SCEPTER v1.0
Simple process-led algorithms for simulating habitats (SPLASH v.2.0): robust calculations of water and energy fluxes
A global behavioural model of human fire use and management: WHAM! v1.0
Terrestrial Ecosystem Model in R (TEMIR) version 1.0: simulating ecophysiological responses of vegetation to atmospheric chemical and meteorological changes
biospheremetrics v1.0.2: an R package to calculate two complementary terrestrial biosphere integrity indicators – human colonization of the biosphere (BioCol) and risk of ecosystem destabilization (EcoRisk)
Modeling boreal forest soil dynamics with the microbially explicit soil model MIMICS+ (v1.0)
Optimal enzyme allocation leads to the constrained enzyme hypothesis: the Soil Enzyme Steady Allocation Model (SESAM; v3.1)
Implementing a dynamic representation of fire and harvest including subgrid-scale heterogeneity in the tile-based land surface model CLASSIC v1.45
Inferring the tree regeneration niche from inventory data using a dynamic forest model
The XSO framework (v0.1) and Phydra library (v0.1) for a flexible, reproducible, and integrated plankton community modeling environment in Python
AgriCarbon-EO v1.0.1: large-scale and high-resolution simulation of carbon fluxes by assimilation of Sentinel-2 and Landsat-8 reflectances using a Bayesian approach
SAMM version 1.0: a numerical model for microbial- mediated soil aggregate formation
A model of the within-population variability of budburst in forest trees
Computationally efficient parameter estimation for high-dimensional ocean biogeochemical models
The community-centered freshwater biogeochemistry model unified RIVE v1.0: a unified version for water column
Observation-based sowing dates and cultivars significantly affect yield and irrigation for some crops in the Community Land Model (CLM5)
The statistical emulators of GGCMI phase 2: responses of year-to-year variation of crop yield to CO2, temperature, water, and nitrogen perturbations
Ying Ye, Guy Munhoven, Peter Köhler, Martin Butzin, Judith Hauck, Özgür Gürses, and Christoph Völker
Geosci. Model Dev., 18, 977–1000, https://doi.org/10.5194/gmd-18-977-2025, https://doi.org/10.5194/gmd-18-977-2025, 2025
Short summary
Short summary
Many biogeochemistry models assume all material reaching the seafloor is remineralized and returned to solution, which is sufficient for studies on short-term climate change. Under long-term climate change, the carbon storage in sediments slows down carbon cycling and influences feedbacks in the atmosphere–ocean–sediment system. This paper describes the coupling of a sediment model to an ocean biogeochemistry model and presents results under the pre-industrial climate and under CO2 perturbation.
Juliette Bernard, Elodie Salmon, Marielle Saunois, Shushi Peng, Penélope Serrano-Ortiz, Antoine Berchet, Palingamoorthy Gnanamoorthy, Joachim Jansen, and Philippe Ciais
Geosci. Model Dev., 18, 863–883, https://doi.org/10.5194/gmd-18-863-2025, https://doi.org/10.5194/gmd-18-863-2025, 2025
Short summary
Short summary
Despite their importance, uncertainties remain in the evaluation of the drivers of temporal variability of methane emissions from wetlands on a global scale. Here, a simplified global model is developed, taking advantage of advances in remote-sensing data and in situ observations. The model reproduces the large spatial and temporal patterns of emissions, albeit with limitations in the tropics due to data scarcity. This model, while simple, can provide valuable insights into sensitivity analyses.
Christian Poppe Terán, Bibi S. Naz, Harry Vereecken, Roland Baatz, Rosie A. Fisher, and Harrie-Jan Hendricks Franssen
Geosci. Model Dev., 18, 287–317, https://doi.org/10.5194/gmd-18-287-2025, https://doi.org/10.5194/gmd-18-287-2025, 2025
Short summary
Short summary
Carbon and water exchanges between the atmosphere and the land surface contribute to water resource availability and climate change mitigation. Land surface models, like the Community Land Model version 5 (CLM5), simulate these. This study finds that CLM5 and other data sets underestimate the magnitudes of and variability in carbon and water exchanges for the most abundant plant functional types compared to observations. It provides essential insights for further research into these processes.
Jianyong Ma, Almut Arneth, Benjamin Smith, Peter Anthoni, Xu-Ri, Peter Eliasson, David Wårlind, Martin Wittenbrink, and Stefan Olin
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-223, https://doi.org/10.5194/gmd-2024-223, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
Nitrous oxide (N2O) is a powerful greenhouse gas mainly released from natural and agricultural soils. This study examines how global soil N2O emissions have changed from 1961 to 2020 and identifies key factors driving these changes using an ecological model. The findings highlight croplands as the largest source, with factors like fertilizer use and climate change enhancing emissions. Rising CO2 levels, however, can partially mitigate N2O emissions through increased plant nitrogen uptake.
Katherine A. Muller, Peishi Jiang, Glenn Hammond, Tasneem Ahmadullah, Hyun-Seob Song, Ravi Kukkadapu, Nicholas Ward, Madison Bowe, Rosalie K. Chu, Qian Zhao, Vanessa A. Garayburu-Caruso, Alan Roebuck, and Xingyuan Chen
Geosci. Model Dev., 17, 8955–8968, https://doi.org/10.5194/gmd-17-8955-2024, https://doi.org/10.5194/gmd-17-8955-2024, 2024
Short summary
Short summary
The new Lambda-PFLOTRAN workflow incorporates organic matter chemistry into reaction networks to simulate aerobic respiration and biogeochemistry. Lambda-PFLOTRAN is a Python-based workflow in a Jupyter notebook interface that digests raw organic matter chemistry data via Fourier transform ion cyclotron resonance mass spectrometry, develops a representative reaction network, and completes a biogeochemical simulation with the open-source, parallel-reactive-flow, and transport code PFLOTRAN.
Ling Li, Peipei Wu, Peng Zhang, Shaojian Huang, and Yanxu Zhang
Geosci. Model Dev., 17, 8683–8695, https://doi.org/10.5194/gmd-17-8683-2024, https://doi.org/10.5194/gmd-17-8683-2024, 2024
Short summary
Short summary
In this study, we incorporate sea surfactants and wave-breaking processes into MITgcm-ECCOv4-Hg. The updated model shows increased fluxes in high-wind-speed and high-wave regions and vice versa, enhancing spatial heterogeneity. It shows that elemental mercury (Hg0) transfer velocity is more sensitive to wind speed. These findings may elucidate the discrepancies in previous estimations and offer insights into global Hg cycling.
Jerome Guiet, Daniele Bianchi, Kim J. N. Scherrer, Ryan F. Heneghan, and Eric D. Galbraith
Geosci. Model Dev., 17, 8421–8454, https://doi.org/10.5194/gmd-17-8421-2024, https://doi.org/10.5194/gmd-17-8421-2024, 2024
Short summary
Short summary
The BiOeconomic mArine Trophic Size-spectrum (BOATSv2) model dynamically simulates global commercial fish populations and their coupling with fishing activity, as emerging from environmental and economic drivers. New features, including separate pelagic and demersal populations, iron limitation, and spatial variation of fishing costs and management, improve the accuracy of high seas fisheries. The updated model code is available to simulate both historical and future scenarios.
Jize Jiang, David S. Stevenson, and Mark A. Sutton
Geosci. Model Dev., 17, 8181–8222, https://doi.org/10.5194/gmd-17-8181-2024, https://doi.org/10.5194/gmd-17-8181-2024, 2024
Short summary
Short summary
A special model called AMmonia–CLIMate (AMCLIM) has been developed to understand and calculate NH3 emissions from fertilizer use and also taking into account how the environment influences these NH3 emissions. It is estimated that about 17 % of applied N in fertilizers was lost due to NH3 emissions. Hot and dry conditions and regions with high-pH soils can expect higher NH3 emissions.
Guillaume Marie, Jina Jeong, Hervé Jactel, Gunnar Petter, Maxime Cailleret, Matthew J. McGrath, Vladislav Bastrikov, Josefine Ghattas, Bertrand Guenet, Anne Sofie Lansø, Kim Naudts, Aude Valade, Chao Yue, and Sebastiaan Luyssaert
Geosci. Model Dev., 17, 8023–8047, https://doi.org/10.5194/gmd-17-8023-2024, https://doi.org/10.5194/gmd-17-8023-2024, 2024
Short summary
Short summary
This research looks at how climate change influences forests, and particularly how altered wind and insect activities could make forests emit instead of absorb carbon. We have updated a land surface model called ORCHIDEE to better examine the effect of bark beetles on forest health. Our findings suggest that sudden events, such as insect outbreaks, can dramatically affect carbon storage, offering crucial insights into tackling climate change.
Stephen Björn Wirth, Johanna Braun, Jens Heinke, Sebastian Ostberg, Susanne Rolinski, Sibyll Schaphoff, Fabian Stenzel, Werner von Bloh, Friedhelm Taube, and Christoph Müller
Geosci. Model Dev., 17, 7889–7914, https://doi.org/10.5194/gmd-17-7889-2024, https://doi.org/10.5194/gmd-17-7889-2024, 2024
Short summary
Short summary
We present a new approach to modelling biological nitrogen fixation (BNF) in the Lund–Potsdam–Jena managed Land dynamic global vegetation model. While in the original approach BNF depended on actual evapotranspiration, the new approach considers soil water content and temperature, vertical root distribution, the nitrogen (N) deficit and carbon (C) costs. The new approach improved simulated BNF compared to the scientific literature and the model ability to project future C and N cycle dynamics.
Saeed Harati-Asl, Liliana Perez, and Roberto Molowny-Horas
Geosci. Model Dev., 17, 7423–7443, https://doi.org/10.5194/gmd-17-7423-2024, https://doi.org/10.5194/gmd-17-7423-2024, 2024
Short summary
Short summary
Social–ecological systems are the subject of many sustainability problems. Because of the complexity of these systems, we must be careful when intervening in them; otherwise we may cause irreversible damage. Using computer models, we can gain insight about these complex systems without harming them. In this paper we describe how we connected an ecological model of forest insect infestation with a social model of cooperation and simulated an intervention measure to save a forest from infestation.
Katarína Merganičová, Ján Merganič, Laura Dobor, Roland Hollós, Zoltán Barcza, Dóra Hidy, Zuzana Sitková, Pavel Pavlenda, Hrvoje Marjanovic, Daniel Kurjak, Michal Bošel'a, Doroteja Bitunjac, Maša Zorana Ostrogović Sever, Jiří Novák, Peter Fleischer, and Tomáš Hlásny
Geosci. Model Dev., 17, 7317–7346, https://doi.org/10.5194/gmd-17-7317-2024, https://doi.org/10.5194/gmd-17-7317-2024, 2024
Short summary
Short summary
We developed a multi-objective calibration approach leading to robust parameter values aiming to strike a balance between their local precision and broad applicability. Using the Biome-BGCMuSo model, we tested the calibrated parameter sets for simulating European beech forest dynamics across large environmental gradients. Leveraging data from 87 plots and five European countries, the results demonstrated reasonable local accuracy and plausible large-scale productivity responses.
Hoa T. T. Nguyen, Ute Daewel, Neil Banas, and Corinna Schrum
EGUsphere, https://doi.org/10.5194/egusphere-2024-2710, https://doi.org/10.5194/egusphere-2024-2710, 2024
Short summary
Short summary
Parameterisation is key in modeling to reproduce observations well but is often done manually. This study presents a Particle Swarm Optimizer-based toolbox for marine ecosystem models, compatible with the Framework for Aquatic Biogeochemical Models, thus enhancing its reusability. Applied to the Sylt ecosystem, the toolbox effectively (1) identified multiple parameter sets that matched observations well, thus providing different insights into ecosystem dynamics, (2) optimized model complexity.
Zhengyang Lin, Ling Huang, Hanqin Tian, Anping Chen, and Xuhui Wang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-170, https://doi.org/10.5194/gmd-2024-170, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
Wildfires release large amounts of greenhouse gases, contributing to global warming. We developed a new model that provides near-real-time estimates of wildfire emissions in China. Our model improves the accuracy of burned area measurements and incorporates advanced data in fuel loads and emission factors. We found that most emissions come from agricultural fires, while emissions from forests and grasslands are decreasing. This model will help reduce the environmental impacts of wildfires.
Zavud Baghirov, Martin Jung, Markus Reichstein, Marco Körner, and Basil Kraft
EGUsphere, https://doi.org/10.5194/egusphere-2024-2044, https://doi.org/10.5194/egusphere-2024-2044, 2024
Short summary
Short summary
We use an innovative approach to study the Earth's water cycle by blending advanced computer learning techniques with a traditional water cycle model. We developed a model that learns from meteorological data, with a special focus on understanding how vegetation influences water movement. Our model closely aligns with real-world observations, yet there are areas that need improvement. This study opens up new possibilities to better understand the water cycle and its interactions with vegetation.
Guohua Liu, Mirco Migliavacca, Christian Reimers, Basil Kraft, Markus Reichstein, Andrew D. Richardson, Lisa Wingate, Nicolas Delpierre, Hui Yang, and Alexander J. Winkler
Geosci. Model Dev., 17, 6683–6701, https://doi.org/10.5194/gmd-17-6683-2024, https://doi.org/10.5194/gmd-17-6683-2024, 2024
Short summary
Short summary
Our study employs long short-term memory (LSTM) networks to model canopy greenness and phenology, integrating meteorological memory effects. The LSTM model outperforms traditional methods, enhancing accuracy in predicting greenness dynamics and phenological transitions across plant functional types. Highlighting the importance of multi-variate meteorological memory effects, our research pioneers unlock the secrets of vegetation phenology responses to climate change with deep learning techniques.
Thi Lan Anh Dinh, Daniel Goll, Philippe Ciais, and Ronny Lauerwald
Geosci. Model Dev., 17, 6725–6744, https://doi.org/10.5194/gmd-17-6725-2024, https://doi.org/10.5194/gmd-17-6725-2024, 2024
Short summary
Short summary
The study assesses the performance of the dynamic global vegetation model (DGVM) ORCHIDEE in capturing the impact of land-use change on carbon stocks across Europe. Comparisons with observations reveal that the model accurately represents carbon fluxes and stocks. Despite the underestimations in certain land-use conversions, the model describes general trends in soil carbon response to land-use change, aligning with the site observations.
Mateus Dantas de Paula, Matthew Forrest, David Warlind, João Paulo Darela Filho, Katrin Fleischer, Anja Rammig, and Thomas Hickler
EGUsphere, https://doi.org/10.5194/egusphere-2024-2592, https://doi.org/10.5194/egusphere-2024-2592, 2024
Short summary
Short summary
Our study maps global nitrogen (N) and phosphorus (P) availability and how they’ve changed from 1901 to 2018. We found that tropical regions are mostly P-limited, while temperate and boreal areas face N limitations. Over time, P limitation has increased, especially in the tropics, while N limitation has decreased. These shifts are key to understanding global plant growth and carbon storage, highlighting the importance of including P dynamics in ecosystem models.
Nathaelle Bouttes, Lester Kwiatkowski, Manon Berger, Victor Brovkin, and Guy Munhoven
Geosci. Model Dev., 17, 6513–6528, https://doi.org/10.5194/gmd-17-6513-2024, https://doi.org/10.5194/gmd-17-6513-2024, 2024
Short summary
Short summary
Coral reefs are crucial for biodiversity, but they also play a role in the carbon cycle on long time scales of a few thousand years. To better simulate the future and past evolution of coral reefs and their effect on the global carbon cycle, hence on atmospheric CO2 concentration, it is necessary to include coral reefs within a climate model. Here we describe the inclusion of coral reef carbonate production in a carbon–climate model and its validation in comparison to existing modern data.
Huajie Zhu, Mousong Wu, Fei Jiang, Michael Vossbeck, Thomas Kaminski, Xiuli Xing, Jun Wang, Weimin Ju, and Jing M. Chen
Geosci. Model Dev., 17, 6337–6363, https://doi.org/10.5194/gmd-17-6337-2024, https://doi.org/10.5194/gmd-17-6337-2024, 2024
Short summary
Short summary
In this work, we developed the Nanjing University Carbon Assimilation System (NUCAS v1.0). Data assimilation experiments were conducted to demonstrate the robustness and investigate the feasibility and applicability of NUCAS. The assimilation of ecosystem carbonyl sulfide (COS) fluxes improved the model performance in gross primary productivity, evapotranspiration, and sensible heat, showing that COS provides constraints on parameters relevant to carbon-, water-, and energy-related processes.
Sergi Molins, Benjamin Andre, Jeffrey Johnson, Glenn Hammond, Benjamin Sulman, Konstantin Lipnikov, Marcus Day, James Beisman, Daniil Svyatsky, Hang Deng, Peter Lichtner, Carl Steefel, and David Moulton
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-108, https://doi.org/10.5194/gmd-2024-108, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
Developing scientific software and making sure it functions properly requires a significant effort. As we advance our understanding of natural systems, however, there is the need to develop yet more complex models and codes. In this work, we present a piece of software that facilitates this work, specifically with regard to reactive processes. Existing tried-and-true codes are made available via this new interface, freeing up resources to focus on the new aspects of the problems at hand.
Fang Li, Zhimin Zhou, Samuel Levis, Stephen Sitch, Felicity Hayes, Zhaozhong Feng, Peter B. Reich, Zhiyi Zhao, and Yanqing Zhou
Geosci. Model Dev., 17, 6173–6193, https://doi.org/10.5194/gmd-17-6173-2024, https://doi.org/10.5194/gmd-17-6173-2024, 2024
Short summary
Short summary
A new scheme is developed to model the surface ozone damage to vegetation in regional and global process-based models. Based on 4210 data points from ozone experiments, it accurately reproduces statistically significant linear or nonlinear photosynthetic and stomatal responses to ozone in observations for all vegetation types. It also enables models to implicitly capture the variability in plant ozone tolerance and the shift among species within a vegetation type.
Luke Oberhagemann, Maik Billing, Werner von Bloh, Markus Drüke, Matthew Forrest, Simon P. K. Bowring, Jessica Hetzer, Jaime Ribalaygua Batalla, and Kirsten Thonicke
EGUsphere, https://doi.org/10.5194/egusphere-2024-1914, https://doi.org/10.5194/egusphere-2024-1914, 2024
Short summary
Short summary
Under climate change, the conditions for wildfires to form are becoming more frequent in many parts of the world. To help predict how wildfires will change in future, global fire models are being developed. We analyze and further develop one such model, SPITFIRE. Our work identifies and corrects sources of substantial bias in the model that are important to the global fire modelling field. With this analysis and these developments, we help to provide a crucial platform for future developments.
Alexander S. Brunmayr, Frank Hagedorn, Margaux Moreno Duborgel, Luisa I. Minich, and Heather D. Graven
Geosci. Model Dev., 17, 5961–5985, https://doi.org/10.5194/gmd-17-5961-2024, https://doi.org/10.5194/gmd-17-5961-2024, 2024
Short summary
Short summary
A new generation of soil models promises to more accurately predict the carbon cycle in soils under climate change. However, measurements of 14C (the radioactive carbon isotope) in soils reveal that the new soil models face similar problems to the traditional models: they underestimate the residence time of carbon in soils and may therefore overestimate the net uptake of CO2 by the land ecosystem. Proposed solutions include restructuring the models and calibrating model parameters with 14C data.
Nina Raoult, Simon Beylat, James M. Salter, Frédéric Hourdin, Vladislav Bastrikov, Catherine Ottlé, and Philippe Peylin
Geosci. Model Dev., 17, 5779–5801, https://doi.org/10.5194/gmd-17-5779-2024, https://doi.org/10.5194/gmd-17-5779-2024, 2024
Short summary
Short summary
We use computer models to predict how the land surface will respond to climate change. However, these complex models do not always simulate what we observe in real life, limiting their effectiveness. To improve their accuracy, we use sophisticated statistical and computational techniques. We test a technique called history matching against more common approaches. This method adapts well to these models, helping us better understand how they work and therefore how to make them more realistic.
Jorn Bruggeman, Karsten Bolding, Lars Nerger, Anna Teruzzi, Simone Spada, Jozef Skákala, and Stefano Ciavatta
Geosci. Model Dev., 17, 5619–5639, https://doi.org/10.5194/gmd-17-5619-2024, https://doi.org/10.5194/gmd-17-5619-2024, 2024
Short summary
Short summary
To understand and predict the ocean’s capacity for carbon sequestration, its ability to supply food, and its response to climate change, we need the best possible estimate of its physical and biogeochemical properties. This is obtained through data assimilation which blends numerical models and observations. We present the Ensemble and Assimilation Tool (EAT), a flexible and efficient test bed that allows any scientist to explore and further develop the state of the art in data assimilation.
Dongyu Zheng, Andrew S. Merdith, Yves Goddéris, Yannick Donnadieu, Khushboo Gurung, and Benjamin J. W. Mills
Geosci. Model Dev., 17, 5413–5429, https://doi.org/10.5194/gmd-17-5413-2024, https://doi.org/10.5194/gmd-17-5413-2024, 2024
Short summary
Short summary
This study uses a deep learning method to upscale the time resolution of paleoclimate simulations to 1 million years. This improved resolution allows a climate-biogeochemical model to more accurately predict climate shifts. The method may be critical in developing new fully continuous methods that are able to be applied over a moving continental surface in deep time with high resolution at reasonable computational expense.
Wolfgang Knorr, Matthew Williams, Tea Thum, Thomas Kaminski, Michael Voßbeck, Marko Scholze, Tristan Quaife, Luke Smallmann, Susan Steele-Dunne, Mariette Vreugdenhil, Tim Green, Sönke Zähle, Mika Aurela, Alexandre Bouvet, Emanuel Bueechi, Wouter Dorigo, Tarek El-Madany, Mirco Migliavacca, Marika Honkanen, Yann Kerr, Anna Kontu, Juha Lemmetyinen, Hannakaisa Lindqvist, Arnaud Mialon, Tuuli Miinalainen, Gaetan Pique, Amanda Ojasalo, Shaun Quegan, Peter Rayner, Pablo Reyes-Muñoz, Nemesio Rodríguez-Fernández, Mike Schwank, Jochem Verrelst, Songyan Zhu, Dirk Schüttemeyer, and Matthias Drusch
EGUsphere, https://doi.org/10.5194/egusphere-2024-1534, https://doi.org/10.5194/egusphere-2024-1534, 2024
Short summary
Short summary
When it comes to climate change, the land surfaces are where the vast majority of impacts happen. The task of monitoring those across the globe is formidable and must necessarily rely on satellites – at a significant cost: the measurements are only indirect and require comprehensive physical understanding. We have created a comprehensive modelling system that we offer to the research community to explore how satellite data can be better exploited to help us see what changes on our lands.
Boris Ťupek, Aleksi Lehtonen, Alla Yurova, Rose Abramoff, Bertrand Guenet, Elisa Bruni, Samuli Launiainen, Mikko Peltoniemi, Shoji Hashimoto, Xianglin Tian, Juha Heikkinen, Kari Minkkinen, and Raisa Mäkipää
Geosci. Model Dev., 17, 5349–5367, https://doi.org/10.5194/gmd-17-5349-2024, https://doi.org/10.5194/gmd-17-5349-2024, 2024
Short summary
Short summary
Updating the Yasso07 soil C model's dependency on decomposition with a hump-shaped Ricker moisture function improved modelled soil organic C (SOC) stocks in a catena of mineral and organic soils in boreal forest. The Ricker function, set to peak at a rate of 1 and calibrated against SOC and CO2 data using a Bayesian approach, showed a maximum in well-drained soils. Using SOC and CO2 data together with the moisture only from the topsoil humus was crucial for accurate model estimates.
Tatsuya Miyauchi, Makoto Saito, Hibiki M. Noda, Akihiko Ito, Tomomichi Kato, and Tsuneo Matsunaga
EGUsphere, https://doi.org/10.5194/egusphere-2024-1542, https://doi.org/10.5194/egusphere-2024-1542, 2024
Short summary
Short summary
Solar-induced chlorophyll fluorescence (SIF) is an effective indicator for monitoring photosynthetic activity. This paper introduces VISIT-SIF, a biogeochemical process-based model developed to represent the global SIF observed by GOSAT. Our model simulation reproduced the global distribution and seasonal variations of GOSAT SIF. The model can be utilized to improve photosynthetic process through the combination of biogeochemical modeling and GOSAT SIF.
Trine Frisbæk Hansen, Donald Eugene Canfield, Ken Haste Andersen, and Christian Jannik Bjerrum
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-53, https://doi.org/10.5194/gmd-2024-53, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
We describe and test the size-based NUM model, that define organisms by a single set of parameters, on planktonic unicellular ecosystems in a eutrophic and an oligotrophic site. Results show both sites can be modelled with similar parameters, and a robust performance over a wide range of parameters. The study show that the NUM model is useful for non-experts and applicable for modelling domains with limited ecosystem data. It holds promise for evolutionary scenarios and deep-time climate models.
Jacquelyn K. Shuman, Rosie A. Fisher, Charles Koven, Ryan Knox, Lara Kueppers, and Chonggang Xu
Geosci. Model Dev., 17, 4643–4671, https://doi.org/10.5194/gmd-17-4643-2024, https://doi.org/10.5194/gmd-17-4643-2024, 2024
Short summary
Short summary
We adapt a fire behavior and effects module for use in a size-structured vegetation demographic model to test how climate, fire regime, and fire-tolerance plant traits interact to determine the distribution of tropical forests and grasslands. Our model captures the connection between fire disturbance and plant fire-tolerance strategies in determining plant distribution and provides a useful tool for understanding the vulnerability of these areas under changing conditions across the tropics.
Naveenkumar Parameswaran, Everardo González, Ewa Burwicz-Galerne, Malte Braack, and Klaus Wallmann
EGUsphere, https://doi.org/10.5194/egusphere-2024-1360, https://doi.org/10.5194/egusphere-2024-1360, 2024
Short summary
Short summary
Our research uses deep learning to predict organic carbon stocks in ocean sediments, crucial for understanding their role in the global carbon cycle. By analyzing over 22,000 samples and various seafloor characteristics, our model gives more accurate results than traditional methods. We estimate the top 10 cm of ocean sediments hold about 171 petagrams of carbon. This work enhances carbon stock estimates and helps plan future sampling strategies to better understand oceanic carbon burial.
Yoshiki Kanzaki, Isabella Chiaravalloti, Shuang Zhang, Noah J. Planavsky, and Christopher T. Reinhard
Geosci. Model Dev., 17, 4515–4532, https://doi.org/10.5194/gmd-17-4515-2024, https://doi.org/10.5194/gmd-17-4515-2024, 2024
Short summary
Short summary
Soil pH is one of the most commonly measured agronomical and biogeochemical indices, mostly reflecting exchangeable acidity. Explicit simulation of both porewater and bulk soil pH is thus crucial to the accurate evaluation of alkalinity required to counteract soil acidification and the resulting capture of anthropogenic carbon dioxide through the enhanced weathering technique. This has been enabled by the updated reactive–transport SCEPTER code and newly developed framework to simulate soil pH.
David Sandoval, Iain Colin Prentice, and Rodolfo L. B. Nóbrega
Geosci. Model Dev., 17, 4229–4309, https://doi.org/10.5194/gmd-17-4229-2024, https://doi.org/10.5194/gmd-17-4229-2024, 2024
Short summary
Short summary
Numerous estimates of water and energy balances depend on empirical equations requiring site-specific calibration, posing risks of "the right answers for the wrong reasons". We introduce novel first-principles formulations to calculate key quantities without requiring local calibration, matching predictions from complex land surface models.
Oliver Perkins, Matthew Kasoar, Apostolos Voulgarakis, Cathy Smith, Jay Mistry, and James D. A. Millington
Geosci. Model Dev., 17, 3993–4016, https://doi.org/10.5194/gmd-17-3993-2024, https://doi.org/10.5194/gmd-17-3993-2024, 2024
Short summary
Short summary
Wildfire is often presented in the media as a danger to human life. Yet globally, millions of people’s livelihoods depend on using fire as a tool. So, patterns of fire emerge from interactions between humans, land use, and climate. This complexity means scientists cannot yet reliably say how fire will be impacted by climate change. So, we developed a new model that represents globally how people use and manage fire. The model reveals the extent and diversity of how humans live with and use fire.
Amos P. K. Tai, David H. Y. Yung, and Timothy Lam
Geosci. Model Dev., 17, 3733–3764, https://doi.org/10.5194/gmd-17-3733-2024, https://doi.org/10.5194/gmd-17-3733-2024, 2024
Short summary
Short summary
We have developed the Terrestrial Ecosystem Model in R (TEMIR), which simulates plant carbon and pollutant uptake and predicts their response to varying atmospheric conditions. This model is designed to couple with an atmospheric chemistry model so that questions related to plant–atmosphere interactions, such as the effects of climate change, rising CO2, and ozone pollution on forest carbon uptake, can be addressed. The model has been well validated with both ground and satellite observations.
Fabian Stenzel, Johanna Braun, Jannes Breier, Karlheinz Erb, Dieter Gerten, Jens Heinke, Sarah Matej, Sebastian Ostberg, Sibyll Schaphoff, and Wolfgang Lucht
Geosci. Model Dev., 17, 3235–3258, https://doi.org/10.5194/gmd-17-3235-2024, https://doi.org/10.5194/gmd-17-3235-2024, 2024
Short summary
Short summary
We provide an R package to compute two biosphere integrity metrics that can be applied to simulations of vegetation growth from the dynamic global vegetation model LPJmL. The pressure metric BioCol indicates that we humans modify and extract > 20 % of the potential preindustrial natural biomass production. The ecosystems state metric EcoRisk shows a high risk of ecosystem destabilization in many regions as a result of climate change and land, water, and fertilizer use.
Elin Ristorp Aas, Heleen A. de Wit, and Terje K. Berntsen
Geosci. Model Dev., 17, 2929–2959, https://doi.org/10.5194/gmd-17-2929-2024, https://doi.org/10.5194/gmd-17-2929-2024, 2024
Short summary
Short summary
By including microbial processes in soil models, we learn how the soil system interacts with its environment and responds to climate change. We present a soil process model, MIMICS+, which is able to reproduce carbon stocks found in boreal forest soils better than a conventional land model. With the model we also find that when adding nitrogen, the relationship between soil microbes changes notably. Coupling the model to a vegetation model will allow for further study of these mechanisms.
Thomas Wutzler, Christian Reimers, Bernhard Ahrens, and Marion Schrumpf
Geosci. Model Dev., 17, 2705–2725, https://doi.org/10.5194/gmd-17-2705-2024, https://doi.org/10.5194/gmd-17-2705-2024, 2024
Short summary
Short summary
Soil microbes provide a strong link for elemental fluxes in the earth system. The SESAM model applies an optimality assumption to model those linkages and their adaptation. We found that a previous heuristic description was a special case of a newly developed more rigorous description. The finding of new behaviour at low microbial biomass led us to formulate the constrained enzyme hypothesis. We now can better describe how microbially mediated linkages of elemental fluxes adapt across decades.
Salvatore R. Curasi, Joe R. Melton, Elyn R. Humphreys, Txomin Hermosilla, and Michael A. Wulder
Geosci. Model Dev., 17, 2683–2704, https://doi.org/10.5194/gmd-17-2683-2024, https://doi.org/10.5194/gmd-17-2683-2024, 2024
Short summary
Short summary
Canadian forests are responding to fire, harvest, and climate change. Models need to quantify these processes and their carbon and energy cycling impacts. We develop a scheme that, based on satellite records, represents fire, harvest, and the sparsely vegetated areas that these processes generate. We evaluate model performance and demonstrate the impacts of disturbance on carbon and energy cycling. This work has implications for land surface modeling and assessing Canada’s terrestrial C cycle.
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
Short summary
Short summary
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.
Benjamin Post, Esteban Acevedo-Trejos, Andrew D. Barton, and Agostino Merico
Geosci. Model Dev., 17, 1175–1195, https://doi.org/10.5194/gmd-17-1175-2024, https://doi.org/10.5194/gmd-17-1175-2024, 2024
Short summary
Short summary
Creating computational models of how phytoplankton grows in the ocean is a technical challenge. We developed a new tool set (Xarray-simlab-ODE) for building such models using the programming language Python. We demonstrate the tool set in a library of plankton models (Phydra). Our goal was to allow scientists to develop models quickly, while also allowing the model structures to be changed easily. This allows us to test many different structures of our models to find the most appropriate one.
Taeken Wijmer, Ahmad Al Bitar, Ludovic Arnaud, Remy Fieuzal, and Eric Ceschia
Geosci. Model Dev., 17, 997–1021, https://doi.org/10.5194/gmd-17-997-2024, https://doi.org/10.5194/gmd-17-997-2024, 2024
Short summary
Short summary
Quantification of carbon fluxes of crops is an essential building block for the construction of a monitoring, reporting, and verification approach. We developed an end-to-end platform (AgriCarbon-EO) that assimilates, through a Bayesian approach, high-resolution (10 m) optical remote sensing data into radiative transfer and crop modelling at regional scale (100 x 100 km). Large-scale estimates of carbon flux are validated against in situ flux towers and yield maps and analysed at regional scale.
Moritz Laub, Sergey Blagodatsky, Marijn Van de Broek, Samuel Schlichenmaier, Benjapon Kunlanit, Johan Six, Patma Vityakon, and Georg Cadisch
Geosci. Model Dev., 17, 931–956, https://doi.org/10.5194/gmd-17-931-2024, https://doi.org/10.5194/gmd-17-931-2024, 2024
Short summary
Short summary
To manage soil organic matter (SOM) sustainably, we need a better understanding of the role that soil microbes play in aggregate protection. Here, we propose the SAMM model, which connects soil aggregate formation to microbial growth. We tested it against data from a tropical long-term experiment and show that SAMM effectively represents the microbial growth, SOM, and aggregate dynamics and that it can be used to explore the importance of aggregate formation in SOM stabilization.
Jianhong Lin, Daniel Berveiller, Christophe François, Heikki Hänninen, Alexandre Morfin, Gaëlle Vincent, Rui Zhang, Cyrille Rathgeber, and Nicolas Delpierre
Geosci. Model Dev., 17, 865–879, https://doi.org/10.5194/gmd-17-865-2024, https://doi.org/10.5194/gmd-17-865-2024, 2024
Short summary
Short summary
Currently, the high variability of budburst between individual trees is overlooked. The consequences of this neglect when projecting the dynamics and functioning of tree communities are unknown. Here we develop the first process-oriented model to describe the difference in budburst dates between individual trees in plant populations. Beyond budburst, the model framework provides a basis for studying the dynamics of phenological traits under climate change, from the individual to the community.
Skyler Kern, Mary E. McGuinn, Katherine M. Smith, Nadia Pinardi, Kyle E. Niemeyer, Nicole S. Lovenduski, and Peter E. Hamlington
Geosci. Model Dev., 17, 621–649, https://doi.org/10.5194/gmd-17-621-2024, https://doi.org/10.5194/gmd-17-621-2024, 2024
Short summary
Short summary
Computational models are used to simulate the behavior of marine ecosystems. The models often have unknown parameters that need to be calibrated to accurately represent observational data. Here, we propose a novel approach to simultaneously determine a large set of parameters for a one-dimensional model of a marine ecosystem in the surface ocean at two contrasting sites. By utilizing global and local optimization techniques, we estimate many parameters in a computationally efficient manner.
Shuaitao Wang, Vincent Thieu, Gilles Billen, Josette Garnier, Marie Silvestre, Audrey Marescaux, Xingcheng Yan, and Nicolas Flipo
Geosci. Model Dev., 17, 449–476, https://doi.org/10.5194/gmd-17-449-2024, https://doi.org/10.5194/gmd-17-449-2024, 2024
Short summary
Short summary
This paper presents unified RIVE v1.0, a unified version of the freshwater biogeochemistry model RIVE. It harmonizes different RIVE implementations, providing the referenced formalisms for microorganism activities to describe full biogeochemical cycles in the water column (e.g., carbon, nutrients, oxygen). Implemented as open-source projects in Python 3 (pyRIVE 1.0) and ANSI C (C-RIVE 0.32), unified RIVE v1.0 promotes and enhances collaboration among research teams and public services.
Sam S. Rabin, William J. Sacks, Danica L. Lombardozzi, Lili Xia, and Alan Robock
Geosci. Model Dev., 16, 7253–7273, https://doi.org/10.5194/gmd-16-7253-2023, https://doi.org/10.5194/gmd-16-7253-2023, 2023
Short summary
Short summary
Climate models can help us simulate how the agricultural system will be affected by and respond to environmental change, but to be trustworthy they must realistically reproduce historical patterns. When farmers plant their crops and what varieties they choose will be important aspects of future adaptation. Here, we improve the crop component of a global model to better simulate observed growing seasons and examine the impacts on simulated crop yields and irrigation demand.
Weihang Liu, Tao Ye, Christoph Müller, Jonas Jägermeyr, James A. Franke, Haynes Stephens, and Shuo Chen
Geosci. Model Dev., 16, 7203–7221, https://doi.org/10.5194/gmd-16-7203-2023, https://doi.org/10.5194/gmd-16-7203-2023, 2023
Short summary
Short summary
We develop a machine-learning-based crop model emulator with the inputs and outputs of multiple global gridded crop model ensemble simulations to capture the year-to-year variation of crop yield under future climate change. The emulator can reproduce the year-to-year variation of simulated yield given by the crop models under CO2, temperature, water, and nitrogen perturbations. Developing this emulator can provide a tool to project future climate change impact in a simple way.
Cited articles
Aalto, J., Aalto, P., Keronen, P., Kolari, P., Rantala, P., Taipale, R., Kajos, M., Patokoski, J., Rinne, J., Ruuskanen, T., Leskinen, M., Laakso, H., Levula, J., Pohja, T., Siivola, E., Kulmala, M., and Ylivinkka, I.: SMEAR II Hyytiälä forest meteorology, greenhouse gases, air quality and soil, University of Helsinki, Institute for Atmospheric and Earth System Research, https://doi.org/10.23729/23dd00b2-b9d7-467a-9cee-b4a122486039, 2022. a
Alekseychik, P., Peltola, O., Li, X., Aurela, M., Hatakka, J., Pihlatie, M., Rinne, J., Haapanala, S., Laakso, H., Taipale, R., Matilainen, T., Salminen, T., and Levula, J.: SMEAR II Siikaneva 1 wetland eddy covariance, University of Helsinki, Institute for Atmospheric and Earth System Research, https://doi.org/10.23729/bcc98726-ead8-45d4-ac39-1e4b1bf5e243, 2019a. a
Alekseychik, P., Kolari, P., Rinne, J., Haapanala, S., Laakso, H., Taipale, R., Matilainen, T., Salminen, T., Levula, J., and Tuittila, E.-S.: SMEAR II Siikaneva 1 wetland meteorology and soil, Universiy of Helsinki, Institute for Atmospheric and Earth System Research, https://doi.org/10.23729/371cd3e4-26ae-41c9-96d7-69acccc206f7, 2019b. a, b
Aurela, M., Riutta, T., Laurila, T., Tuovinen, J.-P., Vesala, T., Tuittila, E.-S., Rinne, J., Haapanala, S., and Laine, J.: CO2 exchange of a sedge fen in southern Finland-The impact of a drought period, Tellus B, 59, 826–837, 2007. a
Aurela, M., Lohila, A., Tuovinen, J.-P., Hatakka, J., Riutta, T., and Laurila, T.: Carbon dioxide exchange on a northern boreal fen, Boreal Environ. Res., 14, 699, 2009. a
Bauer, L. and Hamby, D.: Relative sensitivities of existing and novel model parameters in atmospheric tritium dose estimates, Radiat. Prot. Dosim., 37, 253–260, 1991. a
Bousquet, P., Ciais, P., Miller, J., Dlugokencky, E. J., Hauglustaine, D., Prigent, C., Van der Werf, G., Peylin, P., Brunke, E.-G., Carouge, C., and Langenfelds, R.: Contribution of anthropogenic and natural sources to atmospheric methane variability, Nature, 443, 439–443, 2006. a
Braswell, B. H., Sacks, W. J., Linder, E., and Schimel, D. S.: Estimating diurnal to annual ecosystem parameters by synthesis of a carbon flux model with eddy covariance net ecosystem exchange observations, Glob. Change Biol., 11, 335–355, 2005. a
Bridgham, S. D., Pastor, J., Dewey, B., Weltzin, J. F., and Updegraff, K.: Rapid carbon response of peatlands to climate change, Ecology, 89, 3041–3048, 2008. a
Broecker, W. S. and Peng, T.-H.: Gas exchange rates between air and sea, Tellus, 26, 21–35, 1974. a
Carrassi, A., Bocquet, M., Bertino, L., and Evensen, G.: Data assimilation in the geosciences: An overview of methods, issues, and perspectives, Wiley Interdisciplinary Reviews: Climate Change, 9, e535, https://doi.org/10.1002/wcc.535, 2018. a
Christensen, J. H., Hewitson, B., Busuioc, A., Chen, A., Gao, X., Held, I., Jones, R., Kolli, R. K., Kwon, W.-T., Laprise, R., and Magaña Rueda, V.: Regional climate projections, in: Climate Change 2007: the physical science basis Chapter 11, Cambridge University Press, 847–940, 2007. a
Ciais, P., Sabine, C., Bala, G., Bopp, L., Brovkin, V., Canadell, J., Chhabra, A., DeFries, R., Galloway, J., Heimann, M., and Jones, C.: Carbon and other biogeochemical cycles. Climate change 2013: the physical science basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, Comput. Geom., 18, 95–123, 2013. a
Cronk, J. K. and Fennessy, M. S.: Wetland plants: biology and ecology, CRC press, https://doi.org/10.1201/9781420032925, 2016. a
Dee, D. P.: Bias and data assimilation, Quarterly Journal of the Royal Meteorological Society: A journal of the atmospheric sciences, Applied Meteorology and Physical Oceanography, 131, 3323–3343, 2005. a
Dlugokencky, E.: NOAA/GML (gml. noaa. gov/ccgg/trends_ch4/), NOAA/GML, https://doi.org/10.15138/P8XG-AA10, 2021. a
Forster, P., Storelvmo, T., Armour, K., Collins, W., Dufresne, J.-L., Frame, D., Lunt, D., Mauritsen, T., Palmer, M., Watanabe, M., Wild, M., and Zhang, H.: The Earth’s Energy Budget, Climate Feedbacks, and Climate Sensitivity, Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 923–1054, https://doi.org/10.1017/9781009157896.009, 2021. a
Gelman, A., Roberts, G., and Gilks, W.: Efficient Metropolis jumping rules, in: Bayesian Statistics 5, edited by: Bernardo, J. M., Berger, J. O., Dawid, A. P., and Smith, A. F. M., 599–607, Oxford University Press, https://doi.org/10.1093/oso/9780198523567.003.0038, 1996. a
Ghil, M. and Malanotte-Rizzoli, P.: Data assimilation in meteorology and oceanography, in: Advances in geophysics, 33, 141–266, Elsevier, https://doi.org/10.1016/S0065-2687(08)60442-2, 1991. a
Gustafson, A.: On the role of terrestrial ecosystems in a changing Arctic, Media-Tryck, Lund University, Sweden, 2022. a
Hastings, W. K.: Monte Carlo sampling methods using Markov chains and their applications, Biometrika, 57, 97–97, 1970b. a
Hoffman, F. O. and Miller, C. W.: Uncertainties in environmental radiological assessment models and their implications, Tech. rep., Oak Ridge National Lab., https://doi.org/10.1093/biomet/57.1.97, 1983. a
Jacob, D., Bärring, L., Christensen, O. B., Christensen, J. H., de Castro, M., Deque, M., Giorgi, F., Hagemann, S., Hirschi, M., Jones, R., and Kjellström, E.: An inter-comparison of regional climate models for Europe: model performance in present-day climate, Clim. Change, 81, 31–52, 2007. a
Johansson, T., Malmer, N., Crill, P. M., Friborg, T., Åkerman, J. H., Mastepanov, M., and Christensen, T. R.: Decadal vegetation changes in a northern peatland, greenhouse gas fluxes and net radiative forcing, Glob. Change biol., 12, 2352–2369, 2006. a
Kallingal, J. T., Scholze, M., A. Miller, P., Lindstrom, J., Rinne, J., and Raivonen, M.: Optimising the CH4 simulations from the LPJ-GUESS model using Adaptive MCMC, Zenodo [code, data set], https://doi.org/10.5281/zenodo.7339240, 2022. a
Korrensalo, A., Männistö, E., Alekseychik, P., Mammarella, I., Rinne, J., Vesala, T., and Tuittila, E.-S.: Small spatial variability in methane emission measured from a wet patterned boreal bog, Biogeosciences, 15, 1749–1761, https://doi.org/10.5194/bg-15-1749-2018, 2018. a
Korrensalo, A., Mammarella, I., Alekseychik, P., Vesala, T., and Tuittila, E.: Plant mediated methane efflux from a boreal peatland complex, Plant Soil, 471, 375–392, 2022. a
Kuppel, S., Peylin, P., Chevallier, F., Bacour, C., Maignan, F., and Richardson, A. D.: Constraining a global ecosystem model with multi-site eddy-covariance data, Biogeosciences, 9, 3757–3776, https://doi.org/10.5194/bg-9-3757-2012, 2012. a
Lerman, A.: Geochemical processes. Water and sediment environments, John Wiley and Sons, Inc., 1979. a
Mathijssen, P. J., Väliranta, M., Korrensalo, A., Alekseychik, P., Vesala, T., Rinne, J., and Tuittila, E.-S.: Reconstruction of Holocene carbon dynamics in a large boreal peatland complex, southern Finland, Quaternary Sci. Rev., 142, 1–15, 2016. a
McGuire, A., Sitch, S., Clein, J. S., Dargaville, R., Esser, G., Foley, J., Heimann, M., Joos, F., Kaplan, J., Kicklighter, D., and Meier, R.: Carbon balance of the terrestrial biosphere in the twentieth century: Analyses of CO2, climate and land use effects with four process-based ecosystem models, Global Biogeochem. Cy., 15, 183–206, 2001. a
McGuire, A. D., Christensen, T. R., Hayes, D., Heroult, A., Euskirchen, E., Kimball, J. S., Koven, C., Lafleur, P., Miller, P. A., Oechel, W., Peylin, P., Williams, M., and Yi, Y.: An assessment of the carbon balance of Arctic tundra: comparisons among observations, process models, and atmospheric inversions, Biogeosciences, 9, 3185–3204, https://doi.org/10.5194/bg-9-3185-2012, 2012. a
Metropolis, N., Rosenbluth, A., Rosenbluth, M., Teller, A., and Teller, E.: Equations of state calculations by fast computing machines, J. Chem. Phys., 21, 1087–1092, 1953a. a
Metropolis, N., Rosenbluth, A. W., Rosenbluth, M. N., Teller, A. H., and Teller, E.: Equation of state calculations by fast computing machines, J. Chem. Phys., 21, 1087–1092, 1953b. a
Millington, R. and Quirk, J.: Permeability of porous solids, T. Faraday Soc., 57, 1200–1207, 1961. a
Nord, J., Anthoni, P., Gregor, K., Gustafson, A., Hantson, S., Lindeskog, M., Meyer, B., Miller, P., Nieradzik, L., Olin, S., Papastefanou, P., Smith, B., Tang, J., Wårlind, D., and and past LPJ-GUESS contributors: LPJ-GUESS Release v4.1.1 model code (4.1.1), Zenodo [code], https://doi.org/10.5281/zenodo.8065737, 2021. a
Rinne, J., Tuittila, E.-S., Peltola, O., Li, X., Raivonen, M., Alekseychik, P., Haapanala, S., Pihlatie, M., Aurela, M., Mammarella, I., and Vesala, T.: Temporal variation of ecosystem scale methane emission from a boreal fen in relation to temperature, water table position, and carbon dioxide fluxes, Global Biogeochem. Cy., 32, 1087–1106, 2018. a
Roberts, G., Gelman, A., and Gilks, W.: Weak convergence and optimal scaling of random walk Metropolis algorithms, Ann. Probab., 7, 110–120, 1997. a
Santaren, D., Peylin, P., Bacour, C., Ciais, P., and Longdoz, B.: Ecosystem model optimization using in situ flux observations: benefit of Monte Carlo versus variational schemes and analyses of the year-to-year model performances, Biogeosciences, 11, 7137–7158, https://doi.org/10.5194/bg-11-7137-2014, 2014. a
Saunois, M., Jackson, R., Bousquet, P., Poulter, B., and Canadell, J.: The growing role of methane in anthropogenic climate change, Environ. Res. Lett., 11, 120207, https://doi.org/10.1088/1748-9326/11/12/120207, 2016. a
Saunois, M., Stavert, A. R., Poulter, B., Bousquet, P., Canadell, J. G., Jackson, R. B., Raymond, P. A., Dlugokencky, E. J., Houweling, S., Patra, P. K., Ciais, P., Arora, V. K., Bastviken, D., Bergamaschi, P., Blake, D. R., Brailsford, G., Bruhwiler, L., Carlson, K. M., Carrol, M., Castaldi, S., Chandra, N., Crevoisier, C., Crill, P. M., Covey, K., Curry, C. L., Etiope, G., Frankenberg, C., Gedney, N., Hegglin, M. I., Höglund-Isaksson, L., Hugelius, G., Ishizawa, M., Ito, A., Janssens-Maenhout, G., Jensen, K. M., Joos, F., Kleinen, T., Krummel, P. B., Langenfelds, R. L., Laruelle, G. G., Liu, L., Machida, T., Maksyutov, S., McDonald, K. C., McNorton, J., Miller, P. A., Melton, J. R., Morino, I., Müller, J., Murguia-Flores, F., Naik, V., Niwa, Y., Noce, S., O'Doherty, S., Parker, R. J., Peng, C., Peng, S., Peters, G. P., Prigent, C., Prinn, R., Ramonet, M., Regnier, P., Riley, W. J., Rosentreter, J. A., Segers, A., Simpson, I. J., Shi, H., Smith, S. J., Steele, L. P., Thornton, B. F., Tian, H., Tohjima, Y., Tubiello, F. N., Tsuruta, A., Viovy, N., Voulgarakis, A., Weber, T. S., van Weele, M., van der Werf, G. R., Weiss, R. F., Worthy, D., Wunch, D., Yin, Y., Yoshida, Y., Zhang, W., Zhang, Z., Zhao, Y., Zheng, B., Zhu, Q., Zhu, Q., and Zhuang, Q.: The Global Methane Budget 2000–2017, Earth Syst. Sci. Data, 12, 1561–1623, https://doi.org/10.5194/essd-12-1561-2020, 2020. a
Segers, R.: Methane production and methane consumption: a review of processes underlying wetland methane fluxes, Biogeochemistry, 41, 23–51, 1998. a
Sitch, S., Smith, B., Prentice, I. C., Arneth, A., Bondeau, A., Cramer, W., Kaplan, J. O., Levis, S., Lucht, W., Sykes, M. T., and Thonicke, K.: Evaluation of ecosystem dynamics, plant geography and terrestrial carbon cycling in the LPJ dynamic global vegetation model, Glob. Change Biol., 9, 161–185, 2003. a
Smith, B.: LPJ-GUESS-an ecosystem modelling framework, Department of Physical Geography and Ecosystems Analysis, INES, Sölvegatan, 12, 22362, 2001. a
Smith, B., Wårlind, D., Arneth, A., Hickler, T., Leadley, P., Siltberg, J., and Zaehle, S.: Implications of incorporating N cycling and N limitations on primary production in an individual-based dynamic vegetation model, Biogeosciences, 11, 2027–2054, https://doi.org/10.5194/bg-11-2027-2014, 2014. a, b
Susiluoto, J., Raivonen, M., Backman, L., Laine, M., Makela, J., Peltola, O., Vesala, T., and Aalto, T.: Calibrating the sqHIMMELI v1.0 wetland methane emission model with hierarchical modeling and adaptive MCMC, Geosci. Model Dev., 11, 1199–1228, https://doi.org/10.5194/gmd-11-1199-2018, 2018. a, b, c, d
Tang, J., Miller, P. A., Persson, A., Olefeldt, D., Pilesjö, P., Heliasz, M., Jackowicz-Korczynski, M., Yang, Z., Smith, B., Callaghan, T. V., and Christensen, T. R.: Carbon budget estimation of a subarctic catchment using a dynamic ecosystem model at high spatial resolution, Biogeosciences, 12, 2791–2808, https://doi.org/10.5194/bg-12-2791-2015, 2015. a
Tarantola, A.: Inversion of travel times and seismic waveforms, Seismic tomography, 135–157,https://doi.org/10.1007/978-94-009-3899-1_6, 1987. a, b, c
Wania, R., Ross, I., and Prentice, I. C.: Integrating peatlands and permafrost into a dynamic global vegetation model: 1. Evaluation and sensitivity of physical land surface processes, Global Biogeochem. Cy., 23, https://doi.org/10.1029/2008GB003412, 2009a. a, b
Wania, R., Melton, J. R., Hodson, E. L., Poulter, B., Ringeval, B., Spahni, R., Bohn, T., Avis, C. A., Chen, G., Eliseev, A. V., Hopcroft, P. O., Riley, W. J., Subin, Z. M., Tian, H., van Bodegom, P. M., Kleinen, T., Yu, Z. C., Singarayer, J. S., Zürcher, S., Lettenmaier, D. P., Beerling, D. J., Denisov, S. N., Prigent, C., Papa, F., and Kaplan, J. O.: Present state of global wetland extent and wetland methane modelling: methodology of a model inter-comparison project (WETCHIMP), Geosci. Model Dev., 6, 617–641, https://doi.org/10.5194/gmd-6-617-2013, 2013. a
Wramneby, A., Smith, B., Zaehle, S., and Sykes, M. T.: Parameter uncertainties in the modelling of vegetation dynamics–effects on tree community structure and ecosystem functioning in European forest biomes, Ecol. Model., 216, 277–290, 2008. a
Zhang, W., Miller, P. A., Smith, B., Wania, R., Koenigk, T., and Döscher, R.: Tundra shrubification and tree-line advance amplify arctic climate warming: results from an individual-based dynamic vegetation model, Environ. Res. Lett., 8, 034023, https://doi.org/10.1088/1748-9326/8/3/034023, 2013. a
Zhang, Z., Zimmermann, N. E., Stenke, A., Li, X., Hodson, E. L., Zhu, G., Huang, C., and Poulter, B.: Emerging role of wetland methane emissions in driving 21st century climate change, P. Natl. Acad. Sci. USA, 114, 9647–9652, 2017. a
Short summary
By unlocking the mysteries of CH4 emissions from wetlands, our work improved the accuracy of the LPJ-GUESS vegetation model using Bayesian statistics. Via assimilation of long-term real data from a wetland, we significantly enhanced CH4 emission predictions. This advancement helps us better understand wetland contributions to atmospheric CH4, which are crucial for addressing climate change. Our method offers a promising tool for refining global climate models and guiding conservation efforts
By unlocking the mysteries of CH4 emissions from wetlands, our work improved the accuracy of the...
