Articles | Volume 13, issue 9
https://doi.org/10.5194/gmd-13-4091-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-13-4091-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model evaluation paper
| 
07 Sep 2020
Model evaluation paper |
| 07 Sep 2020
| 07 Sep 2020
Short-term forecasting of regional biospheric CO2 fluxes in Europe using a light-use-efficiency model (VPRM, MPI-BGC version 1.2)
Department of Biogeochemical Signals, Max Planck Institute for
Biogeochemistry, 07745 Jena, Germany
Christoph Gerbig
Department of Biogeochemical Signals, Max Planck Institute for
Biogeochemistry, 07745 Jena, Germany
Julia Marshall
Department of Biogeochemical Signals, Max Planck Institute for
Biogeochemistry, 07745 Jena, Germany
Kai Uwe Totsche
Department of Hydrogeology, Institute of Geosciences, Friedrich Schiller University Jena, 07743 Jena, Germany
Related authors
Alina Fiehn, Julian Kostinek, Maximilian Eckl, Theresa Klausner, Michał Gałkowski, Jinxuan Chen, Christoph Gerbig, Thomas Röckmann, Hossein Maazallahi, Martina Schmidt, Piotr Korbeń, Jarosław Neçki, Pawel Jagoda, Norman Wildmann, Christian Mallaun, Rostyslav Bun, Anna-Leah Nickl, Patrick Jöckel, Andreas Fix, and Anke Roiger
Atmos. Chem. Phys., 20, 12675–12695, https://doi.org/10.5194/acp-20-12675-2020, https://doi.org/10.5194/acp-20-12675-2020, 2020
Short summary
Short summary
A severe reduction of greenhouse gas emissions is necessary to fulfill the Paris Agreement. We use aircraft- and ground-based in situ observations of trace gases and wind speed from two flights over the Upper Silesian Coal Basin, Poland, for independent emission estimation. The derived methane emission estimates are within the range of emission inventories, carbon dioxide estimates are in the lower range and carbon monoxide emission estimates are slightly higher than emission inventory values.
Mengyao Liu, Jintai Lin, Yuchen Wang, Yang Sun, Bo Zheng, Jingyuan Shao, Lulu Chen, Yixuan Zheng, Jinxuan Chen, Tzung-May Fu, Yingying Yan, Qiang Zhang, and Zhaohua Wu
Atmos. Chem. Phys., 18, 12933–12952, https://doi.org/10.5194/acp-18-12933-2018, https://doi.org/10.5194/acp-18-12933-2018, 2018
Short summary
Short summary
Eastern China is heavily polluted by NO2, PM2.5, and other air pollutants. Our study uses EOF–EEMD to analyze the spatiotemporal variability of ground-level NO2, PM2.5, and their associations with meteorological processes. Their regular diurnal cycles are mainly affected by human activities, while irregular day-to-day variations are dominated by weather processes representing synchronous variation or north–south opposing changes over Eastern China.
Fabian Maier, Eva Falge, Maksym Gachkivskyi, Stephan Henne, Ute Karstens, Dafina Kikaj, Ingeborg Levin, Alistair Manning, Christian Rödenbeck, and Christoph Gerbig
EGUsphere, https://doi.org/10.5194/egusphere-2025-477, https://doi.org/10.5194/egusphere-2025-477, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
The radioactive noble gas radon (222Rn) is a suitable natural tracer for atmospheric transport and mixing processes that can be used to validate and calibrate atmospheric transport models. However, this requires accurate estimates of the 222Rn flux from the soil into the atmosphere. In our study, we evaluate the reliability of process-based 222Rn flux maps for Europe using a 222Rn inversion. Our inversion results can give some indications on how to improve the process-based 222Rn flux maps.
Theo Glauch, Julia Marshall, Christoph Gerbig, Santiago Botía, Michał Gałkowski, Sanam N. Vardag, and André Butz
EGUsphere, https://doi.org/10.5194/egusphere-2024-3692, https://doi.org/10.5194/egusphere-2024-3692, 2025
Short summary
Short summary
The Vegetation Photosynthesis and Respiration Model (VPRM) estimates carbon exchange between the atmosphere and biosphere by modeling gross primary production and respiration using satellite data and weather variables. Our new version, pyVPRM, supports diverse satellite products like Sentinel-2, MODIS, VIIRS and new land cover maps, enabling high spatial and temporal resolution. This improves flux estimates, especially in complex landscapes, and ensures continuity as MODIS nears decommissioning.
Saqr Munassar, Christian Rödenbeck, Michał Gałkowski, Frank-Thomas Koch, Kai U. Totsche, Santiago Botía, and Christoph Gerbig
Atmos. Chem. Phys., 25, 639–656, https://doi.org/10.5194/acp-25-639-2025, https://doi.org/10.5194/acp-25-639-2025, 2025
Short summary
Short summary
CO2 mole fractions simulated over a global set of stations showed an overestimation of CO2 if the diurnal cycle is missing in biogenic fluxes. This leads to biases in the estimated fluxes derived from the regional-scale inversions. Interannual variability of estimated biogenic fluxes is also affected by the exclusion of the CO2 diurnal cycle. The findings point to the importance of including the diurnal variations of CO2 in the biogenic fluxes used as priors in global and regional inversions.
Michał Gałkowski, Julia Marshall, Blanca Fuentes Andrade, and Christoph Gerbig
EGUsphere, https://doi.org/10.5194/egusphere-2024-2792, https://doi.org/10.5194/egusphere-2024-2792, 2024
Short summary
Short summary
Observations of GHG emissions are needed to monitor the progress towards Paris Agreement goals. Remote sensing instruments have been used to estimate emissions from the strongest anthropogenic sources. Here, we study the impact of atmospheric turbulence on the estimation of CO2 with a realistic atmospheric model, and we show that the formation of persistent plume structures causes uncertainty on the order of 10 % of total emission that cannot be avoided.
Sven Krautwurst, Christian Fruck, Sebastian Wolff, Jakob Borchardt, Oke Huhs, Konstantin Gerilowski, Michał Gałkowski, Christoph Kiemle, Mathieu Quatrevalet, Martin Wirth, Christian Mallaun, John P. Burrows, Christoph Gerbig, Andreas Fix, Hartmut Bösch, and Heinrich Bovensmann
EGUsphere, https://doi.org/10.5194/egusphere-2024-3182, https://doi.org/10.5194/egusphere-2024-3182, 2024
Short summary
Short summary
Anomalously high CH4 emissions from landfills in Madrid, Spain, have been observed by satellite measurements in recent years. Our investigations of these waste facilities using passive and active airborne remote sensing measurements confirm these high emission rates with values of up to 13 th-1 during the overflight and show excellent agreement between the two techniques. A large fraction of the emissions is attributed to active landfill sites.
David Ho, Michał Gałkowski, Friedemann Reum, Santiago Botía, Julia Marshall, Kai Uwe Totsche, and Christoph Gerbig
Geosci. Model Dev., 17, 7401–7422, https://doi.org/10.5194/gmd-17-7401-2024, https://doi.org/10.5194/gmd-17-7401-2024, 2024
Short summary
Short summary
Atmospheric model users often overlook the impact of the land–atmosphere interaction. This study accessed various setups of WRF-GHG simulations that ensure consistency between the model and driving reanalysis fields. We found that a combination of nudging and frequent re-initialization allows certain improvement by constraining the soil moisture fields and, through its impact on atmospheric mixing, improves atmospheric transport.
Dieu Anh Tran, Christoph Gerbig, Christian Rödenbeck, and Sönke Zaehle
Atmos. Chem. Phys., 24, 8413–8440, https://doi.org/10.5194/acp-24-8413-2024, https://doi.org/10.5194/acp-24-8413-2024, 2024
Short summary
Short summary
The analysis of the atmospheric CO2 record from the Zotino Tall Tower Observatory (ZOTTO) in central Siberia shows significant increases in the length and amplitude of the CO2 uptake and release in the 2010–2021 period. The trend shows a stronger increase in carbon release amplitude compared to the uptake, suggesting that, despite enhanced growing season uptake, during this period climate warming did not elevate the annual net CO2 uptake as cold-season respirations also responded to the warming.
Fabian Maier, Christian Rödenbeck, Ingeborg Levin, Christoph Gerbig, Maksym Gachkivskyi, and Samuel Hammer
Atmos. Chem. Phys., 24, 8183–8203, https://doi.org/10.5194/acp-24-8183-2024, https://doi.org/10.5194/acp-24-8183-2024, 2024
Short summary
Short summary
We investigate the usage of discrete radiocarbon (14C)-based fossil fuel carbon dioxide (ffCO2) concentration estimates vs. continuous carbon monoxide (CO)-based ffCO2 estimates to evaluate the seasonal cycle of ffCO2 emissions in an urban region with an inverse modeling framework. We find that the CO-based ffCO2 estimates allow us to reconstruct robust seasonal cycles, which show the distinct COVID-19 drawdown in 2020 and can be used to validate emission inventories.
Santiago Botía, Saqr Munassar, Thomas Koch, Danilo Custodio, Luana S. Basso, Shujiro Komiya, Jost V. Lavric, David Walter, Manuel Gloor, Giordane Martins, Stijn Naus, Gerbrand Koren, Ingrid Luijkx, Stijn Hantson, John B. Miller, Wouter Peters, Christian Rödenbeck, and Christoph Gerbig
EGUsphere, https://doi.org/10.5194/egusphere-2024-1735, https://doi.org/10.5194/egusphere-2024-1735, 2024
Short summary
Short summary
This study uses CO2 data from the Amazon Tall Tower Observatory and airborne profiles to estimate net carbon exchange. We found that the biogeographic Amazon is a net carbon sink, while the Cerrado and Caatinga biomes are net carbon sources, resulting in an overall neutral balance. To further reduce the uncertainty in our estimates we call for an expansion of the monitoring capacity, especially in the Amazon-Andes foothills.
Theertha Kariyathan, Ana Bastos, Markus Reichstein, Wouter Peters, and Julia Marshall
EGUsphere, https://doi.org/10.5194/egusphere-2024-1382, https://doi.org/10.5194/egusphere-2024-1382, 2024
Short summary
Short summary
The carbon uptake period (CUP) refers to the time of the year when there is net absorption of CO2 from the atmosphere to the land. Several studies have assessed changes in CUP based on seasonal metrics from CO2 mole fraction measurements to understand the response of terrestrial biosphere to climate variations. However, we find that the CUP derived from CO2 mole fraction measurements are not likely to provide an accurate magnitude of the actual changes occurring over the surface.
Vishnu Thilakan, Dhanyalekshmi Pillai, Jithin Sukumaran, Christoph Gerbig, Haseeb Hakkim, Vinayak Sinha, Yukio Terao, Manish Naja, and Monish Vijay Deshpande
Atmos. Chem. Phys., 24, 5315–5335, https://doi.org/10.5194/acp-24-5315-2024, https://doi.org/10.5194/acp-24-5315-2024, 2024
Short summary
Short summary
This study investigates the usability of CO2 mixing ratio observations over India to infer regional carbon sources and sinks. We demonstrate that a high-resolution modelling system can represent the observed CO2 variations reasonably well by improving the transport and flux variations at a fine scale. Future carbon data assimilation systems can thus benefit from these recently available CO2 observations when fine-scale variations are adequately represented in the models.
Christian Rödenbeck, Karina E. Adcock, Markus Eritt, Maksym Gachkivskyi, Christoph Gerbig, Samuel Hammer, Armin Jordan, Ralph F. Keeling, Ingeborg Levin, Fabian Maier, Andrew C. Manning, Heiko Moossen, Saqr Munassar, Penelope A. Pickers, Michael Rothe, Yasunori Tohjima, and Sönke Zaehle
Atmos. Chem. Phys., 23, 15767–15782, https://doi.org/10.5194/acp-23-15767-2023, https://doi.org/10.5194/acp-23-15767-2023, 2023
Short summary
Short summary
The carbon dioxide content of the Earth atmosphere is increasing due to human emissions from burning of fossil fuels, causing global climate change. The strength of the fossil-fuel emissions is estimated by inventories based on energy data, but independent validation of these inventories has been recommended by the Intergovernmental Panel on Climate Change. Here we investigate the potential to validate inventories based on measurements of small changes in the atmospheric oxygen content.
Alina Fiehn, Maximilian Eckl, Julian Kostinek, Michał Gałkowski, Christoph Gerbig, Michael Rothe, Thomas Röckmann, Malika Menoud, Hossein Maazallahi, Martina Schmidt, Piotr Korbeń, Jarosław Neçki, Mila Stanisavljević, Justyna Swolkień, Andreas Fix, and Anke Roiger
Atmos. Chem. Phys., 23, 15749–15765, https://doi.org/10.5194/acp-23-15749-2023, https://doi.org/10.5194/acp-23-15749-2023, 2023
Short summary
Short summary
During the CoMet mission in the Upper Silesian Coal Basin (USCB) ground-based and airborne air samples were taken and analyzed for the isotopic composition of CH4 to derive the mean signature of the USCB and source signatures of individual coal mines. Using δ2H signatures, the biogenic emissions from the USCB account for 15 %–50 % of total emissions, which is underestimated in common emission inventories. This demonstrates the importance of δ2H-CH4 observations for methane source apportionment.
Xinxu Zhao, Jia Chen, Julia Marshall, Michal Gałkowski, Stephan Hachinger, Florian Dietrich, Ankit Shekhar, Johannes Gensheimer, Adrian Wenzel, and Christoph Gerbig
Atmos. Chem. Phys., 23, 14325–14347, https://doi.org/10.5194/acp-23-14325-2023, https://doi.org/10.5194/acp-23-14325-2023, 2023
Short summary
Short summary
We develop a modeling framework using the Weather Research and Forecasting model at a high spatial resolution (up to 400 m) to simulate atmospheric transport of greenhouse gases and interpret column observations. Output is validated against weather stations and column measurements in August 2018. The differential column method is applied, aided by air-mass transport tracing with the Stochastic Time-Inverted Lagrangian Transport (STILT) model, also for an exploratory measurement interpretation.
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.
Theertha Kariyathan, Ana Bastos, Julia Marshall, Wouter Peters, Pieter Tans, and Markus Reichstein
Atmos. Meas. Tech., 16, 3299–3312, https://doi.org/10.5194/amt-16-3299-2023, https://doi.org/10.5194/amt-16-3299-2023, 2023
Short summary
Short summary
The timing and duration of the carbon uptake period (CUP) are sensitive to the occurrence of major phenological events, which are influenced by recent climate change. This study presents an ensemble-based approach for quantifying the timing and duration of the CUP and their uncertainty when derived from atmospheric CO2 measurements with noise and gaps. The CUP metrics derived with the approach are more robust and have less uncertainty than when estimated with the conventional methods.
Aparnna Ravi, Dhanyalekshmi Pillai, Christoph Gerbig, Stephen Sitch, Sönke Zaehle, Vishnu Thilakan, and Chandra Shekhar Jha
EGUsphere, https://doi.org/10.5194/egusphere-2023-817, https://doi.org/10.5194/egusphere-2023-817, 2023
Preprint archived
Short summary
Short summary
We derive high-resolution terrestrial CO2 fluxes over India from 2012 to 2020. This is achieved by utilizing satellite-based vegetation indices and meteorological data in a data-driven biospheric model. The model simulations are improved by incorporating soil variables and SIF retrievals from satellite instruments and relate them to ecosystem productivity across different biomes. The derived flux products better explain the flux variability compared to other existing model estimates.
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.
Dominik Brunner, Gerrit Kuhlmann, Stephan Henne, Erik Koene, Bastian Kern, Sebastian Wolff, Christiane Voigt, Patrick Jöckel, Christoph Kiemle, Anke Roiger, Alina Fiehn, Sven Krautwurst, Konstantin Gerilowski, Heinrich Bovensmann, Jakob Borchardt, Michal Galkowski, Christoph Gerbig, Julia Marshall, Andrzej Klonecki, Pascal Prunet, Robert Hanfland, Margit Pattantyús-Ábrahám, Andrzej Wyszogrodzki, and Andreas Fix
Atmos. Chem. Phys., 23, 2699–2728, https://doi.org/10.5194/acp-23-2699-2023, https://doi.org/10.5194/acp-23-2699-2023, 2023
Short summary
Short summary
We evaluated six atmospheric transport models for their capability to simulate the CO2 plumes from two of the largest power plants in Europe by comparing the models against aircraft observations collected during the CoMet (Carbon Dioxide and Methane Mission) campaign in 2018. The study analyzed how realistically such plumes can be simulated at different model resolutions and how well the planned European satellite mission CO2M will be able to quantify emissions from power plants.
Vishnu Thilakan, Dhanyalekshmi Pillai, Christoph Gerbig, Michal Galkowski, Aparnna Ravi, and Thara Anna Mathew
Atmos. Chem. Phys., 22, 15287–15312, https://doi.org/10.5194/acp-22-15287-2022, https://doi.org/10.5194/acp-22-15287-2022, 2022
Short summary
Short summary
This paper demonstrates how we can use atmospheric observations to improve the CO2 flux estimates in India. This is achieved by improving the representation of terrain, mesoscale transport, and flux variations. We quantify the impact of the unresolved variations in the current models on optimally estimated fluxes via inverse modelling and quantify the associated flux uncertainty. We illustrate how a parameterization scheme captures this variability in the coarse models.
Elise Potier, Grégoire Broquet, Yilong Wang, Diego Santaren, Antoine Berchet, Isabelle Pison, Julia Marshall, Philippe Ciais, François-Marie Bréon, and Frédéric Chevallier
Atmos. Meas. Tech., 15, 5261–5288, https://doi.org/10.5194/amt-15-5261-2022, https://doi.org/10.5194/amt-15-5261-2022, 2022
Short summary
Short summary
Atmospheric inversion at local–regional scales over Europe and pseudo-data assimilation are used to evaluate how CO2 and 14CO2 ground-based measurement networks could complement satellite CO2 imagers to monitor fossil fuel (FF) CO2 emissions. This combination significantly improves precision in the FF emission estimates in areas with a dense network but does not strongly support the separation of the FF from the biogenic signals or the spatio-temporal extrapolation of the satellite information.
Simone M. Pieber, Béla Tuzson, Stephan Henne, Ute Karstens, Christoph Gerbig, Frank-Thomas Koch, Dominik Brunner, Martin Steinbacher, and Lukas Emmenegger
Atmos. Chem. Phys., 22, 10721–10749, https://doi.org/10.5194/acp-22-10721-2022, https://doi.org/10.5194/acp-22-10721-2022, 2022
Short summary
Short summary
Understanding regional greenhouse gas emissions into the atmosphere is a prerequisite to mitigate climate change. In this study, we investigated the regional contributions of carbon dioxide (CO2) at the location of the high Alpine observatory Jungfraujoch (JFJ, Switzerland, 3580 m a.s.l.). To this purpose, we combined receptor-oriented atmospheric transport simulations for CO2 concentration in the period 2009–2017 with stable carbon isotope (δ13C–CO2) information.
Fabian Maier, Christoph Gerbig, Ingeborg Levin, Ingrid Super, Julia Marshall, and Samuel Hammer
Geosci. Model Dev., 15, 5391–5406, https://doi.org/10.5194/gmd-15-5391-2022, https://doi.org/10.5194/gmd-15-5391-2022, 2022
Short summary
Short summary
We show that the default representation of point source emissions in WRF–STILT leads to large overestimations when modelling fossil fuel CO2 concentrations for a 30 m high observation site during stable atmospheric conditions. We therefore introduce a novel point source modelling approach in WRF-STILT that takes into account their effective emission heights and results in a much better agreement with observations.
Saqr Munassar, Christian Rödenbeck, Frank-Thomas Koch, Kai U. Totsche, Michał Gałkowski, Sophia Walther, and Christoph Gerbig
Atmos. Chem. Phys., 22, 7875–7892, https://doi.org/10.5194/acp-22-7875-2022, https://doi.org/10.5194/acp-22-7875-2022, 2022
Short summary
Short summary
The results obtained from ensembles of inversions over 13 years show the largest spread in the a posteriori fluxes over the station set ensemble. Using different prior fluxes in the inversions led to a smaller impact. Drought occurrences in 2018 and 2019 affected CO2 fluxes as seen in net ecosystem exchange estimates. Our study highlights the importance of expanding the atmospheric site network across Europe to better constrain CO2 fluxes in inverse modelling.
Sven Krautwurst, Konstantin Gerilowski, Jakob Borchardt, Norman Wildmann, Michał Gałkowski, Justyna Swolkień, Julia Marshall, Alina Fiehn, Anke Roiger, Thomas Ruhtz, Christoph Gerbig, Jaroslaw Necki, John P. Burrows, Andreas Fix, and Heinrich Bovensmann
Atmos. Chem. Phys., 21, 17345–17371, https://doi.org/10.5194/acp-21-17345-2021, https://doi.org/10.5194/acp-21-17345-2021, 2021
Short summary
Short summary
Quantification of anthropogenic CH4 emissions remains challenging, but it is essential for near-term climate mitigation strategies. We use airborne remote sensing observations to assess bottom-up estimates of coal mining emissions from one of Europe's largest CH4 emission hot spots located in Poland. The analysis reveals that emissions from small groups of shafts can be disentangled, but caution is advised when comparing observations to commonly reported annual emissions.
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.
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.
Vishnu Thilakan, Dhanyalekshmi Pillai, Christoph Gerbig, Michal Galkowski, Aparnna Ravi, and Thara Anna Mathew
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2021-392, https://doi.org/10.5194/acp-2021-392, 2021
Revised manuscript not accepted
Short summary
Short summary
This paper demonstrates how we can make use of atmospheric observations to improve the CO2 flux estimates of India. This is achieved by improving the representation of terrain, mesoscale transport and flux variations. We quantify the impact of unresolved variations in the current models on optimally estimated fluxes via inverse modelling and quantify the associated flux uncertainty. We illustrate how a parameterization scheme captures this variability in the coarse models.
Ashique Vellalassery, Dhanyalekshmi Pillai, Julia Marshall, Christoph Gerbig, Michael Buchwitz, Oliver Schneising, and Aparnna Ravi
Atmos. Chem. Phys., 21, 5393–5414, https://doi.org/10.5194/acp-21-5393-2021, https://doi.org/10.5194/acp-21-5393-2021, 2021
Short summary
Short summary
We investigate factors contributing to the severe and persistent air quality degradation in northern India that has worsened during every winter over the last decade. This is achieved by implementing atmospheric modelling and using recently available Sentinel-5 P satellite data for carbon monoxide. We see a minimal role of biomass burning, except for the state of Punjab. The aim is to focus on residential and industrial emission reduction strategies to tackle air pollution over northern India.
Michał Gałkowski, Armin Jordan, Michael Rothe, Julia Marshall, Frank-Thomas Koch, Jinxuan Chen, Anna Agusti-Panareda, Andreas Fix, and Christoph Gerbig
Atmos. Meas. Tech., 14, 1525–1544, https://doi.org/10.5194/amt-14-1525-2021, https://doi.org/10.5194/amt-14-1525-2021, 2021
Short summary
Short summary
We present results of atmospheric measurements of greenhouse gases, performed over Europe in 2018 aboard German research aircraft HALO as part of the CoMet 1.0 (Carbon Dioxide and Methane Mission). In our analysis, we describe data quality, discuss observed mixing ratios and show an example of describing a regional methane source using stable isotopic composition based on the collected air samples. We also quantitatively compare our results to selected global atmospheric modelling systems.
Alina Fiehn, Julian Kostinek, Maximilian Eckl, Theresa Klausner, Michał Gałkowski, Jinxuan Chen, Christoph Gerbig, Thomas Röckmann, Hossein Maazallahi, Martina Schmidt, Piotr Korbeń, Jarosław Neçki, Pawel Jagoda, Norman Wildmann, Christian Mallaun, Rostyslav Bun, Anna-Leah Nickl, Patrick Jöckel, Andreas Fix, and Anke Roiger
Atmos. Chem. Phys., 20, 12675–12695, https://doi.org/10.5194/acp-20-12675-2020, https://doi.org/10.5194/acp-20-12675-2020, 2020
Short summary
Short summary
A severe reduction of greenhouse gas emissions is necessary to fulfill the Paris Agreement. We use aircraft- and ground-based in situ observations of trace gases and wind speed from two flights over the Upper Silesian Coal Basin, Poland, for independent emission estimation. The derived methane emission estimates are within the range of emission inventories, carbon dioxide estimates are in the lower range and carbon monoxide emission estimates are slightly higher than emission inventory values.
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.
Santiago Botía, Christoph Gerbig, Julia Marshall, Jost V. Lavric, David Walter, Christopher Pöhlker, Bruna Holanda, Gilberto Fisch, Alessandro Carioca de Araújo, Marta O. Sá, Paulo R. Teixeira, Angélica F. Resende, Cleo Q. Dias-Junior, Hella van Asperen, Pablo S. Oliveira, Michel Stefanello, and Otávio C. Acevedo
Atmos. Chem. Phys., 20, 6583–6606, https://doi.org/10.5194/acp-20-6583-2020, https://doi.org/10.5194/acp-20-6583-2020, 2020
Short summary
Short summary
A long record of atmospheric methane concentrations in central Amazonia was analyzed. We describe events in which concentrations at 79 m are higher than at 4 m. These events are more frequent during the nighttime of dry season, but we found no association with fire signals. Instead, we suggest that a combination of nighttime transport and a nearby source could explain such events. Our research gives insights into how methane is transported in the complex nocturnal atmosphere in Amazonia.
Anna-Leah Nickl, Mariano Mertens, Anke Roiger, Andreas Fix, Axel Amediek, Alina Fiehn, Christoph Gerbig, Michal Galkowski, Astrid Kerkweg, Theresa Klausner, Maximilian Eckl, and Patrick Jöckel
Geosci. Model Dev., 13, 1925–1943, https://doi.org/10.5194/gmd-13-1925-2020, https://doi.org/10.5194/gmd-13-1925-2020, 2020
Short summary
Short summary
Based on the global and regional chemistry–climate model system MECO(n), we implemented a forecast system to support the planning of measurement campaign research flights with chemical weather forecasts. We applied this system for the first time to provide 6 d forecasts in support of the CoMet 1.0
campaign targeting methane emitted from coal mining ventilation shafts in the Upper Silesian Coal Basin in Poland. We describe the new forecast system and evaluate its forecast skill.
Martin Kunz, Jost V. Lavric, Rainer Gasche, Christoph Gerbig, Richard H. Grant, Frank-Thomas Koch, Marcus Schumacher, Benjamin Wolf, and Matthias Zeeman
Atmos. Meas. Tech., 13, 1671–1692, https://doi.org/10.5194/amt-13-1671-2020, https://doi.org/10.5194/amt-13-1671-2020, 2020
Short summary
Short summary
The nocturnal boundary layer (NBL) budget method enables the quantification of gas fluxes between ecosystems and the atmosphere under nocturnal stable stratification, a condition under which standard approaches struggle. However, up to now the application of the NBL method has been limited by difficulties in obtaining the required measurements. We show how an unmanned aircraft system (UAS) equipped with a carbon dioxide analyser can make this method more accessible.
Gerrit Kuhlmann, Grégoire Broquet, Julia Marshall, Valentin Clément, Armin Löscher, Yasjka Meijer, and Dominik Brunner
Atmos. Meas. Tech., 12, 6695–6719, https://doi.org/10.5194/amt-12-6695-2019, https://doi.org/10.5194/amt-12-6695-2019, 2019
Short summary
Short summary
The Copernicus Anthropogenic CO2 Monitoring (CO2M) mission is a proposed constellation of imaging satellites with a CO2 instrument as main payload and optionally instruments for NO2, CO and aerosols. This study demonstrates the huge benefit of an NO2 instrument for detecting city plumes and weak point sources. Its main advantages are the higher signal-to-noise ratio and the lower sensitivity to clouds that significantly increases the number of observations available for quantifying CO2 emission.
Xinxu Zhao, Julia Marshall, Stephan Hachinger, Christoph Gerbig, Matthias Frey, Frank Hase, and Jia Chen
Atmos. Chem. Phys., 19, 11279–11302, https://doi.org/10.5194/acp-19-11279-2019, https://doi.org/10.5194/acp-19-11279-2019, 2019
Short summary
Short summary
The Weather Research and Forecasting model (WRF), coupled with greenhouse gas (GHG) modules (WRF-GHG), is considered to be a suitable basis for precise GHG transport analysis in urban areas, especially when combined with differential column methodology (DCM). DCM is an effective method not only for comparing models to observations independently of biases caused, for example, by initial conditions, but also for detecting and understanding sources of GHG emissions quantitatively in urban areas.
Dominik Brunner, Gerrit Kuhlmann, Julia Marshall, Valentin Clément, Oliver Fuhrer, Grégoire Broquet, Armin Löscher, and Yasjka Meijer
Atmos. Chem. Phys., 19, 4541–4559, https://doi.org/10.5194/acp-19-4541-2019, https://doi.org/10.5194/acp-19-4541-2019, 2019
Short summary
Short summary
Atmospheric transport models are increasingly being used to estimate CO2 emissions from atmospheric CO2 measurements. This study demonstrates the importance of distributing CO2 emissions vertically in the model according to realistic profiles, since a major proportion of CO2 is emitted through tall stacks from power plants and industrial sources. With the traditional approach of emitting all CO2 at the surface, models may significantly overestimate the atmospheric CO2 levels.
Friedemann Reum, Christoph Gerbig, Jost V. Lavric, Chris W. Rella, and Mathias Göckede
Atmos. Meas. Tech., 12, 1013–1027, https://doi.org/10.5194/amt-12-1013-2019, https://doi.org/10.5194/amt-12-1013-2019, 2019
Short summary
Short summary
Atmospheric CO2 and CH4 mole fractions are often measured using greenhouse gas analyzers manufactured by Picarro, Inc. We report biases in these measurements that are related to pressure changes in the optical cavity of the analyzers and occur mainly at low water vapor mole fractions. We provide a method to correct the biases, which contributes to keeping the overall accuracy of CO2 and CH4 measurements with Picarro analyzers within the WMO interlaboratory compatibility goals.
Annette Filges, Christoph Gerbig, Chris W. Rella, John Hoffnagle, Herman Smit, Martina Krämer, Nicole Spelten, Christian Rolf, Zoltán Bozóki, Bernhard Buchholz, and Volker Ebert
Atmos. Meas. Tech., 11, 5279–5297, https://doi.org/10.5194/amt-11-5279-2018, https://doi.org/10.5194/amt-11-5279-2018, 2018
Mengyao Liu, Jintai Lin, Yuchen Wang, Yang Sun, Bo Zheng, Jingyuan Shao, Lulu Chen, Yixuan Zheng, Jinxuan Chen, Tzung-May Fu, Yingying Yan, Qiang Zhang, and Zhaohua Wu
Atmos. Chem. Phys., 18, 12933–12952, https://doi.org/10.5194/acp-18-12933-2018, https://doi.org/10.5194/acp-18-12933-2018, 2018
Short summary
Short summary
Eastern China is heavily polluted by NO2, PM2.5, and other air pollutants. Our study uses EOF–EEMD to analyze the spatiotemporal variability of ground-level NO2, PM2.5, and their associations with meteorological processes. Their regular diurnal cycles are mainly affected by human activities, while irregular day-to-day variations are dominated by weather processes representing synchronous variation or north–south opposing changes over Eastern China.
Fabio Boschetti, Valerie Thouret, Greet Janssens Maenhout, Kai Uwe Totsche, Julia Marshall, and Christoph Gerbig
Atmos. Chem. Phys., 18, 9225–9241, https://doi.org/10.5194/acp-18-9225-2018, https://doi.org/10.5194/acp-18-9225-2018, 2018
Short summary
Short summary
Retrieving surface–atmosphere fluxes from the combination of atmospheric observations with atmospheric transport models can benefit from combining multiple species in a single inversion. The underlying effect is that species such as CO2 and CO have partially overlapping emission patterns for given sectors and fuel types and so share part of the uncertainties, both related to the a priori knowledge of emissions, and to model–data mismatch error. We show this for airborne profile data from IAGOS.
Mary E. Whelan, Sinikka T. Lennartz, Teresa E. Gimeno, Richard Wehr, Georg Wohlfahrt, Yuting Wang, Linda M. J. Kooijmans, Timothy W. Hilton, Sauveur Belviso, Philippe Peylin, Róisín Commane, Wu Sun, Huilin Chen, Le Kuai, Ivan Mammarella, Kadmiel Maseyk, Max Berkelhammer, King-Fai Li, Dan Yakir, Andrew Zumkehr, Yoko Katayama, Jérôme Ogée, Felix M. Spielmann, Florian Kitz, Bharat Rastogi, Jürgen Kesselmeier, Julia Marshall, Kukka-Maaria Erkkilä, Lisa Wingate, Laura K. Meredith, Wei He, Rüdiger Bunk, Thomas Launois, Timo Vesala, Johan A. Schmidt, Cédric G. Fichot, Ulli Seibt, Scott Saleska, Eric S. Saltzman, Stephen A. Montzka, Joseph A. Berry, and J. Elliott Campbell
Biogeosciences, 15, 3625–3657, https://doi.org/10.5194/bg-15-3625-2018, https://doi.org/10.5194/bg-15-3625-2018, 2018
Short summary
Short summary
Measurements of the trace gas carbonyl sulfide (OCS) are helpful in quantifying photosynthesis at previously unknowable temporal and spatial scales. While CO2 is both consumed and produced within ecosystems, OCS is mostly produced in the oceans or from specific industries, and destroyed in plant leaves in proportion to CO2. This review summarizes the advancements we have made in the understanding of OCS exchange and applications to vital ecosystem water and carbon cycle questions.
Martin Kunz, Jost V. Lavric, Christoph Gerbig, Pieter Tans, Don Neff, Christine Hummelgård, Hans Martin, Henrik Rödjegård, Burkhard Wrenger, and Martin Heimann
Atmos. Meas. Tech., 11, 1833–1849, https://doi.org/10.5194/amt-11-1833-2018, https://doi.org/10.5194/amt-11-1833-2018, 2018
Short summary
Short summary
Unmanned aircraft could provide a cost-effective way to close gaps in the observation of the carbon cycle, provided that small yet accurate analysers are available. We have developed a COmpact Carbon dioxide analyser for Airborne Platforms (COCAP). During validation of its CO2 measurements in simulated and real flights we found a measurement error of 1.2 μmol mol−1 or better with no indication of bias. COCAP is a self-contained package that has proven well suited for operation on board UASs.
Panagiotis Kountouris, Christoph Gerbig, Christian Rödenbeck, Ute Karstens, Thomas Frank Koch, and Martin Heimann
Atmos. Chem. Phys., 18, 3027–3045, https://doi.org/10.5194/acp-18-3027-2018, https://doi.org/10.5194/acp-18-3027-2018, 2018
Panagiotis Kountouris, Christoph Gerbig, Christian Rödenbeck, Ute Karstens, Thomas F. Koch, and Martin Heimann
Atmos. Chem. Phys., 18, 3047–3064, https://doi.org/10.5194/acp-18-3047-2018, https://doi.org/10.5194/acp-18-3047-2018, 2018
Peter Bergamaschi, Ute Karstens, Alistair J. Manning, Marielle Saunois, Aki Tsuruta, Antoine Berchet, Alexander T. Vermeulen, Tim Arnold, Greet Janssens-Maenhout, Samuel Hammer, Ingeborg Levin, Martina Schmidt, Michel Ramonet, Morgan Lopez, Jost Lavric, Tuula Aalto, Huilin Chen, Dietrich G. Feist, Christoph Gerbig, László Haszpra, Ove Hermansen, Giovanni Manca, John Moncrieff, Frank Meinhardt, Jaroslaw Necki, Michal Galkowski, Simon O'Doherty, Nina Paramonova, Hubertus A. Scheeren, Martin Steinbacher, and Ed Dlugokencky
Atmos. Chem. Phys., 18, 901–920, https://doi.org/10.5194/acp-18-901-2018, https://doi.org/10.5194/acp-18-901-2018, 2018
Short summary
Short summary
European methane (CH4) emissions are estimated for 2006–2012 using atmospheric in situ measurements from 18 European monitoring stations and 7 different inverse models. Our analysis highlights the potential significant contribution of natural emissions from wetlands (including peatlands and wet soils) to the total European emissions. The top-down estimates of total EU-28 CH4 emissions are broadly consistent with the sum of reported anthropogenic CH4 emissions and the estimated natural emissions.
Bernd Kohlhepp, Robert Lehmann, Paul Seeber, Kirsten Küsel, Susan E. Trumbore, and Kai U. Totsche
Hydrol. Earth Syst. Sci., 21, 6091–6116, https://doi.org/10.5194/hess-21-6091-2017, https://doi.org/10.5194/hess-21-6091-2017, 2017
Rebecca Elizabeth Cooper, Karin Eusterhues, Carl-Eric Wegner, Kai Uwe Totsche, and Kirsten Küsel
Biogeosciences, 14, 5171–5188, https://doi.org/10.5194/bg-14-5171-2017, https://doi.org/10.5194/bg-14-5171-2017, 2017
Short summary
Short summary
In this study we show increasing organic matter (OM) content on ferrihydrite surfaces enhances Fe reduction by the model Fe reducer S. oneidensis and a microbial consortia extracted from peat. Similarities in reduction rates between S. oneidensis and the consortia suggest electron shuttling dominates in OM-rich soils. Community profile analyses showed enrichment of fermenters with pure ferrihydrite, whereas OM–mineral complexes favored enrichment of Fe-reducing Desulfobacteria and Pelosinus sp.
Martin E. Nowak, Valérie F. Schwab, Cassandre S. Lazar, Thomas Behrendt, Bernd Kohlhepp, Kai Uwe Totsche, Kirsten Küsel, and Susan E. Trumbore
Hydrol. Earth Syst. Sci., 21, 4283–4300, https://doi.org/10.5194/hess-21-4283-2017, https://doi.org/10.5194/hess-21-4283-2017, 2017
Short summary
Short summary
In the present study we combined measurements of dissolved inorganic carbon (DIC) isotopes with a set of different geochemical and microbiological methods in order to get a comprehensive view of biogeochemical cycling and groundwater flow in two limestone aquifer assemblages. This allowed us to understand interactions and feedbacks between microbial communities, their carbon sources, and water chemistry.
Shreeya Verma, Julia Marshall, Mark Parrington, Anna Agustí-Panareda, Sebastien Massart, Martyn P. Chipperfield, Christopher Wilson, and Christoph Gerbig
Atmos. Chem. Phys., 17, 6663–6678, https://doi.org/10.5194/acp-17-6663-2017, https://doi.org/10.5194/acp-17-6663-2017, 2017
Short summary
Short summary
Aircraft profiles are a useful reference for validation of satellite-based column-averaged dry air mole fraction data. However, these are available only up to about 9–13 km altitude and therefore need to be extended synthetically into the stratosphere using other sources. In this study, we analyse three different data sources that are available for extension of CH4 profiles by comparing the error introduced by each into the total column and provide recommendations regarding the best approach.
Friedemann Reum, Christoph Gerbig, Jost V. Lavric, Chris W. Rella, and Mathias Göckede
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2017-174, https://doi.org/10.5194/amt-2017-174, 2017
Revised manuscript not accepted
Short summary
Short summary
High-accuracy observations of atmospheric CO2 and CH4 levels, which are vital for quantifying sources and sinks of these gases, are often obtained using Picarro greenhouse gas analyzers. These require a correction for the effects of water vapor. We report biases in CO2 and CH4 levels obtained using the traditional water correction for Picarro analyzers related to pressure changes in the optical cavity and mainly affecting measurements at low water vapor mole fractions, and how to correct them.
Valérie F. Schwab, Martina Herrmann, Vanessa-Nina Roth, Gerd Gleixner, Robert Lehmann, Georg Pohnert, Susan Trumbore, Kirsten Küsel, and Kai U. Totsche
Biogeosciences, 14, 2697–2714, https://doi.org/10.5194/bg-14-2697-2017, https://doi.org/10.5194/bg-14-2697-2017, 2017
Short summary
Short summary
We used phospholipid fatty acids (PLFAs) to link specific microbial markers to the spatio-temporal changes of groundwater physico-chemistry. PLFA-based functional groups were directly supported by DNA/RNA results. O2 resulted in increased eukaryotic biomass and abundance of nitrite-oxidizing bacteria but impeded anammox, sulphate-reducing and iron-reducing bacteria. Our study demonstrates the power of PLFA-based approaches to study the nature and activity of microorganisms in pristine aquifers.
Shreeya Verma, Julia Marshall, Christoph Gerbig, Christian Rödenbeck, and Kai Uwe Totsche
Atmos. Chem. Phys., 17, 5665–5675, https://doi.org/10.5194/acp-17-5665-2017, https://doi.org/10.5194/acp-17-5665-2017, 2017
Short summary
Short summary
The inverse modelling approach for estimating surface fluxes is based on transport models that have an imperfect representation of atmospheric processes like vertical mixing. In this paper, we show how assimilating commercial aircraft-based vertical profiles of CO2 into inverse models can help reduce error due to the transport model, thus providing more accurate estimates of surface fluxes. Further, the reduction in flux uncertainty due to aircraft profiles from the IAGOS project is quantified.
Aki Tsuruta, Tuula Aalto, Leif Backman, Janne Hakkarainen, Ingrid T. van der Laan-Luijkx, Maarten C. Krol, Renato Spahni, Sander Houweling, Marko Laine, Ed Dlugokencky, Angel J. Gomez-Pelaez, Marcel van der Schoot, Ray Langenfelds, Raymond Ellul, Jgor Arduini, Francesco Apadula, Christoph Gerbig, Dietrich G. Feist, Rigel Kivi, Yukio Yoshida, and Wouter Peters
Geosci. Model Dev., 10, 1261–1289, https://doi.org/10.5194/gmd-10-1261-2017, https://doi.org/10.5194/gmd-10-1261-2017, 2017
Short summary
Short summary
In this study, we found that the average global methane emission for 2000–2012, estimated by the CTE-CH4 model, was 516±51 Tg CH4 yr-1, and the estimates for 2007–2012 were 4 % larger than for 2000–2006. The model estimates are sensitive to inputs and setups, but according to sensitivity tests the study suggests that the increase in atmospheric methane concentrations during 21st century was due to an increase in emissions from the 35S-EQ latitudinal bands.
Marielle Saunois, Philippe Bousquet, Ben Poulter, Anna Peregon, Philippe Ciais, Josep G. Canadell, Edward J. Dlugokencky, Giuseppe Etiope, David Bastviken, Sander Houweling, Greet Janssens-Maenhout, Francesco N. Tubiello, Simona Castaldi, Robert B. Jackson, Mihai Alexe, Vivek K. Arora, David J. Beerling, Peter Bergamaschi, Donald R. Blake, Gordon Brailsford, Victor Brovkin, Lori Bruhwiler, Cyril Crevoisier, Patrick Crill, Kristofer Covey, Charles Curry, Christian Frankenberg, Nicola Gedney, Lena Höglund-Isaksson, Misa Ishizawa, Akihiko Ito, Fortunat Joos, Heon-Sook Kim, Thomas Kleinen, Paul Krummel, Jean-François Lamarque, Ray Langenfelds, Robin Locatelli, Toshinobu Machida, Shamil Maksyutov, Kyle C. McDonald, Julia Marshall, Joe R. Melton, Isamu Morino, Vaishali Naik, Simon O'Doherty, Frans-Jan W. Parmentier, Prabir K. Patra, Changhui Peng, Shushi Peng, Glen P. Peters, Isabelle Pison, Catherine Prigent, Ronald Prinn, Michel Ramonet, William J. Riley, Makoto Saito, Monia Santini, Ronny Schroeder, Isobel J. Simpson, Renato Spahni, Paul Steele, Atsushi Takizawa, Brett F. Thornton, Hanqin Tian, Yasunori Tohjima, Nicolas Viovy, Apostolos Voulgarakis, Michiel van Weele, Guido R. van der Werf, Ray Weiss, Christine Wiedinmyer, David J. Wilton, Andy Wiltshire, Doug Worthy, Debra Wunch, Xiyan Xu, Yukio Yoshida, Bowen Zhang, Zhen Zhang, and Qiuan Zhu
Earth Syst. Sci. Data, 8, 697–751, https://doi.org/10.5194/essd-8-697-2016, https://doi.org/10.5194/essd-8-697-2016, 2016
Short summary
Short summary
An accurate assessment of the methane budget is important to understand the atmospheric methane concentrations and trends and to provide realistic pathways for climate change mitigation. The various and diffuse sources of methane as well and its oxidation by a very short lifetime radical challenge this assessment. We quantify the methane sources and sinks as well as their uncertainties based on both bottom-up and top-down approaches provided by a broad international scientific community.
Dhanyalekshmi Pillai, Michael Buchwitz, Christoph Gerbig, Thomas Koch, Maximilian Reuter, Heinrich Bovensmann, Julia Marshall, and John P. Burrows
Atmos. Chem. Phys., 16, 9591–9610, https://doi.org/10.5194/acp-16-9591-2016, https://doi.org/10.5194/acp-16-9591-2016, 2016
Short summary
Short summary
Approximately 70 % of total CO2 emissions arise from cities; however, there exist large uncertainties in quantifying urban emissions. The present study investigates the potential of a satellite mission like CarbonSat to retrieve the city emissions via inverse modelling techniques. The study makes a valid conclusion that an instrument like CarbonSat has high potential to provide important information on city emissions when exploiting the observations using a high-resolution modelling system.
Sha Feng, Thomas Lauvaux, Sally Newman, Preeti Rao, Ravan Ahmadov, Aijun Deng, Liza I. Díaz-Isaac, Riley M. Duren, Marc L. Fischer, Christoph Gerbig, Kevin R. Gurney, Jianhua Huang, Seongeun Jeong, Zhijin Li, Charles E. Miller, Darragh O'Keeffe, Risa Patarasuk, Stanley P. Sander, Yang Song, Kam W. Wong, and Yuk L. Yung
Atmos. Chem. Phys., 16, 9019–9045, https://doi.org/10.5194/acp-16-9019-2016, https://doi.org/10.5194/acp-16-9019-2016, 2016
Short summary
Short summary
We developed a high-resolution land–atmosphere modelling system for urban CO2 emissions over the LA Basin. We evaluated various model configurations, FFCO2 products, and the impact of the model resolution. FFCO2 emissions outpace the atmospheric model resolution to represent the CO2 concentration variability across the basin. A novel forward model approach is presented to evaluate the surface measurement network, reinforcing the importance of using high-resolution emission products.
P. Kountouris, C. Gerbig, K.-U. Totsche, A. J. Dolman, A. G. C. A. Meesters, G. Broquet, F. Maignan, B. Gioli, L. Montagnani, and C. Helfter
Biogeosciences, 12, 7403–7421, https://doi.org/10.5194/bg-12-7403-2015, https://doi.org/10.5194/bg-12-7403-2015, 2015
N. Kadygrov, G. Broquet, F. Chevallier, L. Rivier, C. Gerbig, and P. Ciais
Atmos. Chem. Phys., 15, 12765–12787, https://doi.org/10.5194/acp-15-12765-2015, https://doi.org/10.5194/acp-15-12765-2015, 2015
Short summary
Short summary
We study the potential of the European Integrated Carbon Observing System (ICOS) atmospheric network for estimating European CO2 ecosystem fluxes. Regional atmospheric inversions with synthetic data are used to derive it in terms of statistical uncertainty. This potential is high in western Europe and future extensions of the network will increase it in eastern Europe. Future improvements of the models underlying the inversion should also significantly decrease uncertainties at high resolution.
S. N. Vardag, C. Gerbig, G. Janssens-Maenhout, and I. Levin
Atmos. Chem. Phys., 15, 12705–12729, https://doi.org/10.5194/acp-15-12705-2015, https://doi.org/10.5194/acp-15-12705-2015, 2015
Short summary
Short summary
In this model sensitivity study we compare and evaluate the surrogate tracers CO2, CO, δ13C-CO2 and Δ14C-CO2 for estimating continuous anthropogenic CO2. The results can be used to optimize the measurement network design with respect to the partitioning of total CO2 into biospheric and anthropogenic CO2 contributions. This enables improvement and validation of highly resolved emission inventories using atmospheric observation and regional modeling.
G. Biavati, D. G. Feist, C. Gerbig, and R. Kretschmer
Atmos. Meas. Tech., 8, 4215–4230, https://doi.org/10.5194/amt-8-4215-2015, https://doi.org/10.5194/amt-8-4215-2015, 2015
Short summary
Short summary
The goal of this work is to present a method that can be used to estimate the uncertainty for a singular estimate for the mixing height. It is defined here as the localization error. The method is based on the actual signal (radiosonde) and its measurement errors, ant it does not consider the physics causing the signal.
It can be applied to all kind of signals and algorithm when standard error propagation cannot be used to asses the uncertainty of a location of a localized property.
J. F. Mori, T. R. Neu, S. Lu, M. Händel, K. U. Totsche, and K. Küsel
Biogeosciences, 12, 5277–5289, https://doi.org/10.5194/bg-12-5277-2015, https://doi.org/10.5194/bg-12-5277-2015, 2015
Short summary
Short summary
We studied filamentous macroscopic algae growing in metal-rich stream water that leaked from a former uranium-mining district. These algae were encrusted with Fe-deposits that were associated with microbes, mainly Gallionella-related Fe-oxidizing bacteria, and extracellular polymeric substances. Algae with a lower number of chloroplasts often exhibited discontinuous series of precipitates, likely due to the intercalary growth of algae which allowed them to avoid detrimental encrustation.
V. Proschek, G. Kirchengast, S. Schweitzer, J. S. A. Brooke, P. F. Bernath, C. B. Thomas, J.-G. Wang, K. A. Tereszchuk, G. González Abad, R. J. Hargreaves, C. A. Beale, J. J. Harrison, P. A. Martin, V. L. Kasyutich, C. Gerbig, O. Kolle, and A. Loescher
Atmos. Meas. Tech., 8, 3315–3336, https://doi.org/10.5194/amt-8-3315-2015, https://doi.org/10.5194/amt-8-3315-2015, 2015
M. M. Bela, K. M. Longo, S. R. Freitas, D. S. Moreira, V. Beck, S. C. Wofsy, C. Gerbig, K. Wiedemann, M. O. Andreae, and P. Artaxo
Atmos. Chem. Phys., 15, 757–782, https://doi.org/10.5194/acp-15-757-2015, https://doi.org/10.5194/acp-15-757-2015, 2015
Short summary
Short summary
In the Amazon Basin, gases that lead to the formation of ozone (O3), an air pollutant and greenhouse gas, are emitted from fire, urban and biogenic sources. This study presents the first basin wide aircraft measurements of O3 during the dry-to-wet and wet-to-dry transition seasons, which show extremely low values above undisturbed forest and increases from fires. This work also demonstrates the capabilities and limitations of regional atmospheric chemistry models in representing O3 in Amazonia.
D. Tátrai, Z. Bozóki, H. Smit, C. Rolf, N. Spelten, M. Krämer, A. Filges, C. Gerbig, G. Gulyás, and G. Szabó
Atmos. Meas. Tech., 8, 33–42, https://doi.org/10.5194/amt-8-33-2015, https://doi.org/10.5194/amt-8-33-2015, 2015
Short summary
Short summary
Airborne hygrometry is very important in climate research, and the interest in knowing not only water vapor concentration but (cirrus) cloud content as well is increasing. The authors provide a photoacoustic spectroscopy-based dual-channel hygrometer system that can be a good solution for such measurements. The instrument was proven to operate properly from ground level up to the lower stratosphere, giving the possibility even for cirrus cloud studies.
M. Reuter, M. Buchwitz, M. Hilker, J. Heymann, O. Schneising, D. Pillai, H. Bovensmann, J. P. Burrows, H. Bösch, R. Parker, A. Butz, O. Hasekamp, C. W. O'Dell, Y. Yoshida, C. Gerbig, T. Nehrkorn, N. M. Deutscher, T. Warneke, J. Notholt, F. Hase, R. Kivi, R. Sussmann, T. Machida, H. Matsueda, and Y. Sawa
Atmos. Chem. Phys., 14, 13739–13753, https://doi.org/10.5194/acp-14-13739-2014, https://doi.org/10.5194/acp-14-13739-2014, 2014
Short summary
Short summary
Current knowledge about the European terrestrial biospheric carbon sink relies upon bottom-up and global surface flux inverse model estimates using in situ measurements. Our analysis of five satellite data sets comprises a regional inversion designed to be insensitive to potential retrieval biases and transport errors. We show that the satellite-derived sink is larger (1.0±0.3GtC/a) than previous estimates (0.4±0.4GtC/a).
Z. Wang, N. M. Deutscher, T. Warneke, J. Notholt, B. Dils, D. W. T. Griffith, M. Schmidt, M. Ramonet, and C. Gerbig
Atmos. Meas. Tech., 7, 3295–3305, https://doi.org/10.5194/amt-7-3295-2014, https://doi.org/10.5194/amt-7-3295-2014, 2014
K. Eusterhues, A. Hädrich, J. Neidhardt, K. Küsel, T. F. Keller, K. D. Jandt, and K. U. Totsche
Biogeosciences, 11, 4953–4966, https://doi.org/10.5194/bg-11-4953-2014, https://doi.org/10.5194/bg-11-4953-2014, 2014
R. Kretschmer, C. Gerbig, U. Karstens, G. Biavati, A. Vermeulen, F. Vogel, S. Hammer, and K. U. Totsche
Atmos. Chem. Phys., 14, 7149–7172, https://doi.org/10.5194/acp-14-7149-2014, https://doi.org/10.5194/acp-14-7149-2014, 2014
S. Houweling, M. Krol, P. Bergamaschi, C. Frankenberg, E. J. Dlugokencky, I. Morino, J. Notholt, V. Sherlock, D. Wunch, V. Beck, C. Gerbig, H. Chen, E. A. Kort, T. Röckmann, and I. Aben
Atmos. Chem. Phys., 14, 3991–4012, https://doi.org/10.5194/acp-14-3991-2014, https://doi.org/10.5194/acp-14-3991-2014, 2014
J. Winderlich, C. Gerbig, O. Kolle, and M. Heimann
Biogeosciences, 11, 2055–2068, https://doi.org/10.5194/bg-11-2055-2014, https://doi.org/10.5194/bg-11-2055-2014, 2014
M. Buchwitz, M. Reuter, H. Bovensmann, D. Pillai, J. Heymann, O. Schneising, V. Rozanov, T. Krings, J. P. Burrows, H. Boesch, C. Gerbig, Y. Meijer, and A. Löscher
Atmos. Meas. Tech., 6, 3477–3500, https://doi.org/10.5194/amt-6-3477-2013, https://doi.org/10.5194/amt-6-3477-2013, 2013
F. A. Haumann, A. M. Batenburg, G. Pieterse, C. Gerbig, M. C. Krol, and T. Röckmann
Atmos. Chem. Phys., 13, 9401–9413, https://doi.org/10.5194/acp-13-9401-2013, https://doi.org/10.5194/acp-13-9401-2013, 2013
V. Beck, C. Gerbig, T. Koch, M. M. Bela, K. M. Longo, S. R. Freitas, J. O. Kaplan, C. Prigent, P. Bergamaschi, and M. Heimann
Atmos. Chem. Phys., 13, 7961–7982, https://doi.org/10.5194/acp-13-7961-2013, https://doi.org/10.5194/acp-13-7961-2013, 2013
H. Chen, A. Karion, C. W. Rella, J. Winderlich, C. Gerbig, A. Filges, T. Newberger, C. Sweeney, and P. P. Tans
Atmos. Meas. Tech., 6, 1031–1040, https://doi.org/10.5194/amt-6-1031-2013, https://doi.org/10.5194/amt-6-1031-2013, 2013
Related subject area
Biogeosciences
Parameterization toolbox for a physical–biogeochemical model compatible with FABM – a case study: the coupled 1D GOTM–ECOSMO E2E for the Sylt–Rømø Bight, North Sea
H2MV (v1.0): global physically constrained deep learning water cycle model with vegetation
NN-TOC v1: global prediction of total organic carbon in marine sediments using deep neural networks
China Wildfire Emission Dataset (ChinaWED v1) for the period 2012–2022
Process-based modeling of solar-induced chlorophyll fluorescence with VISIT-SIF version 1.0
Including the phosphorus cycle into the LPJ-GUESS dynamic global vegetation model (v4.1, r10994) – global patterns and temporal trends of N and P primary production limitation
A comprehensive land-surface vegetation model for multi-stream data assimilation, D&B v1.0
Sources of uncertainty in the SPITFIRE global fire model: development of LPJmL-SPITFIRE1.9 and directions for future improvements
The unicellular NUM v.0.91: a trait-based plankton model evaluated in two contrasting biogeographic provinces
FESOM2.1-REcoM3-MEDUSA2: an ocean–sea ice–biogeochemistry model coupled to a sediment model
Satellite-based modeling of wetland methane emissions on a global scale (SatWetCH4 1.0)
Emulating grid-based forest carbon dynamics using machine learning: an LPJ-GUESS v4.1.1 application
Systematic underestimation of type-specific ecosystem process variability in the Community Land Model v5 over Europe
pyVPRM: A next-generation Vegetation Photosynthesis and Respiration Model for the post-MODIS era
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 the drought response of European tree species with the dynamic vegetation model LPJ-GUESS (v4.1, 97c552c5)
Simulating Ips typographus L. outbreak dynamics and their influence on carbon balance estimates with ORCHIDEE r8627
Biological nitrogen fixation of natural and agricultural vegetation simulated with LPJmL 5.7.9
Learning from conceptual models – a study of the emergence of cooperation towards resource protection in a social–ecological system
Development and assessment of the physical-biogeochemical ocean regional model in the Northwest Pacific: NPRT v1.0 (ROMS v3.9–TOPAZ v2.0)
TROLL 4.0: representing water and carbon fluxes, leaf phenology and intraspecific trait variation in a mixed-species individual-based forest dynamics model – Part 1: Model description
The biogeochemical model Biome-BGCMuSo v6.2 provides plausible and accurate simulations of the carbon cycle in central European beech forests
TROLL 4.0: representing water and carbon fluxes, leaf phenology, and intraspecific trait variation in a mixed-species individual-based forest dynamics model – Part 2: Model evaluation for two Amazonian sites
Estimation of above- and below-ground ecosystem parameters for the DVM-DOS-TEM v0.7.0 model using MADS v1.7.3: a synthetic case study
DeepPhenoMem V1.0: deep learning modelling of canopy greenness dynamics accounting for multi-variate meteorological memory effects on vegetation phenology
Impacts of land-use change on biospheric carbon: an oriented benchmark using the ORCHIDEE land surface model
Implementing the iCORAL (version 1.0) coral reef CaCO3 production module in the iLOVECLIM climate model
Assimilation of carbonyl sulfide (COS) fluxes within the adjoint-based data assimilation system – Nanjing University Carbon Assimilation System (NUCAS v1.0)
ML4Fire-XGBv1.0: Improving North American wildfire prediction by integrating a machine-learning fire model in a land surface model
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
Radiocarbon analysis reveals underestimation of soil organic carbon persistence in new-generation soil models
Exploring the potential of history matching for land surface model calibration
EAT v1.0.0: a 1D test bed for physical–biogeochemical data assimilation in natural waters
Using deep learning to integrate paleoclimate and global biogeochemistry over the Phanerozoic Eon
Modelling boreal forest's mineral soil and peat C dynamics with the Yasso07 model coupled with the Ricker moisture modifier
Dynamic ecosystem assembly and escaping the “fire trap” in the tropics: insights from FATES_15.0.0
In silico calculation of soil pH by SCEPTER v1.0
Simple process-led algorithms for simulating habitats (SPLASH v.2.0): robust calculations of water and energy fluxes
A global behavioural model of human fire use and management: WHAM! v1.0
Terrestrial Ecosystem Model in R (TEMIR) version 1.0: simulating ecophysiological responses of vegetation to atmospheric chemical and meteorological changes
biospheremetrics v1.0.2: an R package to calculate two complementary terrestrial biosphere integrity indicators – human colonization of the biosphere (BioCol) and risk of ecosystem destabilization (EcoRisk)
Modeling boreal forest soil dynamics with the microbially explicit soil model MIMICS+ (v1.0)
Optimal enzyme allocation leads to the constrained enzyme hypothesis: the Soil Enzyme Steady Allocation Model (SESAM; v3.1)
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
Hoa Nguyen, Ute Daewel, Neil Banas, and Corinna Schrum
Geosci. Model Dev., 18, 2961–2982, https://doi.org/10.5194/gmd-18-2961-2025, https://doi.org/10.5194/gmd-18-2961-2025, 2025
Short summary
Short summary
Parameterization is key in modeling to reproduce observations well but is often done manually. This study presents a particle-swarm-optimizer-based toolbox for marine ecosystem models, compatible with the Framework for Aquatic Biogeochemical Models, thus enhancing its reusability. Applied to the Sylt ecosystem, the toolbox effectively (1) identified multiple parameter sets that matched observations well, providing different insights into ecosystem dynamics, and (2) optimized model complexity.
Zavud Baghirov, Martin Jung, Markus Reichstein, Marco Körner, and Basil Kraft
Geosci. Model Dev., 18, 2921–2943, https://doi.org/10.5194/gmd-18-2921-2025, https://doi.org/10.5194/gmd-18-2921-2025, 2025
Short summary
Short summary
We use an innovative approach to studying the Earth's water cycle by integrating advanced machine learning techniques with a traditional water cycle model. Our model is designed to learn from observational data, with a particular emphasis on understanding the influence of vegetation on water movement. By closely aligning with real-world observations, our model offers new possibilities for enhancing our understanding of the water cycle and its interactions with vegetation.
Naveenkumar Parameswaran, Everardo González, Ewa Burwicz-Galerne, Malte Braack, and Klaus Wallmann
Geosci. Model Dev., 18, 2521–2544, https://doi.org/10.5194/gmd-18-2521-2025, https://doi.org/10.5194/gmd-18-2521-2025, 2025
Short summary
Short summary
Our research uses deep learning to predict organic carbon stocks in ocean sediments, which is crucial for understanding their role in the global carbon cycle. By analysing over 22 000 samples and various seafloor characteristics, our model gives more accurate results than traditional methods. We estimate that the top 10 cm of ocean sediments hold about 156 Pg of carbon. This work enhances carbon stock estimates and helps plan future sampling strategies to better understand oceanic carbon burial.
Zhengyang Lin, Ling Huang, Hanqin Tian, Anping Chen, and Xuhui Wang
Geosci. Model Dev., 18, 2509–2520, https://doi.org/10.5194/gmd-18-2509-2025, https://doi.org/10.5194/gmd-18-2509-2025, 2025
Short summary
Short summary
The China Wildfire Emission Dataset (ChinaWED v1) estimated wildfire emissions in China during 2012–2022 as 78.13 Tg CO2, 279.47 Gg CH4, and 6.26 Gg N2O annually. Agricultural fires dominated emissions, while forest and grassland emissions decreased. Seasonal peaks occurred in late spring, with hotspots in northeast, southwest, and east China. The model emphasizes the importance of using localized emission factors and high-resolution fire estimates for accurate assessments.
Tatsuya Miyauchi, Makoto Saito, Hibiki M. Noda, Akihiko Ito, Tomomichi Kato, and Tsuneo Matsunaga
Geosci. Model Dev., 18, 2329–2347, https://doi.org/10.5194/gmd-18-2329-2025, https://doi.org/10.5194/gmd-18-2329-2025, 2025
Short summary
Short summary
Solar-induced chlorophyll fluorescence (SIF) is an effective indicator for monitoring photosynthetic activity. This paper introduces VISIT-SIF, a biogeochemical model developed based on the Vegetation Integrative Simulator for Trace gases (VISIT) to represent satellite-observed SIF. Our simulations reproduced the global distribution and seasonal variations in observed SIF. VISIT-SIF helps to improve photosynthetic processes through a combination of biogeochemical modeling and observed SIF.
Mateus Dantas de Paula, Matthew Forrest, David Warlind, João Paulo Darela Filho, Katrin Fleischer, Anja Rammig, and Thomas Hickler
Geosci. Model Dev., 18, 2249–2274, https://doi.org/10.5194/gmd-18-2249-2025, https://doi.org/10.5194/gmd-18-2249-2025, 2025
Short summary
Short summary
Our study maps global nitrogen (N) and phosphorus (P) availability and how they changed from 1901 to 2018. We find that tropical regions are mostly P-limited, while temperate and boreal areas face N limitations. Over time, P limitation increased, especially in the tropics, while N limitation decreased. These shifts are key to understanding global plant growth and carbon storage, highlighting the importance of including P dynamics in ecosystem models.
Wolfgang Knorr, Matthew Williams, Tea Thum, Thomas Kaminski, Michael Voßbeck, Marko Scholze, Tristan Quaife, T. Luke Smallman, Susan C. Steele-Dunne, Mariette Vreugdenhil, Tim Green, Sönke Zaehle, Mika Aurela, Alexandre Bouvet, Emanuel Bueechi, Wouter Dorigo, Tarek S. El-Madany, Mirco Migliavacca, Marika Honkanen, Yann H. Kerr, Anna Kontu, Juha Lemmetyinen, Hannakaisa Lindqvist, Arnaud Mialon, Tuuli Miinalainen, Gaétan Pique, Amanda Ojasalo, Shaun Quegan, Peter J. Rayner, Pablo Reyes-Muñoz, Nemesio Rodríguez-Fernández, Mike Schwank, Jochem Verrelst, Songyan Zhu, Dirk Schüttemeyer, and Matthias Drusch
Geosci. Model Dev., 18, 2137–2159, https://doi.org/10.5194/gmd-18-2137-2025, https://doi.org/10.5194/gmd-18-2137-2025, 2025
Short summary
Short summary
When it comes to climate change, the land surface is where the vast majority of impacts happen. The task of monitoring those impacts across the globe is formidable and must necessarily rely on satellites – at a significant cost: the measurements are only indirect and require comprehensive physical understanding. We have created a comprehensive modelling system that we offer to the research community to explore how satellite data can be better exploited to help us capture the changes that happen on our lands.
Luke Oberhagemann, Maik Billing, Werner von Bloh, Markus Drüke, Matthew Forrest, Simon P. K. Bowring, Jessica Hetzer, Jaime Ribalaygua Batalla, and Kirsten Thonicke
Geosci. Model Dev., 18, 2021–2050, https://doi.org/10.5194/gmd-18-2021-2025, https://doi.org/10.5194/gmd-18-2021-2025, 2025
Short summary
Short summary
Under climate change, the conditions necessary for wildfires to form are occurring more frequently in many parts of the world. To help predict how wildfires will change in future, global fire models are being developed. We analyze and further develop one such model, SPITFIRE. Our work identifies and corrects sources of substantial bias in the model that are important to the global fire modelling field. With this analysis and these developments, we help to provide a basis for future improvements.
Trine Frisbæk Hansen, Donald Eugene Canfield, Ken Haste Andersen, and Christian Jannik Bjerrum
Geosci. Model Dev., 18, 1895–1916, https://doi.org/10.5194/gmd-18-1895-2025, https://doi.org/10.5194/gmd-18-1895-2025, 2025
Short summary
Short summary
We describe and test the size-based Nutrient-Unicellular-Multicellular model, which defines unicellular plankton using a single set of parameters, on a eutrophic and oligotrophic ecosystem. The results demonstrate that both sites can be modeled with similar parameters and robust performance over a wide range of parameters. The study shows that the model is useful for non-experts and applicable for modeling ecosystems with limited data. It holds promise for evolutionary and deep-time climate models.
Ying Ye, Guy Munhoven, Peter Köhler, Martin Butzin, Judith Hauck, Özgür Gürses, and Christoph Völker
Geosci. Model Dev., 18, 977–1000, https://doi.org/10.5194/gmd-18-977-2025, https://doi.org/10.5194/gmd-18-977-2025, 2025
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.
Carolina Natel, David Martin Belda, Peter Anthoni, Neele Haß, Sam Rabin, and Almut Arneth
EGUsphere, https://doi.org/10.5194/egusphere-2024-4064, https://doi.org/10.5194/egusphere-2024-4064, 2025
Short summary
Short summary
Complex models predict forest carbon responses to future climate change but are slow and computationally intensive, limiting large-scale analyses. We used machine learning to accelerate predictions from the LPJ-GUESS vegetation model. Our emulators, based on random forests and neural networks, achieved 97 % faster simulations. This approach enables rapid exploration of climate mitigation strategies and supports informed policy decisions.
Christian Poppe Terán, Bibi S. Naz, Harry Vereecken, Roland Baatz, Rosie A. Fisher, and Harrie-Jan Hendricks Franssen
Geosci. Model Dev., 18, 287–317, https://doi.org/10.5194/gmd-18-287-2025, https://doi.org/10.5194/gmd-18-287-2025, 2025
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.
Theo Glauch, Julia Marshall, Christoph Gerbig, Santiago Botía, Michał Gałkowski, Sanam N. Vardag, and André Butz
EGUsphere, https://doi.org/10.5194/egusphere-2024-3692, https://doi.org/10.5194/egusphere-2024-3692, 2025
Short summary
Short summary
The Vegetation Photosynthesis and Respiration Model (VPRM) estimates carbon exchange between the atmosphere and biosphere by modeling gross primary production and respiration using satellite data and weather variables. Our new version, pyVPRM, supports diverse satellite products like Sentinel-2, MODIS, VIIRS and new land cover maps, enabling high spatial and temporal resolution. This improves flux estimates, especially in complex landscapes, and ensures continuity as MODIS nears decommissioning.
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.
Benjamin Franklin Meyer, João Paulo Darela-Filho, Konstantin Gregor, Allan Buras, Qiao-Lin Gu, Andreas Krause, Daijun Liu, Phillip Papastefanou, Sijeh Asuk, Thorsten E. E. Grams, Christian S. Zang, and Anja Rammig
EGUsphere, https://doi.org/10.5194/egusphere-2024-3352, https://doi.org/10.5194/egusphere-2024-3352, 2024
Short summary
Short summary
Climate change has increased the likelihood of drought events across Europe, potentially threatening European forest carbon sink. Dynamic vegetation models with mechanistic plant hydraulic architecture are needed to model these developments. We evaluate the plant hydraulic architecture version of LPJ-GUESS and show it's capability at capturing species-specific evapotranspiration responses to drought and reproducing flux observations of both gross primary production and evapotranspiration.
Guillaume Marie, Jina Jeong, Hervé Jactel, Gunnar Petter, Maxime Cailleret, Matthew J. McGrath, Vladislav Bastrikov, Josefine Ghattas, Bertrand Guenet, Anne Sofie Lansø, Kim Naudts, Aude Valade, Chao Yue, and Sebastiaan Luyssaert
Geosci. Model Dev., 17, 8023–8047, https://doi.org/10.5194/gmd-17-8023-2024, https://doi.org/10.5194/gmd-17-8023-2024, 2024
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.
Daehyuk Kim, Hyun-Chae Jung, Jae-Hong Moon, and Na-Hyeon Lee
EGUsphere, https://doi.org/10.5194/egusphere-2024-1509, https://doi.org/10.5194/egusphere-2024-1509, 2024
Short summary
Short summary
Physical–biogeochemical ocean global models is difficult to analyze oceanic environmental systems. To accurately understand the physical–biogeochemical processes at the regional scale, physical and biogeochemical models were coupled at a high resolution. The results successfully simulated the seasonal variations of chlorophyll and nutrients, particularly in the marginal seas, which were not captured by global models. The model is an important tool for studying physical–biogeochemical processes.
Isabelle Maréchaux, Fabian Jörg Fischer, Sylvain Schmitt, and Jérôme Chave
EGUsphere, https://doi.org/10.5194/egusphere-2024-3104, https://doi.org/10.5194/egusphere-2024-3104, 2024
Short summary
Short summary
We describe TROLL 4.0, a simulator of forest dynamics that represents trees in a virtual space at one-meter resolution. Tree birth, growth, death and the underlying physiological processes such as carbon assimilation, water transpiration and leaf phenology depend on plant traits that are measured in the field for many individuals and species. The model is thus capable of jointly simulating forest structure, diversity and ecosystem functioning, a major challenge in modelling vegetation dynamics.
Katarína Merganičová, Ján Merganič, Laura Dobor, Roland Hollós, Zoltán Barcza, Dóra Hidy, Zuzana Sitková, Pavel Pavlenda, Hrvoje Marjanovic, Daniel Kurjak, Michal Bošel'a, Doroteja Bitunjac, Maša Zorana Ostrogović Sever, Jiří Novák, Peter Fleischer, and Tomáš Hlásny
Geosci. Model Dev., 17, 7317–7346, https://doi.org/10.5194/gmd-17-7317-2024, https://doi.org/10.5194/gmd-17-7317-2024, 2024
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.
Sylvain Schmitt, Fabian Fischer, James Ball, Nicolas Barbier, Marion Boisseaux, Damien Bonal, Benoit Burban, Xiuzhi Chen, Géraldine Derroire, Jeremy Lichstein, Daniela Nemetschek, Natalia Restrepo-Coupe, Scott Saleska, Giacomo Sellan, Philippe Verley, Grégoire Vincent, Camille Ziegler, Jérôme Chave, and Isabelle Maréchaux
EGUsphere, https://doi.org/10.5194/egusphere-2024-3106, https://doi.org/10.5194/egusphere-2024-3106, 2024
Short summary
Short summary
We evaluate the capability of TROLL 4.0, a simulator of forest dynamics, to represent tropical forest structure, diversity and functioning in two Amazonian forests. Evaluation data include forest inventories, carbon and water fluxes between the forest and the atmosphere, and leaf area and canopy height from remote-sensing products. The model realistically predicts the structure and composition, and the seasonality of carbon and water fluxes at both sites.
Elchin E. Jafarov, Helene Genet, Velimir V. Vesselinov, Valeria Briones, Aiza Kabeer, Andrew L. Mullen, Benjamin Maglio, Tobey Carman, Ruth Rutter, Joy Clein, Chu-Chun Chang, Dogukan Teber, Trevor Smith, Joshua M. Rady, Christina Schädel, Jennifer D. Watts, Brendan M. Rogers, and Susan M. Natali
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-158, https://doi.org/10.5194/gmd-2024-158, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
Thawing permafrost could greatly impact global climate. Our study improves modeling of carbon cycling in Arctic ecosystems. We developed an automated method to fine-tune a model that simulates carbon and nitrogen flows, using computer-generated data. Using computer-generated data, we tested our method and found it enhances accuracy and reduces the time needed for calibration. This work helps make climate predictions more reliable in sensitive permafrost regions.
Guohua Liu, Mirco Migliavacca, Christian Reimers, Basil Kraft, Markus Reichstein, Andrew D. Richardson, Lisa Wingate, Nicolas Delpierre, Hui Yang, and Alexander J. Winkler
Geosci. Model Dev., 17, 6683–6701, https://doi.org/10.5194/gmd-17-6683-2024, https://doi.org/10.5194/gmd-17-6683-2024, 2024
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.
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.
Ye Liu, Huilin Huang, Sing-Chun Wang, Tao Zhang, Donghui Xu, and Yang Chen
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-151, https://doi.org/10.5194/gmd-2024-151, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
This study integrates machine learning with a land surface model to improve wildfire predictions in North America. Traditional models struggle with accurately simulating burned areas due to simplified processes. By combining the predictive power of machine learning with a land model, our hybrid framework better captures fire dynamics. This approach enhances our understanding of wildfire behavior and aids in developing more effective climate and fire management strategies.
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.
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.
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.
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.
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.
Cited articles
Agustí-Panareda, A., Massart, S., Chevallier, F., Boussetta, S., Balsamo, G., Beljaars, A., Ciais, P., Deutscher, N. M., Engelen, R., Jones, L., Kivi, R., Paris, J.-D., Peuch, V.-H., Sherlock, V., Vermeulen, A. T., Wennberg, P. O., and Wunch, D.: Forecasting global atmospheric CO2, Atmos. Chem. Phys., 14, 11959–11983, https://doi.org/10.5194/acp-14-11959-2014, 2014.
Agustí-Panareda, A., Massart, S., Chevallier, F., Balsamo, G., Boussetta, S., Dutra, E., and Beljaars, A.: A biogenic CO2 flux adjustment scheme for the mitigation of large-scale biases in global atmospheric CO2 analyses and forecasts, Atmos. Chem. Phys., 16, 10399–10418, https://doi.org/10.5194/acp-16-10399-2016, 2016.
Ahmadov, R., Gerbig, C., Kretschmer, R., Koerner, S., Neininger, B., Dolman,
A., and Sarrat, C.: Mesoscale covariance of transport and CO2 fluxes:
Evidence from observations and simulations using the WRF-VPRM coupled
atmosphere-biosphere model, J. Geophys. Res.-Atmos.,
112, D22107, https://doi.org/10.1029/2007JD008552, 2007.
Amediek, A., Ehret, G., Fix, A., Wirth, M., Budenbender, C., Quatrevalet,
M., Kiemle, C., and Gerbig, C.: CHARM-F-a new airborne integrated-path
differential-absorption lidar for carbon dioxide and methane observations:
measurement performance and quantification of strong point source emissions,
Appl. Opt., 56, 5182–5197, 10.1364/Ao.56.005182, 2017.
Anthoni, P., Knohl, A., Rebmann, C., Freibauer, A., Mund, M., Ziegler, W.,
Kolle, O., and Schulze, E. D.: Forest and agricultural land-use-dependent
CO2 exchange in Thuringia, Germany, Glob. Change Biol., 10, 2005–2019,
2004.
Aubinet, M., Chermanne, B., Vandenhaute, M., Longdoz, B., Yernaux, M., and
Laitat, E.: Long term carbon dioxide exchange above a mixed forest in the
Belgian Ardennes, Agr. Forest Meteorol., 108, 293–315, 2001.
Aulagnier, C., Rayner, P., Ciais, P., Vautard, R., Rivier, L., and Ramonet,
M.: Is the recent build-up of atmospheric CO2 over Europe reproduced by
models. Part 2: an overview with the atmospheric mesoscale transport model
CHIMERE, Tellus B, 62, 14–25, https://doi.org/10.1111/j.1600-0889.2009.00443.x, 2010.
Baldocchi, D., Falge, E., Gu, L., Olson, R., Hollinger, D., Running, S.,
Anthoni, P., Bernhofer, C., Davis, K., and Evans, R.: FLUXNET: A new tool to
study the temporal and spatial variability of ecosystem-scale carbon
dioxide, water vapor, and energy flux densities, B. Am. Meteorol. Soc., 82, 2415–2434, 2001.
Beck, V., Koch, T., Kretschmer, R., Marshall, J., Ahmadov, R., Gerbig, C.,
Pillai, D., and Heimann, M.: The WRF Greenhouse Gas Model (WRF-GHG),
Technical Report No. 25, Max Planck Institute for Biogeochemistry, Jena,
Germany, available at: http://www.bgc-jena.mpg.de/bgc-systems/index.shtml (last access: 1 September 2020), 2011.
Bernhofer, C., Grünwald, T., Moderow, U., Hehn, M., Eichelmann, U., and
Prasse, H.: FLUXNET2015 DE-Obe Oberbärenburg, 10.18140/FLX/1440151, 2008–2014.
Bernhofer, C., Grünwald, T., Moderow, U., Hehn, M., Eichelmann, U., and
Prasse, H.: FLUXNET2015 DE-Akm Anklam, 10.18140/FLX/1440213, 2009-2014.
Bernhofer, C., Grünwald, T., Moderow, U., Hehn, M., Eichelmann, U., and
Prasse, H.: FLUXNET2015 DE-Spw Spreewald, 10.18140/FLX/1440220, 2010–2014.
Boussetta, S., Balsamo, G., Beljaars, A., Panareda, A. A., Calvet, J. C.,
Jacobs, C., van den Hurk, B., Viterbo, P., Lafont, S., Dutra, E., Jarlan,
L., Balzarolo, M., Papale, D., and van der Werf, G.: Natural land carbon
dioxide exchanges in the ECMWF integrated forecasting system: Implementation
and offline validation, J. Geophys. Res.-Atmos., 118, 5923–5946,
https://doi.org/10.1002/jgrd.50488, 2013.
Broquet, G., Chevallier, F., Bréon, F.-M., Kadygrov, N., Alemanno, M., Apadula, F., Hammer, S., Haszpra, L., Meinhardt, F., Morguí, J. A., Necki, J., Piacentino, S., Ramonet, M., Schmidt, M., Thompson, R. L., Vermeulen, A. T., Yver, C., and Ciais, P.: Regional inversion of CO2 ecosystem fluxes from atmospheric measurements: reliability of the uncertainty estimates, Atmos. Chem. Phys., 13, 9039–9056, https://doi.org/10.5194/acp-13-9039-2013, 2013.
Butz, A., Dinger, A. S., Bobrowski, N., Kostinek, J., Fieber, L., Fischerkeller, C., Giuffrida, G. B., Hase, F., Klappenbach, F., Kuhn, J., Lübcke, P., Tirpitz, L., and Tu, Q.: Remote sensing of volcanic CO2, HF, HCl, SO2, and BrO in the downwind plume of Mt. Etna, Atmos. Meas. Tech., 10, 1–14, https://doi.org/10.5194/amt-10-1-2017, 2017.
Chen, J. and Gerbig, C.: Short-term forecasting of regional biospheric CO2 fluxes in Europe using a light-use-efficiency model – Model code and output, Max Planck Society, https://doi.org/10.17617/3.2d, 2019.
Chevallier, F., Wang, T., Ciais, P., Maignan, F., Bocquet, M., Altaf Arain,
M., Cescatti, A., Chen, J., Dolman, A. J., and Law, B. E.: What
eddy-covariance measurements tell us about prior land flux errors in
CO2-flux inversion schemes, Global Biogeochem. Cy., 26, GB1021, https://doi.org/10.1029/2010GB003974, 2012.
Delpierre, N., Berveiller, D., Granda, E., and Dufrêne, E.: Wood
phenology, not carbon input, controls the interannual variability of wood
growth in a temperate oak forest, New Phytol., 210, 459–470, 2016.
Dietiker, D., Buchmann, N., and Eugster, W.: Testing the ability of the DNDC
model to predict CO2 and water vapour fluxes of a Swiss cropland site,
Agr. Ecosyst. Environ., 139, 396–401, 2010.
Dušek, J., Čížková, H., Stellner, S., Czerný, R.,
and Květ, J.: Fluctuating water table affects gross ecosystem production
and gross radiation use efficiency in a sedge-grass marsh, Hydrobiologia,
692, 57–66, 2012.
Etzold, S., Ruehr, N. K., Zweifel, R., Dobbertin, M., Zingg, A., Pluess, P.,
Häsler, R., Eugster, W., and Buchmann, N.: The carbon balance of two
contrasting mountain forest ecosystems in Switzerland: similar annual
trends, but seasonal differences, Ecosystems, 14, 1289–1309, 2011.
Fares, S., Savi, F., Muller, J., Matteucci, G., and Paoletti, E.:
Simultaneous measurements of above and below canopy ozone fluxes help
partitioning ozone deposition between its various sinks in a Mediterranean
Oak Forest, Agr. Forest Meteorol., 198, 181–191, 2014.
Ferréa, C., Zenone, T., Comolli, R., and Seufert, G.: Estimating
heterotrophic and autotrophic soil respiration in a semi-natural forest of
Lombardy, Italy, Pedobiologia, 55, 285–294, 2012.
Galvagno, M., Wohlfahrt, G., Cremonese, E., Rossini, M., Colombo, R.,
Filippa, G., Julitta, T., Manca, G., Siniscalco, C., and di Cella, U. M.:
Phenology and carbon dioxide source/sink strength of a subalpine grassland
in response to an exceptionally short snow season, Environ. Res.
Lett., 8, 025008, https://doi.org/10.1088/1748-9326/8/2/025008, 2013.
Gerilowski, K., Tretner, A., Krings, T., Buchwitz, M., Bertagnolio, P. P., Belemezov, F., Erzinger, J., Burrows, J. P., and Bovensmann, H.: MAMAP – a new spectrometer system for column-averaged methane and carbon dioxide observations from aircraft: instrument description and performance analysis, Atmos. Meas. Tech., 4, 215–243, https://doi.org/10.5194/amt-4-215-2011, 2011.
Grünwald, T. and Bernhofer, C.: A decade of carbon, water and energy
flux measurements of an old spruce forest at the Anchor Station Tharandt,
Tellus B, 59, 387–396, 2007.
Hollinger, D. and Richardson, A.: Uncertainty in eddy covariance
measurements and its application to physiological models, Tree Pphysiol.,
25, 873–885, 2005.
Hommeltenberg, J., Schmid, H. P., Drösler, M., and Werle, P.: Can a bog drained for forestry be a stronger carbon sink than a natural bog forest?, Biogeosciences, 11, 3477–3493, https://doi.org/10.5194/bg-11-3477-2014, 2014.
Imer, D., Merbold, L., Eugster, W., and Buchmann, N.: Temporal and spatial variations of soil CO2, CH4 and N2O fluxes at three differently managed grasslands, Biogeosciences, 10, 5931–5945, https://doi.org/10.5194/bg-10-5931-2013, 2013.
IPCC: Climate Change 2014: Synthesis Report, Contribution of Working Groups
I, II, and III to the Fifth Assessment Report of the Intergovernmental Panel
on Climate Change, edited by: Core Writing Team, Pachauri, R. K., and Meyer, L. A.,
IPCC, Geneva, Switzerland, 151 pp., 2014.
Janssens, I., Segers, J., Roland, M., and Arriga, N.: FLUXNET2015 BE-Bra
Brasschaat, https://doi.org/10.18140/FLX/1440128, 2016.
Jung, M., Henkel, K., Herold, M., and Churkina, G.: Exploiting synergies of
global land cover products for carbon cycle modeling, Remote Sens. Environ.,
101, 534–553, 2006.
Kountouris, P., Gerbig, C., Rödenbeck, C., Karstens, U., Koch, T. F., and Heimann, M.: Technical Note: Atmospheric CO2 inversions on the mesoscale using data-driven prior uncertainties: methodology and system evaluation, Atmos. Chem. Phys., 18, 3027–3045, https://doi.org/10.5194/acp-18-3027-2018, 2018.
Lasslop, G., Reichstein, M., Kattge, J., and Papale, D.: Influences of observation errors in eddy flux data on inverse model parameter estimation, Biogeosciences, 5, 1311-1324, https://doi.org/10.5194/bg-5-1311-2008, 2008.
Le Quéré, C., Raupach, M. R., Canadell, J. G., Marland, G., Bopp, L., Ciais,
P., Conway, T. J., Doney, S. C., Feely, R. A., Foster, P., Friedlingstein,
P., Gurney, K., Houghton, R. A., House, J. I., Huntingford, C., Levy, P. E.,
Lomas, M. R., Majkut, J., Metzl, N., Ometto, J. P., Peters, G. P., Prentice,
I. C., Randerson, J. T., Running, S. W., Sarmiento, J. L., Schuster, U.,
Sitch, S., Takahashi, T., Viovy, N., van der Werf, G. R., and Woodward, F.
I.: Trends in the sources and sinks of carbon dioxide, Nat. Geosci., 2,
831–836, https://doi.org/10.1038/ngeo689, 2009.
Lin, J. C., Pejam, M. R., Chan, E., Wofsy, S. C., Gottlieb, E. W., Margolis,
H. A., and McCaughey, J. H.: Attributing uncertainties in simulated
biospheric carbon fluxes to different error sources, Global Biogeochem. Cy,
25, GB2018, https://doi.org/10.1029/2010gb003884, 2011.
Mahadevan, P., Wofsy, S. C., Matross, D. M., Xiao, X. M., Dunn, A. L., Lin,
J. C., Gerbig, C., Munger, J. W., Chow, V. Y., and Gottlieb, E. W.: A
satellite-based biosphere parameterization for net ecosystem CO2 exchange:
Vegetation Photosynthesis and Respiration Model (VPRM), Global Biogeochem.
Cy., 22, GB2005, https://doi.org/10.1029/2006gb002735, 2008.
Marcolla, B., Pitacco, A., and Cescatti, A.: Canopy architecture and
turbulence structure in a coniferous forest, Bound.-Lay. Meteorol.,
108, 39–59, 2003.
Mauder, M., Cuntz, M., Drüe, C., Graf, A., Rebmann, C., Schmid, H. P.,
Schmidt, M., and Steinbrecher, R.: A strategy for quality and uncertainty
assessment of long-term eddy-covariance measurements, Agr.
Forest Meteorol., 169, 122–135, 2013.
Merbold, L., Eugster, W., Stieger, J., Zahniser, M., Nelson, D., and
Buchmann, N.: Greenhouse gas budget (CO2, CH4 and N2O) of intensively
managed grassland following restoration, Glob. change Biol., 20,
1913–1928, 2014.
Moureaux, C., Debacq, A., Bodson, B., Heinesch, B., and Aubinet, M.: Annual
net ecosystem carbon exchange by a sugar beet crop, Agr. Forest
Meteorol., 139, 25–39, 2006.
Pilegaard, K., Ibrom, A., Courtney, M. S., Hummelshøj, P., and Jensen, N.
O.: Increasing net CO2 uptake by a Danish beech forest during the period
from 1996 to 2009, Agr. Forest Meteorol., 151, 934–946, 2011.
Pillai, D., Buchwitz, M., Gerbig, C., Koch, T., Reuter, M., Bovensmann, H., Marshall, J., and Burrows, J. P.: Tracking city CO2 emissions from space using a high-resolution inverse modelling approach: a case study for Berlin, Germany, Atmos. Chem. Phys., 16, 9591–9610, https://doi.org/10.5194/acp-16-9591-2016, 2016.
Post, H., Hendricks Franssen, H. J., Graf, A., Schmidt, M., and Vereecken, H.: Uncertainty analysis of eddy covariance CO2 flux measurements for different EC tower distances using an extended two-tower approach, Biogeosciences, 12, 1205–1221, https://doi.org/10.5194/bg-12-1205-2015, 2015.
Potter, C. S., Randerson, J. T., Field, C. B., Matson, P. A., Vitousek, P.
M., Mooney, H. A., and Klooster, S. A.: Terrestrial Ecosystem Production – a
Process Model-Based on Global Satellite and Surface Data, Global Biogeochem.
Cy., 7, 811–841, https://doi.org/10.1029/93gb02725, 1993.
Prescher, A.-K., Grünwald, T., and Bernhofer, C.: Land use regulates
carbon budgets in eastern Germany: From NEE to NBP, Agr. Forest
Meteorol., 150, 1016–1025, 2010.
Rambal, S., Joffre, R., Ourcival, J., Cavender-Bares, J., and Rocheteau,
A.: The growth respiration component in eddy CO2 flux from a Quercus ilex
mediterranean forest, Glob. Change Biol., 10, 1460–1469, 2004.
Running, S. W. and Hunt Jr., E. R.: Generalization of a forest ecosystem
process model for other biomes, BIOME-BCG, and an application for
global-scale models, Academic Press, 141–158, https://doi.org/10.1016/B978-0-12-233440-5.50014-2, 1993.
Running, S. W., Thornton, P. E., Nemani, R., and Glassy, J. M.: Global
terrestrial gross and net primary productivity from the Earth Observing
System, in: Methods in ecosystem science, Springer, 44–57, 2000.
Sabbatini, S., Arriga, N., Bertolini, T., Castaldi, S., Chiti, T., Consalvo, C., Njakou Djomo, S., Gioli, B., Matteucci, G., and Papale, D.: Greenhouse gas balance of cropland conversion to bioenergy poplar short-rotation coppice, Biogeosciences, 13, 95–113, https://doi.org/10.5194/bg-13-95-2016, 2016.
Simmons, A., Mureau, R., and Petroliagis, T.: Error growth and estimates of
predictability from the ECMWF forecasting system, Q. J.
Roy. Meteor. Soc., 121, 1739–1771, 1995.
Simmons, A. J. and Hollingsworth, A.: Some aspects of the improvement in
skill of numerical weather prediction, Q. J.
Roy. Meteor. Soc., 128, 647–677, 2002.
Suni, T., Rinne, J., Reissell, A., Altimir, N., Keronen, P., Rannik, U.,
Maso, M., Kulmala, M., and Vesala, T.: Long-term measurements of surface
fluxes above a Scots pine forest in Hyytiala, southern Finland, 1996–2001,
Boreal Environ. Res., 8, 287–302, 2003.
Thum, T., Aalto, T., Laurila, T., Aurela, M., Kolari, P., and Hari, P.:
Parametrization of two photosynthesis models at the canopy scale in a
northern boreal Scots pine forest, Tellus B, 59, 874–890, 2007.
Valentini, R., De Angelis, P., Matteucci, G., Monaco, R., Dore, S., and
Mucnozza, G. S.: Seasonal net carbon dioxide exchange of a beech forest with
the atmosphere, Glob. Change Biol., 2, 199–207, 1996.
Vermote, E.: MOD09A1 MODIS/Terra Surface Reflectance 8-Day L3 Global 500 m SIN Grid V006, Data set, NASA EOSDIS Land Processes DAAC, https://doi.org/10.5067/MODIS/MOD09A1.006, 2015.
Vitale, L., Di Tommasi, P., D'Urso, G., and Magliulo, V.: The response of
ecosystem carbon fluxes to LAI and environmental drivers in a maize crop
grown in two contrasting seasons, Int. J. Biometeorol.,
60, 411–420, 2016.
Woodward, F. I., Smith, T. M., and Emanuel, W. R.: A Global Land Primary
Productivity and Phytogeography Model, Global Biogeochem. Cy., 9, 471–490, https://doi.org/10.1029/95gb02432, 1995.
Wu, K., Lauvaux, T., Davis, K. J., Deng, A., Coto, I. L., Gurney, K. R., and
Patarasuk, R.: Joint inverse estimation of fossil fuel and biogenic CO2
fluxes in an urban environment: An observing system simulation experiment to
assess the impact of multiple uncertainties, Elem. Sci. Anth., 6, 17, https://doi.org/10.1525/elementa.138, 2018.
Xiao, X. M., Hollinger, D., Aber, J., Goltz, M., Davidson, E. A., Zhang, Q.
Y., and Moore, B.: Satellite-based modeling of gross primary production in
an evergreen needleleaf forest, Remote Sens. Environ., 89, 519–534,
https://doi.org/10.1016/j.rse.2003.11.008, 2004.
Zhuang, Q., McGuire, A. D., Melillo, J. M., Clein, J. S., Dargaville, R. J.,
Kicklighter, D. W., Myneni, R. B., Dong, J., Romanovsky, V. E., Harden, J.,
and Hobbie, J. E.: Carbon cycling in extratropical terrestrial ecosystems of
the Northern Hemisphere during the 20th century: a modeling analysis of the
influences of soil thermal dynamics, Tellus B, 55, 751–776, https://doi.org/10.1034/j.1600-0889.2003.00060.x, 2003.
Zielis, S., Etzold, S., Zweifel, R., Eugster, W., Haeni, M., and Buchmann, N.: NEP of a Swiss subalpine forest is significantly driven not only by current but also by previous year's weather, Biogeosciences, 11, 1627–1635, https://doi.org/10.5194/bg-11-1627-2014, 2014.
Short summary
One of the essential challenge for atmospheric CO2 forecasting is predicting CO2 flux variation on synoptic timescale. For CAMS CO2 forecast, a process-based vegetation model is used.
In this research we evaluate another type of model (i.e., the light-use-efficiency model VPRM), which is a data-driven approach and thus ideal for realistic estimation, on its ability of flux prediction. Errors from different sources are assessed, and overall the model is capable of CO2 flux prediction.
One of the essential challenge for atmospheric CO2 forecasting is predicting CO2 flux variation...
