Articles | Volume 18, issue 2
https://doi.org/10.5194/gmd-18-287-2025
© Author(s) 2025. 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-18-287-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model evaluation paper
| 
21 Jan 2025
Model evaluation paper |
| 21 Jan 2025
| 21 Jan 2025
Systematic underestimation of type-specific ecosystem process variability in the Community Land Model v5 over Europe
Christian Poppe Terán
CORRESPONDING AUTHOR
Institute of Bio and Geosciences – Agrosphere (IBG-3), Research Centre Jülich, 52428 Jülich, Germany
Faculty of Georesources and Materials Engineering, RWTH Aachen, 52062 Aachen, Germany
HPSC TerrSys, Geoverbund ABC/J, 52428 Jülich, Germany
Bibi S. Naz
Institute of Bio and Geosciences – Agrosphere (IBG-3), Research Centre Jülich, 52428 Jülich, Germany
HPSC TerrSys, Geoverbund ABC/J, 52428 Jülich, Germany
Harry Vereecken
Institute of Bio and Geosciences – Agrosphere (IBG-3), Research Centre Jülich, 52428 Jülich, Germany
HPSC TerrSys, Geoverbund ABC/J, 52428 Jülich, Germany
Roland Baatz
Research Platform Data Analysis & Simulation, Leibniz Centre for Agricultural Landscape Research (ZALF), 15374 Müncheberg, Germany
Rosie A. Fisher
CICERO Center for International Climate Research, 0349 Oslo, Norway
Harrie-Jan Hendricks Franssen
Institute of Bio and Geosciences – Agrosphere (IBG-3), Research Centre Jülich, 52428 Jülich, Germany
HPSC TerrSys, Geoverbund ABC/J, 52428 Jülich, Germany
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Heye Reemt Bogena, Frank Herrmann, Andreas Lücke, Thomas Pütz, and Harry Vereecken
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-185, https://doi.org/10.5194/essd-2025-185, 2025
Preprint under review for ESSD
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The Wüstebach catchment in Germany’s TERENO network underwent partial deforestation in 2013 to support natural regrowth in Eifel National Park. This data paper presents 16 years (2010–2024) of estimated hourly stream-water flux data for nine macro- and micronutrients, dissolved ionic aluminum, and dissolved organic carbon, along with measured solute concentrations and discharge rates from two stations—one affected by clear-cutting and one unaffected.
Robert Reinecke, Annemarie Bäthge, Ricarda Dietrich, Sebastian Gnann, Simon N. Gosling, Danielle Grogan, Andreas Hartmann, Stefan Kollet, Rohini Kumar, Richard Lammers, Sida Liu, Yan Liu, Nils Moosdorf, Bibi Naz, Sara Nazari, Chibuike Orazulike, Yadu Pokhrel, Jacob Schewe, Mikhail Smilovic, Maryna Strokal, Yoshihide Wada, Shan Zuidema, and Inge de Graaf
EGUsphere, https://doi.org/10.5194/egusphere-2025-1181, https://doi.org/10.5194/egusphere-2025-1181, 2025
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Here we describe a collaborative effort to improve predictions of how climate change will affect groundwater. The ISIMIP groundwater sector combines multiple global groundwater models to capture a range of possible outcomes and reduce uncertainty. Initial comparisons reveal significant differences between models in key metrics like water table depth and recharge rates, highlighting the need for structured model intercomparisons.
Manuela S. Kaufmann, Anja Klotzsche, Jan van der Kruk, Anke Langen, Harry Vereecken, and Lutz Weihermüller
SOIL, 11, 267–285, https://doi.org/10.5194/soil-11-267-2025, https://doi.org/10.5194/soil-11-267-2025, 2025
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To use fertilizers more effectively, non-invasive geophysical methods can be used to understand nutrient distributions in the soil. We utilize, in a long-term field study, geophysical techniques to study soil properties and conditions under different fertilizer treatments. We compared the geophysical response with soil samples and soil sensor data. In particular, electromagnetic induction and electrical resistivity tomography were effective in monitoring changes in nitrate levels over time.
Bamidele Oloruntoba, Stefan Kollet, Carsten Montzka, Harry Vereecken, and Harrie-Jan Hendricks Franssen
Hydrol. Earth Syst. Sci., 29, 1659–1683, https://doi.org/10.5194/hess-29-1659-2025, https://doi.org/10.5194/hess-29-1659-2025, 2025
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We studied how soil and weather data affect land model simulations over Africa. By combining soil data processed in different ways with weather data of varying time intervals, we found that weather inputs had a greater impact on water processes than soil data type. However, the way soil data were processed became crucial when paired with high-frequency weather inputs, showing that detailed weather data can improve local and regional predictions of how water moves and interacts with the land.
Roland Baatz, Gohar Ghazaryan, Michael Hagenlocher, Claas Nendel, Andrea Toreti, and Ehsan Eyshi Rezaei
Hydrol. Earth Syst. Sci., 29, 1379–1393, https://doi.org/10.5194/hess-29-1379-2025, https://doi.org/10.5194/hess-29-1379-2025, 2025
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Our global review of 130 000 peer-reviewed articles reveals that drought forecasting and plant genetics dominate drought research priorities. Using topic modelling, we traced evolving themes from 1901 to 2022, highlighting a shift from ecology to cutting-edge technologies. By applying unsupervised machine learning, we offer insights into how integrated approaches matter, guiding future priorities to strengthen drought resilience and to safeguard water resources.
Salar Saeed Dogar, Cosimo Brogi, Dave O'Leary, Ixchel Hernández-Ochoa, Marco Donat, Harry Vereecken, and Johan Alexander Huisman
EGUsphere, https://doi.org/10.5194/egusphere-2025-827, https://doi.org/10.5194/egusphere-2025-827, 2025
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Farmers need precise information about their fields to use water, fertilizers, and other resources efficiently. This study combines underground soil data and satellite images to create detailed field maps using advanced machine learning. By testing different ways of processing data, we ensured a balanced and accurate approach. The results help farmers manage their land more effectively, leading to better harvests and more sustainable farming practices.
Paolo Nasta, Günter Blöschl, Heye R. Bogena, Steffen Zacharias, Roland Baatz, Gabriëlle De Lannoy, Karsten H. Jensen, Salvatore Manfreda, Laurent Pfister, Ana M. Tarquis, Ilja van Meerveld, Marc Voltz, Yijian Zeng, William Kustas, Xin Li, Harry Vereecken, and Nunzio Romano
Hydrol. Earth Syst. Sci., 29, 465–483, https://doi.org/10.5194/hess-29-465-2025, https://doi.org/10.5194/hess-29-465-2025, 2025
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The Unsolved Problems in Hydrology (UPH) initiative has emphasized the need to establish networks of multi-decadal hydrological observatories to tackle catchment-scale challenges on a global scale. This opinion paper provocatively discusses two endmembers of possible future hydrological observatory (HO) networks for a given hypothesized community budget: a comprehensive set of moderately instrumented observatories or, alternatively, a small number of highly instrumented supersites.
Teng Xu, Sinan Xiao, Sebastian Reuschen, Nils Wildt, Harrie-Jan Hendricks Franssen, and Wolfgang Nowak
Hydrol. Earth Syst. Sci., 28, 5375–5400, https://doi.org/10.5194/hess-28-5375-2024, https://doi.org/10.5194/hess-28-5375-2024, 2024
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We provide a set of benchmarking scenarios for geostatistical inversion, and we encourage the scientific community to use these to compare their newly developed methods. To facilitate transparent, appropriate, and uncertainty-aware comparison of novel methods, we provide some accurate reference solutions, a high-end reference algorithm, and a diverse set of benchmarking metrics, all of which are publicly available. With this, we seek to foster more targeted and transparent progress in the field.
Roland Baatz, Patrick Davies, Paolo Nasta, and Heye Bogena
EGUsphere, https://doi.org/10.5194/egusphere-2024-3108, https://doi.org/10.5194/egusphere-2024-3108, 2024
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This study develops a new method to improve soil moisture measurements from cosmic ray neutron sensors. Using advanced modeling, we account for changes in atmospheric pressure, air humidity, and cosmic ray intensity based on site and sensor characteristics. The results show that precise adjustments are needed to better measure soil moisture, supporting improved decisions in farming, water management, and climate monitoring.
Benjamin M. Sanderson, Ben B. B. Booth, John Dunne, Veronika Eyring, Rosie A. Fisher, Pierre Friedlingstein, Matthew J. Gidden, Tomohiro Hajima, Chris D. Jones, Colin G. Jones, Andrew King, Charles D. Koven, David M. Lawrence, Jason Lowe, Nadine Mengis, Glen P. Peters, Joeri Rogelj, Chris Smith, Abigail C. Snyder, Isla R. Simpson, Abigail L. S. Swann, Claudia Tebaldi, Tatiana Ilyina, Carl-Friedrich Schleussner, Roland Séférian, Bjørn H. Samset, Detlef van Vuuren, and Sönke Zaehle
Geosci. Model Dev., 17, 8141–8172, https://doi.org/10.5194/gmd-17-8141-2024, https://doi.org/10.5194/gmd-17-8141-2024, 2024
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We discuss how, in order to provide more relevant guidance for climate policy, coordinated climate experiments should adopt a greater focus on simulations where Earth system models are provided with carbon emissions from fossil fuels together with land use change instructions, rather than past approaches that have largely focused on experiments with prescribed atmospheric carbon dioxide concentrations. We discuss how these goals might be achieved in coordinated climate modeling experiments.
Benjamin Mark Sanderson, Victor Brovkin, Rosie Fisher, David Hohn, Tatiana Ilyina, Chris Jones, Torben Koenigk, Charles Koven, Hongmei Li, David Lawrence, Peter Lawrence, Spencer Liddicoat, Andrew Macdougall, Nadine Mengis, Zebedee Nicholls, Eleanor O'Rourke, Anastasia Romanou, Marit Sandstad, Jörg Schwinger, Roland Seferian, Lori Sentman, Isla Simpson, Chris Smith, Norman Steinert, Abigail Swann, Jerry Tjiputra, and Tilo Ziehn
EGUsphere, https://doi.org/10.5194/egusphere-2024-3356, https://doi.org/10.5194/egusphere-2024-3356, 2024
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This study investigates how climate models warm in response to simplified carbon emissions trajectories, refining understanding of climate reversibility and commitment. Metrics are defined for warming response to cumulative emissions and for the cessation or ramp-down to net-zero and net-negative levels. Results indicate that previous concentration-driven experiments may have overstated zero emissions commitment due to emissions rates exceeding historical levels.
Ying Zhao, Mehdi Rahmati, Harry Vereecken, and Dani Or
Hydrol. Earth Syst. Sci., 28, 4059–4063, https://doi.org/10.5194/hess-28-4059-2024, https://doi.org/10.5194/hess-28-4059-2024, 2024
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Gao et al. (2023) question the importance of soil in hydrology, sparking debate. We acknowledge some valid points but critique their broad, unsubstantiated views on soil's role. Our response highlights three key areas: (1) the false divide between ecosystem-centric and soil-centric approaches, (2) the vital yet varied impact of soil properties, and (3) the call for a scale-aware framework. We aim to unify these perspectives, enhancing hydrology's comprehensive understanding.
Tobias Karl David Weber, Lutz Weihermüller, Attila Nemes, Michel Bechtold, Aurore Degré, Efstathios Diamantopoulos, Simone Fatichi, Vilim Filipović, Surya Gupta, Tobias L. Hohenbrink, Daniel R. Hirmas, Conrad Jackisch, Quirijn de Jong van Lier, John Koestel, Peter Lehmann, Toby R. Marthews, Budiman Minasny, Holger Pagel, Martine van der Ploeg, Shahab Aldin Shojaeezadeh, Simon Fiil Svane, Brigitta Szabó, Harry Vereecken, Anne Verhoef, Michael Young, Yijian Zeng, Yonggen Zhang, and Sara Bonetti
Hydrol. Earth Syst. Sci., 28, 3391–3433, https://doi.org/10.5194/hess-28-3391-2024, https://doi.org/10.5194/hess-28-3391-2024, 2024
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Pedotransfer functions (PTFs) are used to predict parameters of models describing the hydraulic properties of soils. The appropriateness of these predictions critically relies on the nature of the datasets for training the PTFs and the physical comprehensiveness of the models. This roadmap paper is addressed to PTF developers and users and critically reflects the utility and future of PTFs. To this end, we present a manifesto aiming at a paradigm shift in PTF research.
Joschka Neumann, Nicolas Brüggemann, Patrick Chaumet, Normen Hermes, Jan Huwer, Peter Kirchner, Werner Lesmeister, Wilhelm August Mertens, Thomas Pütz, Jörg Wolters, Harry Vereecken, and Ghaleb Natour
EGUsphere, https://doi.org/10.5194/egusphere-2024-1598, https://doi.org/10.5194/egusphere-2024-1598, 2024
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Climate change in combination with a steadily growing world population and a simultaneous decrease in agricultural land is one of the greatest global challenges facing mankind. In this context, Forschungszentrum Jülich established an "agricultural simulator" (AgraSim), which enables research into the effects of climate change on agricultural ecosystems and the optimization of agricultural cultivation and management strategies with the aid of combined experimental and numerical simulation.
Lukas Strebel, Heye Bogena, Harry Vereecken, Mie Andreasen, Sergio Aranda-Barranco, and Harrie-Jan Hendricks Franssen
Hydrol. Earth Syst. Sci., 28, 1001–1026, https://doi.org/10.5194/hess-28-1001-2024, https://doi.org/10.5194/hess-28-1001-2024, 2024
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We present results from using soil water content measurements from 13 European forest sites in a state-of-the-art land surface model. We use data assimilation to perform a combination of observed and modeled soil water content and show the improvements in the representation of soil water content. However, we also look at the impact on evapotranspiration and see no corresponding improvements.
Denise Degen, Daniel Caviedes Voullième, Susanne Buiter, Harrie-Jan Hendricks Franssen, Harry Vereecken, Ana González-Nicolás, and Florian Wellmann
Geosci. Model Dev., 16, 7375–7409, https://doi.org/10.5194/gmd-16-7375-2023, https://doi.org/10.5194/gmd-16-7375-2023, 2023
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In geosciences, we often use simulations based on physical laws. These simulations can be computationally expensive, which is a problem if simulations must be performed many times (e.g., to add error bounds). We show how a novel machine learning method helps to reduce simulation time. In comparison to other approaches, which typically only look at the output of a simulation, the method considers physical laws in the simulation itself. The method provides reliable results faster than standard.
Junyan Ding, Polly Buotte, Roger Bales, Bradley Christoffersen, Rosie A. Fisher, Michael Goulden, Ryan Knox, Lara Kueppers, Jacquelyn Shuman, Chonggang Xu, and Charles D. Koven
Biogeosciences, 20, 4491–4510, https://doi.org/10.5194/bg-20-4491-2023, https://doi.org/10.5194/bg-20-4491-2023, 2023
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We used a vegetation model to investigate how the different combinations of plant rooting depths and the sensitivity of leaves and stems to drying lead to differential responses of a pine forest to drought conditions in California, USA. We found that rooting depths are the strongest control in that ecosystem. Deep roots allow trees to fully utilize the soil water during a normal year but result in prolonged depletion of soil moisture during a severe drought and hence a high tree mortality risk.
Chonggang Xu, Bradley Christoffersen, Zachary Robbins, Ryan Knox, Rosie A. Fisher, Rutuja Chitra-Tarak, Martijn Slot, Kurt Solander, Lara Kueppers, Charles Koven, and Nate McDowell
Geosci. Model Dev., 16, 6267–6283, https://doi.org/10.5194/gmd-16-6267-2023, https://doi.org/10.5194/gmd-16-6267-2023, 2023
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We introduce a plant hydrodynamic model for the U.S. Department of Energy (DOE)-sponsored model, the Functionally Assembled Terrestrial Ecosystem Simulator (FATES). To better understand this new model system and its functionality in tropical forest ecosystems, we conducted a global parameter sensitivity analysis at Barro Colorado Island, Panama. We identified the key parameters that affect the simulated plant hydrodynamics to guide both modeling and field campaign studies.
Theresa Boas, Heye Reemt Bogena, Dongryeol Ryu, Harry Vereecken, Andrew Western, and Harrie-Jan Hendricks Franssen
Hydrol. Earth Syst. Sci., 27, 3143–3167, https://doi.org/10.5194/hess-27-3143-2023, https://doi.org/10.5194/hess-27-3143-2023, 2023
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In our study, we tested the utility and skill of a state-of-the-art forecasting product for the prediction of regional crop productivity using a land surface model. Our results illustrate the potential value and skill of combining seasonal forecasts with modelling applications to generate variables of interest for stakeholders, such as annual crop yield for specific cash crops and regions. In addition, this study provides useful insights for future technical model evaluations and improvements.
Lingcheng Li, Yilin Fang, Zhonghua Zheng, Mingjie Shi, Marcos Longo, Charles D. Koven, Jennifer A. Holm, Rosie A. Fisher, Nate G. McDowell, Jeffrey Chambers, and L. Ruby Leung
Geosci. Model Dev., 16, 4017–4040, https://doi.org/10.5194/gmd-16-4017-2023, https://doi.org/10.5194/gmd-16-4017-2023, 2023
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Accurately modeling plant coexistence in vegetation demographic models like ELM-FATES is challenging. This study proposes a repeatable method that uses machine-learning-based surrogate models to optimize plant trait parameters in ELM-FATES. Our approach significantly improves plant coexistence modeling, thus reducing errors. It has important implications for modeling ecosystem dynamics in response to climate change.
Bibi S. Naz, Wendy Sharples, Yueling Ma, Klaus Goergen, and Stefan Kollet
Geosci. Model Dev., 16, 1617–1639, https://doi.org/10.5194/gmd-16-1617-2023, https://doi.org/10.5194/gmd-16-1617-2023, 2023
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It is challenging to apply a high-resolution integrated land surface and groundwater model over large spatial scales. In this paper, we demonstrate the application of such a model over a pan-European domain at 3 km resolution and perform an extensive evaluation of simulated water states and fluxes by comparing with in situ and satellite data. This study can serve as a benchmark and baseline for future studies of climate change impact projections and for hydrological forecasting.
Cosimo Brogi, Heye Reemt Bogena, Markus Köhli, Johan Alexander Huisman, Harrie-Jan Hendricks Franssen, and Olga Dombrowski
Geosci. Instrum. Method. Data Syst., 11, 451–469, https://doi.org/10.5194/gi-11-451-2022, https://doi.org/10.5194/gi-11-451-2022, 2022
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Accurate monitoring of water in soil can improve irrigation efficiency, which is important considering climate change and the growing world population. Cosmic-ray neutrons sensors (CRNSs) are a promising tool in irrigation monitoring due to a larger sensed area and to lower maintenance than other ground-based sensors. Here, we analyse the feasibility of irrigation monitoring with CRNSs and the impact of the irrigated field dimensions, of the variations of water in soil, and of instrument design.
Marius S. A. Lambert, Hui Tang, Kjetil S. Aas, Frode Stordal, Rosie A. Fisher, Yilin Fang, Junyan Ding, and Frans-Jan W. Parmentier
Geosci. Model Dev., 15, 8809–8829, https://doi.org/10.5194/gmd-15-8809-2022, https://doi.org/10.5194/gmd-15-8809-2022, 2022
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In this study, we implement a hardening mortality scheme into CTSM5.0-FATES-Hydro and evaluate how it impacts plant hydraulics and vegetation growth. Our work shows that the hydraulic modifications prescribed by the hardening scheme are necessary to model realistic vegetation growth in cold climates, in contrast to the default model that simulates almost nonexistent and declining vegetation due to abnormally large water loss through the roots.
Olga Dombrowski, Cosimo Brogi, Harrie-Jan Hendricks Franssen, Damiano Zanotelli, and Heye Bogena
Geosci. Model Dev., 15, 5167–5193, https://doi.org/10.5194/gmd-15-5167-2022, https://doi.org/10.5194/gmd-15-5167-2022, 2022
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Soil carbon storage and food production of fruit orchards will be influenced by climate change. However, they lack representation in models that study such processes. We developed and tested a new sub-model, CLM5-FruitTree, that describes growth, biomass distribution, and management practices in orchards. The model satisfactorily predicted yield and exchange of carbon, energy, and water in an apple orchard and can be used to study land surface processes in fruit orchards at different scales.
Jordan Bates, Francois Jonard, Rajina Bajracharya, Harry Vereecken, and Carsten Montzka
AGILE GIScience Ser., 3, 23, https://doi.org/10.5194/agile-giss-3-23-2022, https://doi.org/10.5194/agile-giss-3-23-2022, 2022
Wei Qu, Heye Bogena, Christoph Schüth, Harry Vereecken, Zongmei Li, and Stephan Schulz
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-131, https://doi.org/10.5194/gmd-2022-131, 2022
Publication in GMD not foreseen
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We applied the global sensitivity analysis LH-OAT to the integrated hydrology model ParFlow-CLM to investigate the sensitivity of the 12 parameters for different scenarios. And we found that the general patterns of the parameter sensitivities were consistent, however, for some parameters a significantly larger span of the sensitivities was observed, especially for the higher slope and in subarctic climatic scenarios.
Nicholas Jarvis, Jannis Groh, Elisabet Lewan, Katharina H. E. Meurer, Walter Durka, Cornelia Baessler, Thomas Pütz, Elvin Rufullayev, and Harry Vereecken
Hydrol. Earth Syst. Sci., 26, 2277–2299, https://doi.org/10.5194/hess-26-2277-2022, https://doi.org/10.5194/hess-26-2277-2022, 2022
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We apply an eco-hydrological model to data on soil water balance and grassland growth obtained at two sites with contrasting climates. Our results show that the grassland in the drier climate had adapted by developing deeper roots, which maintained water supply to the plants in the face of severe drought. Our study emphasizes the importance of considering such plastic responses of plant traits to environmental stress in the modelling of soil water balance and plant growth under climate change.
Heye Reemt Bogena, Martin Schrön, Jannis Jakobi, Patrizia Ney, Steffen Zacharias, Mie Andreasen, Roland Baatz, David Boorman, Mustafa Berk Duygu, Miguel Angel Eguibar-Galán, Benjamin Fersch, Till Franke, Josie Geris, María González Sanchis, Yann Kerr, Tobias Korf, Zalalem Mengistu, Arnaud Mialon, Paolo Nasta, Jerzy Nitychoruk, Vassilios Pisinaras, Daniel Rasche, Rafael Rosolem, Hami Said, Paul Schattan, Marek Zreda, Stefan Achleitner, Eduardo Albentosa-Hernández, Zuhal Akyürek, Theresa Blume, Antonio del Campo, Davide Canone, Katya Dimitrova-Petrova, John G. Evans, Stefano Ferraris, Félix Frances, Davide Gisolo, Andreas Güntner, Frank Herrmann, Joost Iwema, Karsten H. Jensen, Harald Kunstmann, Antonio Lidón, Majken Caroline Looms, Sascha Oswald, Andreas Panagopoulos, Amol Patil, Daniel Power, Corinna Rebmann, Nunzio Romano, Lena Scheiffele, Sonia Seneviratne, Georg Weltin, and Harry Vereecken
Earth Syst. Sci. Data, 14, 1125–1151, https://doi.org/10.5194/essd-14-1125-2022, https://doi.org/10.5194/essd-14-1125-2022, 2022
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Monitoring of increasingly frequent droughts is a prerequisite for climate adaptation strategies. This data paper presents long-term soil moisture measurements recorded by 66 cosmic-ray neutron sensors (CRNS) operated by 24 institutions and distributed across major climate zones in Europe. Data processing followed harmonized protocols and state-of-the-art methods to generate consistent and comparable soil moisture products and to facilitate continental-scale analysis of hydrological extremes.
Lukas Strebel, Heye R. Bogena, Harry Vereecken, and Harrie-Jan Hendricks Franssen
Geosci. Model Dev., 15, 395–411, https://doi.org/10.5194/gmd-15-395-2022, https://doi.org/10.5194/gmd-15-395-2022, 2022
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We present the technical coupling between a land surface model (CLM5) and the Parallel Data Assimilation Framework (PDAF). This coupling enables measurement data to update simulated model states and parameters in a statistically optimal way. We demonstrate the viability of the model framework using an application in a forested catchment where the inclusion of soil water measurements significantly improved the simulation quality.
Veronika Forstner, Jannis Groh, Matevz Vremec, Markus Herndl, Harry Vereecken, Horst H. Gerke, Steffen Birk, and Thomas Pütz
Hydrol. Earth Syst. Sci., 25, 6087–6106, https://doi.org/10.5194/hess-25-6087-2021, https://doi.org/10.5194/hess-25-6087-2021, 2021
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Lysimeter-based manipulative and observational experiments were used to identify responses of water fluxes and aboveground biomass (AGB) to climatic change in permanent grassland. Under energy-limited conditions, elevated temperature actual evapotranspiration (ETa) increased, while seepage, dew, and AGB decreased. Elevated CO2 mitigated the effect on ETa. Under water limitation, elevated temperature resulted in reduced ETa, and AGB was negatively correlated with an increasing aridity.
Yafei Huang, Jonas Weis, Harry Vereecken, and Harrie-Jan Hendricks Franssen
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2021-569, https://doi.org/10.5194/hess-2021-569, 2021
Manuscript not accepted for further review
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Trends in agricultural droughts cannot be easily deduced from measurements. Here trends in agricultural droughts over 31 German and Dutch sites were calculated with model simulations and long-term observed meteorological data as input. We found that agricultural droughts are increasing although precipitation hardly decreases. The increase is driven by increase in evapotranspiration. The year 2018 was for half of the sites the year with the most extreme agricultural drought in the last 55 years.
Mengna Li, Yijian Zeng, Maciek W. Lubczynski, Jean Roy, Lianyu Yu, Hui Qian, Zhenyu Li, Jie Chen, Lei Han, Han Zheng, Tom Veldkamp, Jeroen M. Schoorl, Harrie-Jan Hendricks Franssen, Kai Hou, Qiying Zhang, Panpan Xu, Fan Li, Kai Lu, Yulin Li, and Zhongbo Su
Earth Syst. Sci. Data, 13, 4727–4757, https://doi.org/10.5194/essd-13-4727-2021, https://doi.org/10.5194/essd-13-4727-2021, 2021
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The Tibetan Plateau is the source of most of Asia's major rivers and has been called the Asian Water Tower. Due to its remoteness and the harsh environment, there is a lack of field survey data to investigate its hydrogeology. Borehole core lithology analysis, an altitude survey, soil thickness measurement, hydrogeological surveys, and hydrogeophysical surveys were conducted in the Maqu catchment within the Yellow River source region to improve a full–picture understanding of the water cycle.
Bernd Schalge, Gabriele Baroni, Barbara Haese, Daniel Erdal, Gernot Geppert, Pablo Saavedra, Vincent Haefliger, Harry Vereecken, Sabine Attinger, Harald Kunstmann, Olaf A. Cirpka, Felix Ament, Stefan Kollet, Insa Neuweiler, Harrie-Jan Hendricks Franssen, and Clemens Simmer
Earth Syst. Sci. Data, 13, 4437–4464, https://doi.org/10.5194/essd-13-4437-2021, https://doi.org/10.5194/essd-13-4437-2021, 2021
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In this study, a 9-year simulation of complete model output of a coupled atmosphere–land-surface–subsurface model on the catchment scale is discussed. We used the Neckar catchment in SW Germany as the basis of this simulation. Since the dataset includes the full model output, it is not only possible to investigate model behavior and interactions between the component models but also use it as a virtual truth for comparison of, for example, data assimilation experiments.
Jan Vanderborght, Valentin Couvreur, Felicien Meunier, Andrea Schnepf, Harry Vereecken, Martin Bouda, and Mathieu Javaux
Hydrol. Earth Syst. Sci., 25, 4835–4860, https://doi.org/10.5194/hess-25-4835-2021, https://doi.org/10.5194/hess-25-4835-2021, 2021
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Root water uptake is an important process in the terrestrial water cycle. How this process depends on soil water content, root distributions, and root properties is a soil–root hydraulic problem. We compare different approaches to implementing root hydraulics in macroscopic soil water flow and land surface models.
Youri Rothfuss, Maria Quade, Nicolas Brüggemann, Alexander Graf, Harry Vereecken, and Maren Dubbert
Biogeosciences, 18, 3701–3732, https://doi.org/10.5194/bg-18-3701-2021, https://doi.org/10.5194/bg-18-3701-2021, 2021
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The partitioning of evapotranspiration into evaporation from soil and transpiration from plants is crucial for a wide range of parties, from farmers to policymakers. In this work, we focus on a particular partitioning method, based on the stable isotopic analysis of water. In particular, we aim at highlighting the challenges that this method is currently facing and, in light of recent methodological developments, propose ways forward for the isotopic-partitioning community.
Cosimo Brogi, Johan A. Huisman, Lutz Weihermüller, Michael Herbst, and Harry Vereecken
SOIL, 7, 125–143, https://doi.org/10.5194/soil-7-125-2021, https://doi.org/10.5194/soil-7-125-2021, 2021
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There is a need in agriculture for detailed soil maps that carry quantitative information. Geophysics-based soil maps have the potential to deliver such products, but their added value has not been fully investigated yet. In this study, we compare the use of a geophysics-based soil map with the use of two commonly available maps as input for crop growth simulations. The geophysics-based product results in better simulations, with improvements that depend on precipitation, soil, and crop type.
Theresa Boas, Heye Bogena, Thomas Grünwald, Bernard Heinesch, Dongryeol Ryu, Marius Schmidt, Harry Vereecken, Andrew Western, and Harrie-Jan Hendricks Franssen
Geosci. Model Dev., 14, 573–601, https://doi.org/10.5194/gmd-14-573-2021, https://doi.org/10.5194/gmd-14-573-2021, 2021
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In this study we were able to significantly improve CLM5 model performance for European cropland sites by adding a winter wheat representation, specific plant parameterizations for important cash crops, and a cover-cropping and crop rotation subroutine to its crop module. Our modifications should be applied in future studies of CLM5 to improve regional yield predictions and to better understand large-scale impacts of agricultural management on carbon, water, and energy fluxes.
Benjamin Fersch, Till Francke, Maik Heistermann, Martin Schrön, Veronika Döpper, Jannis Jakobi, Gabriele Baroni, Theresa Blume, Heye Bogena, Christian Budach, Tobias Gränzig, Michael Förster, Andreas Güntner, Harrie-Jan Hendricks Franssen, Mandy Kasner, Markus Köhli, Birgit Kleinschmit, Harald Kunstmann, Amol Patil, Daniel Rasche, Lena Scheiffele, Ulrich Schmidt, Sandra Szulc-Seyfried, Jannis Weimar, Steffen Zacharias, Marek Zreda, Bernd Heber, Ralf Kiese, Vladimir Mares, Hannes Mollenhauer, Ingo Völksch, and Sascha Oswald
Earth Syst. Sci. Data, 12, 2289–2309, https://doi.org/10.5194/essd-12-2289-2020, https://doi.org/10.5194/essd-12-2289-2020, 2020
Jannis Groh, Jan Vanderborght, Thomas Pütz, Hans-Jörg Vogel, Ralf Gründling, Holger Rupp, Mehdi Rahmati, Michael Sommer, Harry Vereecken, and Horst H. Gerke
Hydrol. Earth Syst. Sci., 24, 1211–1225, https://doi.org/10.5194/hess-24-1211-2020, https://doi.org/10.5194/hess-24-1211-2020, 2020
Michael Paul Stockinger, Heye Reemt Bogena, Andreas Lücke, Christine Stumpp, and Harry Vereecken
Hydrol. Earth Syst. Sci., 23, 4333–4347, https://doi.org/10.5194/hess-23-4333-2019, https://doi.org/10.5194/hess-23-4333-2019, 2019
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Precipitation moves through the soil to become stream water. The fraction of precipitation that becomes stream water after 3 months (Fyw) can be calculated with the stable isotopes of water. Previously, this was done for all the isotope data available, e.g., for several years. We used 1 year of data to calculate Fyw and moved this calculation time window over the time series. Results highlight that Fyw varies in time. Comparison studies of different regions should take this into account.
Anne Klosterhalfen, Alexander Graf, Nicolas Brüggemann, Clemens Drüe, Odilia Esser, María P. González-Dugo, Günther Heinemann, Cor M. J. Jacobs, Matthias Mauder, Arnold F. Moene, Patrizia Ney, Thomas Pütz, Corinna Rebmann, Mario Ramos Rodríguez, Todd M. Scanlon, Marius Schmidt, Rainer Steinbrecher, Christoph K. Thomas, Veronika Valler, Matthias J. Zeeman, and Harry Vereecken
Biogeosciences, 16, 1111–1132, https://doi.org/10.5194/bg-16-1111-2019, https://doi.org/10.5194/bg-16-1111-2019, 2019
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To obtain magnitudes of flux components of H2O and CO2 (e.g., transpiration, soil respiration), we applied source partitioning approaches after Scanlon and Kustas (2010) and after Thomas et al. (2008) to high-frequency eddy covariance measurements of 12 study sites covering various ecosystems (croplands, grasslands, and forests) in different climatic regions. We analyzed the interrelations among turbulence, site characteristics, and the performance of both partitioning methods.
Bibi S. Naz, Wolfgang Kurtz, Carsten Montzka, Wendy Sharples, Klaus Goergen, Jessica Keune, Huilin Gao, Anne Springer, Harrie-Jan Hendricks Franssen, and Stefan Kollet
Hydrol. Earth Syst. Sci., 23, 277–301, https://doi.org/10.5194/hess-23-277-2019, https://doi.org/10.5194/hess-23-277-2019, 2019
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This study investigates the value of assimilating coarse-resolution remotely sensed soil moisture data into high-resolution land surface models for improving soil moisture and runoff modeling. The soil moisture estimates in this study, with complete spatio-temporal coverage and improved spatial resolution from the assimilation, offer a new reanalysis product for the monitoring of surface soil water content and other hydrological fluxes at 3 km resolution over Europe.
Nevil Quinn, Günter Blöschl, András Bárdossy, Attilio Castellarin, Martyn Clark, Christophe Cudennec, Demetris Koutsoyiannis, Upmanu Lall, Lubomir Lichner, Juraj Parajka, Christa D. Peters-Lidard, Graham Sander, Hubert Savenije, Keith Smettem, Harry Vereecken, Alberto Viglione, Patrick Willems, Andy Wood, Ross Woods, Chong-Yu Xu, and Erwin Zehe
Proc. IAHS, 380, 3–8, https://doi.org/10.5194/piahs-380-3-2018, https://doi.org/10.5194/piahs-380-3-2018, 2018
Nevil Quinn, Günter Blöschl, András Bárdossy, Attilio Castellarin, Martyn Clark, Christophe Cudennec, Demetris Koutsoyiannis, Upmanu Lall, Lubomir Lichner, Juraj Parajka, Christa D. Peters-Lidard, Graham Sander, Hubert Savenije, Keith Smettem, Harry Vereecken, Alberto Viglione, Patrick Willems, Andy Wood, Ross Woods, Chong-Yu Xu, and Erwin Zehe
Hydrol. Earth Syst. Sci., 22, 5735–5739, https://doi.org/10.5194/hess-22-5735-2018, https://doi.org/10.5194/hess-22-5735-2018, 2018
Wendy Sharples, Ilya Zhukov, Markus Geimer, Klaus Goergen, Sebastian Luehrs, Thomas Breuer, Bibi Naz, Ketan Kulkarni, Slavko Brdar, and Stefan Kollet
Geosci. Model Dev., 11, 2875–2895, https://doi.org/10.5194/gmd-11-2875-2018, https://doi.org/10.5194/gmd-11-2875-2018, 2018
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Next-generation geoscientific models are based on complex model implementations and workflows. Next-generation HPC systems require new programming paradigms and code optimization. In order to meet the challenge of running complex simulations on new massively parallel HPC systems, we developed a run control framework that facilitates code portability, code profiling, and provenance tracking to reduce both the duration and the cost of code migration and development, while ensuring reproducibility.
Mehdi Rahmati, Lutz Weihermüller, Jan Vanderborght, Yakov A. Pachepsky, Lili Mao, Seyed Hamidreza Sadeghi, Niloofar Moosavi, Hossein Kheirfam, Carsten Montzka, Kris Van Looy, Brigitta Toth, Zeinab Hazbavi, Wafa Al Yamani, Ammar A. Albalasmeh, Ma'in Z. Alghzawi, Rafael Angulo-Jaramillo, Antônio Celso Dantas Antonino, George Arampatzis, Robson André Armindo, Hossein Asadi, Yazidhi Bamutaze, Jordi Batlle-Aguilar, Béatrice Béchet, Fabian Becker, Günter Blöschl, Klaus Bohne, Isabelle Braud, Clara Castellano, Artemi Cerdà, Maha Chalhoub, Rogerio Cichota, Milena Císlerová, Brent Clothier, Yves Coquet, Wim Cornelis, Corrado Corradini, Artur Paiva Coutinho, Muriel Bastista de Oliveira, José Ronaldo de Macedo, Matheus Fonseca Durães, Hojat Emami, Iraj Eskandari, Asghar Farajnia, Alessia Flammini, Nándor Fodor, Mamoun Gharaibeh, Mohamad Hossein Ghavimipanah, Teamrat A. Ghezzehei, Simone Giertz, Evangelos G. Hatzigiannakis, Rainer Horn, Juan José Jiménez, Diederik Jacques, Saskia Deborah Keesstra, Hamid Kelishadi, Mahboobeh Kiani-Harchegani, Mehdi Kouselou, Madan Kumar Jha, Laurent Lassabatere, Xiaoyan Li, Mark A. Liebig, Lubomír Lichner, María Victoria López, Deepesh Machiwal, Dirk Mallants, Micael Stolben Mallmann, Jean Dalmo de Oliveira Marques, Miles R. Marshall, Jan Mertens, Félicien Meunier, Mohammad Hossein Mohammadi, Binayak P. Mohanty, Mansonia Pulido-Moncada, Suzana Montenegro, Renato Morbidelli, David Moret-Fernández, Ali Akbar Moosavi, Mohammad Reza Mosaddeghi, Seyed Bahman Mousavi, Hasan Mozaffari, Kamal Nabiollahi, Mohammad Reza Neyshabouri, Marta Vasconcelos Ottoni, Theophilo Benedicto Ottoni Filho, Mohammad Reza Pahlavan-Rad, Andreas Panagopoulos, Stephan Peth, Pierre-Emmanuel Peyneau, Tommaso Picciafuoco, Jean Poesen, Manuel Pulido, Dalvan José Reinert, Sabine Reinsch, Meisam Rezaei, Francis Parry Roberts, David Robinson, Jesús Rodrigo-Comino, Otto Corrêa Rotunno Filho, Tadaomi Saito, Hideki Suganuma, Carla Saltalippi, Renáta Sándor, Brigitta Schütt, Manuel Seeger, Nasrollah Sepehrnia, Ehsan Sharifi Moghaddam, Manoj Shukla, Shiraki Shutaro, Ricardo Sorando, Ajayi Asishana Stanley, Peter Strauss, Zhongbo Su, Ruhollah Taghizadeh-Mehrjardi, Encarnación Taguas, Wenceslau Geraldes Teixeira, Ali Reza Vaezi, Mehdi Vafakhah, Tomas Vogel, Iris Vogeler, Jana Votrubova, Steffen Werner, Thierry Winarski, Deniz Yilmaz, Michael H. Young, Steffen Zacharias, Yijian Zeng, Ying Zhao, Hong Zhao, and Harry Vereecken
Earth Syst. Sci. Data, 10, 1237–1263, https://doi.org/10.5194/essd-10-1237-2018, https://doi.org/10.5194/essd-10-1237-2018, 2018
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This paper presents and analyzes a global database of soil infiltration data, the SWIG database, for the first time. In total, 5023 infiltration curves were collected across all continents in the SWIG database. These data were either provided and quality checked by the scientists or they were digitized from published articles. We are convinced that the SWIG database will allow for a better parameterization of the infiltration process in land surface models and for testing infiltration models.
Roland Baatz, Pamela L. Sullivan, Li Li, Samantha R. Weintraub, Henry W. Loescher, Michael Mirtl, Peter M. Groffman, Diana H. Wall, Michael Young, Tim White, Hang Wen, Steffen Zacharias, Ingolf Kühn, Jianwu Tang, Jérôme Gaillardet, Isabelle Braud, Alejandro N. Flores, Praveen Kumar, Henry Lin, Teamrat Ghezzehei, Julia Jones, Henry L. Gholz, Harry Vereecken, and Kris Van Looy
Earth Syst. Dynam., 9, 593–609, https://doi.org/10.5194/esd-9-593-2018, https://doi.org/10.5194/esd-9-593-2018, 2018
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Focusing on the usage of integrated models and in situ Earth observatory networks, three challenges are identified to advance understanding of ESD, in particular to strengthen links between biotic and abiotic, and above- and below-ground processes. We propose developing a model platform for interdisciplinary usage, to formalize current network infrastructure based on complementarities and operational synergies, and to extend the reanalysis concept to the ecosystem and critical zone.
Gaochao Cai, Jan Vanderborght, Matthias Langensiepen, Andrea Schnepf, Hubert Hüging, and Harry Vereecken
Hydrol. Earth Syst. Sci., 22, 2449–2470, https://doi.org/10.5194/hess-22-2449-2018, https://doi.org/10.5194/hess-22-2449-2018, 2018
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Different crop growths had consequences for the parameterization of root water uptake models. The root hydraulic parameters of the Couvreur model but not the water stress parameters of the Feddes–Jarvis model could be constrained by the field data measured from rhizotron facilities. The simulated differences in transpiration from the two soils and the different water treatments could be confirmed by sap flow measurements. The Couvreur model predicted the ratios of transpiration fluxes better.
Hanna Post, Harrie-Jan Hendricks Franssen, Xujun Han, Roland Baatz, Carsten Montzka, Marius Schmidt, and Harry Vereecken
Biogeosciences, 15, 187–208, https://doi.org/10.5194/bg-15-187-2018, https://doi.org/10.5194/bg-15-187-2018, 2018
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Estimated values of selected key CLM4.5-BGC parameters obtained with the Markov chain Monte Carlo (MCMC) approach DREAM(zs) strongly altered catchment-scale NEE predictions in comparison to global default parameter values. The effect of perturbed meteorological input data on the uncertainty of the predicted carbon fluxes was notably higher for C3-grass and C3-crop than for coniferous and deciduous forest. A future distinction of different crop types including management is considered essential.
Hongjuan Zhang, Harrie-Jan Hendricks Franssen, Xujun Han, Jasper A. Vrugt, and Harry Vereecken
Hydrol. Earth Syst. Sci., 21, 4927–4958, https://doi.org/10.5194/hess-21-4927-2017, https://doi.org/10.5194/hess-21-4927-2017, 2017
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Applications of data assimilation (DA) arise in many fields of geosciences, perhaps most importantly in weather forecasting and hydrology. We want to investigate the roles of data assimilation methods and land surface models (LSMs) in joint estimation of states and parameters in the assimilation experiments. We find that all DA methods can improve prediction of states, and that differences between DA methods were limited but that the differences between LSMs were much larger.
Carsten Montzka, Michael Herbst, Lutz Weihermüller, Anne Verhoef, and Harry Vereecken
Earth Syst. Sci. Data, 9, 529–543, https://doi.org/10.5194/essd-9-529-2017, https://doi.org/10.5194/essd-9-529-2017, 2017
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Global climate models require adequate parameterization of soil hydraulic properties, but typical resampling to the model grid introduces uncertainties. Here we present a method to scale hydraulic parameters to individual model grids and provide a global data set that overcomes the problems. It preserves the information of sub-grid variability of the water retention curve by deriving local scaling parameters that enables modellers to perturb hydraulic parameters for model ensemble generation.
Roland Baatz, Harrie-Jan Hendricks Franssen, Xujun Han, Tim Hoar, Heye Reemt Bogena, and Harry Vereecken
Hydrol. Earth Syst. Sci., 21, 2509–2530, https://doi.org/10.5194/hess-21-2509-2017, https://doi.org/10.5194/hess-21-2509-2017, 2017
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Soil moisture is a major variable that affects regional climate, weather and hydrologic processes on the Earth's surface. In this study, real-world data of a network of cosmic-ray sensors were assimilated into a regional land surface model to improve model states and soil hydraulic parameters. The results show the potential of these networks for improving model states and parameters. It is suggested to widen the number of observed variables and to increase the number of estimated parameters.
Xiaoqian Jiang, Roland Bol, Barbara J. Cade-Menun, Volker Nischwitz, Sabine Willbold, Sara L. Bauke, Harry Vereecken, Wulf Amelung, and Erwin Klumpp
Biogeosciences, 14, 1153–1164, https://doi.org/10.5194/bg-14-1153-2017, https://doi.org/10.5194/bg-14-1153-2017, 2017
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It is the first study to distinguish the species of nano-sized (d=1−20 nm), small-sized (d=20−450 nm) colloidal P, and dissolved P (d<1 nm) of hydromorphic surface grassland soils from Cambisol, Stagnic Cambisol to Stagnosol using FFF and 31P-NMR. Evidence of nano-sized associations of OC–Fe(Al)–PO43/pyrophosphate in Stagnosol. Stagnic properties affect P speciation and availability by releasing dissolved inorganic and ester-bound P forms as well as nano-sized organic matter–Fe/Al–P colloids.
Bernd Schalge, Jehan Rihani, Gabriele Baroni, Daniel Erdal, Gernot Geppert, Vincent Haefliger, Barbara Haese, Pablo Saavedra, Insa Neuweiler, Harrie-Jan Hendricks Franssen, Felix Ament, Sabine Attinger, Olaf A. Cirpka, Stefan Kollet, Harald Kunstmann, Harry Vereecken, and Clemens Simmer
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2016-557, https://doi.org/10.5194/hess-2016-557, 2016
Manuscript not accepted for further review
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In this work we show how we used a coupled atmosphere-land surface-subsurface model at highest possible resolution to create a testbed for data assimilation. The model was able to capture all important processes and interactions between the compartments as well as showing realistic statistical behavior. This proves that using a model as a virtual truth is possible and it will enable us to develop data assimilation methods where states and parameters are updated across compartment.
Wei Qu, Heye R. Bogena, Johan A. Huisman, Marius Schmidt, Ralf Kunkel, Ansgar Weuthen, Henning Schiedung, Bernd Schilling, Jürgen Sorg, and Harry Vereecken
Earth Syst. Sci. Data, 8, 517–529, https://doi.org/10.5194/essd-8-517-2016, https://doi.org/10.5194/essd-8-517-2016, 2016
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The Rollesbroich catchment is a hydrological observatory of the TERENO (Terrestrial Environmental Observatories) initiative. Hydrometeorological data and spatiotemporal variations in soil water content are measured at high temporal resolution and can be used for many purposes, e.g. validation of remote sensing retrievals, improving hydrological understanding, optimizing data assimilation and inverse modelling techniques. The data set is freely available online (http://www.tereno.net).
Wolfgang Kurtz, Guowei He, Stefan J. Kollet, Reed M. Maxwell, Harry Vereecken, and Harrie-Jan Hendricks Franssen
Geosci. Model Dev., 9, 1341–1360, https://doi.org/10.5194/gmd-9-1341-2016, https://doi.org/10.5194/gmd-9-1341-2016, 2016
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This paper describes the development of a modular data assimilation (DA) system for the integrated Earth system model TerrSysMP with the help of the PDAF data assimilation library.
Currently, pressure and soil moisture data can be used to update model states and parameters in the subsurface compartment of TerrSysMP.
Results from an idealized twin experiment show that the developed DA system provides a good parallel performance and is also applicable for high-resolution modelling problems.
X. Jiang, R. Bol, S. Willbold, H. Vereecken, and E. Klumpp
Biogeosciences, 12, 6443–6452, https://doi.org/10.5194/bg-12-6443-2015, https://doi.org/10.5194/bg-12-6443-2015, 2015
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Overall P content increased with decreasing size of soil aggregate-sized fractions. The relative distribution and speciation of varying P forms were independent of particle size. The majority of alkaline extractable P was in the amorphous Fe/Al oxide fraction, most of which was orthophosphate. Significant amounts of monoester P were also bound to these oxides. Residual P contained similar amounts of P occluded in amorphous and crystalline Fe oxides. This P may be released by FeO dissolution.
Y. Rothfuss, S. Merz, J. Vanderborght, N. Hermes, A. Weuthen, A. Pohlmeier, H. Vereecken, and N. Brüggemann
Hydrol. Earth Syst. Sci., 19, 4067–4080, https://doi.org/10.5194/hess-19-4067-2015, https://doi.org/10.5194/hess-19-4067-2015, 2015
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Profiles of soil water stable isotopes were followed non-destructively and with high precision for a period of 290 days in the laboratory
Rewatering at the end of the experiment led to instantaneous resetting of the isotope profiles, which could be closely followed with the new method
The evaporation depth dynamics was determined from isotope gradients calculation
Uncertainty associated with the determination of isotope kinetic fractionation where highlighted from inverse modeling.
X. Han, X. Li, G. He, P. Kumbhar, C. Montzka, S. Kollet, T. Miyoshi, R. Rosolem, Y. Zhang, H. Vereecken, and H.-J. H. Franssen
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmdd-8-7395-2015, https://doi.org/10.5194/gmdd-8-7395-2015, 2015
Revised manuscript not accepted
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DasPy is a ready to use open source parallel multivariate land data assimilation framework with joint state and parameter estimation using Local Ensemble Transform Kalman Filter. The Community Land Model (4.5) was integrated as model operator. The Community Microwave Emission Modelling platform, COsmic-ray Soil Moisture Interaction Code and the Two-Source Formulation were integrated as observation operators for the multivariate assimilation of soil moisture and soil temperature, respectively.
J. Iwema, R. Rosolem, R. Baatz, T. Wagener, and H. R. Bogena
Hydrol. Earth Syst. Sci., 19, 3203–3216, https://doi.org/10.5194/hess-19-3203-2015, https://doi.org/10.5194/hess-19-3203-2015, 2015
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The cosmic-ray neutron sensor can provide soil moisture content averages over areas of roughly half a kilometre by half a kilometre. Although this sensor is usually calibrated using soil samples taken on a single day, we found that multiple sampling days are needed. The calibration results were also affected by the soil wetness conditions of the sampling days. The outcome of this study will help researchers to calibrate/validate new cosmic-ray neutron sensor sites more accurately.
S. Gebler, H.-J. Hendricks Franssen, T. Pütz, H. Post, M. Schmidt, and H. Vereecken
Hydrol. Earth Syst. Sci., 19, 2145–2161, https://doi.org/10.5194/hess-19-2145-2015, https://doi.org/10.5194/hess-19-2145-2015, 2015
H. Post, H. J. Hendricks Franssen, A. Graf, M. Schmidt, and H. Vereecken
Biogeosciences, 12, 1205–1221, https://doi.org/10.5194/bg-12-1205-2015, https://doi.org/10.5194/bg-12-1205-2015, 2015
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This study introduces an extension of the classical two-tower approach for uncertainty estimation of measured net CO2 fluxes (NEE). Because land surface properties cannot be assumed identical at two eddy covariance towers, a correction for systematic flux differences is proposed to be added to the classical weather filter. With this extension, the overestimation of NEE uncertainty due to systematic flux differences (which are assumed to increase with tower distance) can considerably be reduced.
B. Scharnagl, S. C. Iden, W. Durner, H. Vereecken, and M. Herbst
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hessd-12-2155-2015, https://doi.org/10.5194/hessd-12-2155-2015, 2015
Preprint withdrawn
X. Han, H.-J. H. Franssen, R. Rosolem, R. Jin, X. Li, and H. Vereecken
Hydrol. Earth Syst. Sci., 19, 615–629, https://doi.org/10.5194/hess-19-615-2015, https://doi.org/10.5194/hess-19-615-2015, 2015
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This paper presents the joint assimilation of cosmic-ray neutron counts and land surface temperature with parameter estimation of leaf area index at an irrigated corn field. The results show that the data assimilation can reduce the systematic input errors due to the lack of irrigation data. The estimations of soil moisture, evapotranspiration and leaf area index can be improved in the joint assimilation framework.
W. Kurtz, H.-J. Hendricks Franssen, P. Brunner, and H. Vereecken
Hydrol. Earth Syst. Sci., 17, 3795–3813, https://doi.org/10.5194/hess-17-3795-2013, https://doi.org/10.5194/hess-17-3795-2013, 2013
V. R. N. Pauwels, G. J. M. De Lannoy, H.-J. Hendricks Franssen, and H. Vereecken
Hydrol. Earth Syst. Sci., 17, 3499–3521, https://doi.org/10.5194/hess-17-3499-2013, https://doi.org/10.5194/hess-17-3499-2013, 2013
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Assimilation of carbonyl sulfide (COS) fluxes within the adjoint-based data assimilation system – Nanjing University Carbon Assimilation System (NUCAS v1.0)
ML4Fire-XGBv1.0: Improving North American wildfire prediction by integrating a machine-learning fire model in a land surface model
Quantifying the role of ozone-caused damage to vegetation in the Earth system: a new parameterization scheme for photosynthetic and stomatal responses
Radiocarbon analysis reveals underestimation of soil organic carbon persistence in new-generation soil models
Exploring the potential of history matching for land surface model calibration
EAT v1.0.0: a 1D test bed for physical–biogeochemical data assimilation in natural waters
Using deep learning to integrate paleoclimate and global biogeochemistry over the Phanerozoic Eon
Modelling boreal forest's mineral soil and peat C dynamics with the Yasso07 model coupled with the Ricker moisture modifier
Dynamic ecosystem assembly and escaping the “fire trap” in the tropics: insights from FATES_15.0.0
In silico calculation of soil pH by SCEPTER v1.0
Simple process-led algorithms for simulating habitats (SPLASH v.2.0): robust calculations of water and energy fluxes
A global behavioural model of human fire use and management: WHAM! v1.0
Terrestrial Ecosystem Model in R (TEMIR) version 1.0: simulating ecophysiological responses of vegetation to atmospheric chemical and meteorological changes
biospheremetrics v1.0.2: an R package to calculate two complementary terrestrial biosphere integrity indicators – human colonization of the biosphere (BioCol) and risk of ecosystem destabilization (EcoRisk)
Modeling boreal forest soil dynamics with the microbially explicit soil model MIMICS+ (v1.0)
Optimal enzyme allocation leads to the constrained enzyme hypothesis: the Soil Enzyme Steady Allocation Model (SESAM; v3.1)
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
Optimising CH4 simulations from the LPJ-GUESS model v4.1 using an adaptive Markov chain Monte Carlo algorithm
Sergi Molins, Benjamin J. Andre, Jeffrey N. Johnson, Glenn E. Hammond, Benjamin N. Sulman, Konstantin Lipnikov, Marcus S. Day, James J. Beisman, Daniil Svyatsky, Hang Deng, Peter C. Lichtner, Carl I. Steefel, and J. David Moulton
Geosci. Model Dev., 18, 3241–3263, https://doi.org/10.5194/gmd-18-3241-2025, https://doi.org/10.5194/gmd-18-3241-2025, 2025
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Developing scientific software and making sure it functions properly requires a significant effort. As we advance our understanding of natural systems, however, there is the need to develop yet more complex models and codes. In this work, we present a piece of software that facilitates this work, specifically with regard to reactive processes. Existing tried-and-true codes are made available via this new interface, freeing up resources to focus on the new aspects of the problems at hand.
Jianyong Ma, Almut Arneth, Benjamin Smith, Peter Anthoni, Xu-Ri, Peter Eliasson, David Wårlind, Martin Wittenbrink, and Stefan Olin
Geosci. Model Dev., 18, 3131–3155, https://doi.org/10.5194/gmd-18-3131-2025, https://doi.org/10.5194/gmd-18-3131-2025, 2025
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Nitrous oxide (N2O) is a powerful greenhouse gas mainly released from natural and agricultural soils. This study examines how global soil N2O emissions changed from 1961 to 2020 and identifies key factors driving these changes using an ecological model. The findings highlight croplands as the largest source, with factors like fertilizer use and climate change enhancing emissions. Rising CO2 levels, however, can partially mitigate N2O emissions through increased plant nitrogen uptake.
Hoa Nguyen, Ute Daewel, Neil Banas, and Corinna Schrum
Geosci. Model Dev., 18, 2961–2982, https://doi.org/10.5194/gmd-18-2961-2025, https://doi.org/10.5194/gmd-18-2961-2025, 2025
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Parameterization is key in modeling to reproduce observations well but is often done manually. This study presents a particle-swarm-optimizer-based toolbox for marine ecosystem models, compatible with the Framework for Aquatic Biogeochemical Models, thus enhancing its reusability. Applied to the Sylt ecosystem, the toolbox effectively (1) identified multiple parameter sets that matched observations well, providing different insights into ecosystem dynamics, and (2) optimized model complexity.
Zavud Baghirov, Martin Jung, Markus Reichstein, Marco Körner, and Basil Kraft
Geosci. Model Dev., 18, 2921–2943, https://doi.org/10.5194/gmd-18-2921-2025, https://doi.org/10.5194/gmd-18-2921-2025, 2025
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We use an innovative approach to studying the Earth's water cycle by integrating advanced machine learning techniques with a traditional water cycle model. Our model is designed to learn from observational data, with a particular emphasis on understanding the influence of vegetation on water movement. By closely aligning with real-world observations, our model offers new possibilities for enhancing our understanding of the water cycle and its interactions with vegetation.
Naveenkumar Parameswaran, Everardo González, Ewa Burwicz-Galerne, Malte Braack, and Klaus Wallmann
Geosci. Model Dev., 18, 2521–2544, https://doi.org/10.5194/gmd-18-2521-2025, https://doi.org/10.5194/gmd-18-2521-2025, 2025
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Our research uses deep learning to predict organic carbon stocks in ocean sediments, which is crucial for understanding their role in the global carbon cycle. By analysing over 22 000 samples and various seafloor characteristics, our model gives more accurate results than traditional methods. We estimate that the top 10 cm of ocean sediments hold about 156 Pg of carbon. This work enhances carbon stock estimates and helps plan future sampling strategies to better understand oceanic carbon burial.
Zhengyang Lin, Ling Huang, Hanqin Tian, Anping Chen, and Xuhui Wang
Geosci. Model Dev., 18, 2509–2520, https://doi.org/10.5194/gmd-18-2509-2025, https://doi.org/10.5194/gmd-18-2509-2025, 2025
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The China Wildfire Emission Dataset (ChinaWED v1) estimated wildfire emissions in China during 2012–2022 as 78.13 Tg CO2, 279.47 Gg CH4, and 6.26 Gg N2O annually. Agricultural fires dominated emissions, while forest and grassland emissions decreased. Seasonal peaks occurred in late spring, with hotspots in northeast, southwest, and east China. The model emphasizes the importance of using localized emission factors and high-resolution fire estimates for accurate assessments.
Tatsuya Miyauchi, Makoto Saito, Hibiki M. Noda, Akihiko Ito, Tomomichi Kato, and Tsuneo Matsunaga
Geosci. Model Dev., 18, 2329–2347, https://doi.org/10.5194/gmd-18-2329-2025, https://doi.org/10.5194/gmd-18-2329-2025, 2025
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Solar-induced chlorophyll fluorescence (SIF) is an effective indicator for monitoring photosynthetic activity. This paper introduces VISIT-SIF, a biogeochemical model developed based on the Vegetation Integrative Simulator for Trace gases (VISIT) to represent satellite-observed SIF. Our simulations reproduced the global distribution and seasonal variations in observed SIF. VISIT-SIF helps to improve photosynthetic processes through a combination of biogeochemical modeling and observed SIF.
Mateus Dantas de Paula, Matthew Forrest, David Warlind, João Paulo Darela Filho, Katrin Fleischer, Anja Rammig, and Thomas Hickler
Geosci. Model Dev., 18, 2249–2274, https://doi.org/10.5194/gmd-18-2249-2025, https://doi.org/10.5194/gmd-18-2249-2025, 2025
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Our study maps global nitrogen (N) and phosphorus (P) availability and how they changed from 1901 to 2018. We find that tropical regions are mostly P-limited, while temperate and boreal areas face N limitations. Over time, P limitation increased, especially in the tropics, while N limitation decreased. These shifts are key to understanding global plant growth and carbon storage, highlighting the importance of including P dynamics in ecosystem models.
Wolfgang Knorr, Matthew Williams, Tea Thum, Thomas Kaminski, Michael Voßbeck, Marko Scholze, Tristan Quaife, T. Luke Smallman, Susan C. Steele-Dunne, Mariette Vreugdenhil, Tim Green, Sönke Zaehle, Mika Aurela, Alexandre Bouvet, Emanuel Bueechi, Wouter Dorigo, Tarek S. El-Madany, Mirco Migliavacca, Marika Honkanen, Yann H. Kerr, Anna Kontu, Juha Lemmetyinen, Hannakaisa Lindqvist, Arnaud Mialon, Tuuli Miinalainen, Gaétan Pique, Amanda Ojasalo, Shaun Quegan, Peter J. Rayner, Pablo Reyes-Muñoz, Nemesio Rodríguez-Fernández, Mike Schwank, Jochem Verrelst, Songyan Zhu, Dirk Schüttemeyer, and Matthias Drusch
Geosci. Model Dev., 18, 2137–2159, https://doi.org/10.5194/gmd-18-2137-2025, https://doi.org/10.5194/gmd-18-2137-2025, 2025
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When it comes to climate change, the land surface is where the vast majority of impacts happen. The task of monitoring those impacts across the globe is formidable and must necessarily rely on satellites – at a significant cost: the measurements are only indirect and require comprehensive physical understanding. We have created a comprehensive modelling system that we offer to the research community to explore how satellite data can be better exploited to help us capture the changes that happen on our lands.
Luke Oberhagemann, Maik Billing, Werner von Bloh, Markus Drüke, Matthew Forrest, Simon P. K. Bowring, Jessica Hetzer, Jaime Ribalaygua Batalla, and Kirsten Thonicke
Geosci. Model Dev., 18, 2021–2050, https://doi.org/10.5194/gmd-18-2021-2025, https://doi.org/10.5194/gmd-18-2021-2025, 2025
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Under climate change, the conditions necessary for wildfires to form are occurring more frequently in many parts of the world. To help predict how wildfires will change in future, global fire models are being developed. We analyze and further develop one such model, SPITFIRE. Our work identifies and corrects sources of substantial bias in the model that are important to the global fire modelling field. With this analysis and these developments, we help to provide a basis for future improvements.
Trine Frisbæk Hansen, Donald Eugene Canfield, Ken Haste Andersen, and Christian Jannik Bjerrum
Geosci. Model Dev., 18, 1895–1916, https://doi.org/10.5194/gmd-18-1895-2025, https://doi.org/10.5194/gmd-18-1895-2025, 2025
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We describe and test the size-based Nutrient-Unicellular-Multicellular model, which defines unicellular plankton using a single set of parameters, on a eutrophic and oligotrophic ecosystem. The results demonstrate that both sites can be modeled with similar parameters and robust performance over a wide range of parameters. The study shows that the model is useful for non-experts and applicable for modeling ecosystems with limited data. It holds promise for evolutionary and deep-time climate models.
Ying Ye, Guy Munhoven, Peter Köhler, Martin Butzin, Judith Hauck, Özgür Gürses, and Christoph Völker
Geosci. Model Dev., 18, 977–1000, https://doi.org/10.5194/gmd-18-977-2025, https://doi.org/10.5194/gmd-18-977-2025, 2025
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Many biogeochemistry models assume all material reaching the seafloor is remineralized and returned to solution, which is sufficient for studies on short-term climate change. Under long-term climate change, the carbon storage in sediments slows down carbon cycling and influences feedbacks in the atmosphere–ocean–sediment system. This paper describes the coupling of a sediment model to an ocean biogeochemistry model and presents results under the pre-industrial climate and under CO2 perturbation.
Juliette Bernard, Elodie Salmon, Marielle Saunois, Shushi Peng, Penélope Serrano-Ortiz, Antoine Berchet, Palingamoorthy Gnanamoorthy, Joachim Jansen, and Philippe Ciais
Geosci. Model Dev., 18, 863–883, https://doi.org/10.5194/gmd-18-863-2025, https://doi.org/10.5194/gmd-18-863-2025, 2025
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Despite their importance, uncertainties remain in the evaluation of the drivers of temporal variability of methane emissions from wetlands on a global scale. Here, a simplified global model is developed, taking advantage of advances in remote-sensing data and in situ observations. The model reproduces the large spatial and temporal patterns of emissions, albeit with limitations in the tropics due to data scarcity. This model, while simple, can provide valuable insights into sensitivity analyses.
Carolina Natel, David Martin Belda, Peter Anthoni, Neele Haß, Sam Rabin, and Almut Arneth
EGUsphere, https://doi.org/10.5194/egusphere-2024-4064, https://doi.org/10.5194/egusphere-2024-4064, 2025
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Complex models predict forest carbon responses to future climate change but are slow and computationally intensive, limiting large-scale analyses. We used machine learning to accelerate predictions from the LPJ-GUESS vegetation model. Our emulators, based on random forests and neural networks, achieved 97 % faster simulations. This approach enables rapid exploration of climate mitigation strategies and supports informed policy decisions.
Theo Glauch, Julia Marshall, Christoph Gerbig, Santiago Botía, Michał Gałkowski, Sanam N. Vardag, and André Butz
EGUsphere, https://doi.org/10.5194/egusphere-2024-3692, https://doi.org/10.5194/egusphere-2024-3692, 2025
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The Vegetation Photosynthesis and Respiration Model (VPRM) estimates carbon exchange between the atmosphere and biosphere by modeling gross primary production and respiration using satellite data and weather variables. Our new version, pyVPRM, supports diverse satellite products like Sentinel-2, MODIS, VIIRS and new land cover maps, enabling high spatial and temporal resolution. This improves flux estimates, especially in complex landscapes, and ensures continuity as MODIS nears decommissioning.
Katherine A. Muller, Peishi Jiang, Glenn Hammond, Tasneem Ahmadullah, Hyun-Seob Song, Ravi Kukkadapu, Nicholas Ward, Madison Bowe, Rosalie K. Chu, Qian Zhao, Vanessa A. Garayburu-Caruso, Alan Roebuck, and Xingyuan Chen
Geosci. Model Dev., 17, 8955–8968, https://doi.org/10.5194/gmd-17-8955-2024, https://doi.org/10.5194/gmd-17-8955-2024, 2024
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The new Lambda-PFLOTRAN workflow incorporates organic matter chemistry into reaction networks to simulate aerobic respiration and biogeochemistry. Lambda-PFLOTRAN is a Python-based workflow in a Jupyter notebook interface that digests raw organic matter chemistry data via Fourier transform ion cyclotron resonance mass spectrometry, develops a representative reaction network, and completes a biogeochemical simulation with the open-source, parallel-reactive-flow, and transport code PFLOTRAN.
Ling Li, Peipei Wu, Peng Zhang, Shaojian Huang, and Yanxu Zhang
Geosci. Model Dev., 17, 8683–8695, https://doi.org/10.5194/gmd-17-8683-2024, https://doi.org/10.5194/gmd-17-8683-2024, 2024
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In this study, we incorporate sea surfactants and wave-breaking processes into MITgcm-ECCOv4-Hg. The updated model shows increased fluxes in high-wind-speed and high-wave regions and vice versa, enhancing spatial heterogeneity. It shows that elemental mercury (Hg0) transfer velocity is more sensitive to wind speed. These findings may elucidate the discrepancies in previous estimations and offer insights into global Hg cycling.
Jerome Guiet, Daniele Bianchi, Kim J. N. Scherrer, Ryan F. Heneghan, and Eric D. Galbraith
Geosci. Model Dev., 17, 8421–8454, https://doi.org/10.5194/gmd-17-8421-2024, https://doi.org/10.5194/gmd-17-8421-2024, 2024
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The BiOeconomic mArine Trophic Size-spectrum (BOATSv2) model dynamically simulates global commercial fish populations and their coupling with fishing activity, as emerging from environmental and economic drivers. New features, including separate pelagic and demersal populations, iron limitation, and spatial variation of fishing costs and management, improve the accuracy of high seas fisheries. The updated model code is available to simulate both historical and future scenarios.
Jize Jiang, David S. Stevenson, and Mark A. Sutton
Geosci. Model Dev., 17, 8181–8222, https://doi.org/10.5194/gmd-17-8181-2024, https://doi.org/10.5194/gmd-17-8181-2024, 2024
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A special model called AMmonia–CLIMate (AMCLIM) has been developed to understand and calculate NH3 emissions from fertilizer use and also taking into account how the environment influences these NH3 emissions. It is estimated that about 17 % of applied N in fertilizers was lost due to NH3 emissions. Hot and dry conditions and regions with high-pH soils can expect higher NH3 emissions.
Benjamin Franklin Meyer, João Paulo Darela-Filho, Konstantin Gregor, Allan Buras, Qiao-Lin Gu, Andreas Krause, Daijun Liu, Phillip Papastefanou, Sijeh Asuk, Thorsten E. E. Grams, Christian S. Zang, and Anja Rammig
EGUsphere, https://doi.org/10.5194/egusphere-2024-3352, https://doi.org/10.5194/egusphere-2024-3352, 2024
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Climate change has increased the likelihood of drought events across Europe, potentially threatening European forest carbon sink. Dynamic vegetation models with mechanistic plant hydraulic architecture are needed to model these developments. We evaluate the plant hydraulic architecture version of LPJ-GUESS and show it's capability at capturing species-specific evapotranspiration responses to drought and reproducing flux observations of both gross primary production and evapotranspiration.
Guillaume Marie, Jina Jeong, Hervé Jactel, Gunnar Petter, Maxime Cailleret, Matthew J. McGrath, Vladislav Bastrikov, Josefine Ghattas, Bertrand Guenet, Anne Sofie Lansø, Kim Naudts, Aude Valade, Chao Yue, and Sebastiaan Luyssaert
Geosci. Model Dev., 17, 8023–8047, https://doi.org/10.5194/gmd-17-8023-2024, https://doi.org/10.5194/gmd-17-8023-2024, 2024
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This research looks at how climate change influences forests, and particularly how altered wind and insect activities could make forests emit instead of absorb carbon. We have updated a land surface model called ORCHIDEE to better examine the effect of bark beetles on forest health. Our findings suggest that sudden events, such as insect outbreaks, can dramatically affect carbon storage, offering crucial insights into tackling climate change.
Stephen Björn Wirth, Johanna Braun, Jens Heinke, Sebastian Ostberg, Susanne Rolinski, Sibyll Schaphoff, Fabian Stenzel, Werner von Bloh, Friedhelm Taube, and Christoph Müller
Geosci. Model Dev., 17, 7889–7914, https://doi.org/10.5194/gmd-17-7889-2024, https://doi.org/10.5194/gmd-17-7889-2024, 2024
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We present a new approach to modelling biological nitrogen fixation (BNF) in the Lund–Potsdam–Jena managed Land dynamic global vegetation model. While in the original approach BNF depended on actual evapotranspiration, the new approach considers soil water content and temperature, vertical root distribution, the nitrogen (N) deficit and carbon (C) costs. The new approach improved simulated BNF compared to the scientific literature and the model ability to project future C and N cycle dynamics.
Saeed Harati-Asl, Liliana Perez, and Roberto Molowny-Horas
Geosci. Model Dev., 17, 7423–7443, https://doi.org/10.5194/gmd-17-7423-2024, https://doi.org/10.5194/gmd-17-7423-2024, 2024
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Social–ecological systems are the subject of many sustainability problems. Because of the complexity of these systems, we must be careful when intervening in them; otherwise we may cause irreversible damage. Using computer models, we can gain insight about these complex systems without harming them. In this paper we describe how we connected an ecological model of forest insect infestation with a social model of cooperation and simulated an intervention measure to save a forest from infestation.
Daehyuk Kim, Hyun-Chae Jung, Jae-Hong Moon, and Na-Hyeon Lee
EGUsphere, https://doi.org/10.5194/egusphere-2024-1509, https://doi.org/10.5194/egusphere-2024-1509, 2024
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Physical–biogeochemical ocean global models is difficult to analyze oceanic environmental systems. To accurately understand the physical–biogeochemical processes at the regional scale, physical and biogeochemical models were coupled at a high resolution. The results successfully simulated the seasonal variations of chlorophyll and nutrients, particularly in the marginal seas, which were not captured by global models. The model is an important tool for studying physical–biogeochemical processes.
Isabelle Maréchaux, Fabian Jörg Fischer, Sylvain Schmitt, and Jérôme Chave
EGUsphere, https://doi.org/10.5194/egusphere-2024-3104, https://doi.org/10.5194/egusphere-2024-3104, 2024
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We describe TROLL 4.0, a simulator of forest dynamics that represents trees in a virtual space at one-meter resolution. Tree birth, growth, death and the underlying physiological processes such as carbon assimilation, water transpiration and leaf phenology depend on plant traits that are measured in the field for many individuals and species. The model is thus capable of jointly simulating forest structure, diversity and ecosystem functioning, a major challenge in modelling vegetation dynamics.
Katarína Merganičová, Ján Merganič, Laura Dobor, Roland Hollós, Zoltán Barcza, Dóra Hidy, Zuzana Sitková, Pavel Pavlenda, Hrvoje Marjanovic, Daniel Kurjak, Michal Bošel'a, Doroteja Bitunjac, Maša Zorana Ostrogović Sever, Jiří Novák, Peter Fleischer, and Tomáš Hlásny
Geosci. Model Dev., 17, 7317–7346, https://doi.org/10.5194/gmd-17-7317-2024, https://doi.org/10.5194/gmd-17-7317-2024, 2024
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We developed a multi-objective calibration approach leading to robust parameter values aiming to strike a balance between their local precision and broad applicability. Using the Biome-BGCMuSo model, we tested the calibrated parameter sets for simulating European beech forest dynamics across large environmental gradients. Leveraging data from 87 plots and five European countries, the results demonstrated reasonable local accuracy and plausible large-scale productivity responses.
Sylvain Schmitt, Fabian Fischer, James Ball, Nicolas Barbier, Marion Boisseaux, Damien Bonal, Benoit Burban, Xiuzhi Chen, Géraldine Derroire, Jeremy Lichstein, Daniela Nemetschek, Natalia Restrepo-Coupe, Scott Saleska, Giacomo Sellan, Philippe Verley, Grégoire Vincent, Camille Ziegler, Jérôme Chave, and Isabelle Maréchaux
EGUsphere, https://doi.org/10.5194/egusphere-2024-3106, https://doi.org/10.5194/egusphere-2024-3106, 2024
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We evaluate the capability of TROLL 4.0, a simulator of forest dynamics, to represent tropical forest structure, diversity and functioning in two Amazonian forests. Evaluation data include forest inventories, carbon and water fluxes between the forest and the atmosphere, and leaf area and canopy height from remote-sensing products. The model realistically predicts the structure and composition, and the seasonality of carbon and water fluxes at both sites.
Elchin E. Jafarov, Helene Genet, Velimir V. Vesselinov, Valeria Briones, Aiza Kabeer, Andrew L. Mullen, Benjamin Maglio, Tobey Carman, Ruth Rutter, Joy Clein, Chu-Chun Chang, Dogukan Teber, Trevor Smith, Joshua M. Rady, Christina Schädel, Jennifer D. Watts, Brendan M. Rogers, and Susan M. Natali
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-158, https://doi.org/10.5194/gmd-2024-158, 2024
Revised manuscript accepted for GMD
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Thawing permafrost could greatly impact global climate. Our study improves modeling of carbon cycling in Arctic ecosystems. We developed an automated method to fine-tune a model that simulates carbon and nitrogen flows, using computer-generated data. Using computer-generated data, we tested our method and found it enhances accuracy and reduces the time needed for calibration. This work helps make climate predictions more reliable in sensitive permafrost regions.
Guohua Liu, Mirco Migliavacca, Christian Reimers, Basil Kraft, Markus Reichstein, Andrew D. Richardson, Lisa Wingate, Nicolas Delpierre, Hui Yang, and Alexander J. Winkler
Geosci. Model Dev., 17, 6683–6701, https://doi.org/10.5194/gmd-17-6683-2024, https://doi.org/10.5194/gmd-17-6683-2024, 2024
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Our study employs long short-term memory (LSTM) networks to model canopy greenness and phenology, integrating meteorological memory effects. The LSTM model outperforms traditional methods, enhancing accuracy in predicting greenness dynamics and phenological transitions across plant functional types. Highlighting the importance of multi-variate meteorological memory effects, our research pioneers unlock the secrets of vegetation phenology responses to climate change with deep learning techniques.
Thi Lan Anh Dinh, Daniel Goll, Philippe Ciais, and Ronny Lauerwald
Geosci. Model Dev., 17, 6725–6744, https://doi.org/10.5194/gmd-17-6725-2024, https://doi.org/10.5194/gmd-17-6725-2024, 2024
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The study assesses the performance of the dynamic global vegetation model (DGVM) ORCHIDEE in capturing the impact of land-use change on carbon stocks across Europe. Comparisons with observations reveal that the model accurately represents carbon fluxes and stocks. Despite the underestimations in certain land-use conversions, the model describes general trends in soil carbon response to land-use change, aligning with the site observations.
Nathaelle Bouttes, Lester Kwiatkowski, Manon Berger, Victor Brovkin, and Guy Munhoven
Geosci. Model Dev., 17, 6513–6528, https://doi.org/10.5194/gmd-17-6513-2024, https://doi.org/10.5194/gmd-17-6513-2024, 2024
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Coral reefs are crucial for biodiversity, but they also play a role in the carbon cycle on long time scales of a few thousand years. To better simulate the future and past evolution of coral reefs and their effect on the global carbon cycle, hence on atmospheric CO2 concentration, it is necessary to include coral reefs within a climate model. Here we describe the inclusion of coral reef carbonate production in a carbon–climate model and its validation in comparison to existing modern data.
Huajie Zhu, Mousong Wu, Fei Jiang, Michael Vossbeck, Thomas Kaminski, Xiuli Xing, Jun Wang, Weimin Ju, and Jing M. Chen
Geosci. Model Dev., 17, 6337–6363, https://doi.org/10.5194/gmd-17-6337-2024, https://doi.org/10.5194/gmd-17-6337-2024, 2024
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In this work, we developed the Nanjing University Carbon Assimilation System (NUCAS v1.0). Data assimilation experiments were conducted to demonstrate the robustness and investigate the feasibility and applicability of NUCAS. The assimilation of ecosystem carbonyl sulfide (COS) fluxes improved the model performance in gross primary productivity, evapotranspiration, and sensible heat, showing that COS provides constraints on parameters relevant to carbon-, water-, and energy-related processes.
Ye Liu, Huilin Huang, Sing-Chun Wang, Tao Zhang, Donghui Xu, and Yang Chen
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-151, https://doi.org/10.5194/gmd-2024-151, 2024
Revised manuscript accepted for GMD
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This study integrates machine learning with a land surface model to improve wildfire predictions in North America. Traditional models struggle with accurately simulating burned areas due to simplified processes. By combining the predictive power of machine learning with a land model, our hybrid framework better captures fire dynamics. This approach enhances our understanding of wildfire behavior and aids in developing more effective climate and fire management strategies.
Fang Li, Zhimin Zhou, Samuel Levis, Stephen Sitch, Felicity Hayes, Zhaozhong Feng, Peter B. Reich, Zhiyi Zhao, and Yanqing Zhou
Geosci. Model Dev., 17, 6173–6193, https://doi.org/10.5194/gmd-17-6173-2024, https://doi.org/10.5194/gmd-17-6173-2024, 2024
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A new scheme is developed to model the surface ozone damage to vegetation in regional and global process-based models. Based on 4210 data points from ozone experiments, it accurately reproduces statistically significant linear or nonlinear photosynthetic and stomatal responses to ozone in observations for all vegetation types. It also enables models to implicitly capture the variability in plant ozone tolerance and the shift among species within a vegetation type.
Alexander S. Brunmayr, Frank Hagedorn, Margaux Moreno Duborgel, Luisa I. Minich, and Heather D. Graven
Geosci. Model Dev., 17, 5961–5985, https://doi.org/10.5194/gmd-17-5961-2024, https://doi.org/10.5194/gmd-17-5961-2024, 2024
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A new generation of soil models promises to more accurately predict the carbon cycle in soils under climate change. However, measurements of 14C (the radioactive carbon isotope) in soils reveal that the new soil models face similar problems to the traditional models: they underestimate the residence time of carbon in soils and may therefore overestimate the net uptake of CO2 by the land ecosystem. Proposed solutions include restructuring the models and calibrating model parameters with 14C data.
Nina Raoult, Simon Beylat, James M. Salter, Frédéric Hourdin, Vladislav Bastrikov, Catherine Ottlé, and Philippe Peylin
Geosci. Model Dev., 17, 5779–5801, https://doi.org/10.5194/gmd-17-5779-2024, https://doi.org/10.5194/gmd-17-5779-2024, 2024
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We use computer models to predict how the land surface will respond to climate change. However, these complex models do not always simulate what we observe in real life, limiting their effectiveness. To improve their accuracy, we use sophisticated statistical and computational techniques. We test a technique called history matching against more common approaches. This method adapts well to these models, helping us better understand how they work and therefore how to make them more realistic.
Jorn Bruggeman, Karsten Bolding, Lars Nerger, Anna Teruzzi, Simone Spada, Jozef Skákala, and Stefano Ciavatta
Geosci. Model Dev., 17, 5619–5639, https://doi.org/10.5194/gmd-17-5619-2024, https://doi.org/10.5194/gmd-17-5619-2024, 2024
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To understand and predict the ocean’s capacity for carbon sequestration, its ability to supply food, and its response to climate change, we need the best possible estimate of its physical and biogeochemical properties. This is obtained through data assimilation which blends numerical models and observations. We present the Ensemble and Assimilation Tool (EAT), a flexible and efficient test bed that allows any scientist to explore and further develop the state of the art in data assimilation.
Dongyu Zheng, Andrew S. Merdith, Yves Goddéris, Yannick Donnadieu, Khushboo Gurung, and Benjamin J. W. Mills
Geosci. Model Dev., 17, 5413–5429, https://doi.org/10.5194/gmd-17-5413-2024, https://doi.org/10.5194/gmd-17-5413-2024, 2024
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This study uses a deep learning method to upscale the time resolution of paleoclimate simulations to 1 million years. This improved resolution allows a climate-biogeochemical model to more accurately predict climate shifts. The method may be critical in developing new fully continuous methods that are able to be applied over a moving continental surface in deep time with high resolution at reasonable computational expense.
Boris Ťupek, Aleksi Lehtonen, Alla Yurova, Rose Abramoff, Bertrand Guenet, Elisa Bruni, Samuli Launiainen, Mikko Peltoniemi, Shoji Hashimoto, Xianglin Tian, Juha Heikkinen, Kari Minkkinen, and Raisa Mäkipää
Geosci. Model Dev., 17, 5349–5367, https://doi.org/10.5194/gmd-17-5349-2024, https://doi.org/10.5194/gmd-17-5349-2024, 2024
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Updating the Yasso07 soil C model's dependency on decomposition with a hump-shaped Ricker moisture function improved modelled soil organic C (SOC) stocks in a catena of mineral and organic soils in boreal forest. The Ricker function, set to peak at a rate of 1 and calibrated against SOC and CO2 data using a Bayesian approach, showed a maximum in well-drained soils. Using SOC and CO2 data together with the moisture only from the topsoil humus was crucial for accurate model estimates.
Jacquelyn K. Shuman, Rosie A. Fisher, Charles Koven, Ryan Knox, Lara Kueppers, and Chonggang Xu
Geosci. Model Dev., 17, 4643–4671, https://doi.org/10.5194/gmd-17-4643-2024, https://doi.org/10.5194/gmd-17-4643-2024, 2024
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We adapt a fire behavior and effects module for use in a size-structured vegetation demographic model to test how climate, fire regime, and fire-tolerance plant traits interact to determine the distribution of tropical forests and grasslands. Our model captures the connection between fire disturbance and plant fire-tolerance strategies in determining plant distribution and provides a useful tool for understanding the vulnerability of these areas under changing conditions across the tropics.
Yoshiki Kanzaki, Isabella Chiaravalloti, Shuang Zhang, Noah J. Planavsky, and Christopher T. Reinhard
Geosci. Model Dev., 17, 4515–4532, https://doi.org/10.5194/gmd-17-4515-2024, https://doi.org/10.5194/gmd-17-4515-2024, 2024
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Soil pH is one of the most commonly measured agronomical and biogeochemical indices, mostly reflecting exchangeable acidity. Explicit simulation of both porewater and bulk soil pH is thus crucial to the accurate evaluation of alkalinity required to counteract soil acidification and the resulting capture of anthropogenic carbon dioxide through the enhanced weathering technique. This has been enabled by the updated reactive–transport SCEPTER code and newly developed framework to simulate soil pH.
David Sandoval, Iain Colin Prentice, and Rodolfo L. B. Nóbrega
Geosci. Model Dev., 17, 4229–4309, https://doi.org/10.5194/gmd-17-4229-2024, https://doi.org/10.5194/gmd-17-4229-2024, 2024
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Numerous estimates of water and energy balances depend on empirical equations requiring site-specific calibration, posing risks of "the right answers for the wrong reasons". We introduce novel first-principles formulations to calculate key quantities without requiring local calibration, matching predictions from complex land surface models.
Oliver Perkins, Matthew Kasoar, Apostolos Voulgarakis, Cathy Smith, Jay Mistry, and James D. A. Millington
Geosci. Model Dev., 17, 3993–4016, https://doi.org/10.5194/gmd-17-3993-2024, https://doi.org/10.5194/gmd-17-3993-2024, 2024
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Wildfire is often presented in the media as a danger to human life. Yet globally, millions of people’s livelihoods depend on using fire as a tool. So, patterns of fire emerge from interactions between humans, land use, and climate. This complexity means scientists cannot yet reliably say how fire will be impacted by climate change. So, we developed a new model that represents globally how people use and manage fire. The model reveals the extent and diversity of how humans live with and use fire.
Amos P. K. Tai, David H. Y. Yung, and Timothy Lam
Geosci. Model Dev., 17, 3733–3764, https://doi.org/10.5194/gmd-17-3733-2024, https://doi.org/10.5194/gmd-17-3733-2024, 2024
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We have developed the Terrestrial Ecosystem Model in R (TEMIR), which simulates plant carbon and pollutant uptake and predicts their response to varying atmospheric conditions. This model is designed to couple with an atmospheric chemistry model so that questions related to plant–atmosphere interactions, such as the effects of climate change, rising CO2, and ozone pollution on forest carbon uptake, can be addressed. The model has been well validated with both ground and satellite observations.
Fabian Stenzel, Johanna Braun, Jannes Breier, Karlheinz Erb, Dieter Gerten, Jens Heinke, Sarah Matej, Sebastian Ostberg, Sibyll Schaphoff, and Wolfgang Lucht
Geosci. Model Dev., 17, 3235–3258, https://doi.org/10.5194/gmd-17-3235-2024, https://doi.org/10.5194/gmd-17-3235-2024, 2024
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We provide an R package to compute two biosphere integrity metrics that can be applied to simulations of vegetation growth from the dynamic global vegetation model LPJmL. The pressure metric BioCol indicates that we humans modify and extract > 20 % of the potential preindustrial natural biomass production. The ecosystems state metric EcoRisk shows a high risk of ecosystem destabilization in many regions as a result of climate change and land, water, and fertilizer use.
Elin Ristorp Aas, Heleen A. de Wit, and Terje K. Berntsen
Geosci. Model Dev., 17, 2929–2959, https://doi.org/10.5194/gmd-17-2929-2024, https://doi.org/10.5194/gmd-17-2929-2024, 2024
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By including microbial processes in soil models, we learn how the soil system interacts with its environment and responds to climate change. We present a soil process model, MIMICS+, which is able to reproduce carbon stocks found in boreal forest soils better than a conventional land model. With the model we also find that when adding nitrogen, the relationship between soil microbes changes notably. Coupling the model to a vegetation model will allow for further study of these mechanisms.
Thomas Wutzler, Christian Reimers, Bernhard Ahrens, and Marion Schrumpf
Geosci. Model Dev., 17, 2705–2725, https://doi.org/10.5194/gmd-17-2705-2024, https://doi.org/10.5194/gmd-17-2705-2024, 2024
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Soil microbes provide a strong link for elemental fluxes in the earth system. The SESAM model applies an optimality assumption to model those linkages and their adaptation. We found that a previous heuristic description was a special case of a newly developed more rigorous description. The finding of new behaviour at low microbial biomass led us to formulate the constrained enzyme hypothesis. We now can better describe how microbially mediated linkages of elemental fluxes adapt across decades.
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
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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
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Many forest models include detailed mechanisms of forest growth and mortality, but regeneration is often simplified. Testing and improving forest regeneration models is challenging. We address this issue by exploring how forest inventories from unmanaged European forests can be used to improve such models. We find that competition for light among trees is captured by the model, unknown model components can be informed by forest inventory data, and climatic effects are challenging to capture.
Jalisha T. Kallingal, Johan Lindström, Paul A. Miller, Janne Rinne, Maarit Raivonen, and Marko Scholze
Geosci. Model Dev., 17, 2299–2324, https://doi.org/10.5194/gmd-17-2299-2024, https://doi.org/10.5194/gmd-17-2299-2024, 2024
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By unlocking the mysteries of CH4 emissions from wetlands, our work improved the accuracy of the LPJ-GUESS vegetation model using Bayesian statistics. Via assimilation of long-term real data from a wetland, we significantly enhanced CH4 emission predictions. This advancement helps us better understand wetland contributions to atmospheric CH4, which are crucial for addressing climate change. Our method offers a promising tool for refining global climate models and guiding conservation efforts
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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.
Carbon and water exchanges between the atmosphere and the land surface contribute to water...
