Articles | Volume 19, issue 10
https://doi.org/10.5194/gmd-19-4661-2026
© Author(s) 2026. 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-19-4661-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
01 Jun 2026
Model description paper |
| 01 Jun 2026
| 01 Jun 2026
ForEdgeClim v1.0: a 3D process-based microclimate model incorporating vertical and lateral radiative and thermal fluxes to simulate forest edge-to-core transitions
Emma Van de Walle
CORRESPONDING AUTHOR
Q-ForestLab, Laboratory of Quantitative Forest Ecosystem Science, Department of Environment, Faculty of Bioscience Engineering, Ghent University, Ghent, Belgium
Kermit, Department of Data Analysis and Mathematical Modelling, Faculty of Bioscience Engineering, Ghent University, Ghent, Belgium
Félicien Meunier
Q-ForestLab, Laboratory of Quantitative Forest Ecosystem Science, Department of Environment, Faculty of Bioscience Engineering, Ghent University, Ghent, Belgium
Department of Water and Climate, Vrije Universiteit Brussel, Brussels, Belgium
Steven J. De Hertog
Q-ForestLab, Laboratory of Quantitative Forest Ecosystem Science, Department of Environment, Faculty of Bioscience Engineering, Ghent University, Ghent, Belgium
Louise Terryn
Q-ForestLab, Laboratory of Quantitative Forest Ecosystem Science, Department of Environment, Faculty of Bioscience Engineering, Ghent University, Ghent, Belgium
Pieter Sanczuk
Forest & Nature Lab, Department of Environment, Faculty of Bioscience Engineering, Ghent University, Gontrode, Belgium
Kim Calders
Q-ForestLab, Laboratory of Quantitative Forest Ecosystem Science, Department of Environment, Faculty of Bioscience Engineering, Ghent University, Ghent, Belgium
Francis wyffels
IDLab, Internet technology and Data science Lab, Ghent University-imec, Ghent, Belgium
Pieter De Frenne
Forest & Nature Lab, Department of Environment, Faculty of Bioscience Engineering, Ghent University, Gontrode, Belgium
Michiel Stock
Kermit, Department of Data Analysis and Mathematical Modelling, Faculty of Bioscience Engineering, Ghent University, Ghent, Belgium
Hans Verbeeck
Q-ForestLab, Laboratory of Quantitative Forest Ecosystem Science, Department of Environment, Faculty of Bioscience Engineering, Ghent University, Ghent, Belgium
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Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2026-226, https://doi.org/10.5194/essd-2026-226, 2026
Preprint under review for ESSD
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Derrick Muheki, Koen Hufkens, Kim Jacobsen, Hans Verbeeck, Pascal Boeckx, Dominique Kankonde Ntumba, Olivier Kapalay Moulasa, Bas Vercruysse, Julie M. Birkholz, Christophe Verbruggen, Ed Hawkins, Seppe Lampe, Emmanuel Kasongo Yakusu, Fils Makanzu Imwangana, José Mbifo, Théophile Besango Likwela, Félicien Meunier, Olivier Dewitte, Peter Thorne, and Wim Thiery
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This preprint is open for discussion and under review for Earth System Dynamics (ESD).
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W. A. J. Van den Broeck, L. Terryn, W. Cherlet, Z. T. Cooper, and K. Calders
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Joseph Okello, Marijn Bauters, Hans Verbeeck, Samuel Bodé, John Kasenene, Astrid Françoys, Till Engelhardt, Klaus Butterbach-Bahl, Ralf Kiese, and Pascal Boeckx
Biogeosciences, 20, 719–735, https://doi.org/10.5194/bg-20-719-2023, https://doi.org/10.5194/bg-20-719-2023, 2023
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The increase in global and regional temperatures has the potential to drive accelerated soil organic carbon losses in tropical forests. We simulated climate warming by translocating intact soil cores from higher to lower elevations. The results revealed increasing temperature sensitivity and decreasing losses of soil organic carbon with increasing elevation. Our results suggest that climate warming may trigger enhanced losses of soil organic carbon from tropical montane forests.
Félicien Meunier, Wim Verbruggen, Hans Verbeeck, and Marc Peaucelle
Geosci. Model Dev., 15, 7573–7591, https://doi.org/10.5194/gmd-15-7573-2022, https://doi.org/10.5194/gmd-15-7573-2022, 2022
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Drought stress occurs in plants when water supply (i.e. root water uptake) is lower than the water demand (i.e. atmospheric demand). It is strongly related to soil properties and expected to increase in intensity and frequency in the tropics due to climate change. In this study, we show that contrary to the expectations, state-of-the-art terrestrial biosphere models are mostly insensitive to soil texture and hence probably inadequate to reproduce in silico the plant water status in drying soils.
Flossie Brown, Gerd A. Folberth, Stephen Sitch, Susanne Bauer, Marijn Bauters, Pascal Boeckx, Alexander W. Cheesman, Makoto Deushi, Inês Dos Santos Vieira, Corinne Galy-Lacaux, James Haywood, James Keeble, Lina M. Mercado, Fiona M. O'Connor, Naga Oshima, Kostas Tsigaridis, and Hans Verbeeck
Atmos. Chem. Phys., 22, 12331–12352, https://doi.org/10.5194/acp-22-12331-2022, https://doi.org/10.5194/acp-22-12331-2022, 2022
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Surface ozone can decrease plant productivity and impair human health. In this study, we evaluate the change in surface ozone due to climate change over South America and Africa using Earth system models. We find that if the climate were to change according to the worst-case scenario used here, models predict that forested areas in biomass burning locations and urban populations will be at increasing risk of ozone exposure, but other areas will experience a climate benefit.
Félicien Meunier, Sruthi M. Krishna Moorthy, Marc Peaucelle, Kim Calders, Louise Terryn, Wim Verbruggen, Chang Liu, Ninni Saarinen, Niall Origo, Joanne Nightingale, Mathias Disney, Yadvinder Malhi, and Hans Verbeeck
Geosci. Model Dev., 15, 4783–4803, https://doi.org/10.5194/gmd-15-4783-2022, https://doi.org/10.5194/gmd-15-4783-2022, 2022
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We integrated state-of-the-art observations of the structure of the vegetation in a temperate forest to constrain a vegetation model that aims to reproduce such an ecosystem in silico. We showed that the use of this information helps to constrain the model structure, its critical parameters, as well as its initial state. This research confirms the critical importance of the representation of the vegetation structure in vegetation models and proposes a method to overcome this challenge.
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.
Maurizio Santoro, Oliver Cartus, Nuno Carvalhais, Danaë M. A. Rozendaal, Valerio Avitabile, Arnan Araza, Sytze de Bruin, Martin Herold, Shaun Quegan, Pedro Rodríguez-Veiga, Heiko Balzter, João Carreiras, Dmitry Schepaschenko, Mikhail Korets, Masanobu Shimada, Takuya Itoh, Álvaro Moreno Martínez, Jura Cavlovic, Roberto Cazzolla Gatti, Polyanna da Conceição Bispo, Nasheta Dewnath, Nicolas Labrière, Jingjing Liang, Jeremy Lindsell, Edward T. A. Mitchard, Alexandra Morel, Ana Maria Pacheco Pascagaza, Casey M. Ryan, Ferry Slik, Gaia Vaglio Laurin, Hans Verbeeck, Arief Wijaya, and Simon Willcock
Earth Syst. Sci. Data, 13, 3927–3950, https://doi.org/10.5194/essd-13-3927-2021, https://doi.org/10.5194/essd-13-3927-2021, 2021
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Forests play a crucial role in Earth’s carbon cycle. To understand the carbon cycle better, we generated a global dataset of forest above-ground biomass, i.e. carbon stocks, from satellite data of 2010. This dataset provides a comprehensive and detailed portrait of the distribution of carbon in forests, although for dense forests in the tropics values are somewhat underestimated. This dataset will have a considerable impact on climate, carbon, and socio-economic modelling schemes.
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Short summary
We present ForEdgeClim, a process-based model that simulates forest microclimate temperatures from edges to forest interiors. The model combines high-resolution forest structure, meteorological data, and a physically based energy balance that includes vertical and lateral radiation and heat exchange. Validation with field measurements shows that ForEdgeClim captures observed edge-to-core temperature gradients, supporting its use for studying forest fragmentation and climate impacts.
We present ForEdgeClim, a process-based model that simulates forest microclimate temperatures...
