Articles | Volume 13, issue 3
https://doi.org/10.5194/gmd-13-905-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-13-905-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
05 Mar 2020
Model description paper |
| 05 Mar 2020
| 05 Mar 2020
HETEROFOR 1.0: a spatially explicit model for exploring the response of structurally complex forests to uncertain future conditions – Part 1: Carbon fluxes and tree dimensional growth
Mathieu Jonard
CORRESPONDING AUTHOR
Earth and Life Institute, Université catholique de Louvain,
Louvain-la-Neuve, 1348, Belgium
Frédéric André
Earth and Life Institute, Université catholique de Louvain,
Louvain-la-Neuve, 1348, Belgium
François de Coligny
AMAP, Univ Montpellier, CIRAD, CNRS, INRAE, IRD, 34000 Montpellier,
France
Louis de Wergifosse
Earth and Life Institute, Université catholique de Louvain,
Louvain-la-Neuve, 1348, Belgium
Nicolas Beudez
AMAP, Univ Montpellier, CIRAD, CNRS, INRAE, IRD, 34000 Montpellier,
France
Hendrik Davi
Ecologie des Forêts Méditerranéennes (URFM), Institut National de la Recherche pour l'Agriculture, l'Alimentation et l'Environnement (INRAE), Avignon, 84914, France
Gauthier Ligot
Gembloux Agro-Bio Tech, Université de Liège, Gembloux, 5030, Belgium
Quentin Ponette
Earth and Life Institute, Université catholique de Louvain,
Louvain-la-Neuve, 1348, Belgium
Caroline Vincke
Earth and Life Institute, Université catholique de Louvain,
Louvain-la-Neuve, 1348, Belgium
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Louis de Wergifosse, Frédéric André, Nicolas Beudez, François de Coligny, Hugues Goosse, François Jonard, Quentin Ponette, Hugues Titeux, Caroline Vincke, and Mathieu Jonard
Geosci. Model Dev., 13, 1459–1498, https://doi.org/10.5194/gmd-13-1459-2020, https://doi.org/10.5194/gmd-13-1459-2020, 2020
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Zhun Mao, Delphine Derrien, Markus Didion, Jari Liski, Thomas Eglin, Manuel Nicolas, Mathieu Jonard, and Laurent Saint-André
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Marta Camino-Serrano, Elisabeth Graf Pannatier, Sara Vicca, Sebastiaan Luyssaert, Mathieu Jonard, Philippe Ciais, Bertrand Guenet, Bert Gielen, Josep Peñuelas, Jordi Sardans, Peter Waldner, Sophia Etzold, Guia Cecchini, Nicholas Clarke, Zoran Galić, Laure Gandois, Karin Hansen, Jim Johnson, Uwe Klinck, Zora Lachmanová, Antti-Jussi Lindroos, Henning Meesenburg, Tiina M. Nieminen, Tanja G. M. Sanders, Kasia Sawicka, Walter Seidling, Anne Thimonier, Elena Vanguelova, Arne Verstraeten, Lars Vesterdal, and Ivan A. Janssens
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We investigated the long-term trends of dissolved organic carbon (DOC) in soil solution and the drivers of changes in over 100 forest monitoring plots across Europe. An overall increasing trend was detected in the organic layers, but no overall trend was found in the mineral horizons. There are strong interactions between controls acting at local and regional scales. Our findings are relevant for researchers focusing on the link between terrestrial and aquatic ecosystems and for C-cycle models.
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The performance of weather and climate prediction systems is variable in time and space. It is of interest how this performance varies in different situations. We provide a decomposition of a skill score (a measure of forecast performance) as a tool for detailed assessment of performance variability to support model development or forecast improvement. The framework is exemplified with decadal forecasts to assess the impact of different ocean states in the North Atlantic on temperature forecast.
Maria R. Russo, Sadie L. Bartholomew, David Hassell, Alex M. Mason, Erica Neininger, A. James Perman, David A. J. Sproson, Duncan Watson-Parris, and Nathan Luke Abraham
Geosci. Model Dev., 18, 181–191, https://doi.org/10.5194/gmd-18-181-2025, https://doi.org/10.5194/gmd-18-181-2025, 2025
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Observational data and modelling capabilities have expanded in recent years, but there are still barriers preventing these two data sources from being used in synergy. Proper comparison requires generating, storing, and handling a large amount of data. This work describes the first step in the development of a new set of software tools, the VISION toolkit, which can enable the easy and efficient integration of observational and model data required for model evaluation.
Bijan Fallah, Masoud Rostami, Emmanuele Russo, Paula Harder, Christoph Menz, Peter Hoffmann, Iulii Didovets, and Fred F. Hattermann
Geosci. Model Dev., 18, 161–180, https://doi.org/10.5194/gmd-18-161-2025, https://doi.org/10.5194/gmd-18-161-2025, 2025
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We tried to contribute to a local climate change impact study in central Asia, a region that is water-scarce and vulnerable to global climate change. We use regional models and machine learning to produce reliable local data from global climate models. We find that regional models show more realistic and detailed changes in heavy precipitation than global climate models. Our work can help assess the future risks of extreme events and plan adaptation strategies in central Asia.
Thomas Rackow, Xabier Pedruzo-Bagazgoitia, Tobias Becker, Sebastian Milinski, Irina Sandu, Razvan Aguridan, Peter Bechtold, Sebastian Beyer, Jean Bidlot, Souhail Boussetta, Willem Deconinck, Michail Diamantakis, Peter Dueben, Emanuel Dutra, Richard Forbes, Rohit Ghosh, Helge F. Goessling, Ioan Hadade, Jan Hegewald, Thomas Jung, Sarah Keeley, Lukas Kluft, Nikolay Koldunov, Aleksei Koldunov, Tobias Kölling, Josh Kousal, Christian Kühnlein, Pedro Maciel, Kristian Mogensen, Tiago Quintino, Inna Polichtchouk, Balthasar Reuter, Domokos Sármány, Patrick Scholz, Dmitry Sidorenko, Jan Streffing, Birgit Sützl, Daisuke Takasuka, Steffen Tietsche, Mirco Valentini, Benoît Vannière, Nils Wedi, Lorenzo Zampieri, and Florian Ziemen
Geosci. Model Dev., 18, 33–69, https://doi.org/10.5194/gmd-18-33-2025, https://doi.org/10.5194/gmd-18-33-2025, 2025
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Detailed global climate model simulations have been created based on a numerical weather prediction model, offering more accurate spatial detail down to the scale of individual cities ("kilometre-scale") and a better understanding of climate phenomena such as atmospheric storms, whirls in the ocean, and cracks in sea ice. The new model aims to provide globally consistent information on local climate change with greater precision, benefiting environmental planning and local impact modelling.
Yilin Fang, Hoang Viet Tran, and L. Ruby Leung
Geosci. Model Dev., 18, 19–32, https://doi.org/10.5194/gmd-18-19-2025, https://doi.org/10.5194/gmd-18-19-2025, 2025
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Hurricanes may worsen water quality in the lower Mississippi River basin (LMRB) by increasing nutrient runoff. We found that runoff parameterizations greatly affect nitrate–nitrogen runoff simulated using an Earth system land model. Our simulations predicted increased nitrogen runoff in the LMRB during Hurricane Ida in 2021, albeit less pronounced than the observations, indicating areas for model improvement to better understand and manage nutrient runoff loss during hurricanes in the region.
Giovanni Seijo-Ellis, Donata Giglio, Gustavo Marques, and Frank Bryan
Geosci. Model Dev., 17, 8989–9021, https://doi.org/10.5194/gmd-17-8989-2024, https://doi.org/10.5194/gmd-17-8989-2024, 2024
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A CESM–MOM6 regional configuration of the Caribbean Sea was developed in response to the rising need for high-resolution models for climate impact studies. The configuration is validated for the period 2000–2020 and improves significant errors in a low-resolution model. Oceanic properties are well represented. Patterns of freshwater associated with the Amazon River are well captured, and the mean flows of ocean waters across multiple passages in the Caribbean Sea agree with observations.
Deifilia To, Julian Quinting, Gholam Ali Hoshyaripour, Markus Götz, Achim Streit, and Charlotte Debus
Geosci. Model Dev., 17, 8873–8884, https://doi.org/10.5194/gmd-17-8873-2024, https://doi.org/10.5194/gmd-17-8873-2024, 2024
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Pangu-Weather is a breakthrough machine learning model in medium-range weather forecasting that considers 3D atmospheric information. We show that using a simpler 2D framework improves robustness, speeds up training, and reduces computational needs by 20 %–30 %. We introduce a training procedure that varies the importance of atmospheric variables over time to speed up training convergence. Decreasing computational demand increases the accessibility of training and working with the model.
Fang Li, Xiang Song, Sandy P. Harrison, Jennifer R. Marlon, Zhongda Lin, L. Ruby Leung, Jörg Schwinger, Virginie Marécal, Shiyu Wang, Daniel S. Ward, Xiao Dong, Hanna Lee, Lars Nieradzik, Sam S. Rabin, and Roland Séférian
Geosci. Model Dev., 17, 8751–8771, https://doi.org/10.5194/gmd-17-8751-2024, https://doi.org/10.5194/gmd-17-8751-2024, 2024
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This study provides the first comprehensive assessment of historical fire simulations from 19 Earth system models in phase 6 of the Coupled Model Intercomparison Project (CMIP6). Most models reproduce global totals, spatial patterns, seasonality, and regional historical changes well but fail to simulate the recent decline in global burned area and underestimate the fire response to climate variability. CMIP6 simulations address three critical issues of phase-5 models.
Seung H. Baek, Paul A. Ullrich, Bo Dong, and Jiwoo Lee
Geosci. Model Dev., 17, 8665–8681, https://doi.org/10.5194/gmd-17-8665-2024, https://doi.org/10.5194/gmd-17-8665-2024, 2024
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We evaluate downscaled products by examining locally relevant co-variances during precipitation events. Common statistical downscaling techniques preserve expected co-variances during convective precipitation (a stationary phenomenon). However, they dampen future intensification of frontal precipitation (a non-stationary phenomenon) captured in global climate models and dynamical downscaling. Our study quantifies a ramification of the stationarity assumption underlying statistical downscaling.
Emmanuel Nyenah, Petra Döll, Daniel S. Katz, and Robert Reinecke
Geosci. Model Dev., 17, 8593–8611, https://doi.org/10.5194/gmd-17-8593-2024, https://doi.org/10.5194/gmd-17-8593-2024, 2024
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Research software is vital for scientific progress but is often developed by scientists with limited skills, time, and funding, leading to challenges in usability and maintenance. Our study across 10 sectors shows strengths in version control, open-source licensing, and documentation while emphasizing the need for containerization and code quality. We recommend workshops; code quality metrics; funding; and following the findable, accessible, interoperable, and reusable (FAIR) standards.
Chris Smith, Donald P. Cummins, Hege-Beate Fredriksen, Zebedee Nicholls, Malte Meinshausen, Myles Allen, Stuart Jenkins, Nicholas Leach, Camilla Mathison, and Antti-Ilari Partanen
Geosci. Model Dev., 17, 8569–8592, https://doi.org/10.5194/gmd-17-8569-2024, https://doi.org/10.5194/gmd-17-8569-2024, 2024
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Climate projections are only useful if the underlying models that produce them are well calibrated and can reproduce observed climate change. We formalise a software package that calibrates the open-source FaIR simple climate model to full-complexity Earth system models. Observations, including historical warming, and assessments of key climate variables such as that of climate sensitivity are used to constrain the model output.
Jingwei Xie, Xi Wang, Hailong Liu, Pengfei Lin, Jiangfeng Yu, Zipeng Yu, Junlin Wei, and Xiang Han
Geosci. Model Dev., 17, 8469–8493, https://doi.org/10.5194/gmd-17-8469-2024, https://doi.org/10.5194/gmd-17-8469-2024, 2024
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We propose the concept of mesoscale ocean direct numerical simulation (MODNS), which should resolve the first baroclinic deformation radius and ensure the numerical dissipative effects do not directly contaminate the mesoscale motions. It can be a benchmark for testing mesoscale ocean large eddy simulation (MOLES) methods in ocean models. We build an idealized Southern Ocean model using MITgcm to generate a type of MODNS. We also illustrate the diversity of multiscale eddy interactions.
Emily Black, John Ellis, and Ross I. Maidment
Geosci. Model Dev., 17, 8353–8372, https://doi.org/10.5194/gmd-17-8353-2024, https://doi.org/10.5194/gmd-17-8353-2024, 2024
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We present General TAMSAT-ALERT, a computationally lightweight and versatile tool for generating ensemble forecasts from time series data. General TAMSAT-ALERT is capable of combining multiple streams of monitoring and meteorological forecasting data into probabilistic hazard assessments. In this way, it complements existing systems and enhances their utility for actionable hazard assessment.
Sarah Schöngart, Lukas Gudmundsson, Mathias Hauser, Peter Pfleiderer, Quentin Lejeune, Shruti Nath, Sonia Isabelle Seneviratne, and Carl-Friedrich Schleussner
Geosci. Model Dev., 17, 8283–8320, https://doi.org/10.5194/gmd-17-8283-2024, https://doi.org/10.5194/gmd-17-8283-2024, 2024
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Precipitation and temperature are two of the most impact-relevant climatic variables. Yet, projecting future precipitation and temperature data under different emission scenarios relies on complex models that are computationally expensive. In this study, we propose a method that allows us to generate monthly means of local precipitation and temperature at low computational costs. Our modelling framework is particularly useful for all downstream applications of climate model data.
Gang Tang, Zebedee Nicholls, Chris Jones, Thomas Gasser, Alexander Norton, Tilo Ziehn, Alejandro Romero-Prieto, and Malte Meinshausen
EGUsphere, https://doi.org/10.5194/egusphere-2024-3522, https://doi.org/10.5194/egusphere-2024-3522, 2024
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We analyzed carbon and nitrogen mass conservation in data from CMIP6 Earth System Models. Our findings reveal significant discrepancies between flux and pool size data, particularly in nitrogen, where cumulative imbalances can reach hundreds of gigatons. These imbalances appear primarily due to missing or inconsistently reported fluxes – especially for land use and fire emissions. To enhance data quality, we recommend that future climate data protocols address this issue at the reporting stage.
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.
Peter Berg, Thomas Bosshard, Denica Bozhinova, Lars Bärring, Joakim Löw, Carolina Nilsson, Gustav Strandberg, Johan Södling, Johan Thuresson, Renate Wilcke, and Wei Yang
Geosci. Model Dev., 17, 8173–8179, https://doi.org/10.5194/gmd-17-8173-2024, https://doi.org/10.5194/gmd-17-8173-2024, 2024
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When bias adjusting climate model data using quantile mapping, one needs to prescribe what to do at the tails of the distribution, where a larger data range is likely encountered outside of the calibration period. The end result is highly dependent on the method used. We show that, to avoid discontinuities in the time series, one needs to exclude data in the calibration range to also activate the extrapolation functionality in that time period.
Philip J. Rasch, Haruki Hirasawa, Mingxuan Wu, Sarah J. Doherty, Robert Wood, Hailong Wang, Andy Jones, James Haywood, and Hansi Singh
Geosci. Model Dev., 17, 7963–7994, https://doi.org/10.5194/gmd-17-7963-2024, https://doi.org/10.5194/gmd-17-7963-2024, 2024
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We introduce a protocol to compare computer climate simulations to better understand a proposed strategy intended to counter warming and climate impacts from greenhouse gas increases. This slightly changes clouds in six ocean regions to reflect more sunlight and cool the Earth. Example changes in clouds and climate are shown for three climate models. Cloud changes differ between the models, but precipitation and surface temperature changes are similar when their cooling effects are made similar.
Trude Eidhammer, Andrew Gettelman, Katherine Thayer-Calder, Duncan Watson-Parris, Gregory Elsaesser, Hugh Morrison, Marcus van Lier-Walqui, Ci Song, and Daniel McCoy
Geosci. Model Dev., 17, 7835–7853, https://doi.org/10.5194/gmd-17-7835-2024, https://doi.org/10.5194/gmd-17-7835-2024, 2024
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We describe a dataset where 45 parameters related to cloud processes in the Community Earth System Model version 2 (CESM2) Community Atmosphere Model version 6 (CAM6) are perturbed. Three sets of perturbed parameter ensembles (263 members) were created: current climate, preindustrial aerosol loading and future climate with sea surface temperature increased by 4 K.
Ha Thi Minh Ho-Hagemann, Vera Maurer, Stefan Poll, and Irina Fast
Geosci. Model Dev., 17, 7815–7834, https://doi.org/10.5194/gmd-17-7815-2024, https://doi.org/10.5194/gmd-17-7815-2024, 2024
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The regional Earth system model GCOAST-AHOI v2.0 that includes the regional climate model ICON-CLM coupled to the ocean model NEMO and the hydrological discharge model HD via the OASIS3-MCT coupler can be a useful tool for conducting long-term regional climate simulations over the EURO-CORDEX domain. The new OASIS3-MCT coupling interface implemented in ICON-CLM makes it more flexible for coupling to an external ocean model and an external hydrological discharge model.
Sandro Vattioni, Rahel Weber, Aryeh Feinberg, Andrea Stenke, John A. Dykema, Beiping Luo, Georgios A. Kelesidis, Christian A. Bruun, Timofei Sukhodolov, Frank N. Keutsch, Thomas Peter, and Gabriel Chiodo
Geosci. Model Dev., 17, 7767–7793, https://doi.org/10.5194/gmd-17-7767-2024, https://doi.org/10.5194/gmd-17-7767-2024, 2024
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We quantified impacts and efficiency of stratospheric solar climate intervention via solid particle injection. Microphysical interactions of solid particles with the sulfur cycle were interactively coupled to the heterogeneous chemistry scheme and the radiative transfer code of an aerosol–chemistry–climate model. Compared to injection of SO2 we only find a stronger cooling efficiency for solid particles when normalizing to the aerosol load but not when normalizing to the injection rate.
Ingo Richter, Ping Chang, Gokhan Danabasoglu, Dietmar Dommenget, Guillaume Gastineau, Aixue Hu, Takahito Kataoka, Noel Keenlyside, Fred Kucharski, Yuko Okumura, Wonsun Park, Malte Stuecker, Andrea Taschetto, Chunzai Wang, Stephen Yeager, and Sang-Wook Yeh
EGUsphere, https://doi.org/10.5194/egusphere-2024-3110, https://doi.org/10.5194/egusphere-2024-3110, 2024
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The tropical ocean basins influence each other through multiple pathways and mechanisms, here referred to as tropical basin interaction (TBI). Many researchers have examined TBI using comprehensive climate models, but have obtained conflicting results. This may be partly due to differences in experiment protocols, and partly due to systematic model errors. TBIMIP aims to address this problem by designing a set of TBI experiments that will be performed by multiple models.
Samuel Rémy, Swen Metzger, Vincent Huijnen, Jason E. Williams, and Johannes Flemming
Geosci. Model Dev., 17, 7539–7567, https://doi.org/10.5194/gmd-17-7539-2024, https://doi.org/10.5194/gmd-17-7539-2024, 2024
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In this paper we describe the development of the future operational cycle 49R1 of the IFS-COMPO system, used for operational forecasts of atmospheric composition in the CAMS project, and focus on the implementation of the thermodynamical model EQSAM4Clim version 12. The implementation of EQSAM4Clim significantly improves the simulated secondary inorganic aerosol surface concentration. The new aerosol and precipitation acidity diagnostics showed good agreement against observational datasets.
Maximillian Van Wyk de Vries, Tom Matthews, L. Baker Perry, Nirakar Thapa, and Rob Wilby
Geosci. Model Dev., 17, 7629–7643, https://doi.org/10.5194/gmd-17-7629-2024, https://doi.org/10.5194/gmd-17-7629-2024, 2024
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This paper introduces the AtsMOS workflow, a new tool for improving weather forecasts in mountainous areas. By combining advanced statistical techniques with local weather data, AtsMOS can provide more accurate predictions of weather conditions. Using data from Mount Everest as an example, AtsMOS has shown promise in better forecasting hazardous weather conditions, making it a valuable tool for communities in mountainous regions and beyond.
Sofia Allende, Anne Marie Treguier, Camille Lique, Clément de Boyer Montégut, François Massonnet, Thierry Fichefet, and Antoine Barthélemy
Geosci. Model Dev., 17, 7445–7466, https://doi.org/10.5194/gmd-17-7445-2024, https://doi.org/10.5194/gmd-17-7445-2024, 2024
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We study the parameters of the turbulent-kinetic-energy mixed-layer-penetration scheme in the NEMO model with regard to sea-ice-covered regions of the Arctic Ocean. This evaluation reveals the impact of these parameters on mixed-layer depth, sea surface temperature and salinity, and ocean stratification. Our findings demonstrate significant impacts on sea ice thickness and sea ice concentration, emphasizing the need for accurately representing ocean mixing to understand Arctic climate dynamics.
Sabin I. Taranu, David M. Lawrence, Yoshihide Wada, Ting Tang, Erik Kluzek, Sam Rabin, Yi Yao, Steven J. De Hertog, Inne Vanderkelen, and Wim Thiery
Geosci. Model Dev., 17, 7365–7399, https://doi.org/10.5194/gmd-17-7365-2024, https://doi.org/10.5194/gmd-17-7365-2024, 2024
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In this study, we improved a climate model by adding the representation of water use sectors such as domestic, industry, and agriculture. This new feature helps us understand how water is used and supplied in various areas. We tested our model from 1971 to 2010 and found that it accurately identifies areas with water scarcity. By modelling the competition between sectors when water availability is limited, the model helps estimate the intensity and extent of individual sectors' water shortages.
Florian Börgel, Sven Karsten, Karoline Rummel, and Ulf Gräwe
EGUsphere, https://doi.org/10.5194/egusphere-2024-2685, https://doi.org/10.5194/egusphere-2024-2685, 2024
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Forecasting river runoff, crucial for managing water resources and understanding climate impacts, can be challenging. This study introduces a new method using Convolutional Long Short-Term Memory (ConvLSTM) networks, a machine learning model that processes spatial and temporal data. Focusing on the Baltic Sea region, our model uses weather data as input to predict daily river runoff for 97 rivers.
Thi Nhu Ngoc Do, Kengo Sudo, Akihiko Ito, Louisa Emmons, Vaishali Naik, Kostas Tsigaridis, Øyvind Seland, Gerd A. Folberth, and Douglas I. Kelley
EGUsphere, https://doi.org/10.5194/egusphere-2024-2313, https://doi.org/10.5194/egusphere-2024-2313, 2024
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Understanding historical isoprene emission changes is important for predicting future climate, but trends and their controlling factors remain uncertain. This study shows that long-term isoprene trends vary among Earth System Models mainly due to partially incorporating CO2 effects and land cover changes rather than climate. Future models that refine these factors’ effects on isoprene emissions, along with long-term observations, are essential for better understanding plant-climate interactions.
Michael Nole, Jonah Bartrand, Fawz Naim, and Glenn Hammond
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-162, https://doi.org/10.5194/gmd-2024-162, 2024
Revised manuscript accepted for GMD
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Safe carbon dioxide (CO2) storage is likely to be critical for mitigating some of the most dangerous effects of climate change. We present a simulation framework for modeling CO2 storage beneath the seafloor where CO2 can form a solid. This can aid in permanent CO2 storage for long periods of time. Our models show what a commercial-scale CO2 injection would look like in a marine environment. We discuss what would need to be considered when designing a sub-sea CO2 injection.
Cynthia Whaley, Montana Etten-Bohm, Courtney Schumacher, Ayodeji Akingunola, Vivek Arora, Jason Cole, Michael Lazare, David Plummer, Knut von Salzen, and Barbara Winter
Geosci. Model Dev., 17, 7141–7155, https://doi.org/10.5194/gmd-17-7141-2024, https://doi.org/10.5194/gmd-17-7141-2024, 2024
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This paper describes how lightning was added as a process in the Canadian Earth System Model in order to interactively respond to climate changes. As lightning is an important cause of global wildfires, this new model development allows for more realistic projections of how wildfires may change in the future, responding to a changing climate.
Erik Gustafsson, Bo G. Gustafsson, Martijn Hermans, Christoph Humborg, and Christian Stranne
Geosci. Model Dev., 17, 7157–7179, https://doi.org/10.5194/gmd-17-7157-2024, https://doi.org/10.5194/gmd-17-7157-2024, 2024
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Methane (CH4) cycling in the Baltic Proper is studied through model simulations, enabling a first estimate of key CH4 fluxes. A preliminary budget identifies benthic CH4 release as the dominant source and two main sinks: CH4 oxidation in the water (92 % of sinks) and outgassing to the atmosphere (8 % of sinks). This study addresses CH4 emissions from coastal seas and is a first step toward understanding the relative importance of open-water outgassing compared with local coastal hotspots.
Daniel Ries, Katherine Goode, Kellie McClernon, and Benjamin Hillman
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-133, https://doi.org/10.5194/gmd-2024-133, 2024
Revised manuscript accepted for GMD
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Machine learning has advanced research in the climate science domain, but its models are difficult to understand. In order to understand the impacts and consequences of climate interventions such as stratospheric aerosol injection, complex models are often necessary. We use a case study to illustrate how we can understand the inner workings of a complex model. We present this technique as an exploratory tool that can be used to quickly discover and assess relationships in complex climate data.
Florian Zabel, Matthias Knüttel, and Benjamin Poschlod
EGUsphere, https://doi.org/10.5194/egusphere-2024-2526, https://doi.org/10.5194/egusphere-2024-2526, 2024
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CropSuite is a fuzzy-logic based high resolution open-source crop suitability model considering the impact of climate variability. We apply CropSuite for 48 important staple and cash crops at 1 km spatial resolution for Africa. We find that climate variability significantly impacts on suitable areas, but also affects optimal sowing dates, and multiple cropping potentials. The results provide information that can be used for climate impact assessments, adaptation and land-use planning.
Kerstin Hartung, Bastian Kern, Nils-Arne Dreier, Jörn Geisbüsch, Mahnoosh Haghighatnasab, Patrick Jöckel, Astrid Kerkweg, Wilton Jaciel Loch, Florian Prill, and Daniel Rieger
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-135, https://doi.org/10.5194/gmd-2024-135, 2024
Revised manuscript accepted for GMD
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The Icosahedral Nonhydrostatic (ICON) Model Community Interface (ComIn) library supports connecting third-party modules to the ICON model. Third-party modules can range from simple diagnostic Python scripts to full chemistry models. ComIn offers a low barrier for code extensions to ICON, provides multi-language support (Fortran, C/C++ and Python) and reduces the migration effort in response to new ICON releases. This paper presents the ComIn design principles and a range of use cases.
Tridib Banerjee, Patrick Scholz, Sergey Danilov, Knut Klingbeil, and Dmitry Sidorenko
Geosci. Model Dev., 17, 7051–7065, https://doi.org/10.5194/gmd-17-7051-2024, https://doi.org/10.5194/gmd-17-7051-2024, 2024
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In this paper we propose a new alternative to one of the functionalities of the sea ice model FESOM2. The alternative we propose allows the model to capture and simulate fast changes in quantities like sea surface elevation more accurately. We also demonstrate that the new alternative is faster and more adept at taking advantages of highly parallelized computing infrastructure. We therefore show that this new alternative is a great addition to the sea ice model FESOM2.
Yuwen Fan, Zhao Yang, Min-Hui Lo, Jina Hur, and Eun-Soon Im
Geosci. Model Dev., 17, 6929–6947, https://doi.org/10.5194/gmd-17-6929-2024, https://doi.org/10.5194/gmd-17-6929-2024, 2024
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Irrigated agriculture in the North China Plain (NCP) has a significant impact on the local climate. To better understand this impact, we developed a specialized model specifically for the NCP region. This model allows us to simulate the double-cropping vegetation and the dynamic irrigation practices that are commonly employed in the NCP. This model shows improved performance in capturing the general crop growth, such as crop stages, biomass, crop yield, and vegetation greenness.
Gang Tang, Zebedee Nicholls, Alexander Norton, Sönke Zaehle, and Malte Meinshausen
EGUsphere, https://doi.org/10.5194/egusphere-2024-1941, https://doi.org/10.5194/egusphere-2024-1941, 2024
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We studied the coupled carbon-nitrogen cycle effect in Earth System Models by developing a carbon-nitrogen coupling in a reduced complexity model, MAGICC. Our model successfully emulated the global carbon-nitrogen cycle dynamics seen in CMIP6 complex models. Results indicate consistent nitrogen limitations on plant growth (net primary production) from 1850 to 2100. Our findings suggest that nitrogen deficiency could reduce future land carbon sequestration.
Ed Blockley, Emma Fiedler, Jeff Ridley, Luke Roberts, Alex West, Dan Copsey, Daniel Feltham, Tim Graham, David Livings, Clement Rousset, David Schroeder, and Martin Vancoppenolle
Geosci. Model Dev., 17, 6799–6817, https://doi.org/10.5194/gmd-17-6799-2024, https://doi.org/10.5194/gmd-17-6799-2024, 2024
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This paper documents the sea ice model component of the latest Met Office coupled model configuration, which will be used as the physical basis for UK contributions to CMIP7. Documentation of science options used in the configuration are given along with a brief model evaluation. This is the first UK configuration to use NEMO’s new SI3 sea ice model. We provide details on how SI3 was adapted to work with Met Office coupling methodology and documentation of coupling processes in the model.
Jean-François Lemieux, William H. Lipscomb, Anthony Craig, David A. Bailey, Elizabeth C. Hunke, Philippe Blain, Till A. S. Rasmussen, Mats Bentsen, Frédéric Dupont, David Hebert, and Richard Allard
Geosci. Model Dev., 17, 6703–6724, https://doi.org/10.5194/gmd-17-6703-2024, https://doi.org/10.5194/gmd-17-6703-2024, 2024
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We present the latest version of the CICE model. It solves equations that describe the dynamics and the growth and melt of sea ice. To do so, the domain is divided into grid cells and variables are positioned at specific locations in the cells. A new implementation (C-grid) is presented, with the velocity located on cell edges. Compared to the previous B-grid, the C-grid allows for a natural coupling with some oceanic and atmospheric models. It also allows for ice transport in narrow channels.
Victor Couplet, Marina Martínez Montero, and Michel Crucifix
EGUsphere, https://doi.org/10.5194/egusphere-2024-2279, https://doi.org/10.5194/egusphere-2024-2279, 2024
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We present SURFER v3.0, a simple climate model designed to estimate the impact of CO2 and CH4 emissions on global temperatures, sea levels, and ocean pH. We added new carbon cycle processes and calibrated the model to observations and results from more complex models, enabling use over time scales ranging from decades to millions of years. SURFER v3.0 is fast, transparent, and easy to use, making it an ideal tool for policy assessments and suitable for educational purposes.
Rachid El Montassir, Olivier Pannekoucke, and Corentin Lapeyre
Geosci. Model Dev., 17, 6657–6681, https://doi.org/10.5194/gmd-17-6657-2024, https://doi.org/10.5194/gmd-17-6657-2024, 2024
Short summary
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This study introduces a novel approach that combines physics and artificial intelligence (AI) for improved cloud cover forecasting. This approach outperforms traditional deep learning (DL) methods in producing realistic and physically consistent results while requiring less training data. This architecture provides a promising solution to overcome the limitations of classical AI methods and contributes to open up new possibilities for combining physical knowledge with deep learning models.
Marit Sandstad, Borgar Aamaas, Ane Nordlie Johansen, Marianne Tronstad Lund, Glen Philip Peters, Bjørn Hallvard Samset, Benjamin Mark Sanderson, and Ragnhild Bieltvedt Skeie
Geosci. Model Dev., 17, 6589–6625, https://doi.org/10.5194/gmd-17-6589-2024, https://doi.org/10.5194/gmd-17-6589-2024, 2024
Short summary
Short summary
The CICERO-SCM has existed as a Fortran model since 1999 that calculates the radiative forcing and concentrations from emissions and is an upwelling diffusion energy balance model of the ocean that calculates temperature change. In this paper, we describe an updated version ported to Python and publicly available at https://github.com/ciceroOslo/ciceroscm (https://doi.org/10.5281/zenodo.10548720). This version contains functionality for parallel runs and automatic calibration.
Cited articles
Aber, J., Neilson, R. P., McNulty, S., Lenihan, J. M., Bachelet, D., and
Drapek, R. J.: Forest processes and global environmental change: predicting
the effects of individual and multiple stressors, Bioscience, 51, 735–751,
2001.
André, F., Jonard, M., and Ponette, Q.: Precipitation water storage
capacity in a temperate mixed oak–beech canopy, Hydrol. Process., 22,
4130–4141, 2008a.
André, F., Jonard, M., and Ponette, Q.: Influence of species and rain
event characteristics on stemflow volume in a temperate mixed oak–beech
stand, Hydrol. Process., 22, 4455–4466, 2008b.
André, F., Jonard, M., and Ponette, Q.: Biomass and nutrient content of
sessile oak (Quercus petraea (Matt.) Liebl.) and beech (Fagus sylvatica L.) stem and branches in a mixed
stand in southern Belgium, Sci. Total Environ., 408, 2285–2294, 2010.
André, F., Jonard, M., Jonard, F., and Ponette, Q.: Spatial and temporal
patterns of throughfall volume in a deciduous mixed-species stand, J.
Hydrol., 400, 244–255, 2011.
Anlauf, R. and Liu, Y. P.: Simulation of simple one-dimensional transport
processes, in: Models for Processes in the Soil: Programs
and Exercises, edited by: Richter, J., Catena Verlag, Cremlingen-Desdedt, Germany, 1990.
Baker, D. L. and Don Scott, H.: A limited tutorial on using finite
differences in soil physics problems, available at:
http://www.aquarien.com/findif/Findifa4.html (last access: 29 February 2020), 1998.
Ball, J. T., Woodrow, I. E., and Berry, J. A.: A model predicting stomatal
conductance and its contribution to the control of photosynthetis under
different environmental conditions, in: Progress in
Photosynthesis Research, edited by: Biggins, J., vol. 4, 221–224, 1987.
Berger, U., Piou, C., Schiffers, K., and Grimm, V.: Competition among plants: concepts, individual-based modelling approaches, and a proposal for a future research strategy, Perspect. Plant Ecol., 9, 121–135, 2008.
Boisvenue, C. and Running, S. W.: Impacts of climate change on natural forest
productivity–evidence since the middle of the 20th century, Glob. Change
Biol., 12, 862–882, 2006.
Bontemps, J. D., Hervé, J. C., Leban, J. M., and Dhôte, J. F.: Nitrogen footprint in a long-term observation of forest growth over the twentieth century., Trees, 25, 237–251, 2011.
Bosc, A.: EMILION, a tree functional-structural model: presentation and
first application to the analysis of branch carbon balance, Ann. Forest Sci.,
57, 555–569, 2000.
Bravo, F., Fabrika, M., Ammer, C., Barreiro, S., Bielak, K., Coll, L., Fonseca, T., Kangur, A., Löf, M., Merganicova, K., Pach, M., Pretzsch, H., Stojanovic, D., Schuler, L., Peric, S., Rötzer, T., del Rio, M., Dodan, M., and Bravo-Oviedo, A.: Modelling approaches for mixed forests dynamics prognosis, Research gaps and opportunities, Forest Syst., 28, eR002, doi:10.5424/fs/2019281-14342, 2019.
Campioli, M., Vincke, C., Jonard, M., Kint, V., Demarée, G., and Ponette,
Q.: Current status and predicted impact of climate change on forest
production and biogeochemistry in the temperate oceanic European zone:
review and prospects for Belgium as a case study, J. Forest Res., 17, 1–18,
2012.
Cantarello, E., Newton, A. C., Martin, P. A., Evans, P. M., Gosal, A., and
Lucash, M. S.: Quantifying resilience of multiple ecosystem services and
biodiversity in a temperate forest landscape, Ecol. Evol., 7, 9661–9675,
2017.
Carl, C., Biber, P., Veste, M., Landgraf, D., and Pretzsch, H.: Key drivers
of competition and growth partitioning among Robinia pseudoacacia L. trees,
Forest Ecol. Manage., 430, 86–93, 2018.
Charlton, S. R. and Parkhurst, D. L.: Modules based on the geochemical model
PHREEQC for use in scripting and programming languages, Comput. Geosci.,
37, 1653–1663, 2011.
Cichota, R., Elias, E. A., and van Lier, Q. D. J.: Testing a finite-difference model for soil heat transfer by comparing numerical and analytical solutions, Environ. Model. Softw., 19, 495–506, 2004.
Collalti, A., Trotta, C., Keenan, T. F., Ibrom, A., Bond-Lamberty, B.,
Grote, R., Vicca, S., Reyer, C. P. O., Migliavacca, M., Veroustraete, F., Anav, A., Campioli, M., Scoccimarro, E., Šigut, L., Grieco, E., Cescatti, A., and Matteucci G.: Thinning can reduce losses in carbon use efficiency and
carbon stocks in managed forests under warmer climate, J. Adv. Model. Earth
Sy., 10, 2427–2452, 2018.
Collalti, A. and Prentice, I. C.: Is NPP proportional to GPP? Waring's
hypothesis 20 years on, Tree Physiol. 39, 1473–1483, 2019.
Collins, M., Knutti, R., Arblaster, J., Dufresne, J. L., Fichefet, T.,
Friedlingstein, P., Gao, X., Gutowski, W. J., Johns, T., Krinner, G.,
Shongwe, M., Tebaldi, C., Weaver, A. J., and Wehner, M.: Long-term Climate
Change: Projections, Commitments and Irreversibility, in: Climate Change 2013: The Physical Science Basis, Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Stocker, T. F., Qin, D., Plattner, G. K., Tignor, M., Allen, S. K., Boschung, J., Nauels, A., Xia, Y., Bex, V., Midgley, P. M., Cambridge University Press, Cambridge, UK, New York, NY, USA, 2013.
Courbaud, B., de Coligny, F., and Cordonnier, T.: Simulating radiation
distribution in a heterogeneous Norway spruce forest on a slope, Agr. Forest
Meteorol., 116, 1–18, 2003.
Dagnelie, P., Palm, R., Rondeux, J., and Thill, A.: Tables de cubage des arbres
et des peuplements forestiers, Les Presses Agronomiques de Gembloux,
Gembloux, Belgique, 1999.
Damesin, C., Ceschia, E., Le Goff, N., Ottorini, J. M., and Dufrêne, E.:
Stem and branch respiration of beech: from tree measurements to estimations
at the stand level, New Phytol., 153, 159–172, 2002.
Davi, H., Dufrêne, E., Francois, C., Le Maire, G., Loustau, D., Bosc,
A., Rambal, S., Granier, A., and Moors, E.: Sensitivity of water and carbon
fluxes to climate changes from 1960 to 2100 in European forest ecosystems,
Agr. Forest Meteorol., 141, 35–56, 2006.
Davi, H., Cailleret, M., Restoux, G., Amm, A., Pichot, C., and Fady, B.:
Disentangling the factors driving tree reproduction,
Ecosphere, 7, e01389, https://doi.org/10.1002/ecs2.1389, 2016.
del Río, M., Bravo-Oviedo, A., Ruiz-Peinado, R., and Condés, S.:
Tree allometry variation in response to intra- and inter-specific
competitions, Trees, 33, 121–138, 2019.
de Wergifosse, L., André, F., Beudez, N., de Coligny, F., Goosse, H., Jonard, F., Ponette, Q., Titeux, H., Vincke, C., and Jonard, M.: HETEROFOR 1.0: a spatially explicit model for exploring the response of structurally complex forests to uncertain future conditions. II. Phenology and water cycle, Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2019-201, in review, 2019.
de Wergifosse, L., André, F., Goosse, H., Caluwaerts, S., De Cruz, L.,
De Troch, R., and Van Schaeybroeck, B.: CO2 fertilization, water deficit and vegetation period drive the response of mixed broadleaved forests to a changing climate in Wallonia, Ann. Forest Sci., in review, 2020.
Dufour-Kowalski, S., Courbaud, B., Dreyfus, P., Meredieu, C., and de
Coligny, F.: Capsis: an open software framework and community for forest
growth modelling, Ann. Forest Sci., 69, 221–233, 2012.
Dufrêne, E., Davi, H., François, C., Le Maire, G., Le Dantec, V.,
and Granier, A.: Modelling carbon and water cycles in a beech forest: Part
I: Model description and uncertainty analysis on modelled NEE, Ecol. Model.,
185, 407–436, 2005.
Duursma, R. A. and Medlyn, B. E.: MAESPA: a model to study interactions between water limitation, environmental drivers and vegetation function at tree and stand levels, with an example application to [CO2] × drought interactions, Geosci. Model Dev., 5, 919–940, https://doi.org/10.5194/gmd-5-919-2012, 2012.
Ennos, R., Cottrell, J., Hall, J., and O'Brien, D.: Is the introduction of
novel exotic forest tree species a rational response to rapid environmental
change? – A British perspective, Forest Ecol. Manag., 432, 718–728,
2019.
Epron, D., Le Dantec, V., Dufrêne, E., and Granier, A.: Seasonal
dynamics of soil carbon efflux and simulated rhizosphere respiration in a
beech forest, Tree Physiol., 21, 145–152, 2001.
Farquhar, G. D., von Caemmerer, S., and Berry, J. A.: A biochemical model of
photosynthetic CO2 assimilation in leaves of C3 species, Planta, 149,
78–80, 1980.
Fernandez-Martinez, M., Vicca, S., Janssens, I. A., Sardans, J., Luyssaert,
S., Campioli, M., Chapin III, F. S., Ciais, P., Malhi, Y., Obersteiner, M.,
Papale, D., Piao, S. L., Reichstein, M., Rodà, F., and Peñuelas, J.:
Nutrient availability as the key regulator of global forest carbon balance.
Nat. Clim. Change, 4, 471–476, 2014.
Forrester, D. I. and Albrecht, A. T.: Light absorption and light-use
efficiency in mixtures of Abies alba and Picea abies along a productivity
gradient, Forest Ecol. Manag., 328, 94–102, 2014.
Genet, H., Bréda, N., and Dufrêne, E.: Age-related variation in
carbon allocation at tree and stand scales in beech (Fagus sylvatica L.) and sessile oak
(Quercus petraea (Matt.) Liebl.) using a chronosequence approach, Tree Physiol., 30, 177–192, 2010.
Genet, A., Wernsdörfer, H., Jonard, M., Pretzsch, H., Rauch, M.,
Ponette, Q., Nys, C., Legout, A., Ranger, J., Vallet P., and
Saint-André, L.: Ontogeny partly explains the apparent heterogeneity of
published biomass equations for Fagus sylvatica in central Europe, Forest
Ecol. Manag., 261, 1188–1202, 2011.
Giot, O., Termonia, P., Degrauwe, D., De Troch, R., Caluwaerts, S., Smet, G., Berckmans, J., Deckmyn, A., De Cruz, L., De Meutter, P., Duerinckx, A., Gerard, L., Hamdi, R., Van den Bergh, J., Van Ginderachter, M., and Van Schaeybroeck, B.: Validation of the ALARO-0 model within the EURO-CORDEX framework, Geosci. Model Dev., 9, 1143–1152, https://doi.org/10.5194/gmd-9-1143-2016, 2016.
Greene, D., Messier, C., Asselin, H., and Fortin, M.: The effect of light
availability and basal area on cone production in Abies balsamea and Picea
glauca, Can. J. Bot., 80, 370–377, 2002.
Grote, R. and Pretzsch, H.: A model for individual tree development based on
physiological processes, Plant Biol., 4, 167–180, 2002.
Haxeltine, A. and Prentice, I. C.: A general model for the light use
efficiency of primary production by terrestrial ecosystems, Funct. Ecol.,
10, 551–561, 1996.
Helmisaari, H. S., Derome, J., Nöjd, P., and Kukkola, M.: Fine root
biomass in relation to site and stand characteristics in Norway spruce and
Scots pine stands, Tree Physiol., 27, 1493–1504, 2007.
Henry, H. A. L. and Aarssen, L. W.: The interpretation of stem diameter-height allometry in trees: biomechanical constraints, neighbour effects, or biased
regressions?, Ecol. Lett., 2, 89–97, 1999.
Hounzandji, A. P., Jonard, M., Nys, C., Saint-André, L., and Ponette, Q.:
Improving the robustness of biomass functions: from empirical to functional
approaches, Ann. Forest Sci., 72, 795–810, 2015.
Janssen, P. H. M. and Heuberger, P. S. C.: Calibration of process-oriented
models, Ecol. Model., 83, 55–66, 1995.
Jonard, M., André, F., and Ponette, Q.: Modeling leaf dispersal in mixed
hardwood forests using a ballistic approach, Ecology, 87, 2306–2318, 2006.
Jonard, M., André, F., Jonard, F., Mouton, N., Procès, P., and
Ponette, Q.: Soil carbon dioxide efflux in pure and mixed stands of oak and
beech, Ann. Forest Sci., 64, 141–150, 2007.
Jonard, M., André, F., and Ponette, Q.: Tree species mediated effects on
leaf litter dynamics in pure and mixed stands of oak and beech, Can. J.
Forest Res., 38, 528–538, 2008.
Jonard, F., André, F., Ponette, Q., Vincke, C., and Jonard, M.: Sap flux
density and stomatal conductance of European beech and sessile oak trees in
pure and mixed stands during the summer drought of 2003, J. Hydrol., 409,
371–381, 2011.
Jonard, M., Fürst, A., Verstraeten, A., Thimonier, A., Timmermann, V.,
Potocic, N., Waldner, P., Benham, S., Hansen, K., Merila, P., Ponette, Q., De La Cruz, A. C., Roskams, P., Nicolas, M., Croisé, L., Ingerslev,
M., Matteuci, G., Decinti, B., Bascietto, M., and Rautio, P.: Tree mineral
nutrition is deteriorating in Europe, Global Change Biol., 21, 418–430,
2015.
Jonard, M., André, F., and de Wergifosse, L.: Code of HETEROFOR 1.0, https://doi.org/10.5281/zenodo.3591348, 2019.
Jonard, M., André, F., and de Wergifosse, L.: Installer of HETEROFOR 1.0, http://amap-dev.cirad.fr/projects/capsis/files, last access: 29 February 2020.
Jucker, T., Bouriaud, O., and Coomes, D. A.: Crown plasticity enables trees to
optimize canopy packing in mixed-species forest, Funct. Ecol., 29,
1078–1086, 2015.
Kersten, M. S.: Laboratory research for the determination of the thermal
properties of soils, University of Minnesota, Engineering Experiment
Station, 1949.
Le Moguédec, G. and Dhôte, J. F.: Fagacées: a tree-centered
growth and yield model for sessile oak (Quercus petraea L.) and common beech (Fagus sylvatica L.), Ann.
Forest Sci., 69, 257–269, 2012.
Letort, V., Cournède, P. H., Mathieu, A., de Reffye, P., and Constant,
T.: Parametric identification of a functional-structural tree growth model
and application to beech trees (Fagus sylvatica), Funct. Plant Biol., 35, 951–963, 2008.
Ligot, G., Balandier, P., Courbaud, B., Jonard, M., and Kneeshaw, D.:
Managing understory light to maintain a mixture of species with different
shade tolerance, Forest Ecol. Manag., 327, 189–200, 2014.
Lindner, M., Maroschek, M., Netherer, S., Kremer, A., Barbati, A.,
Garcia-Gonzalo, J., Seidl, R., Delzon, S., Corona, P., Kolström, M.,
Lexer, M. J., and Marchetti, M.: Climate change impacts, adaptive capacity,
and vulnerability of European forest ecosystems, Forest Ecol. Manag., 259,
698–709, 2010.
Lindner, M., Fitzgerald, J. B., Zimmermann, N. E., Reyer, C., Delzon, S., van
der Maaten, E., Schelhaas, M.-J. Lasch, P., Eggers, J., van der
Maaten-Theunissen, M., Suckow, F., Psomas, A., Poulter, B., and Hanewinkel,
M.: Climate change and European forests: What do we know, what are the
uncertainties, and what are the implications for forest management? J.
Environ. Manage., 146, 69–83, 2014.
Lines, E. R., Zavala, M. A., Purves, D. W., and Coomes, D. A.: Predictable
changes in aboveground allometry of trees along gradients of temperature,
aridity and competition, Glob. Ecol. Biogeogr., 21, 1017–1028, 2012.
Mäkelä, A.: Implications of the pipe model theory on dry matter
partitioning and height growth in trees, J. Theor. Biol., 123, 103–120,
1986.
Mäkelä, A. and Valentine, H. T.: The ratio of NPP to GPP: evidence of
change over the course of stand development, Tree Physiol., 21, 1015–1030,
2001.
Manion, P. D.: Tree Disease Concepts, Prentice-Hall, Englewood Cliffs, NJ,
402 pp., 1981.
Maraun, D. and Widmann, M.: Statistical downscaling and bias correction for
climate research, Cambridge University Press, Cambridge, 2018.
Mellert, K. H. and Göttlein, A.: Comparison of new foliar nutrient
thresholds derived from van den Burg's literature compilation with
established central European references, Eur. J. Forest Res., 131, 1461–1472,
2012.
Messier, C., Puettmann, K., Chazdon, R., Andersson, K. P., Angers, V. A.,
Brotons, L., Filotas, E., Tittler, R., Parrrott, L., and Levin, S. A.: From
management to stewardship: viewing forests as complex adaptative systems in
an uncertain world, Conserv. Lett., 8, 368–377, 2015.
Monteith, J. L.: Climate and the efficiency of crop production in Britain,
Philos. Trans. Royal Soc. B, 281, 277–294, 1977.
Morales, P., Hickler, T., Rowell, D. P., Smith, B., and Sykes, M. T.: Changes
in European ecosystem productivity and carbon balance driven by regional
climate model output, Global Change Biol., 13, 108–122, 2007.
Oliver, T. H., Heard, M. S., Isaac, N. J. B., Roy, D. B., Procter, D., Eigenbrod, F., Freckleton, R., Hector, A., Orme, C. D. L., Petchey, O. L., Proença, V., Raffaelli, D., Suttle, K. B., Mace, G. M., Martín López, B., Woodcock, B. A., and Bullock, J. M.: Biodiversity and resilience of ecosystem
functions, Trends Ecol Evol., 30, 673–684, 2015.
Penning de Vries, F. W. T.: The cost of maintenance processes in plant cells,
Ann. Bot., 39, 77–92, 1975.
Pretzsch, H.: Canopy space filling and tree crown morphology in mixed-species
stands compared with monocultures, Forest Ecol. Manag., 327, 251–264, 2014.
Pretzsch, H., Forrester, D. I., and Rötzer, T.: Representation of species
mixing in forest growth models, A review and perspective, Ecol. Model., 313,
276–292, 2015.
R Core Team: R: A language and environment for statistical computing, 2013.
Reyer, C., Lasch-Born, P., Suckow, F., Gutsch, M., Murawski, A., and Pilz,
T.: Projections of regional changes in forest net primary productivity for
different tree species in Europe driven by climate change and carbon
dioxide, Ann. Forest Sci., 71, 211–225, 2014.
Rodríguez-Calcerrada, J., Martin-St. Paul, N. K., Lempereur, M., Ourcival, J. M., del Carmen del Rey, M., Joffre, R., and Rambal, S.: Stem CO2 efflux and its contribution to ecosystem CO2 efflux decrease with drought in a Mediterranean forest stand, Agr. Forest Meteorol., 195–196, 61–72, 2014.
Rodríguez-Calcerrada, J., López, R., Salomón, R., Gordaliza,
G. G., Valbuena-Carabaña, M., Oleksyn, J., and Gil, L.: Stem CO2
efflux in six co-occurring tree species: underlying factors and ecological
implications, Plant Cell Environ., 38, 1104–1115, 2015.
Rötzer, T., Liao, Y., Goergen, K., Schüler, G., and Pretzsch, H.:
Modelling the impact of climate change on the productivity and water-use
efficiency of a central European beech forest, Clim. Res., 58, 81–95, 2013.
Ryan, M. G.: Effects of climate change on plant respiration, Ecol. Appl., 1,
157–167, 1991.
Ryan, M. G. and Yoder, B. J.: Hydraulic limits to tree height and tree growth.
What keeps trees from growing beyond a certain height? BioScience, 47,
235–242, 1997.
Schäfer, K. V. R., Oren, R., and Tenhunen, J. D.: The effect of tree height on crown level stomatal conductance, Plant Cell Environ., 23, 365–375,
2000.
Schwalm, C. R. and Ek, A. R.: A process-based model of forest ecosystems
driven by meteorology, Ecol. Model., 179, 317–348, 2004.
Simioni, G., Marie, G., and Huc, R.: Influence of vegetation spatial
structure on growth and water fluxes of a mixed forest: Results from the
NOTG 3D model, Ecol. Model., 328, 119–135, 2016.
Teh, C. B. S.: Introduction to mathematical modeling of crop growth. How the
equations are derived and assembled into a computer program, Brown Walker
Press, Boca Raton, Florida, USA, 2006.
Tetens, O.: Uber einige meteorologische Begriffe, Z. Geophys., 6, 297–309,
1930.
Thompson, I., Mackey, B., McNulty, S., and Mosseler, A.: Forest resilience,
biodiversity, and climate change. A synthesis of the
biodiversity/resilience/stability relationship in forest ecosystems.
Secretariat of the Convention on Biological Diversity, Montreal, Technical
Series no. 43, 2009.
Thurm, E. A., Biber, P., and Pretzsch, H.: Stem growth is favored at expenses
of root growth in mixed stands and humid conditions for Douglas-fir
(Pseudotsuga menziesii) and European beech (Fagus sylvatica), Trees-Struct.
Funct., 31, 349–365, 2017.
Trouvé, R., Bontemps, J. D., Seynave, I., Collet, C., and Lebourgeois,
F.: Stand density, tree social status and water stress influence allocation
in height and diameter growth of Quercus petraea (Liebl.), Tree Physiol., 35, 1035–1046,
2015.
Van Wijk, W. R. and De Vries, D. A.: Periodic temperature variations in a
homogenous soil, in: Physics of Plant Environment, edited by: Van Wijk, W. R., North Holland Publishing Company, Amsterdam, 1963.
Villar, R., Held, A. A., and Merino, J.: Dark leaf respiration in light and
darkness of an evergreen and a deciduous plant species, Plant Physiol., 107,
421–427, 1995.
Voldoire, A., Sanchez-Gomez, E., Salas y Mélia, D., Decharme, B.,
Cassou, C., Sénési, S., Valcke, S., Beau, I., Alias, A., Chevallier,
M., Déqué, M., Deshayes, J., Douville, H., Fernandez, E., Madec, G.,
Maisonnave, E., Moine, M. P., Planton, S., Saint-Martin, D., Szopa, S.,
Tyteca, S., Alkama, R., Belamari, S., Braun, A., Coquart, L., and Chauvin,
F.: The CNRM-CM5.1 global climate model: description and basic evaluation,
Clim. Dynam., 40, 2091–2121, 2013.
Vose, J. M. and Bolstad, P. V.: Challenges to modelling NPP in diverse eastern deciduous forests: species-level comparisons of foliar respiration responses to temperature and nitrogen, Ecol. Model., 122, 165–174, 1999.
Yamori, W., Hikosaka, K., and Way, D. A.: Temperature response of
photosynthesis in C3, C4, and CAM plants: temperature acclimation and
temperature adaptation, Photosynth. Res., 119, 101–117, 2013.
Short summary
To explore the forest response to new forestry practices under a changing environment, one needs models combining a process-based approach with a detailed spatial representation, which is very rare. We decided to develop our own model according to a spatially explicit approach describing individual tree growth based on resource sharing (light, water and nutrients). A first evaluation showed that HETEROFOR predicts well individual radial growth and is able to reproduce size–growth relationships.
To explore the forest response to new forestry practices under a changing environment, one needs...
