Articles | Volume 11, issue 1
https://doi.org/10.5194/gmd-11-467-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-11-467-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Model description paper
| 
01 Feb 2018
Model description paper |
| 01 Feb 2018
CITRATE 1.0: Phytoplankton continuous trait-distribution model with one-dimensional physical transport applied to the North Pacific
Bingzhang Chen
CORRESPONDING AUTHOR
Research Center for Global Change Research, JAMSTEC (Japan Agency for
Marine-Earth Science and Technology), 3173-25 Showa-machi, Kanazawa-ku,
Yokohama 236-0001, Japan
Sherwood Lan Smith
Research Center for Global Change Research, JAMSTEC (Japan Agency for
Marine-Earth Science and Technology), 3173-25 Showa-machi, Kanazawa-ku,
Yokohama 236-0001, Japan
Related authors
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Onur Kerimoglu, Markus Pahlow, Prima Anugerahanti, and Sherwood Lan Smith
Geosci. Model Dev., 16, 95–108, https://doi.org/10.5194/gmd-16-95-2023, https://doi.org/10.5194/gmd-16-95-2023, 2023
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In classical models that track the changes in the elemental composition of phytoplankton, additional state variables are required for each element resolved. In this study, we show how the behavior of such an explicit model can be approximated using an
instantaneous acclimationapproach, in which the elemental composition of the phytoplankton is assumed to adjust to an optimal value instantaneously. Through rigorous tests, we evaluate the consistency of this scheme.
Yoshikazu Sasai, Sherwood Lan Smith, Eko Siswanto, Hideharu Sasaki, and Masami Nonaka
Biogeosciences, 19, 4865–4882, https://doi.org/10.5194/bg-19-4865-2022, https://doi.org/10.5194/bg-19-4865-2022, 2022
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We have investigated the adaptive response of phytoplankton growth to changing light, nutrients, and temperature over the North Pacific using two physical-biological models. We compare modeled chlorophyll and primary production from an inflexible control model (InFlexPFT), which assumes fixed carbon (C):nitrogen (N):chlorophyll (Chl) ratios, to a recently developed flexible phytoplankton functional type model (FlexPFT), which incorporates photoacclimation and variable C:N:Chl ratios.
Onur Kerimoglu, Prima Anugerahanti, and Sherwood Lan Smith
Geosci. Model Dev., 14, 6025–6047, https://doi.org/10.5194/gmd-14-6025-2021, https://doi.org/10.5194/gmd-14-6025-2021, 2021
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In large-scale models, variations in cellular composition of phytoplankton are often insufficiently represented. Detailed modeling approaches exist, but they require additional state variables that increase the computational costs. In this study, we test an instantaneous acclimation model in a spatially explicit setup and show that its behavior is mostly similar to that of a variant with an additional state variable but different from that of a fixed composition variant.
Guillaume Le Gland, Sergio M. Vallina, S. Lan Smith, and Pedro Cermeño
Geosci. Model Dev., 14, 1949–1985, https://doi.org/10.5194/gmd-14-1949-2021, https://doi.org/10.5194/gmd-14-1949-2021, 2021
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We present an ecological model called SPEAD wherein various phytoplankton compete for nutrients. Phytoplankton in SPEAD are characterized by two continuously distributed traits: optimal temperature and nutrient half-saturation. Trait diversity is sustained by allowing the traits to mutate at each generation. We show that SPEAD agrees well with a more classical discrete model for only a fraction of the cost. We also identify realistic values for the mutation rates to be used in future models.
Esteban Acevedo-Trejos, Gunnar Brandt, S. Lan Smith, and Agostino Merico
Geosci. Model Dev., 9, 4071–4085, https://doi.org/10.5194/gmd-9-4071-2016, https://doi.org/10.5194/gmd-9-4071-2016, 2016
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Marine phytoplankton plays a prominent role in regulating Earth’s climate. Numerical models are important tools that help us investigate the interactions between these microbes and their environment. We proposed PhytoSFDM as an open-source model to quantify size structure and functional diversity of marine phytoplankton communities. This tool allows us, in a manageable and computationally efficient way, to study patterns in planktonic ecosystems and their feedbacks with a changing environment.
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Geosci. Model Dev., 15, 7593–7639, https://doi.org/10.5194/gmd-15-7593-2022, https://doi.org/10.5194/gmd-15-7593-2022, 2022
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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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Geosci. Model Dev., 15, 7325–7351, https://doi.org/10.5194/gmd-15-7325-2022, https://doi.org/10.5194/gmd-15-7325-2022, 2022
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Shanlin Tong, Weiguang Wang, Jie Chen, Chong-Yu Xu, Hisashi Sato, and Guoqing Wang
Geosci. Model Dev., 15, 7075–7098, https://doi.org/10.5194/gmd-15-7075-2022, https://doi.org/10.5194/gmd-15-7075-2022, 2022
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Plant carbon storage potential is central to moderate atmospheric CO2 concentration buildup and mitigation of climate change. There is an ongoing debate about the main driver of carbon storage. To reconcile this discrepancy, we use SEIB-DGVM to investigate the trend and response mechanism of carbon stock fractions among water limitation regions. Results show that the impact of CO2 and temperature on carbon stock depends on water limitation, offering a new perspective on carbon–water coupling.
Jing Fang, Herman H. Shugart, Feng Liu, Xiaodong Yan, Yunkun Song, and Fucheng Lv
Geosci. Model Dev., 15, 6863–6872, https://doi.org/10.5194/gmd-15-6863-2022, https://doi.org/10.5194/gmd-15-6863-2022, 2022
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Our study provided a detailed description and a package of an individual tree-based carbon model, FORCCHN2. This model used non-structural carbohydrate (NSC) pools to couple tree growth and phenology. The model could reproduce daily carbon fluxes across Northern Hemisphere forests. Given the potential importance of the application of this model, there is substantial scope for using FORCCHN2 in fields as diverse as forest ecology, climate change, and carbon estimation.
Johannes Oberpriller, Christine Herschlein, Peter Anthoni, Almut Arneth, Andreas Krause, Anja Rammig, Mats Lindeskog, Stefan Olin, and Florian Hartig
Geosci. Model Dev., 15, 6495–6519, https://doi.org/10.5194/gmd-15-6495-2022, https://doi.org/10.5194/gmd-15-6495-2022, 2022
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Understanding uncertainties of projected ecosystem dynamics under environmental change is of immense value for research and climate change policy. Here, we analyzed these across European forests. We find that uncertainties are dominantly induced by parameters related to water, mortality, and climate, with an increasing importance of climate from north to south. These results highlight that climate not only contributes uncertainty but also modifies uncertainties in other ecosystem processes.
Jens Heinke, Susanne Rolinski, and Christoph Müller
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-176, https://doi.org/10.5194/gmd-2022-176, 2022
Revised manuscript accepted for GMD
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We develop a livestock module for the global vegetation model LPJmL5.0 to simulate the impact of grazing dairy cattle on carbon and nitrogen cycles in grasslands. A novelty of the approach is that it accounts for the effect of feed quality on feed uptake and feed utilisation by animals. The portioning of dietary nitrogen into milk, feces, and urine shows very good agreement with estimates obtained from animal trials.
Marcus Falls, Raffaele Bernardello, Miguel Castrillo, Mario Acosta, Joan Llort, and Martí Galí
Geosci. Model Dev., 15, 5713–5737, https://doi.org/10.5194/gmd-15-5713-2022, https://doi.org/10.5194/gmd-15-5713-2022, 2022
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This paper describes and tests a method which uses a genetic algorithm (GA), a type of optimisation algorithm, on an ocean biogeochemical model. The aim is to produce a set of numerical parameters that best reflect the observed data of particulate organic carbon in a specific region of the ocean. We show that the GA can provide optimised model parameters in a robust and efficient manner and can also help detect model limitations, ultimately leading to a reduction in the model uncertainties.
Julien Ruffault, François Pimont, Hervé Cochard, Jean-Luc Dupuy, and Nicolas Martin-StPaul
Geosci. Model Dev., 15, 5593–5626, https://doi.org/10.5194/gmd-15-5593-2022, https://doi.org/10.5194/gmd-15-5593-2022, 2022
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A widespread increase in tree mortality has been observed around the globe, and this trend is likely to continue because of ongoing climate change. Here we present SurEau-Ecos, a trait-based plant hydraulic model to predict tree desiccation and mortality. SurEau-Ecos can help determine the areas and ecosystems that are most vulnerable to drying conditions.
Rebecca J. Oliver, Lina M. Mercado, Doug B. Clark, Chris Huntingford, Christopher M. Taylor, Pier Luigi Vidale, Patrick C. McGuire, Markus Todt, Sonja Folwell, Valiyaveetil Shamsudheen Semeena, and Belinda E. Medlyn
Geosci. Model Dev., 15, 5567–5592, https://doi.org/10.5194/gmd-15-5567-2022, https://doi.org/10.5194/gmd-15-5567-2022, 2022
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We introduce new representations of plant physiological processes into a land surface model. Including new biological understanding improves modelled carbon and water fluxes for the present in tropical and northern-latitude forests. Future climate simulations demonstrate the sensitivity of photosynthesis to temperature is important for modelling carbon cycle dynamics in a warming world. Accurate representation of these processes in models is necessary for robust predictions of climate change.
Mahdi André Nakhavali, Lina M. Mercado, Iain P. Hartley, Stephen Sitch, Fernanda V. Cunha, Raffaello di Ponzio, Laynara F. Lugli, Carlos A. Quesada, Kelly M. Andersen, Sarah E. Chadburn, Andy J. Wiltshire, Douglas B. Clark, Gyovanni Ribeiro, Lara Siebert, Anna C. M. Moraes, Jéssica Schmeisk Rosa, Rafael Assis, and José L. Camargo
Geosci. Model Dev., 15, 5241–5269, https://doi.org/10.5194/gmd-15-5241-2022, https://doi.org/10.5194/gmd-15-5241-2022, 2022
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In tropical ecosystems, the availability of rock-derived elements such as P can be very low. Thus, without a representation of P cycling, tropical forest responses to rising atmospheric CO2 conditions in areas such as Amazonia remain highly uncertain. We introduced P dynamics and its interactions with the N and P cycles into the JULES model. Our results highlight the potential for high P limitation and therefore lower CO2 fertilization capacity in the Amazon forest with low-fertility soils.
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.
Jiaying Zhang, Rafael L. Bras, Marcos Longo, and Tamara Heartsill Scalley
Geosci. Model Dev., 15, 5107–5126, https://doi.org/10.5194/gmd-15-5107-2022, https://doi.org/10.5194/gmd-15-5107-2022, 2022
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We implemented hurricane disturbance in a vegetation dynamics model and calibrated the model with observations of a tropical forest. We used the model to study forest recovery from hurricane disturbance and found that a single hurricane disturbance enhances AGB and BA in the long term compared with a no-hurricane situation. The model developed and results presented in this study can be utilized to understand the impact of hurricane disturbances on forest recovery under the changing climate.
Prabhat Raj Dahal, Maria Lumbierres, Stuart H. M. Butchart, Paul F. Donald, and Carlo Rondinini
Geosci. Model Dev., 15, 5093–5105, https://doi.org/10.5194/gmd-15-5093-2022, https://doi.org/10.5194/gmd-15-5093-2022, 2022
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This paper describes the validation of area of habitat (AOH) maps produced for terrestrial birds and mammals. The main objective was to assess the accuracy of the maps based on independent data. We used open access data from repositories, such as ebird and gbif to check if our maps were a better reflection of species' distribution than random. When points were not available we used logistic models to validate the AOH maps. The majority of AOH maps were found to have a high accuracy.
Yoshiki Kanzaki, Shuang Zhang, Noah J. Planavsky, and Christopher T. Reinhard
Geosci. Model Dev., 15, 4959–4990, https://doi.org/10.5194/gmd-15-4959-2022, https://doi.org/10.5194/gmd-15-4959-2022, 2022
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Increasing carbon dioxide in the atmosphere is an urgent issue in the coming century. Enhanced rock weathering in soils can be one of the most efficient C capture strategies. On the basis as a weathering simulator, the newly developed SCEPTER model implements bio-mixing by fauna/humans and enables organic matter and crushed rocks/minerals at the soil surface with an option to track their particle size distributions. Those features can be useful for evaluating the carbon capture efficiency.
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.
Joe R. Melton, Ed Chan, Koreen Millard, Matthew Fortier, R. Scott Winton, Javier M. Martín-López, Hinsby Cadillo-Quiroz, Darren Kidd, and Louis V. Verchot
Geosci. Model Dev., 15, 4709–4738, https://doi.org/10.5194/gmd-15-4709-2022, https://doi.org/10.5194/gmd-15-4709-2022, 2022
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Peat-ML is a high-resolution global peatland extent map generated using machine learning techniques. Peatlands are important in the global carbon and water cycles, but their extent is poorly known. We generated Peat-ML using drivers of peatland formation including climate, soil, geomorphology, and vegetation data, and we train the model with regional peatland maps. Our accuracy estimation approaches suggest Peat-ML is of similar or higher quality than other available peatland mapping products.
Qianyu Li, Shawn P. Serbin, Julien Lamour, Kenneth J. Davidson, Kim S. Ely, and Alistair Rogers
Geosci. Model Dev., 15, 4313–4329, https://doi.org/10.5194/gmd-15-4313-2022, https://doi.org/10.5194/gmd-15-4313-2022, 2022
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Stomatal conductance is the rate of water release from leaves’ pores. We implemented an optimal stomatal conductance model in a vegetation model. We then tested and compared it with the existing empirical model in terms of model responses to key environmental variables. We also evaluated the model with measurements at a tropical forest site. Our study suggests that the parameterization of conductance models and current model response to drought are the critical areas for improving models.
Veli Çağlar Yumruktepe, Annette Samuelsen, and Ute Daewel
Geosci. Model Dev., 15, 3901–3921, https://doi.org/10.5194/gmd-15-3901-2022, https://doi.org/10.5194/gmd-15-3901-2022, 2022
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We describe the coupled bio-physical model ECOSMO II(CHL), which is used for regional configurations for the North Atlantic and the Arctic hind-casting and operational purposes. The model is consistent with the large-scale climatological nutrient settings and is capable of representing regional and seasonal changes, and model primary production agrees with previous measurements. For the users of this model, this paper provides the underlying science, model evaluation and its development.
Nicolas Azaña Schnedler-Meyer, Tobias Kuhlmann Andersen, Fenjuan Rose Schmidt Hu, Karsten Bolding, Anders Nielsen, and Dennis Trolle
Geosci. Model Dev., 15, 3861–3878, https://doi.org/10.5194/gmd-15-3861-2022, https://doi.org/10.5194/gmd-15-3861-2022, 2022
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We present the Water Ecosystems Tool (WET) – a new modular aquatic ecosystem model configurable to a wide array of physical setups, ecosystems and research questions based on the popular FABM–PCLake model. We aim for the model to become a community staple, thus helping to consolidate the state of the art under a few flexible models, with the aim of improving comparability across studies and preventing the
re-inventions of the wheelthat are common to our scientific modeling community.
Hamze Dokoohaki, Bailey D. Morrison, Ann Raiho, Shawn P. Serbin, Katie Zarada, Luke Dramko, and Michael Dietze
Geosci. Model Dev., 15, 3233–3252, https://doi.org/10.5194/gmd-15-3233-2022, https://doi.org/10.5194/gmd-15-3233-2022, 2022
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We present a new terrestrial carbon cycle data assimilation system, built on the PEcAn model–data eco-informatics system, and its application for the development of a proof-of-concept carbon
reanalysisproduct that harmonizes carbon pools (leaf, wood, soil) and fluxes (GPP, Ra, Rh, NEE) across the contiguous United States from 1986–2019. Here, we build on a decade of work on uncertainty propagation to generate the most complete and robust uncertainty accounting available to date.
Hisashi Sato and Takeshi Ise
Geosci. Model Dev., 15, 3121–3132, https://doi.org/10.5194/gmd-15-3121-2022, https://doi.org/10.5194/gmd-15-3121-2022, 2022
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Accurately predicting global coverage of terrestrial biome is one of the earliest ecological concerns, and many empirical schemes have been proposed to characterize their relationship. Here, we demonstrate an accurate and practical method to construct empirical models for operational biome mapping via a convolutional neural network (CNN) approach.
Licheng Liu, Shaoming Xu, Jinyun Tang, Kaiyu Guan, Timothy J. Griffis, Matthew D. Erickson, Alexander L. Frie, Xiaowei Jia, Taegon Kim, Lee T. Miller, Bin Peng, Shaowei Wu, Yufeng Yang, Wang Zhou, Vipin Kumar, and Zhenong Jin
Geosci. Model Dev., 15, 2839–2858, https://doi.org/10.5194/gmd-15-2839-2022, https://doi.org/10.5194/gmd-15-2839-2022, 2022
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By incorporating the domain knowledge into a machine learning model, KGML-ag overcomes the well-known limitations of process-based models due to insufficient representations and constraints, and unlocks the “black box” of machine learning models. Therefore, KGML-ag can outperform existing approaches on capturing the hot moment and complex dynamics of N2O flux. This study will be a critical reference for the new generation of modeling paradigm for biogeochemistry and other geoscience processes.
Elodie Salmon, Fabrice Jégou, Bertrand Guenet, Line Jourdain, Chunjing Qiu, Vladislav Bastrikov, Christophe Guimbaud, Dan Zhu, Philippe Ciais, Philippe Peylin, Sébastien Gogo, Fatima Laggoun-Défarge, Mika Aurela, M. Syndonia Bret-Harte, Jiquan Chen, Bogdan H. Chojnicki, Housen Chu, Colin W. Edgar, Eugenie S. Euskirchen, Lawrence B. Flanagan, Krzysztof Fortuniak, David Holl, Janina Klatt, Olaf Kolle, Natalia Kowalska, Lars Kutzbach, Annalea Lohila, Lutz Merbold, Włodzimierz Pawlak, Torsten Sachs, and Klaudia Ziemblińska
Geosci. Model Dev., 15, 2813–2838, https://doi.org/10.5194/gmd-15-2813-2022, https://doi.org/10.5194/gmd-15-2813-2022, 2022
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A methane model that features methane production and transport by plants, the ebullition process and diffusion in soil, oxidation to CO2, and CH4 fluxes to the atmosphere has been embedded in the ORCHIDEE-PEAT land surface model, which includes an explicit representation of northern peatlands. This model, ORCHIDEE-PCH4, was calibrated and evaluated on 14 peatland sites. Results show that the model is sensitive to temperature and substrate availability over the top 75 cm of soil depth.
Suman Halder, Susanne K. M. Arens, Kai Jensen, Tais W. Dahl, and Philipp Porada
Geosci. Model Dev., 15, 2325–2343, https://doi.org/10.5194/gmd-15-2325-2022, https://doi.org/10.5194/gmd-15-2325-2022, 2022
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A dynamic vegetation model, designed to estimate potential impacts of early vascular vegetation, namely, lycopsids, on the biogeochemical cycle at a local scale. Lycopsid Model (LYCOm) estimates the productivity and physiological properties of lycopsids across a broad climatic range along with natural selection, which is then utilized to adjudge their weathering potential. It lays the foundation for estimation of their impacts during their long evolutionary history starting from the Ordovician.
Dóra Hidy, Zoltán Barcza, Roland Hollós, Laura Dobor, Tamás Ács, Dóra Zacháry, Tibor Filep, László Pásztor, Dóra Incze, Márton Dencső, Eszter Tóth, Katarína Merganičová, Peter Thornton, Steven Running, and Nándor Fodor
Geosci. Model Dev., 15, 2157–2181, https://doi.org/10.5194/gmd-15-2157-2022, https://doi.org/10.5194/gmd-15-2157-2022, 2022
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Biogeochemical models used by the scientific community can support society in the quantification of the expected environmental impacts caused by global climate change. The Biome-BGCMuSo v6.2 biogeochemical model has been created by implementing a lot of developments related to soil hydrology as well as the soil carbon and nitrogen cycle and by integrating crop model components. Detailed descriptions of developments with case studies are presented in this paper.
Lei Ma, George Hurtt, Lesley Ott, Ritvik Sahajpal, Justin Fisk, Rachel Lamb, Hao Tang, Steve Flanagan, Louise Chini, Abhishek Chatterjee, and Joseph Sullivan
Geosci. Model Dev., 15, 1971–1994, https://doi.org/10.5194/gmd-15-1971-2022, https://doi.org/10.5194/gmd-15-1971-2022, 2022
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We present a global version of the Ecosystem Demography (ED) model which can track vegetation 3-D structure and scale up ecological processes from individual vegetation to ecosystem scale. Model evaluation against multiple benchmarking datasets demonstrated the model’s capability to simulate global vegetation dynamics across a range of temporal and spatial scales. With this version, ED has the potential to be linked with remote sensing observations to address key scientific questions.
Ignacio Hermoso de Mendoza, Etienne Boucher, Fabio Gennaretti, Aliénor Lavergne, Robert Field, and Laia Andreu-Hayles
Geosci. Model Dev., 15, 1931–1952, https://doi.org/10.5194/gmd-15-1931-2022, https://doi.org/10.5194/gmd-15-1931-2022, 2022
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We modify the numerical model of forest growth MAIDENiso by explicitly simulating snow. This allows us to use the model in boreal environments, where snow is dominant. We tested the performance of the model before and after adding snow, using it at two Canadian sites to simulate tree-ring isotopes and comparing with local observations. We found that modelling snow improves significantly the simulation of the hydrological cycle, the plausibility of the model and the simulated isotopes.
Toni Viskari, Janne Pusa, Istem Fer, Anna Repo, Julius Vira, and Jari Liski
Geosci. Model Dev., 15, 1735–1752, https://doi.org/10.5194/gmd-15-1735-2022, https://doi.org/10.5194/gmd-15-1735-2022, 2022
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We wanted to examine how the chosen measurement data and calibration process affect soil organic carbon model calibration. In our results we found that there is a benefit in using data from multiple litter-bag decomposition experiments simultaneously, even with the required assumptions. Additionally, due to the amount of noise and uncertainties in the system, more advanced calibration methods should be used to parameterize the models.
Glenn E. Hammond
Geosci. Model Dev., 15, 1659–1676, https://doi.org/10.5194/gmd-15-1659-2022, https://doi.org/10.5194/gmd-15-1659-2022, 2022
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This paper describes a simplified interface for implementing and testing new chemical reactions within the reactive transport simulator PFLOTRAN. The paper describes the interface, providing example code for the interface. The paper includes several chemical reactions implemented through the interface.
Sarah E. Chadburn, Eleanor J. Burke, Angela V. Gallego-Sala, Noah D. Smith, M. Syndonia Bret-Harte, Dan J. Charman, Julia Drewer, Colin W. Edgar, Eugenie S. Euskirchen, Krzysztof Fortuniak, Yao Gao, Mahdi Nakhavali, Włodzimierz Pawlak, Edward A. G. Schuur, and Sebastian Westermann
Geosci. Model Dev., 15, 1633–1657, https://doi.org/10.5194/gmd-15-1633-2022, https://doi.org/10.5194/gmd-15-1633-2022, 2022
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We present a new method to include peatlands in an Earth system model (ESM). Peatlands store huge amounts of carbon that accumulates very slowly but that can be rapidly destabilised, emitting greenhouse gases. Our model captures the dynamic nature of peat by simulating the change in surface height and physical properties of the soil as carbon is added or decomposed. Thus, we model, for the first time in an ESM, peat dynamics and its threshold behaviours that can lead to destabilisation.
Philippe Ciais, Ana Bastos, Frédéric Chevallier, Ronny Lauerwald, Ben Poulter, Josep G. Canadell, Gustaf Hugelius, Robert B. Jackson, Atul Jain, Matthew Jones, Masayuki Kondo, Ingrid T. Luijkx, Prabir K. Patra, Wouter Peters, Julia Pongratz, Ana Maria Roxana Petrescu, Shilong Piao, Chunjing Qiu, Celso Von Randow, Pierre Regnier, Marielle Saunois, Robert Scholes, Anatoly Shvidenko, Hanqin Tian, Hui Yang, Xuhui Wang, and Bo Zheng
Geosci. Model Dev., 15, 1289–1316, https://doi.org/10.5194/gmd-15-1289-2022, https://doi.org/10.5194/gmd-15-1289-2022, 2022
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The second phase of the Regional Carbon Cycle Assessment and Processes (RECCAP) will provide updated quantification and process understanding of CO2, CH4, and N2O emissions and sinks for ten regions of the globe. In this paper, we give definitions, review different methods, and make recommendations for estimating different components of the total land–atmosphere carbon exchange for each region in a consistent and complete approach.
Nils Wallenberg, Fredrik Lindberg, and David Rayner
Geosci. Model Dev., 15, 1107–1128, https://doi.org/10.5194/gmd-15-1107-2022, https://doi.org/10.5194/gmd-15-1107-2022, 2022
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Exposure to solar radiation on clear and warm days can lead to heat stress and thermal discomfort. This can be alleviated by planting trees providing shade in particularly warm areas. Here, we use a model to locate trees and optimize their blocking of solar radiation. Our results show that locations can differ depending, e.g., tree size (juvenile or mature) and number of trees that are positioned simultaneously. The model is available as a tool for accessibility by researchers and others.
Kai Wang, Xiujun Wang, Raghu Murtugudde, Dongxiao Zhang, and Rong-Hua Zhang
Geosci. Model Dev., 15, 1017–1035, https://doi.org/10.5194/gmd-15-1017-2022, https://doi.org/10.5194/gmd-15-1017-2022, 2022
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We use observational data of dissolved oxygen (DO) and organic nitrogen to calibrate a basin-scale model (OGCM-DEMC V1.4) and then evaluate model capacity for simulating mid-depth DO in the tropical Pacific. Sensitivity studies show that enhanced vertical mixing combined with reduced biological consumption performs well in reproducing asymmetric oxygen minimum zones (OMZs). We find that DO is more sensitive to biological processes in the upper OMZs but to physical processes in the lower OMZs.
Pedro Duarte, Philipp Assmy, Karley Campbell, and Arild Sundfjord
Geosci. Model Dev., 15, 841–857, https://doi.org/10.5194/gmd-15-841-2022, https://doi.org/10.5194/gmd-15-841-2022, 2022
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Sea ice modeling is an important part of Earth system models (ESMs). The results of ESMs are used by the Intergovernmental Panel on Climate Change in their reports. In this study we present an improvement to calculate the exchange of nutrients between the ocean and the sea ice. This nutrient exchange is an essential process to keep the ice-associated ecosystem functioning. We found out that previous calculation methods may underestimate the primary production of the ice-associated ecosystem.
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Short summary
Marine phytoplankton accounts for half of global primary production. Phytoplankton size is an important trait affecting its fitness and ecosystem functioning. We have developed a plankton model with continuous size distribution for phytoplankton and applied it in the North Pacific. This model is able to capture the general patterns of phytoplankton size distribution in the real ocean and can be used for understanding the mechanisms controlling phytoplankton size structure and diversity.
Marine phytoplankton accounts for half of global primary production. Phytoplankton size is an...
