Articles | Volume 18, issue 11
https://doi.org/10.5194/gmd-18-3241-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-18-3241-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
02 Jun 2025
Model description paper |
| 02 Jun 2025
| 02 Jun 2025
Alquimia v1.0: a generic interface to biogeochemical codes – a tool for interoperable development, prototyping and benchmarking for multiphysics simulators
Energy Geosciences Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Rd, Berkeley, CA 94720, USA
Benjamin J. Andre
Energy Geosciences Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Rd, Berkeley, CA 94720, USA
Jeffrey N. Johnson
Energy Geosciences Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Rd, Berkeley, CA 94720, USA
Cohere Consulting, LLC, Seattle, WA 98105, USA
Glenn E. Hammond
Energy and Environment Directorate, Pacific Northwest National Laboratory, Richland, WA 99354, USA
Benjamin N. Sulman
Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37830, USA
Konstantin Lipnikov
Applied Mathematics and Plasma Physics, Los Alamos National Laboratory, Los Alamos, NM 87545, USA
Marcus S. Day
Computational Science Center, National Renewable Energy Laboratory, Golden, CO 80401, USA
James J. Beisman
Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37830, USA
Daniil Svyatsky
Applied Mathematics and Plasma Physics, Los Alamos National Laboratory, Los Alamos, NM 87545, USA
Hang Deng
Department of Energy and Resources Engineering, Peking University, Peking, 100871, China
Peter C. Lichtner
Department of Civil Engineering, University of New Mexico, Albuquerque, NM 87131, USA
Carl I. Steefel
Energy Geosciences Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Rd, Berkeley, CA 94720, USA
J. David Moulton
Applied Mathematics and Plasma Physics, Los Alamos National Laboratory, Los Alamos, NM 87545, USA
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We use an innovative approach to studying the Earth's water cycle by integrating advanced machine learning techniques with a traditional water cycle model. Our model is designed to learn from observational data, with a particular emphasis on understanding the influence of vegetation on water movement. By closely aligning with real-world observations, our model offers new possibilities for enhancing our understanding of the water cycle and its interactions with vegetation.
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We improved the representation of soil water movement in a state-of-the-art dynamic vegetation model. This is especially important for dry ecosystems, as they are often driven by changes in soil water availability. We showed that this update resulted in a generally better match with observations, and that the updated model is more sensitive to soil texture. This updated model will help scientists to better understand the future of dry ecosystems under climate change.
Mateus Dantas de Paula, Matthew Forrest, David Warlind, João Paulo Darela Filho, Katrin Fleischer, Anja Rammig, and Thomas Hickler
Geosci. Model Dev., 18, 2249–2274, https://doi.org/10.5194/gmd-18-2249-2025, https://doi.org/10.5194/gmd-18-2249-2025, 2025
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Our study maps global nitrogen (N) and phosphorus (P) availability and how they changed from 1901 to 2018. We find that tropical regions are mostly P-limited, while temperate and boreal areas face N limitations. Over time, P limitation increased, especially in the tropics, while N limitation decreased. These shifts are key to understanding global plant growth and carbon storage, highlighting the importance of including P dynamics in ecosystem models.
Wolfgang Knorr, Matthew Williams, Tea Thum, Thomas Kaminski, Michael Voßbeck, Marko Scholze, Tristan Quaife, T. Luke Smallman, Susan C. Steele-Dunne, Mariette Vreugdenhil, Tim Green, Sönke Zaehle, Mika Aurela, Alexandre Bouvet, Emanuel Bueechi, Wouter Dorigo, Tarek S. El-Madany, Mirco Migliavacca, Marika Honkanen, Yann H. Kerr, Anna Kontu, Juha Lemmetyinen, Hannakaisa Lindqvist, Arnaud Mialon, Tuuli Miinalainen, Gaétan Pique, Amanda Ojasalo, Shaun Quegan, Peter J. Rayner, Pablo Reyes-Muñoz, Nemesio Rodríguez-Fernández, Mike Schwank, Jochem Verrelst, Songyan Zhu, Dirk Schüttemeyer, and Matthias Drusch
Geosci. Model Dev., 18, 2137–2159, https://doi.org/10.5194/gmd-18-2137-2025, https://doi.org/10.5194/gmd-18-2137-2025, 2025
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When it comes to climate change, the land surface is where the vast majority of impacts happen. The task of monitoring those impacts across the globe is formidable and must necessarily rely on satellites – at a significant cost: the measurements are only indirect and require comprehensive physical understanding. We have created a comprehensive modelling system that we offer to the research community to explore how satellite data can be better exploited to help us capture the changes that happen on our lands.
Luke Oberhagemann, Maik Billing, Werner von Bloh, Markus Drüke, Matthew Forrest, Simon P. K. Bowring, Jessica Hetzer, Jaime Ribalaygua Batalla, and Kirsten Thonicke
Geosci. Model Dev., 18, 2021–2050, https://doi.org/10.5194/gmd-18-2021-2025, https://doi.org/10.5194/gmd-18-2021-2025, 2025
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Under climate change, the conditions necessary for wildfires to form are occurring more frequently in many parts of the world. To help predict how wildfires will change in future, global fire models are being developed. We analyze and further develop one such model, SPITFIRE. Our work identifies and corrects sources of substantial bias in the model that are important to the global fire modelling field. With this analysis and these developments, we help to provide a basis for future improvements.
Lei Zhu, Philippe Ciais, Yitong Yao, Daniel Goll, Sebastiaan Luyssaert, Isabel Martínez Cano, Arthur Fendrich, Laurent Li, Hui Yang, Sassan Saatchi, and Wei Li
EGUsphere, https://doi.org/10.5194/egusphere-2025-397, https://doi.org/10.5194/egusphere-2025-397, 2025
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This study enhances the accuracy of modeling the carbon dynamics of Amazon rainforest by optimizing key model parameters based on satellite data. Using spatially varying parameters for tree mortality and photosynthesis, we improved predictions of biomass, productivity, and tree mortality. Our findings highlight the critical role of wood density and water availability in forest processes, offering insights to refine global carbon cycle models.
Trine Frisbæk Hansen, Donald Eugene Canfield, Ken Haste Andersen, and Christian Jannik Bjerrum
Geosci. Model Dev., 18, 1895–1916, https://doi.org/10.5194/gmd-18-1895-2025, https://doi.org/10.5194/gmd-18-1895-2025, 2025
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We describe and test the size-based Nutrient-Unicellular-Multicellular model, which defines unicellular plankton using a single set of parameters, on a eutrophic and oligotrophic ecosystem. The results demonstrate that both sites can be modeled with similar parameters and robust performance over a wide range of parameters. The study shows that the model is useful for non-experts and applicable for modeling ecosystems with limited data. It holds promise for evolutionary and deep-time climate models.
Ying Ye, Guy Munhoven, Peter Köhler, Martin Butzin, Judith Hauck, Özgür Gürses, and Christoph Völker
Geosci. Model Dev., 18, 977–1000, https://doi.org/10.5194/gmd-18-977-2025, https://doi.org/10.5194/gmd-18-977-2025, 2025
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Many biogeochemistry models assume all material reaching the seafloor is remineralized and returned to solution, which is sufficient for studies on short-term climate change. Under long-term climate change, the carbon storage in sediments slows down carbon cycling and influences feedbacks in the atmosphere–ocean–sediment system. This paper describes the coupling of a sediment model to an ocean biogeochemistry model and presents results under the pre-industrial climate and under CO2 perturbation.
Juliette Bernard, Elodie Salmon, Marielle Saunois, Shushi Peng, Penélope Serrano-Ortiz, Antoine Berchet, Palingamoorthy Gnanamoorthy, Joachim Jansen, and Philippe Ciais
Geosci. Model Dev., 18, 863–883, https://doi.org/10.5194/gmd-18-863-2025, https://doi.org/10.5194/gmd-18-863-2025, 2025
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Despite their importance, uncertainties remain in the evaluation of the drivers of temporal variability of methane emissions from wetlands on a global scale. Here, a simplified global model is developed, taking advantage of advances in remote-sensing data and in situ observations. The model reproduces the large spatial and temporal patterns of emissions, albeit with limitations in the tropics due to data scarcity. This model, while simple, can provide valuable insights into sensitivity analyses.
Yi Xi, Philippe Ciais, Dan Zhu, Chunjing Qiu, Yuan Zhang, Shushi Peng, Gustaf Hugelius, Simon P. K. Bowring, Daniel S. Goll, and Ying-Ping Wang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-206, https://doi.org/10.5194/gmd-2024-206, 2025
Revised manuscript accepted for GMD
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Including high-latitude deep carbon is critical for projecting future soil carbon emissions, yet it’s absent in most land surface models. Here we propose a new carbon accumulation protocol by integrating deep carbon from Yedoma deposits and representing the observed history of peat carbon formation in ORCHIDEE-MICT. Our results show an additional 157 PgC in present-day Yedoma deposits and a 1–5 m shallower peat depth, 43 % less passive soil carbon in peatlands against the convention protocol.
Christian Poppe Terán, Bibi S. Naz, Harry Vereecken, Roland Baatz, Rosie A. Fisher, and Harrie-Jan Hendricks Franssen
Geosci. Model Dev., 18, 287–317, https://doi.org/10.5194/gmd-18-287-2025, https://doi.org/10.5194/gmd-18-287-2025, 2025
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Carbon and water exchanges between the atmosphere and the land surface contribute to water resource availability and climate change mitigation. Land surface models, like the Community Land Model version 5 (CLM5), simulate these. This study finds that CLM5 and other data sets underestimate the magnitudes of and variability in carbon and water exchanges for the most abundant plant functional types compared to observations. It provides essential insights for further research into these processes.
Theo Glauch, Julia Marshall, Christoph Gerbig, Santiago Botía, Michał Gałkowski, Sanam N. Vardag, and André Butz
EGUsphere, https://doi.org/10.5194/egusphere-2024-3692, https://doi.org/10.5194/egusphere-2024-3692, 2025
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The Vegetation Photosynthesis and Respiration Model (VPRM) estimates carbon exchange between the atmosphere and biosphere by modeling gross primary production and respiration using satellite data and weather variables. Our new version, pyVPRM, supports diverse satellite products like Sentinel-2, MODIS, VIIRS and new land cover maps, enabling high spatial and temporal resolution. This improves flux estimates, especially in complex landscapes, and ensures continuity as MODIS nears decommissioning.
Katherine A. Muller, Peishi Jiang, Glenn Hammond, Tasneem Ahmadullah, Hyun-Seob Song, Ravi Kukkadapu, Nicholas Ward, Madison Bowe, Rosalie K. Chu, Qian Zhao, Vanessa A. Garayburu-Caruso, Alan Roebuck, and Xingyuan Chen
Geosci. Model Dev., 17, 8955–8968, https://doi.org/10.5194/gmd-17-8955-2024, https://doi.org/10.5194/gmd-17-8955-2024, 2024
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The new Lambda-PFLOTRAN workflow incorporates organic matter chemistry into reaction networks to simulate aerobic respiration and biogeochemistry. Lambda-PFLOTRAN is a Python-based workflow in a Jupyter notebook interface that digests raw organic matter chemistry data via Fourier transform ion cyclotron resonance mass spectrometry, develops a representative reaction network, and completes a biogeochemical simulation with the open-source, parallel-reactive-flow, and transport code PFLOTRAN.
Felix Nößler, Thibault Moulin, Oksana Buzhdygan, Britta Tietjen, and Felix May
EGUsphere, https://doi.org/10.5194/egusphere-2024-3798, https://doi.org/10.5194/egusphere-2024-3798, 2024
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To predict the response of grassland plant communities to management and climate change, we developed the computer model GrasslandTraitSim.jl. Unlike other models, it uses measurable plant traits such as height, leaf thinness, and root structure as inputs, rather than hard-to-measure species data. This allows realistic simulation of many species. The model tracks daily changes in above- and below-ground biomass, plant height, and soil water, linking plant community composition to biomass supply.
Ling Li, Peipei Wu, Peng Zhang, Shaojian Huang, and Yanxu Zhang
Geosci. Model Dev., 17, 8683–8695, https://doi.org/10.5194/gmd-17-8683-2024, https://doi.org/10.5194/gmd-17-8683-2024, 2024
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In this study, we incorporate sea surfactants and wave-breaking processes into MITgcm-ECCOv4-Hg. The updated model shows increased fluxes in high-wind-speed and high-wave regions and vice versa, enhancing spatial heterogeneity. It shows that elemental mercury (Hg0) transfer velocity is more sensitive to wind speed. These findings may elucidate the discrepancies in previous estimations and offer insights into global Hg cycling.
Jerome Guiet, Daniele Bianchi, Kim J. N. Scherrer, Ryan F. Heneghan, and Eric D. Galbraith
Geosci. Model Dev., 17, 8421–8454, https://doi.org/10.5194/gmd-17-8421-2024, https://doi.org/10.5194/gmd-17-8421-2024, 2024
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The BiOeconomic mArine Trophic Size-spectrum (BOATSv2) model dynamically simulates global commercial fish populations and their coupling with fishing activity, as emerging from environmental and economic drivers. New features, including separate pelagic and demersal populations, iron limitation, and spatial variation of fishing costs and management, improve the accuracy of high seas fisheries. The updated model code is available to simulate both historical and future scenarios.
Jize Jiang, David S. Stevenson, and Mark A. Sutton
Geosci. Model Dev., 17, 8181–8222, https://doi.org/10.5194/gmd-17-8181-2024, https://doi.org/10.5194/gmd-17-8181-2024, 2024
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A special model called AMmonia–CLIMate (AMCLIM) has been developed to understand and calculate NH3 emissions from fertilizer use and also taking into account how the environment influences these NH3 emissions. It is estimated that about 17 % of applied N in fertilizers was lost due to NH3 emissions. Hot and dry conditions and regions with high-pH soils can expect higher NH3 emissions.
Carlos Enmanuel Soto López, Fabio Anselmi, Mirna Gharbi Dit Kacem, and Paolo Lazzari
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-174, https://doi.org/10.5194/gmd-2024-174, 2024
Revised manuscript accepted for GMD
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Our goal was to use an analytical expression to estimate the density of optical constituents, allowing us to have an interpretable formulation consistent with the laws of physics. We focused on a probabilistic approach, optimizing the model and retrieving quantities with their respective uncertainty. Considering future application to Big Data, we also explored a Neural Network based method, retrieving computationally efficient estimates, maintaining consistency with the analytical expression.
Benjamin Franklin Meyer, João Paulo Darela-Filho, Konstantin Gregor, Allan Buras, Qiao-Lin Gu, Andreas Krause, Daijun Liu, Phillip Papastefanou, Sijeh Asuk, Thorsten E. E. Grams, Christian S. Zang, and Anja Rammig
EGUsphere, https://doi.org/10.5194/egusphere-2024-3352, https://doi.org/10.5194/egusphere-2024-3352, 2024
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Climate change has increased the likelihood of drought events across Europe, potentially threatening European forest carbon sink. Dynamic vegetation models with mechanistic plant hydraulic architecture are needed to model these developments. We evaluate the plant hydraulic architecture version of LPJ-GUESS and show it's capability at capturing species-specific evapotranspiration responses to drought and reproducing flux observations of both gross primary production and evapotranspiration.
Guillaume Marie, Jina Jeong, Hervé Jactel, Gunnar Petter, Maxime Cailleret, Matthew J. McGrath, Vladislav Bastrikov, Josefine Ghattas, Bertrand Guenet, Anne Sofie Lansø, Kim Naudts, Aude Valade, Chao Yue, and Sebastiaan Luyssaert
Geosci. Model Dev., 17, 8023–8047, https://doi.org/10.5194/gmd-17-8023-2024, https://doi.org/10.5194/gmd-17-8023-2024, 2024
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This research looks at how climate change influences forests, and particularly how altered wind and insect activities could make forests emit instead of absorb carbon. We have updated a land surface model called ORCHIDEE to better examine the effect of bark beetles on forest health. Our findings suggest that sudden events, such as insect outbreaks, can dramatically affect carbon storage, offering crucial insights into tackling climate change.
Stephen Björn Wirth, Johanna Braun, Jens Heinke, Sebastian Ostberg, Susanne Rolinski, Sibyll Schaphoff, Fabian Stenzel, Werner von Bloh, Friedhelm Taube, and Christoph Müller
Geosci. Model Dev., 17, 7889–7914, https://doi.org/10.5194/gmd-17-7889-2024, https://doi.org/10.5194/gmd-17-7889-2024, 2024
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We present a new approach to modelling biological nitrogen fixation (BNF) in the Lund–Potsdam–Jena managed Land dynamic global vegetation model. While in the original approach BNF depended on actual evapotranspiration, the new approach considers soil water content and temperature, vertical root distribution, the nitrogen (N) deficit and carbon (C) costs. The new approach improved simulated BNF compared to the scientific literature and the model ability to project future C and N cycle dynamics.
Nicolette Chang, Sarah-Anne Nicholson, Marcel du Plessis, Alice D. Lebehot, Thulwaneng Mashifane, Tumelo C. Moalusi, N. Precious Mongwe, and Pedro M. S. Monteiro
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-182, https://doi.org/10.5194/gmd-2024-182, 2024
Revised manuscript accepted for GMD
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Mesoscale features (10's to 100's of km) in the Southern Ocean (SO) are crucial for global heat and carbon transport, but often unresolved in models due to high computational costs. To address this source of uncertainty, we use a regional, NEMO model of the SO at 8 km resolution with coupled ocean, ice, and biogeochemistry, BIOPERIANT12. This serves as an experimental platform to explore physical-biogeochemical interactions, model parameters/formulations, and configuring future models.
Saeed Harati-Asl, Liliana Perez, and Roberto Molowny-Horas
Geosci. Model Dev., 17, 7423–7443, https://doi.org/10.5194/gmd-17-7423-2024, https://doi.org/10.5194/gmd-17-7423-2024, 2024
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Social–ecological systems are the subject of many sustainability problems. Because of the complexity of these systems, we must be careful when intervening in them; otherwise we may cause irreversible damage. Using computer models, we can gain insight about these complex systems without harming them. In this paper we describe how we connected an ecological model of forest insect infestation with a social model of cooperation and simulated an intervention measure to save a forest from infestation.
Isabelle Maréchaux, Fabian Jörg Fischer, Sylvain Schmitt, and Jérôme Chave
EGUsphere, https://doi.org/10.5194/egusphere-2024-3104, https://doi.org/10.5194/egusphere-2024-3104, 2024
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We describe TROLL 4.0, a simulator of forest dynamics that represents trees in a virtual space at one-meter resolution. Tree birth, growth, death and the underlying physiological processes such as carbon assimilation, water transpiration and leaf phenology depend on plant traits that are measured in the field for many individuals and species. The model is thus capable of jointly simulating forest structure, diversity and ecosystem functioning, a major challenge in modelling vegetation dynamics.
Katarína Merganičová, Ján Merganič, Laura Dobor, Roland Hollós, Zoltán Barcza, Dóra Hidy, Zuzana Sitková, Pavel Pavlenda, Hrvoje Marjanovic, Daniel Kurjak, Michal Bošel'a, Doroteja Bitunjac, Maša Zorana Ostrogović Sever, Jiří Novák, Peter Fleischer, and Tomáš Hlásny
Geosci. Model Dev., 17, 7317–7346, https://doi.org/10.5194/gmd-17-7317-2024, https://doi.org/10.5194/gmd-17-7317-2024, 2024
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We developed a multi-objective calibration approach leading to robust parameter values aiming to strike a balance between their local precision and broad applicability. Using the Biome-BGCMuSo model, we tested the calibrated parameter sets for simulating European beech forest dynamics across large environmental gradients. Leveraging data from 87 plots and five European countries, the results demonstrated reasonable local accuracy and plausible large-scale productivity responses.
Sylvain Schmitt, Fabian Fischer, James Ball, Nicolas Barbier, Marion Boisseaux, Damien Bonal, Benoit Burban, Xiuzhi Chen, Géraldine Derroire, Jeremy Lichstein, Daniela Nemetschek, Natalia Restrepo-Coupe, Scott Saleska, Giacomo Sellan, Philippe Verley, Grégoire Vincent, Camille Ziegler, Jérôme Chave, and Isabelle Maréchaux
EGUsphere, https://doi.org/10.5194/egusphere-2024-3106, https://doi.org/10.5194/egusphere-2024-3106, 2024
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We evaluate the capability of TROLL 4.0, a simulator of forest dynamics, to represent tropical forest structure, diversity and functioning in two Amazonian forests. Evaluation data include forest inventories, carbon and water fluxes between the forest and the atmosphere, and leaf area and canopy height from remote-sensing products. The model realistically predicts the structure and composition, and the seasonality of carbon and water fluxes at both sites.
Joshua Coupe, Nicole S. Lovenduski, Luise S. Gleason, Michael N. Levy, Kristen Krumhardt, Keith Lindsay, Charles Bardeen, Clay Tabor, Cheryl Harrison, Kenneth G. MacLeod, Siddhartha Mitra, and Julio Sepúlveda
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-94, https://doi.org/10.5194/gmd-2024-94, 2024
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We develop a new feature in the atmosphere and ocean components of the Community Earth System Model version 2. We have implemented ultraviolet (UV) radiation inhibition of photosynthesis of four marine phytoplankton functional groups represented in the Marine Biogeochemistry Library. The new feature is tested with varying levels of UV radiation. The new feature will enable an analysis of an asteroid impact’s effect on the ozone layer and how that affects the base of the marine food web.
Guohua Liu, Mirco Migliavacca, Christian Reimers, Basil Kraft, Markus Reichstein, Andrew D. Richardson, Lisa Wingate, Nicolas Delpierre, Hui Yang, and Alexander J. Winkler
Geosci. Model Dev., 17, 6683–6701, https://doi.org/10.5194/gmd-17-6683-2024, https://doi.org/10.5194/gmd-17-6683-2024, 2024
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Our study employs long short-term memory (LSTM) networks to model canopy greenness and phenology, integrating meteorological memory effects. The LSTM model outperforms traditional methods, enhancing accuracy in predicting greenness dynamics and phenological transitions across plant functional types. Highlighting the importance of multi-variate meteorological memory effects, our research pioneers unlock the secrets of vegetation phenology responses to climate change with deep learning techniques.
Thi Lan Anh Dinh, Daniel Goll, Philippe Ciais, and Ronny Lauerwald
Geosci. Model Dev., 17, 6725–6744, https://doi.org/10.5194/gmd-17-6725-2024, https://doi.org/10.5194/gmd-17-6725-2024, 2024
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The study assesses the performance of the dynamic global vegetation model (DGVM) ORCHIDEE in capturing the impact of land-use change on carbon stocks across Europe. Comparisons with observations reveal that the model accurately represents carbon fluxes and stocks. Despite the underestimations in certain land-use conversions, the model describes general trends in soil carbon response to land-use change, aligning with the site observations.
Nathaelle Bouttes, Lester Kwiatkowski, Manon Berger, Victor Brovkin, and Guy Munhoven
Geosci. Model Dev., 17, 6513–6528, https://doi.org/10.5194/gmd-17-6513-2024, https://doi.org/10.5194/gmd-17-6513-2024, 2024
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Coral reefs are crucial for biodiversity, but they also play a role in the carbon cycle on long time scales of a few thousand years. To better simulate the future and past evolution of coral reefs and their effect on the global carbon cycle, hence on atmospheric CO2 concentration, it is necessary to include coral reefs within a climate model. Here we describe the inclusion of coral reef carbonate production in a carbon–climate model and its validation in comparison to existing modern data.
Huajie Zhu, Mousong Wu, Fei Jiang, Michael Vossbeck, Thomas Kaminski, Xiuli Xing, Jun Wang, Weimin Ju, and Jing M. Chen
Geosci. Model Dev., 17, 6337–6363, https://doi.org/10.5194/gmd-17-6337-2024, https://doi.org/10.5194/gmd-17-6337-2024, 2024
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In this work, we developed the Nanjing University Carbon Assimilation System (NUCAS v1.0). Data assimilation experiments were conducted to demonstrate the robustness and investigate the feasibility and applicability of NUCAS. The assimilation of ecosystem carbonyl sulfide (COS) fluxes improved the model performance in gross primary productivity, evapotranspiration, and sensible heat, showing that COS provides constraints on parameters relevant to carbon-, water-, and energy-related processes.
Fang Li, Zhimin Zhou, Samuel Levis, Stephen Sitch, Felicity Hayes, Zhaozhong Feng, Peter B. Reich, Zhiyi Zhao, and Yanqing Zhou
Geosci. Model Dev., 17, 6173–6193, https://doi.org/10.5194/gmd-17-6173-2024, https://doi.org/10.5194/gmd-17-6173-2024, 2024
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A new scheme is developed to model the surface ozone damage to vegetation in regional and global process-based models. Based on 4210 data points from ozone experiments, it accurately reproduces statistically significant linear or nonlinear photosynthetic and stomatal responses to ozone in observations for all vegetation types. It also enables models to implicitly capture the variability in plant ozone tolerance and the shift among species within a vegetation type.
Alexander S. Brunmayr, Frank Hagedorn, Margaux Moreno Duborgel, Luisa I. Minich, and Heather D. Graven
Geosci. Model Dev., 17, 5961–5985, https://doi.org/10.5194/gmd-17-5961-2024, https://doi.org/10.5194/gmd-17-5961-2024, 2024
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A new generation of soil models promises to more accurately predict the carbon cycle in soils under climate change. However, measurements of 14C (the radioactive carbon isotope) in soils reveal that the new soil models face similar problems to the traditional models: they underestimate the residence time of carbon in soils and may therefore overestimate the net uptake of CO2 by the land ecosystem. Proposed solutions include restructuring the models and calibrating model parameters with 14C data.
Nina Raoult, Simon Beylat, James M. Salter, Frédéric Hourdin, Vladislav Bastrikov, Catherine Ottlé, and Philippe Peylin
Geosci. Model Dev., 17, 5779–5801, https://doi.org/10.5194/gmd-17-5779-2024, https://doi.org/10.5194/gmd-17-5779-2024, 2024
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We use computer models to predict how the land surface will respond to climate change. However, these complex models do not always simulate what we observe in real life, limiting their effectiveness. To improve their accuracy, we use sophisticated statistical and computational techniques. We test a technique called history matching against more common approaches. This method adapts well to these models, helping us better understand how they work and therefore how to make them more realistic.
Jorn Bruggeman, Karsten Bolding, Lars Nerger, Anna Teruzzi, Simone Spada, Jozef Skákala, and Stefano Ciavatta
Geosci. Model Dev., 17, 5619–5639, https://doi.org/10.5194/gmd-17-5619-2024, https://doi.org/10.5194/gmd-17-5619-2024, 2024
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To understand and predict the ocean’s capacity for carbon sequestration, its ability to supply food, and its response to climate change, we need the best possible estimate of its physical and biogeochemical properties. This is obtained through data assimilation which blends numerical models and observations. We present the Ensemble and Assimilation Tool (EAT), a flexible and efficient test bed that allows any scientist to explore and further develop the state of the art in data assimilation.
Dongyu Zheng, Andrew S. Merdith, Yves Goddéris, Yannick Donnadieu, Khushboo Gurung, and Benjamin J. W. Mills
Geosci. Model Dev., 17, 5413–5429, https://doi.org/10.5194/gmd-17-5413-2024, https://doi.org/10.5194/gmd-17-5413-2024, 2024
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This study uses a deep learning method to upscale the time resolution of paleoclimate simulations to 1 million years. This improved resolution allows a climate-biogeochemical model to more accurately predict climate shifts. The method may be critical in developing new fully continuous methods that are able to be applied over a moving continental surface in deep time with high resolution at reasonable computational expense.
Boris Ťupek, Aleksi Lehtonen, Alla Yurova, Rose Abramoff, Bertrand Guenet, Elisa Bruni, Samuli Launiainen, Mikko Peltoniemi, Shoji Hashimoto, Xianglin Tian, Juha Heikkinen, Kari Minkkinen, and Raisa Mäkipää
Geosci. Model Dev., 17, 5349–5367, https://doi.org/10.5194/gmd-17-5349-2024, https://doi.org/10.5194/gmd-17-5349-2024, 2024
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Updating the Yasso07 soil C model's dependency on decomposition with a hump-shaped Ricker moisture function improved modelled soil organic C (SOC) stocks in a catena of mineral and organic soils in boreal forest. The Ricker function, set to peak at a rate of 1 and calibrated against SOC and CO2 data using a Bayesian approach, showed a maximum in well-drained soils. Using SOC and CO2 data together with the moisture only from the topsoil humus was crucial for accurate model estimates.
Jacquelyn K. Shuman, Rosie A. Fisher, Charles Koven, Ryan Knox, Lara Kueppers, and Chonggang Xu
Geosci. Model Dev., 17, 4643–4671, https://doi.org/10.5194/gmd-17-4643-2024, https://doi.org/10.5194/gmd-17-4643-2024, 2024
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We adapt a fire behavior and effects module for use in a size-structured vegetation demographic model to test how climate, fire regime, and fire-tolerance plant traits interact to determine the distribution of tropical forests and grasslands. Our model captures the connection between fire disturbance and plant fire-tolerance strategies in determining plant distribution and provides a useful tool for understanding the vulnerability of these areas under changing conditions across the tropics.
Yoshiki Kanzaki, Isabella Chiaravalloti, Shuang Zhang, Noah J. Planavsky, and Christopher T. Reinhard
Geosci. Model Dev., 17, 4515–4532, https://doi.org/10.5194/gmd-17-4515-2024, https://doi.org/10.5194/gmd-17-4515-2024, 2024
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Soil pH is one of the most commonly measured agronomical and biogeochemical indices, mostly reflecting exchangeable acidity. Explicit simulation of both porewater and bulk soil pH is thus crucial to the accurate evaluation of alkalinity required to counteract soil acidification and the resulting capture of anthropogenic carbon dioxide through the enhanced weathering technique. This has been enabled by the updated reactive–transport SCEPTER code and newly developed framework to simulate soil pH.
David Sandoval, Iain Colin Prentice, and Rodolfo L. B. Nóbrega
Geosci. Model Dev., 17, 4229–4309, https://doi.org/10.5194/gmd-17-4229-2024, https://doi.org/10.5194/gmd-17-4229-2024, 2024
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Numerous estimates of water and energy balances depend on empirical equations requiring site-specific calibration, posing risks of "the right answers for the wrong reasons". We introduce novel first-principles formulations to calculate key quantities without requiring local calibration, matching predictions from complex land surface models.
Oliver Perkins, Matthew Kasoar, Apostolos Voulgarakis, Cathy Smith, Jay Mistry, and James D. A. Millington
Geosci. Model Dev., 17, 3993–4016, https://doi.org/10.5194/gmd-17-3993-2024, https://doi.org/10.5194/gmd-17-3993-2024, 2024
Short summary
Short summary
Wildfire is often presented in the media as a danger to human life. Yet globally, millions of people’s livelihoods depend on using fire as a tool. So, patterns of fire emerge from interactions between humans, land use, and climate. This complexity means scientists cannot yet reliably say how fire will be impacted by climate change. So, we developed a new model that represents globally how people use and manage fire. The model reveals the extent and diversity of how humans live with and use fire.
Cited articles
Andre, B., Molins, S., Johnson, J., and Steefel, C.: Alquimia, U.S. Department of Energy Office of Scientific and Technical Information, https://doi.org/10.11578/DC.20210416.49, 2013. a, b
Andre, B., Molins, S., Johnson, J., and Steefel, C. I.: Alquimia, GitHub, https://github.com/LBL-EESA/alquimia-dev (last access: 25 May 2025), 2015. a
Balos, C. J., Day, M., Esclapez, L., Felden, A. M., Gardner, D. J., Hassanaly, M., Reynolds, D. R., Rood, J. S., Sexton, J. M., Wimer, N. T., and Woodward, C. S.: SUNDIALS time integrators for exascale applications with many independent systems of ordinary differential equations, Int. J. High Perform. C., 39, 123–146, https://doi.org/10.1177/10943420241280060, 2025. a
Bao, C., Li, L., Shi, Y., and Duffy, C.: Understanding watershed hydrogeochemistry: 1. Development of RT?Flux?PIHM, Water Resour. Res., 53, 2328–2345, https://doi.org/10.1002/2016WR018934, 2017. a
Bartlett, R., Demeshko, I., Gamblin, T., Hammond, G., Heroux, M. A., Johnson, J., Klinvex, A., Li, X., McInnes, L. C., Moulton, J. D., Osei-Kuffuor, D., Sarich, J., Smith, B., Willenbring, J., and Yang, U. M.: xSDK Foundations: Toward an Extreme-scale Scientific Software Development Kit, Supercomputing Frontiers and Innovations, 4, 69–82, https://doi.org/10.14529/jsfi170104, 2017. a, b
Beisman, J., Maxwell, R., Navarre-Sitchler, A., Steefel, C., and Molins, S.: ParCrunchFlow: an efficient, parallel reactive transport simulation tool for physically and chemically heterogeneous saturated subsurface environments, Comput. Geosci., 19, 403–422, https://doi.org/10.1007/s10596-015-9475-x, 2015. a, b, c
Bethke, C. M.: The Geochemist's Workbench® Release 17 ChemPlugin™ User's Guide, Aqueous Solutions, LLC, Champaign, Illinois, https://www.gwb.com/pdf/GWB/ChemPluginUsersGuide.pdf (last access: 24 May 2025), 2024. a
CFFI: CFFI documentation – CFFI 1.15.1 documentation, https://cffi.readthedocs.io/en/latest/ (last access: 24 May 2025), 2023. a
Chang, E., Zavarin, M., Beverly, L., and Wainwright, H.: A chemistry-informed hybrid machine learning approach to predict metal adsorption onto mineral surfaces, Appl. Geochem., 155, 105731, https://doi.org/10.1016/j.apgeochem.2023.105731, 2023. a
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, https://doi.org/10.1016/j.cageo.2011.02.005, 2011. a
Coon, E., Svyatsky, D., Jan, A., Kikinzon, E., Berndt, M., Atchley, A., Harp, D., Manzini, G., Shelef, E., Lipnikov, K., Garimella, R., Xu, C., Moulton, D., Karra, S., Painter, S., Jafarov, E., and Molins, S.: Advanced Terrestrial Simulator, U.S. Department of Energy Office of Scientific and Technical Information, https://doi.org/10.11578/DC.20190911.1, 2019. a, b
De Lucia, M., Kühn, M., Lindemann, A., Lübke, M., and Schnor, B.: POET (v0.1): speedup of many-core parallel reactive transport simulations with fast DHT lookups, Geosci. Model Dev., 14, 7391–7409, https://doi.org/10.5194/gmd-14-7391-2021, 2021. a
Dubey, A., Almgren, A., Bell, J., Berzins, M., Brandt, S., Bryan, G., Colella, P., Graves, D., Lijewski, M., L”offler, F., O'Shea, B., Schnetter, E., Van Straalen, B., and Weide, K.: A survey of high level frameworks in block-structured adaptive mesh refinement packages, J. Parallel and Distr. Com., 74, 3217–3227, https://doi.org/10.1016/j.jpdc.2014.07.001, 2014. a, b, c
GitHub: GitHub Actions documentation, https://docs.github.com/en/actions (last access: 24 May 2025), 2024. a
Greskowiak, J., Gwo, J., Jacques, D., Yin, J., and Mayer, K. U.: A benchmark for multi-rate surface complexation and 1D dual-domain multi-component reactive transport of U(VI), Comput. Geosci., 19, 585–597, https://doi.org/10.1007/s10596-014-9457-4, 2015. a
Gupta, A. D., Lake, L. W., Pope, G. A., Sepehrnoori, K. T. U., and King, M. J. B. R.: High-Resolution Monotonic Schemes for Reservoir Fluid Flow Simulation, In Situ, (United States), 15, https://www.osti.gov/scitech/biblio/5799660 (last access: 24 May 2025), 1991. a
Hammond, G. E.: The PFLOTRAN Reaction Sandbox, Geosci. Model Dev., 15, 1659–1676, https://doi.org/10.5194/gmd-15-1659-2022, 2022. a, b, c, d
Hammond, G. E., Lichtner, P. C., and Mills, R. T.: Evaluating the performance of parallel subsurface simulators: An illustrative example with PFLOTRAN, Water Resour. Res., 50, 208–228, https://doi.org/10.1002/2012WR013483, 2014. a
Jara, D., de Dreuzy, J.-R., and Cochepin, B.: TReacLab: An object-oriented implementation of non-intrusive splitting methods to couple independent transport and geochemical software, Comput. Geosci., 109, 281–294, https://doi.org/10.1016/j.cageo.2017.09.005, 2017. a
Jaysaval, P., Hammond, G. E., and Johnson, T. C.: Massively parallel modeling and inversion of electrical resistivity tomography data using PFLOTRAN, Geosci. Model Dev., 16, 961–976, https://doi.org/10.5194/gmd-16-961-2023, 2023. a
LaFond-Hudson, S. and Sulman, B.: Modeling strategies and data needs for representing coastal wetland vegetation in land surface models, New Phytol., 238, 938–951, https://doi.org/10.1111/nph.18760, 2023. a, b, c
Leal, A. M. M., Kyas, S., Kulik, D. A., and Saar, M. O.: Accelerating Reactive Transport Modeling: On-Demand Machine Learning Algorithm for Chemical Equilibrium Calculations, Transport Porous Med., 133, 161–204, https://doi.org/10.1007/s11242-020-01412-1, 2020. a
Li, L., Maher, K., Navarre-Sitchler, A., Druhan, J., Meile, C., Lawrence, C., Moore, J., Perdrial, J., Sullivan, P., Thompson, A., Jin, L., Bolton, E. W., Brantley, S. L., Dietrich, W. E., Mayer, K. U., Steefel, C. I., Valocchi, A., Zachara, J., Kocar, B., Mcintosh, J., Bao, C., Tutolo, B. M., Beisman, J., Kumar, M., and Sonnenthal, E.: Expanding the role of reactive transport models in critical zone processes, Earth-Sci. Rev., 165, 280–301, https://doi.org/10.1016/j.earscirev.2016.09.001, 2017. a, b
Lichtner, P. C.: The Quasi-Stationary State Approximation to Fluid/Rock Reaction: Local Equilibrium Revisited, in: Diffusion, Atomic Ordering, and Mass Transport: Selected Topics in Geochemistry, edited by: Ganguly, J., Advances in Physical Geochemistry, Springer US, New York, NY, 452–560, ISBN 978-1-4613-9019-0, https://doi.org/10.1007/978-1-4613-9019-0_13, 1991. a
Lichtner, P. C., Hammond, G. E., Lu, C., Karra, S., Bisht, G., Andre, B. N. C. F. A. R., Lawrence Berkeley National Lab. (LBNL), B., Mills, R. I. C., Univ. of Tennessee, K., and Kumar, J.: Pflotran User Manual: A Massively Parallel Reactive Flow and Transport Model for Describing Surface and Subsurface Processes, Tech. Rep. LA-UR–15-20403, Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Sandia National Lab. (SNL-NM), Albuquerque, NM (United States), Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States), Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States), OFM Research, Redmond, WA, USA, https://doi.org/10.2172/1168703, 2015. a
Maxwell, R. M. and Miller, N. L.: Development of a Coupled Land Surface and Groundwater Model, J. Hydrometeorol., 6, 233–247, https://doi.org/10.1175/JHM422.1, 2005. a
Maxwell, R. M., Putti, M., Meyerhoff, S., Delfs, J.-O., Ferguson, I. M., Ivanov, V., Kim, J., Kolditz, O., Kollet, S. J., Kumar, M., Lopez, S., Niu, J., Paniconi, C., Park, Y.-J., Phanikumar, M. S., Shen, C., Sudicky, E. A., and Sulis, M.: Surface-subsurface model intercomparison: A first set of benchmark results to diagnose integrated hydrology and feedbacks, Water Resour. Res., 50, 1531–1549, https://doi.org/10.1002/2013WR013725, 2014. a
Mayer, K. U., Frind, E. O., and Blowes, D. W.: Multicomponent reactive transport modeling in variably saturated porous media using a generalized formulation for kinetically controlled reactions, Water Resour. Res., 38, 1174, https://doi.org/10.1029/2001WR000862, 2002. a
Molins, S.: Reactive Interfaces in Direct Numerical Simulation of Pore-Scale Processes, Rev. Mineral. Geochem., 80, 461–481, https://doi.org/10.2138/rmg.2015.80.14, 2015. a
Molins, S., Trebotich, D., Steefel, C. I., and Shen, C.: An investigation of the effect of pore scale flow on average geochemical reaction rates using direct numerical simulation, Water Resour. Res., 48, https://doi.org/10.1029/2011WR011404, 2012. a, b
Molins, S., Soulaine, C., Prasianakis, N. I., Abbasi, A., Poncet, P., Ladd, A. J. C., Starchenko, V., Roman, S., Trebotich, D., Tchelepi, H. A., and Steefel, C. I.: Simulation of mineral dissolution at the pore scale with evolving fluid-solid interfaces: review of approaches and benchmark problem set, Comput. Geosci., 25, 1285–1318, https://doi.org/10.1007/s10596-019-09903-x, 2020. a, b
Molins, S., Andre, B., Johnson, J., Hammond, G., Sulman, B., Lipnikov, K., Day, M., Beisman, J., Svyatskiy, D., Deng, H., Lichtner, P., Steefel, C., and Moulton, D.: Alquimia: A generic interface to biogeochemical codes – A tool for interoperable development, prototyping and benchmarking for multiphysics simulators, Zenodo [code], https://doi.org/10.5281/zenodo.11414442, 2024a. a
Molins, S., Trebotich, D., and Steefel, C. I.: Approaches for the simulation of coupled processes in evolving fractured porous media enabled by exascale computing, Comput. Sci. Eng., 26, 33–42, https://doi.org/10.1109/MCSE.2024.3403983, 2024b. a
Nardi, A., Idiart, A., Trinchero, P., de Vries, L. M., and Molinero, J.: Interface COMSOL-PHREEQC (iCP), an efficient numerical framework for the solution of coupled multiphysics and geochemistry, Comput. Geosci., 69, 10–21, https://doi.org/10.1016/j.cageo.2014.04.011, 2014. a
OpenFOAM: Open-source Field Operation And Manipulation, https://www.openfoam.com/ (last access: 24 May 2025), 2022. a
Parkhurst, D. L. and Wissmeier, L.: PhreeqcRM: A reaction module for transport simulators based on the geochemical model PHREEQC, Adv. Water Resour., 83, 176–189, https://doi.org/10.1016/j.advwatres.2015.06.001, 2015. a
Parkhurst, D. L., Kipp, K. L., and Charlton, S. R.: PHAST Version 2 – A program for simulating groundwater flow, solute transport, and multicomponent geochemical reactions, in: U.S. Geological Survey Techniques and Methods, 6-A35, 235, https://doi.org/10.3133/tm6A35, 2010. a
Prommer, H. and Post, V.: PHT3D: A ReactiveMulticomponent Transport Model for Saturated Porous Media, User's Manual v2.10, http://www.pht3d.org (last access: 24 May 2025), 2010. a
Simunek, J., Jacques, D., Langergraber, G., Bradford, S. A., Šejna, M., and Genuchten, M. T. v.: Numerical Modeling of Contaminant Transport Using HYDRUS and its Specialized Modules, J. Indian I. Sci., 93, 265–284, https://journal.iisc.ac.in/index.php/iisc/article/view/1224 (last access: 24 May 2025), 2013. a
Sonnenthal, E., Spycher, N., Xu, T., and Zheng, L.: TOUGHREACT V4.12-OMP and TReactMech V1.0 Geochemical and Reactive-Transport User Guide, https://escholarship.org/uc/item/8945d2c1 (last access: 24 May 2025), 2021. a
Sphinx: Welcome – Sphinx documentation, https://www.sphinx-doc.org/en/master/ (last access: 24 May 2025), 2024. a
Steefel, C. I., DePaolo, D. J., and Lichtner, P. C.: Reactive transport modeling: An essential tool and a new research approach for the Earth sciences, Earth Planet. Sc. Lett., 240, 539–558, https://doi.org/10.1016/j.epsl.2005.09.017, 2005. a
Steefel, C. I., Appelo, C. A. J., Arora, B., Jacques, D., Kalbacher, T., Kolditz, O., Lagneau, V., Lichtner, P. C., Mayer, K. U., Meeussen, J. C. L., Molins, S., Moulton, D., Shao, H., Šimůnek, J., Spycher, N., Yabusaki, S. B., and Yeh, G. T.: Reactive transport codes for subsurface environmental simulation, Comput. Geosci., 19, 445–478, https://doi.org/10.1007/s10596-014-9443-x, 2015. a, b, c, d, e, f, g, h, i
Sulman, B., Yuan, F., O'Meara, T., Graham, D., Gu, B., Herndon, E., and Zheng, J.: Simulated hydrological dynamics and coupled iron redox cycling impact methane production in an Arctic soil: Modeling Archive, ESS-Dive [code], https://doi.org/10.5440/1814844, 2020. a, b
Sulman, B., Wang, J., LaFond-Hudson, S., O'Meara, T., Yuan, F., Molins, S., Forbrich, I., Cardon, Z., and Giblin, A.: Model simulations of Plum Island Ecosystems LTER low marsh site using ELM-PFLOTRAN, ESS-Dive [code], https://doi.org/10.15485/1991625, 2023. a
Sulman, B. N., Yuan, F., O'Meara, T., Gu, B., Herndon, E. M., Zheng, J., Thornton, P. E., and Graham, D. E.: Simulated Hydrological Dynamics and Coupled Iron Redox Cycling Impact Methane Production in an Arctic Soil, J. Geophys. Res.-Biogeo., 127, e2021JG006662, https://doi.org/10.1029/2021JG006662, 2022. a, b, c
Sulman, B. N., Wang, J., LaFond-Hudson, S., O'Meara, T., Yuan, F., Molins, S., Hammond, G. E., Forbrich, I., Cardon, Z., and Giblin, A.: Integrating tide-driven wetland soil redox and biogeochemical interactions into a land surface model, J. Adv. Model. Earth Sy., 16, e2023MS004002, https://doi.org/10.1029/2023MS004002, 2024. a, b, c, d, e, f
Tang, G., Yuan, F., Bisht, G., Hammond, G. E., Lichtner, P. C., Kumar, J., Mills, R. T., Xu, X., Andre, B., Hoffman, F. M., Painter, S. L., and Thornton, P. E.: Addressing numerical challenges in introducing a reactive transport code into a land surface model: a biogeochemical modeling proof-of-concept with CLM–PFLOTRAN 1.0, Geosci. Model Dev., 9, 927–946, https://doi.org/10.5194/gmd-9-927-2016, 2016. a
van der Lee, J., De Windt, L., Lagneau, V., and Goblet, P.: Module-oriented modeling of reactive transport with HYTEC, Comput. Geosci., 29, 265–275, https://doi.org/10.1016/S0098-3004(03)00004-9, 2003. a
Wang, J., O'Meara, T., LaFond-Hudson, S., He, S., Maiti, K., Ward, E. J., and Sulman, B. N.: Subsurface Redox Interactions Regulate Ebullitive Methane Flux in Heterogeneous Mississippi River Deltaic Wetland, J. Adv. Model. Earth Sy., 16, e2023MS003762, https://doi.org/10.1029/2023MS003762, 2024. a, b, c
Zhang, Q., Deng, H., Dong, Y., Molins, S., Li, X., and Steefel, C.: Investigation of Coupled Processes in Fractures and the Bordering Matrix via a Micro-Continuum Reactive Transport Model, Water Resour. Res., 58, e2021WR030578, https://doi.org/10.1029/2021WR030578, 2022. a
Zhang, Q., Dong, Y., Molins, S., and Deng, H.: The Impacts of Micro-Porosity and Mineralogical Texture on Fractured Rock Alteration, Water Resour. Res., 60, e2023WR036266, https://doi.org/10.1029/2023WR036266, 2024. a
Short summary
Developing scientific software and making sure it functions properly requires a significant effort. As we advance our understanding of natural systems, however, there is the need to develop yet more complex models and codes. In this work, we present a piece of software that facilitates this work, specifically with regard to reactive processes. Existing tried-and-true codes are made available via this new interface, freeing up resources to focus on the new aspects of the problems at hand.
Developing scientific software and making sure it functions properly requires a significant...
