Articles | Volume 6, issue 4
https://doi.org/10.5194/gmd-6-1367-2013
© Author(s) 2013. 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-6-1367-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Development and technical paper
| 
30 Aug 2013
Development and technical paper |
| 30 Aug 2013
Mathematics of the total alkalinity–pH equation – pathway to robust and universal solution algorithms: the SolveSAPHE package v1.0.1
G. Munhoven
Département d'Astrophysique, Géophysique et Océanographie, Université de Liège, 4000 Liège, Belgium
Related authors
Ying Ye, Guy Munhoven, Peter Köhler, Martin Butzin, Judith Hauck, Özgür Gürses, and Christoph Völker
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-181, https://doi.org/10.5194/gmd-2023-181, 2023
Revised manuscript under review for GMD
Short summary
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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 storage of carbon in sediments slows down carbon cycling and influences feedbacks in the atmosphere-ocean-sediment system. Here we coupled a sediment model to an ocean biogeochemistry model and found a shift of carbon storage from the atmosphere to the ocean-sediment system.
Nathaelle Bouttes, Lester Kwiatkowski, Manon Berger, Victor Brovkin, and Guy Munhoven
EGUsphere, https://doi.org/10.5194/egusphere-2023-1162, https://doi.org/10.5194/egusphere-2023-1162, 2023
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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.
Matteo Willeit, Tatiana Ilyina, Bo Liu, Christoph Heinze, Mahé Perrette, Malte Heinemann, Daniela Dalmonech, Victor Brovkin, Guy Munhoven, Janine Börker, Jens Hartmann, Gibran Romero-Mujalli, and Andrey Ganopolski
Geosci. Model Dev., 16, 3501–3534, https://doi.org/10.5194/gmd-16-3501-2023, https://doi.org/10.5194/gmd-16-3501-2023, 2023
Short summary
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In this paper we present the carbon cycle component of the newly developed fast Earth system model CLIMBER-X. The model can be run with interactive atmospheric CO2 to investigate the feedbacks between climate and the carbon cycle on temporal scales ranging from decades to > 100 000 years. CLIMBER-X is expected to be a useful tool for studying past climate–carbon cycle changes and for the investigation of the long-term future evolution of the Earth system.
Guy Munhoven
Geosci. Model Dev., 14, 4225–4240, https://doi.org/10.5194/gmd-14-4225-2021, https://doi.org/10.5194/gmd-14-4225-2021, 2021
Short summary
Short summary
SolveSAPHE (Munhoven, 2013) was the first package to calculate pH reliably from any physically sensible pair of total alkalinity (AlkT) and dissolved inorganic carbon (CT) data and to do so in an autonomous and efficient way. Here, we extend it to use CO2, HCO3 or CO3 instead of CT. For each one of these pairs, the new SolveSAPHE calculates all of the possible pH values (0, 1, or 2), again without any prior knowledge of the solutions.
Guy Munhoven
Geosci. Model Dev., 14, 3603–3631, https://doi.org/10.5194/gmd-14-3603-2021, https://doi.org/10.5194/gmd-14-3603-2021, 2021
Short summary
Short summary
Sea-floor sediments play an important role in biogeochemical cycling of elements (e.g. carbon, silicon, nutrients) in the ocean. Realistic sediment modules are, however, not yet commonly used in global ocean biogeochemical models. Here we present MEDUSA, a model of the processes taking place in the surface sea-floor sediments which control the interaction between the sediments and the ocean. MEDUSA can be configured to meet the exact needs of any given ocean biogeochemical model.
Takasumi Kurahashi-Nakamura, André Paul, Guy Munhoven, Ute Merkel, and Michael Schulz
Geosci. Model Dev., 13, 825–840, https://doi.org/10.5194/gmd-13-825-2020, https://doi.org/10.5194/gmd-13-825-2020, 2020
Short summary
Short summary
Chemical processes in ocean-floor sediments have a large influence on the marine carbon cycle, hence the global climate, at long timescales. We developed a new coupling scheme for a chemical sediment model and a comprehensive climate model. The new coupled model outperformed the original uncoupled climate model in reproducing the global distribution of sediment properties. The sediment model will also act as a
bridgebetween the ocean model and paleoceanographic data.
Thomas Kleinen, Victor Brovkin, and Guy Munhoven
Clim. Past, 12, 2145–2160, https://doi.org/10.5194/cp-12-2145-2016, https://doi.org/10.5194/cp-12-2145-2016, 2016
Short summary
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We investigate trends in atmospheric CO2 during three recent interglacials – the Holocene, the Eemian and MIS 11 – using an earth system model of intermediate complexity. Our model experiments show a considerable improvement in the modelled CO2 trends for all three interglacials if peat accumulation and shallow water CaCO3 sedimentation are included, forcing the model only with orbital and sea level changes. The Holocene CO2 trend requires anthropogenic emissions of CO2 only after 3 ka BP.
Ying Ye, Guy Munhoven, Peter Köhler, Martin Butzin, Judith Hauck, Özgür Gürses, and Christoph Völker
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-181, https://doi.org/10.5194/gmd-2023-181, 2023
Revised manuscript under review for GMD
Short summary
Short summary
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 storage of carbon in sediments slows down carbon cycling and influences feedbacks in the atmosphere-ocean-sediment system. Here we coupled a sediment model to an ocean biogeochemistry model and found a shift of carbon storage from the atmosphere to the ocean-sediment system.
Nathaelle Bouttes, Lester Kwiatkowski, Manon Berger, Victor Brovkin, and Guy Munhoven
EGUsphere, https://doi.org/10.5194/egusphere-2023-1162, https://doi.org/10.5194/egusphere-2023-1162, 2023
Short summary
Short summary
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.
Matteo Willeit, Tatiana Ilyina, Bo Liu, Christoph Heinze, Mahé Perrette, Malte Heinemann, Daniela Dalmonech, Victor Brovkin, Guy Munhoven, Janine Börker, Jens Hartmann, Gibran Romero-Mujalli, and Andrey Ganopolski
Geosci. Model Dev., 16, 3501–3534, https://doi.org/10.5194/gmd-16-3501-2023, https://doi.org/10.5194/gmd-16-3501-2023, 2023
Short summary
Short summary
In this paper we present the carbon cycle component of the newly developed fast Earth system model CLIMBER-X. The model can be run with interactive atmospheric CO2 to investigate the feedbacks between climate and the carbon cycle on temporal scales ranging from decades to > 100 000 years. CLIMBER-X is expected to be a useful tool for studying past climate–carbon cycle changes and for the investigation of the long-term future evolution of the Earth system.
Guy Munhoven
Geosci. Model Dev., 14, 4225–4240, https://doi.org/10.5194/gmd-14-4225-2021, https://doi.org/10.5194/gmd-14-4225-2021, 2021
Short summary
Short summary
SolveSAPHE (Munhoven, 2013) was the first package to calculate pH reliably from any physically sensible pair of total alkalinity (AlkT) and dissolved inorganic carbon (CT) data and to do so in an autonomous and efficient way. Here, we extend it to use CO2, HCO3 or CO3 instead of CT. For each one of these pairs, the new SolveSAPHE calculates all of the possible pH values (0, 1, or 2), again without any prior knowledge of the solutions.
Guy Munhoven
Geosci. Model Dev., 14, 3603–3631, https://doi.org/10.5194/gmd-14-3603-2021, https://doi.org/10.5194/gmd-14-3603-2021, 2021
Short summary
Short summary
Sea-floor sediments play an important role in biogeochemical cycling of elements (e.g. carbon, silicon, nutrients) in the ocean. Realistic sediment modules are, however, not yet commonly used in global ocean biogeochemical models. Here we present MEDUSA, a model of the processes taking place in the surface sea-floor sediments which control the interaction between the sediments and the ocean. MEDUSA can be configured to meet the exact needs of any given ocean biogeochemical model.
Takasumi Kurahashi-Nakamura, André Paul, Guy Munhoven, Ute Merkel, and Michael Schulz
Geosci. Model Dev., 13, 825–840, https://doi.org/10.5194/gmd-13-825-2020, https://doi.org/10.5194/gmd-13-825-2020, 2020
Short summary
Short summary
Chemical processes in ocean-floor sediments have a large influence on the marine carbon cycle, hence the global climate, at long timescales. We developed a new coupling scheme for a chemical sediment model and a comprehensive climate model. The new coupled model outperformed the original uncoupled climate model in reproducing the global distribution of sediment properties. The sediment model will also act as a
bridgebetween the ocean model and paleoceanographic data.
Thomas Kleinen, Victor Brovkin, and Guy Munhoven
Clim. Past, 12, 2145–2160, https://doi.org/10.5194/cp-12-2145-2016, https://doi.org/10.5194/cp-12-2145-2016, 2016
Short summary
Short summary
We investigate trends in atmospheric CO2 during three recent interglacials – the Holocene, the Eemian and MIS 11 – using an earth system model of intermediate complexity. Our model experiments show a considerable improvement in the modelled CO2 trends for all three interglacials if peat accumulation and shallow water CaCO3 sedimentation are included, forcing the model only with orbital and sea level changes. The Holocene CO2 trend requires anthropogenic emissions of CO2 only after 3 ka BP.
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Soyoung Ha, Jonathan J. Guerrette, Ivette Hernandez Banos, William C. Skamarock, and Michael G. Duda
EGUsphere, https://doi.org/10.5194/egusphere-2023-2299, https://doi.org/10.5194/egusphere-2023-2299, 2023
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Wangbin Shen, Zhaohui Lin, Zhengkun Qin, and Juan Li
EGUsphere, https://doi.org/10.5194/egusphere-2023-2473, https://doi.org/10.5194/egusphere-2023-2473, 2023
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Tor Nordam, Ruben Kristiansen, Raymond Nepstad, Erik van Sebille, and Andy M. Booth
Geosci. Model Dev., 16, 5339–5363, https://doi.org/10.5194/gmd-16-5339-2023, https://doi.org/10.5194/gmd-16-5339-2023, 2023
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We describe and compare two common methods, Eulerian and Lagrangian models, used to simulate the vertical transport of material in the ocean. They both solve the same transport problems but use different approaches for representing the underlying equations on the computer. The main focus of our study is on the numerical accuracy of the two approaches. Our results should be useful for other researchers creating or using these types of transport models.
Luan Carlos de Sena Monteiro Ozelim, Michéle Dal Toé Casagrande, and André Luís Brasil Cavalcante
EGUsphere, https://doi.org/10.5194/egusphere-2023-1690, https://doi.org/10.5194/egusphere-2023-1690, 2023
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The paper addresses the quantity and complexity of synthetic datasets for nonlinear constitutive modelling of soils following the NorSand model by simulating both drained and undrained triaxial tests of 2000 soil types, with a total of 160000 triaxial test results made available. Each simulation dataset comprises a 4000 by 10 matrix that can be used for general multivariate forecasting benchmarks, apart from direct geotechnical and soil science applications.
Mathieu Gravey and Grégoire Mariethoz
Geosci. Model Dev., 16, 5265–5279, https://doi.org/10.5194/gmd-16-5265-2023, https://doi.org/10.5194/gmd-16-5265-2023, 2023
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Multiple‐point geostatistics are widely used to simulate complex spatial structures based on a training image. The use of these methods relies on the possibility of finding optimal training images and parametrization of the simulation algorithms. Here, we propose finding an optimal set of parameters using only the training image as input. The main advantage of our approach is to remove the risk of overfitting an objective function.
Siting Li, Ping Wang, Hong Wang, Yue Peng, Zhaodong Liu, Wenjie Zhang, Hongli Liu, Yaqiang Wang, Huizheng Che, and Xiaoye Zhang
Geosci. Model Dev., 16, 4171–4191, https://doi.org/10.5194/gmd-16-4171-2023, https://doi.org/10.5194/gmd-16-4171-2023, 2023
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Optimizing the initial state of atmospheric chemistry model input is one of the most essential methods to improve forecast accuracy. Considering the large computational load of the model, we introduce an ensemble optimal interpolation scheme (EnOI) for operational use and efficient updating of the initial fields of chemical components. The results suggest that EnOI provides a practical and cost-effective technique for improving the accuracy of chemical weather numerical forecasts.
Thomas Richter, Véronique Dansereau, Christian Lessig, and Piotr Minakowski
Geosci. Model Dev., 16, 3907–3926, https://doi.org/10.5194/gmd-16-3907-2023, https://doi.org/10.5194/gmd-16-3907-2023, 2023
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Sea ice covers not only the pole regions but affects the weather and climate globally. For example, its white surface reflects more sunlight than land. The oceans around the poles are therefore kept cool, which affects the circulation in the oceans worldwide. Simulating the behavior and changes in sea ice on a computer is, however, very difficult. We propose a new computer simulation that better models how cracks in the ice change over time and show this by comparing to other simulations.
Federica Castino, Feijia Yin, Volker Grewe, Hiroshi Yamashita, Sigrun Matthes, Simone Dietmüller, Sabine Baumann, Manuel Soler, Abolfazl Simorgh, Maximilian Mendiguchia Meuser, Florian Linke, and Benjamin Lührs
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-88, https://doi.org/10.5194/gmd-2023-88, 2023
Revised manuscript accepted for GMD
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We introduce SolFinder 1.0, a decision-making tool to select trade-offs between different objective functions, including fuel use, flight time, NOx emissions, contrail distance, and climate impact. The module is included in the AirTraf 3.0 submodel, which optimizes trajectories under weather conditions simulated by an atmospheric model (EMAC). This paper focuses on the ability of the module to identify eco-efficient trajectories, which reduce the flights climate impact at limited cost penalties.
Emma J. MacKie, Michael Field, Lijing Wang, Zhen Yin, Nathan Schoedl, Matthew Hibbs, and Allan Zhang
Geosci. Model Dev., 16, 3765–3783, https://doi.org/10.5194/gmd-16-3765-2023, https://doi.org/10.5194/gmd-16-3765-2023, 2023
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Earth scientists often have to fill in spatial gaps in measurements. This gap-filling or interpolation can be accomplished with geostatistical methods, where the statistical relationships between measurements are used to inform how these gaps should be filled. Despite the broad utility of these methods, there are few freely available geostatistical software applications. We present GStatSim, a Python package for performing different geostatistical interpolation methods.
Ian Madden, Simone Marras, and Jenny Suckale
Geosci. Model Dev., 16, 3479–3500, https://doi.org/10.5194/gmd-16-3479-2023, https://doi.org/10.5194/gmd-16-3479-2023, 2023
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To aid risk managers who may wish to rapidly assess tsunami risk but may lack high-performance computing infrastructure, we provide an accessible software package able to rapidly model tsunami inundation over real topography by leveraging Google's Tensor Processing Unit, a high-performance hardware. Minimally trained users can take advantage of the rapid modeling abilities provided by this package via a web browser thanks to the ease of use of Google Cloud Platform.
Youtong Rong, Paul Bates, and Jeffrey Neal
Geosci. Model Dev., 16, 3291–3311, https://doi.org/10.5194/gmd-16-3291-2023, https://doi.org/10.5194/gmd-16-3291-2023, 2023
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A novel subgrid channel (SGC) model is developed for river–floodplain modelling, allowing utilization of subgrid-scale bathymetric information while performing computations on relatively coarse grids. By including adaptive artificial diffusion, potential numerical instability, which the original SGC solver had, in low-friction regions such as urban areas is addressed. Evaluation of the new SGC model through structured tests confirmed that the accuracy and stability have improved.
Xiaqiong Zhou and Hann-Ming Henry Juang
Geosci. Model Dev., 16, 3263–3274, https://doi.org/10.5194/gmd-16-3263-2023, https://doi.org/10.5194/gmd-16-3263-2023, 2023
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The National Centers for Environmental Prediction Global Forecast System version 16 experienced model instability failures in real-time runs resolved by increasing the minimum thickness depth parameter. Further investigation revealed that the issue was caused by the advection of geopotential heights at the model's layer interfaces. By replacing high-order boundary conditions with zero-gradient boundary conditions for interface-wind reconstruction, the instability was effectively addressed.
Grant T. Euen, Shangxin Liu, Rene Gassmöller, Timo Heister, and Scott D. King
Geosci. Model Dev., 16, 3221–3239, https://doi.org/10.5194/gmd-16-3221-2023, https://doi.org/10.5194/gmd-16-3221-2023, 2023
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Due to the increasing availability of high-performance computing over the past few decades, numerical models have become an important tool for research. Here we test two geodynamic codes that produce such models: ASPECT, a newer code, and CitcomS, an older one. We show that they produce solutions that are extremely close. As methods and codes become more complex over time, showing reproducibility allows us to seamlessly link previously known information to modern methodologies.
Ali Dashti, Jens Carsten Grimmer, Christophe Geuzaine, Florian Bauer, and Thomas Kohl
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-105, https://doi.org/10.5194/gmd-2023-105, 2023
Revised manuscript accepted for GMD
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This study developed a new meshing workflow to enable making meshes that follow geological models. This workflow also allows us to import several geological models as input for the mesh generator and later on export the same number of watertight meshes. This way, geological uncertainty can be directly included in the numerical simulations. This study evaluates the impact of the geological uncertainty on thermohydraulic performance of the reservoir for high temperature heat storage applications.
Mohammad Kazem Sharifian, Georges Kesserwani, Alovya Ahmed Chowdhury, Jeffrey Neal, and Paul Bates
Geosci. Model Dev., 16, 2391–2413, https://doi.org/10.5194/gmd-16-2391-2023, https://doi.org/10.5194/gmd-16-2391-2023, 2023
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This paper describes a new release of the LISFLOOD-FP model for fast and efficient flood simulations. It features a new non-uniform grid generator that uses multiwavelet analyses to sensibly coarsens the resolutions where the local topographic variations are smooth. Moreover, the model is parallelised on the graphical processing units (GPUs) to further boost computational efficiency. The performance of the model is assessed for five real-world case studies, noting its potential applications.
Bruno K. Zürcher
Geosci. Model Dev., 16, 1697–1711, https://doi.org/10.5194/gmd-16-1697-2023, https://doi.org/10.5194/gmd-16-1697-2023, 2023
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We present a novel algorithm to efficiently compute Barnes interpolation, which is a method for transforming data values recorded at irregularly spaced points into a corresponding regular grid. In contrast to naive implementations with an algorithmic complexity that depends on the product of the number of sample points and the number of grid points, our approach reduces this dependency to their sum.
David H. Marsico and Paul A. Ullrich
Geosci. Model Dev., 16, 1537–1551, https://doi.org/10.5194/gmd-16-1537-2023, https://doi.org/10.5194/gmd-16-1537-2023, 2023
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Climate models involve several different components, such as the atmosphere, ocean, and land models. Information needs to be exchanged, or remapped, between these models, and devising algorithms for performing this exchange is important for ensuring the accuracy of climate simulations. In this paper, we examine the efficacy of several traditional and novel approaches to remapping on the sphere and demonstrate where our approaches offer improvement.
Moritz Liebl, Jörg Robl, Stefan Hergarten, David Lundbek Egholm, and Kurt Stüwe
Geosci. Model Dev., 16, 1315–1343, https://doi.org/10.5194/gmd-16-1315-2023, https://doi.org/10.5194/gmd-16-1315-2023, 2023
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In this study, we benchmark a topography-based model for glacier erosion (OpenLEM) with a well-established process-based model (iSOSIA). Our experiments show that large-scale erosion patterns and particularly the transformation of valley length geometry from fluvial to glacial conditions are very similar in both models. This finding enables the application of OpenLEM to study the influence of climate and tectonics on glaciated mountains with reasonable computational effort on standard PCs.
James Kent, Thomas Melvin, and Golo Albert Wimmer
Geosci. Model Dev., 16, 1265–1276, https://doi.org/10.5194/gmd-16-1265-2023, https://doi.org/10.5194/gmd-16-1265-2023, 2023
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This paper introduces the Met Office's new shallow water model. The shallow water model is a building block towards the Met Office's new atmospheric dynamical core. The shallow water model is tested on a number of standard spherical shallow water test cases, including flow over mountains and unstable jets. Results show that the model produces similar results to other shallow water models in the literature.
Anthony Gruber, Max Gunzburger, Lili Ju, Rihui Lan, and Zhu Wang
Geosci. Model Dev., 16, 1213–1229, https://doi.org/10.5194/gmd-16-1213-2023, https://doi.org/10.5194/gmd-16-1213-2023, 2023
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This work applies a novel technical tool, multifidelity Monte Carlo (MFMC) estimation, to three climate-related benchmark experiments involving oceanic, atmospheric, and glacial modeling. By considering useful quantities such as maximum sea height and total (kinetic) energy, we show that MFMC leads to predictions which are more accurate and less costly than those obtained by standard methods. This suggests MFMC as a potential drop-in replacement for estimation in realistic climate models.
Piyoosh Jaysaval, Glenn E. Hammond, and Timothy C. Johnson
Geosci. Model Dev., 16, 961–976, https://doi.org/10.5194/gmd-16-961-2023, https://doi.org/10.5194/gmd-16-961-2023, 2023
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We present a robust and highly scalable implementation of numerical forward modeling and inversion algorithms for geophysical electrical resistivity tomography data. The implementation is publicly available and developed within the framework of PFLOTRAN (http://www.pflotran.org), an open-source, state-of-the-art massively parallel subsurface flow and transport simulation code. The paper details all the theoretical and implementation aspects of the new capabilities along with test examples.
Lucas Schauer, Michael J. Schmidt, Nicholas B. Engdahl, Stephen D. Pankavich, David A. Benson, and Diogo Bolster
Geosci. Model Dev., 16, 833–849, https://doi.org/10.5194/gmd-16-833-2023, https://doi.org/10.5194/gmd-16-833-2023, 2023
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We develop a multi-dimensional, parallelized domain decomposition strategy for mass-transfer particle tracking methods in two and three dimensions, investigate different procedures for decomposing the domain, and prescribe an optimal tiling based on physical problem parameters and the number of available CPU cores. For an optimally subdivided diffusion problem, the parallelized algorithm achieves nearly perfect linear speedup in comparison with the serial run-up to thousands of cores.
John Mern and Jef Caers
Geosci. Model Dev., 16, 289–313, https://doi.org/10.5194/gmd-16-289-2023, https://doi.org/10.5194/gmd-16-289-2023, 2023
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In this work, we formulate the sequential geoscientific data acquisition problem as a problem that is similar to playing chess against nature, except the pieces are not fully observed. Solutions to these problems are given in AI and rarely used in geoscientific data planning. We illustrate our approach to a simple 2D problem of mineral exploration.
Jevgenijs Steinbuks, Yongyang Cai, Jonas Jaegermeyr, and Thomas W. Hertel
EGUsphere, https://doi.org/10.5194/egusphere-2022-863, https://doi.org/10.5194/egusphere-2022-863, 2023
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This paper applies cutting-edge numerical methods to show how uncertain climate change and technological progress affect the future utilization of the scarce world's land resources. The paper's key insight is to illustrate how much global cropland will expand when future crop yields are unknown. The more uncertain the future crop yields are, the more forest conversion will be necessary to sustain human welfare. Some of that conversion takes place even when crop yields are not actually affected.
Ziqi Gao, Yifeng Wang, Petros Vasilakos, Cesunica E. Ivey, Khanh Do, and Armistead G. Russell
Geosci. Model Dev., 15, 9015–9029, https://doi.org/10.5194/gmd-15-9015-2022, https://doi.org/10.5194/gmd-15-9015-2022, 2022
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While the national ambient air quality standard of ozone is based on the 3-year average of the fourth highest 8 h maximum (MDA8) ozone concentrations, these predicted extreme values using numerical methods are always biased low. We built four computational models (GAM, MARS, random forest and SVR) to predict the fourth highest MDA8 ozone in Southern California using precursor emissions, meteorology and climatological patterns. All models presented acceptable performance, with GAM being the best.
Zhihao Wang, Jason Goetz, and Alexander Brenning
Geosci. Model Dev., 15, 8765–8784, https://doi.org/10.5194/gmd-15-8765-2022, https://doi.org/10.5194/gmd-15-8765-2022, 2022
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A lack of inventory data can be a limiting factor in developing landslide predictive models, which are crucial for supporting hazard policy and decision-making. We show how case-based reasoning and domain adaptation (transfer-learning techniques) can effectively retrieve similar landslide modeling situations for prediction in new data-scarce areas. Using cases in Italy, Austria, and Ecuador, our findings support the application of transfer learning for areas that require rapid model development.
Till Sachau, Haibin Yang, Justin Lang, Paul D. Bons, and Louis Moresi
Geosci. Model Dev., 15, 8749–8764, https://doi.org/10.5194/gmd-15-8749-2022, https://doi.org/10.5194/gmd-15-8749-2022, 2022
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Knowledge of the internal structures of the major continental ice sheets is improving, thanks to new investigative techniques. These structures are an essential indication of the flow behavior and dynamics of ice transport, which in turn is important for understanding the actual impact of the vast amounts of water trapped in continental ice sheets on global sea-level rise. The software studied here is specifically designed to simulate such structures and their evolution.
Keith J. Roberts, Alexandre Olender, Lucas Franceschini, Robert C. Kirby, Rafael S. Gioria, and Bruno S. Carmo
Geosci. Model Dev., 15, 8639–8667, https://doi.org/10.5194/gmd-15-8639-2022, https://doi.org/10.5194/gmd-15-8639-2022, 2022
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Finite-element methods (FEMs) permit the use of more flexible unstructured meshes but are rarely used in full waveform inversions (FWIs), an iterative process that reconstructs velocity models of earth’s subsurface, due to computational and memory storage costs. To reduce those costs, novel software is presented allowing the use of high-order mass-lumped FEMs on triangular meshes, together with a material-property mesh-adaptation performance-enhancing strategy, enabling its use in FWIs.
Konstantinos Papadakis, Yann Pfau-Kempf, Urs Ganse, Markus Battarbee, Markku Alho, Maxime Grandin, Maxime Dubart, Lucile Turc, Hongyang Zhou, Konstantinos Horaites, Ivan Zaitsev, Giulia Cozzani, Maarja Bussov, Evgeny Gordeev, Fasil Tesema, Harriet George, Jonas Suni, Vertti Tarvus, and Minna Palmroth
Geosci. Model Dev., 15, 7903–7912, https://doi.org/10.5194/gmd-15-7903-2022, https://doi.org/10.5194/gmd-15-7903-2022, 2022
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Vlasiator is a plasma simulation code that simulates the entire near-Earth space at a global scale. As 6D simulations require enormous amounts of computational resources, Vlasiator uses adaptive mesh refinement (AMR) to lighten the computational burden. However, due to Vlasiator’s grid topology, AMR simulations suffer from grid aliasing artifacts that affect the global results. In this work, we present and evaluate the performance of a mechanism for alleviating those artifacts.
Artur Safin, Damien Bouffard, Firat Ozdemir, Cintia L. Ramón, James Runnalls, Fotis Georgatos, Camille Minaudo, and Jonas Šukys
Geosci. Model Dev., 15, 7715–7730, https://doi.org/10.5194/gmd-15-7715-2022, https://doi.org/10.5194/gmd-15-7715-2022, 2022
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Reconciling the differences between numerical model predictions and observational data is always a challenge. In this paper, we investigate the viability of a novel approach to the calibration of a three-dimensional hydrodynamic model of Lake Geneva, where the target parameters are inferred in terms of distributions. We employ a filtering technique that generates physically consistent model trajectories and implement a neural network to enable bulk-to-skin temperature conversion.
Colin Grudzien and Marc Bocquet
Geosci. Model Dev., 15, 7641–7681, https://doi.org/10.5194/gmd-15-7641-2022, https://doi.org/10.5194/gmd-15-7641-2022, 2022
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Iterative optimization techniques, the state of the art in data assimilation, have largely focused on extending forecast accuracy to moderate- to long-range forecast systems. However, current methodology may not be cost-effective in reducing forecast errors in online, short-range forecast systems. We propose a novel optimization of these techniques for online, short-range forecast cycles, simultaneously providing an improvement in forecast accuracy and a reduction in the computational cost.
Yangyang Yu, Shaoqing Zhang, Haohuan Fu, Lixin Wu, Dexun Chen, Yang Gao, Zhiqiang Wei, Dongning Jia, and Xiaopei Lin
Geosci. Model Dev., 15, 6695–6708, https://doi.org/10.5194/gmd-15-6695-2022, https://doi.org/10.5194/gmd-15-6695-2022, 2022
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To understand the scientific consequence of perturbations caused by slave cores in heterogeneous computing environments, we examine the influence of perturbation amplitudes on the determination of the cloud bottom and cloud top and compute the probability density function (PDF) of generated clouds. A series of comparisons of the PDFs between homogeneous and heterogeneous systems show consistently acceptable error tolerances when using slave cores in heterogeneous computing environments.
Cited articles
Anderson, N. and Björk, A.: A new high order method of regula falsi type for computing a root of an equation, BIT, 13, 253–264, 1973.
Antoine, D. and Morel, A.: Modelling the seasonal course of the upper ocean pCO2 (I). Development of a one-dimensional model, Tellus B, 47, 103–121, https://doi.org/10.1034/j.1600-0889.47.issue1.11.x, 1995.
Arndt, S., Regnier, P., Goddéris, Y., and Donnadieu, Y.: GEOCLIM reloaded (v 1.0): a new coupled earth system model for past climate change, Geosci. Model Dev., 4, 451–481, https://doi.org/10.5194/gmd-4-451-2011, 2011.
Aumont, O. and Bopp, L.: Globalizing results from ocean in situ iron fertilization studies, Global Biogeochem. Cy., 20, GB2017, https://doi.org/10.1029/2005GB002591, 2006.
Bacastow, R.: Numerical evaluation of the evasion factor, in: Carbon Cycle Modelling, vol. 16 of SCOPE, chap. 3.4, edited by: Bolin, B., John Wiley & Sons, Chichester, NY, 95–98, 1981.
Bacastow, R. and Keeling, C. D.: Atmospheric carbon dioxide and radiocarbon in the natural carbon cycle. II. Changes from A.D. 1700 to 2070 as deduced from a geochemical model, in: Carbon and the Biosphere, Proceedings of the 24th Brookhaven Symposium in Biology, 16–18 May 1972, edited by: Woodwell, G. M. and Pecan, E. V., US Atomic Energy Commission, 86–135, Upton, NY, 1973.
Bates, R. G.: pH measurements in the marine environment, Pure Appl. Chem., 54, 229–232, https://doi.org/10.1351/pac198254010229, 1982.
Bates, R. G. and Culberson, C. H.: Hydrogen ions and the thermodynamic state of marine systems, in: The Fate of Fossil Fuel CO2 in the Oceans, edited by: Andersen, N. R. and Malahoff, A., Plenum Press, New York, NY, 45–61, 1977.
Bolin, B., Björkström, A., Holmén, K., and Moore, B.: The simultaneous use of tracers for ocean circulation studies, Tellus B, 35, 206–236, 1983.
Broecker, W. S. and Peng, T.-H.: Tracers in the Sea, Lamont-Doherty Geological Observatory of Columbia University, Palisades, NY 10964, 1982.
Buck, R. P., Rondinini, S., Covington, A. K., Baucke, F. G. K., Brett, C. M. A., Camões, M. F., Milton, M. J. T., Mussini, T., Naumann, R., Pratt, K. W., Spitzer, P., and Wilson, G. S.: Measurement of pH. D}efinition, standards, and procedures (IUPAC {Recommendations 2002), Pure Appl. Chem., 74, 2169–2200, https://doi.org/10.1351/pac200274112169, 2002.
Bus, J. C. P. and Dekker, T. J.: Two efficient algorithms with guaranteed convergence for finding a zero of a function, ACM T. Math. Software, 1, 330–345, 1975.
Caldeira, K. and Wickett, M. E.: Oceanography: anthropogenic carbon and ocean pH, Nature, 425, p. 365, https://doi.org/10.1038/425365a, 2003.
Dickson, A. G.: An exact definition of total alkalinity and a procedure for the estimation of alkalinity and total inorganic carbon from titration data, Deep-Sea Res., 28A, 609–623, 1981.
Dickson, A. G.: pH scales and proton-transfer reactions in saline media such as sea water, Geochim. Cosmochim. Ac., 48, 2299–2308, 1984.
Dickson, A. G.: Standard potential of the reaction: AgCl(s) + ½H2(g) = Ag(s) + HCl(aq), and the standard acidity constant of the ion HSO4- in synthetic sea water from 273.15 to 318.15 K, J. Chem. Thermodyn., 22, 113–127, https://doi.org/10.1016/0021-9614(90)90074-Z, 1990.
Dickson, A. G.: The measurement of sea water pH, Mar. Chem., 44, 131–142, https://doi.org/10.1016/0304-4203(93)90198-W, 1993.
Dickson, A. G.: The carbon dioxide system in seawater: equilibrium chemistry and measurements, in: Guide to best practices for ocean acidification research and data reporting, edited by: Riebesell, U., Fabry, V. J., Hansson, L., and Gattuso, J.-P., Publications Office of the European Union, Luxembourg, 17–40, https://doi.org/10.2777/58454, 2010.
Dickson, A. G. and Riley, J. P.: The estimation of acid dissolution constants in seawater media from potentiometric titrations with strong base. I. The ionic product of water – Kw, Mar. Chem., 7, 89–99, 1979.
Dickson, A. G., Sabine, C. L., and Christian, J. R., editors.: Guide to Best Practices for Ocean CO2 Measurements, vol. 3 of \em PICES Special Publication\/, Carbon Dioxide Information and Analysis Center, Oak Ridge (TN), available at: http://cdiac.ornl.gov/oceans/Handbook_2007.html, last access: 11 September 2012, 2007.
Doney, S. C., Lindsay, K., Fung, I., and John, J.: Natural variability in a stable, 1000-yr global coupled climate-carbon cycle simulation, J. Climate, 19, 3033–3054, https://doi.org/10.1175/JCLI3783.1, 2006.
Dowell, M. and Jarrett, P.: A modified regula falsi method for computing the root of an equation, BIT, 11, 168–174, 1971.
Dyrssen, D. W.: Framvaren and the Black Sea – similarities and differences, Aquat. Geochem., 5, 59–73, https://doi.org/10.1023/A:1009663704604, 1999.
Follows, M. J., Ito, T., and Dutkiewicz, S.: On the solution of the carbonate chemistry system in ocean biogeochemistry models, Ocean Model., 12, 290–301, https://doi.org/10.1016/j.ocemod.2005.05.004, 2006.
Gangstø, R., Joos, F., and Gehlen, M.: Sensitivity of pelagic calcification to ocean acidification, Biogeosciences, 8, 433–458, https://doi.org/10.5194/bg-8-433-2011, 2011.
Goosse, H., Brovkin, V., Fichefet, T., Haarsma, R., Huybrechts, P., Jongma, J., Mouchet, A., Selten, F., Barriat, P.-Y., Campin, J.-M., Deleersnijder, E., Driesschaert, E., Goelzer, H., Janssens, I., Loutre, M.-F., Morales Maqueda, M. A., Opsteegh, T., Mathieu, P.-P., Munhoven, G., Pettersson, E. J., Renssen, H., Roche, D. M., Schaeffer, M., Tartinville, B., Timmermann, A., and Weber, S. L.: Description of the Earth system model of intermediate complexity LOVECLIM version 1.2, Geosci. Model Dev., 3, 603–633, https://doi.org/10.5194/gmd-3-603-2010, 2010.
Hansson, I.: A new set of pH-scales and standard buffers for sea water, Deep-Sea Res., 20, 479–491, 1973.
Heinze, C., Maier-Reimer, E., and Winn, K.: Glacial pCO2 reduction by the World Ocean: experiments with the Hamburg Carbon Cycle Model, Paleoceanography, 6, 395–430, 1991.
Hoffert, M. I., Wey, Y.-C., Callegari, A. J., and Broecker, W. S.: Atmospheric response to deep-sea injections of fossil-fuel carbon dioxide, Climatic Change, 2, 53–68, https://doi.org/10.1007/BF00138226, 1979.
Hofmann, A. F., Soetaert, K., Middelburg, J. J., and Meysman, F. J. R.: AquaEnv}: An Aquatic Acid-Base Modelling Environment in {R, Aquat. Geochem., 16, 507–546, https://doi.org/10.1007/s10498-009-9084-1, 2010.
Hofmann, A. F., Soetaert, K., and Meysman, F. J.: AquaEnv}: {AquaEnv – an integrated development toolbox for aquatic chemical model generation. R package version 1.0-3., available at: http://cran.r-project.org/web/packages/AquaEnv/index.html, last access: 29 May 2013, 2012.
Keeling, C. D.: The carbon dioxide cycle: reservoir models to depict the exchange of atmospheric carbon dioxide with the oceans and land plants, in: Chemistry of the Lower Atmosphere, chap. 6, edited by: Rasool, S. I., Plenum Press, New York, NY, 251–329, 1973.
Khoo, K. H., Ramette, R. W., Culberson, C. H., and Bates, R. G.: Determination of hydrogen ion concentrations in seawater from 5 to 40 °C}: Standard potentials at salinities from 20 to {45 \permil, Anal. Chem., 49, 29–34, https://doi.org/10.1021/ac50009a016, 1977.
Kirby, C. S. and Cravotta III, C. A.: Net alkalinity and net acidity. 1: Theoretical considerations, Appl. Geochem., 20, 1920–1940, https://doi.org/10.1016/j.apgeochem.2005.07.002, 2005.
Lavigne, H. and Gattuso, J.-P.: Seacarb: Seawater Carbonate Chemistry with R, R Package Version 2.4., available at: http://cran.r-project.org/web/packages/seacarb/index.html, last access: 13 December 2012, 2012.
Le Hir, G., Donnadieu, Y., Yves Goddéris, Y., Pierrehumbert, R. T., Halverson, G. T., Macouin, M., Nédélec, A., and Ramstein, G.: The snowball Earth aftermath: exploring the limits of continental weathering processes, Earth Planet. Sc. Lett., 277, 453–463, https://doi.org/10.1016/j.epsl.2008.11.010, 2009.
Lewis, E. and Wallace, D.: Program Developed for CO2 System Calculations, Tech. Rep. 105, Carbon Dioxide Analysis Center, Oak Ridge National Laboratory, Oak Ridge (TN), 1998.
Luff, R., Haeckel, M., and Wallmann, K.: Robust and fast FORTRAN and MATLAB libraries to calculate pH distributions in marine systems, Comput. Geosci., 27, 157–169, 2001.
Maier-Reimer, E.: Geochemical cycles in an Ocean General Circulation Model. Preindustrial tracer distributions, Global Biogeochem. Cy., 7, 645–677, 1993.
Maier-Reimer, E. and Hasselmann, K.: Transport and storage of CO2 in the ocean – an inorganic ocean-circulation carbon cycle model, Clim. Dynam., 2, 63–90, 1987.
Maier-Reimer, E., Kriest, I., Segschneider, J., and Wetzel, P.: The HAM}burg Ocean Carbon Cycle Model {HAMOCC 5.1 – Technical Description Release 1.1, Berichte zur Erdsystemforschung, Reports on Earth System Science 14, Max-Planck-Institut für Meteorologie, Hamburg, Germany, 2005.
Marchal, O., Stocker, T. F., and Joos, F.: A latitude-depth, circulation-biogeochemical ocean model for paleoclimate studies. Development and sensitivities, Tellus B, 50, 290–316, https://doi.org/10.1034/j.1600-0889.1998.t01-2-00006.x, 1998.
Marion, G. M., Millero, F. J., Camões, M. F., Spitzer, P., Feistel, R., and Chen, C.-T. A.: pH of seawater, Mar. Chem., 126, 89–96, https://doi.org/10.1016/j.marchem.2011.04.002, 2011.
Millero, F. J. and Sohn, M. L.: Chemical Oceanography, CRC Press, Boca Raton, Florida, 531 pp., 1992.
Millero, F. J., Feistel, R., Wright, D. G., and McDougall, T. J.: The composition of standard seawater and the definition of the reference-composition salinity scale, Deep-Sea Res. Pt. I, 55, 50–72, https://doi.org/10.1016/j.dsr.2007.10.001, 2008.
Millero, F. J., Woosley, R., DiTrolio, B., and Waters, J.: Effect of ocean acidification on the speciation of metals in seawater, Oceanography, 22, 72–85, https://doi.org/10.5670/oceanog.2009.98, 2009.
Müller, S. A., Joos, F., Plattner, G.-K., Edwards, N. R., and Stocker, T. F.: Modeled natural and excess radiocarbon: sensitivities to the gas exchange formulation and ocean transport strength, Global Biogeochem. Cy., 22, GB3011, https://doi.org/10.1029/2007GB003065, 2008.
Munhoven, G.: Modelling Glacial-Interglacial Atmospheric CO2 Variations: The Role of Continental Weathering, Ph.D. thesis, Université de Liège, Liège, available at: http://www.astro.ulg.ac.be/ munhoven/en/PhDThesis.pdf (last access: 21 February 2013), 1997.
Munhoven, G.: Glacial-interglacial rain ratio changes: implications for atmospheric CO2 and ocean-sediment interaction, Deep-Sea Res. Pt. II, 54, 722–746, https://doi.org/10.1016/j.dsr2.2007.01.008, 2007.
Munhoven, G.: Future CCD and CSH variations: deep-sea impact of ocean acidification, Geochim. Cosmochim. Ac., 73, p. A917, 2009.
Munhoven, G. and Fran\c cois, L. M.: Glacial-interglacial variability of atmospheric CO2 due to changing continental silicate rock weathering: a model study, J. Geophys. Res., 101, 21423–21437, https://doi.org/10.1029/96JD01842, 1996.
Opdyke, B. N. and Walker, J. C. G.: Return of the coral reef hypothesis: basin to shelf partitioning of CaCO3 and its effect on atmospheric CO2, Geology, 20, 733–736, 1992.
Orr, J., Najjar, R., Sabine, C., and Joos, F.: Abiotic-HOWTO, available at: http://ocmip5.ipsl.jussieu.fr/OCMIP/phase2/simulations/Abiotic/HOWTO-Abiotic.html, last access: 20 July 2012, 2000.
Palmer, J. R. and Totterdell, I. J.: Production and export in a global ocean ecosystem model, Deep-Sea Res. Pt. I, 48, 1169–1198, https://doi.org/10.1016/S0967-0637(00)00080-7, 2001.
Park, P. K.: Oceanic CO2 system: an evaluation of ten methods of investigation, Limnol. Oceanogr., 14, 179–186, 1969.
Peng, T.-H., Takahashi, T., Broecker, W. S., and Olafsson, J.: Seasonal variability of carbon dioxide, nutrients and oxygen in the northern North Atlantic surface water: observations and a model, Tellus B, 39, 439–458, 1987.
Press, W. H., Flannery, B. P., Teukolsky, S. A., and Vetterling, W. T.: Numerical Recipes (FORTRAN Version), Cambridge University Press, Cambridge, 1989.
Ridgwell, A. J.: Glacial-Interglacial Pertubations of the Global Carbon Cycle, Ph.D. thesis, University of East Anglia, Norwich, 2001.
Ridgwell, A. and Schmidt, D. N.: Past constraints on the vulnerability of marine calcifiers to massive carbon dioxide release, Nat. Geosci., 3, 196–200, https://doi.org/10.1038/ngeo755, 2010.
Ridgwell, A., Hargreaves, J. C., Edwards, N. R., Annan, J. D., Lenton, T. M., Marsh, R., Yool, A., and Watson, A.: Marine geochemical data assimilation in an efficient Earth System Model of global biogeochemical cycling, Biogeosciences, 4, 87–104, https://doi.org/10.5194/bg-4-87-2007, 2007.
Shaffer, G., Malskær Olsen, S., and Pepke Pedersen, J. O.: Presentation, calibration and validation of the low-order, DCESS Earth System Model (Version 1), Geosci. Model Dev., 1, 17–51, https://doi.org/10.5194/gmd-1-17-2008, 2008.
Walker, J. C. G. and Opdyke, B. N.: Influence of variable rates of neritic carbonate deposition on atmospheric carbon dioxide and pelagic sediments, Paleoceanography, 10, 415–427, 1995.
Waters, J. F. and Millero, F. J.: The free proton concentration scale for seawater pH, Mar. Chem., 149, 8–22, https://doi.org/10.1016/j.marchem.2012.11.003, 2013.
Wolf-Gladrow, D. A., Zeebe, R. E., Klaas, C., Körtzinger, A., and Dickson, A. G.: Total alkalinity: the explicit conservative expression and its application to biogeochemical processes, Mar. Chem., 106, 287–300, https://doi.org/10.1016/j.marchem.2007.01.006, 2007.
Yao, W. and Millero, F. J.: The chemistry of the anoxic waters in the Framvaren Fjord, Norway, Aquat. Geochem., 1, 53–88, 1995.
Zeebe, R. E.: LOSCAR: Long-term Ocean-atmosphere-Sediment CArbon cycle Reservoir Model v2.0.4, Geosci. Model Dev., 5, 149–166, https://doi.org/10.5194/gmd-5-149-2012, 2012.
Zeebe, R. E. and Wolf-Gladrow, D.: CO2 in seawater: equilibrium, kinetics, isotopes, vol. 65 of Elsevier Oceanography Series, Elsevier, Amsterdam (NL), 2001.
