Articles | Volume 15, issue 23
https://doi.org/10.5194/gmd-15-8749-2022
© Author(s) 2022. 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-15-8749-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model evaluation paper
| 
02 Dec 2022
Model evaluation paper |
| 02 Dec 2022
| 02 Dec 2022
ISMIP-HOM benchmark experiments using Underworld
Department of Geosciences, Eberhard Karls University
Tübingen, Tübingen, Germany
Haibin Yang
Research School of Earth Sciences, Australian National University,
Canberra, Australia
Justin Lang
Department of Geosciences, Eberhard Karls University
Tübingen, Tübingen, Germany
Paul D. Bons
Department of Geosciences, Eberhard Karls University
Tübingen, Tübingen, Germany
School of Earth Science and Resources, China University of
Geosciences, Beijing, China
Louis Moresi
Research School of Earth Sciences, Australian National University,
Canberra, Australia
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Paul D. Bons, Tamara de Riese, Steven Franke, Maria-Gema Llorens, Till Sachau, Nicolas Stoll, Ilka Weikusat, Julien Westhoff, and Yu Zhang
The Cryosphere, 15, 2251–2254, https://doi.org/10.5194/tc-15-2251-2021, https://doi.org/10.5194/tc-15-2251-2021, 2021
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The modelling of Smith-Johnson et al. (The Cryosphere, 14, 841–854, 2020) suggests that a very large heat flux of more than 10 times the usual geothermal heat flux is required to have initiated or to control the huge Northeast Greenland Ice Stream. Our comparison with known hotspots, such as Iceland and Yellowstone, shows that such an exceptional heat flux would be unique in the world and is incompatible with known geological processes that can raise the heat flux.
T. Sachau and D. Koehn
Geosci. Model Dev., 7, 243–247, https://doi.org/10.5194/gmd-7-243-2014, https://doi.org/10.5194/gmd-7-243-2014, 2014
Nicolas Stoll, Ilka Weikusat, Daniela Jansen, Paul Bons, Kyra Darányi, Julien Westhoff, Mária-Gema Llorens, David Wallis, Jan Eichler, Tomotaka Saruya, Tomoyuki Homma, Martyn Drury, Frank Wilhelms, Sepp Kipfstuhl, Dorthe Dahl-Jensen, and Johanna Kerch
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A better understanding of ice flow requires more observational data. The EastGRIP core is the first ice core through an active ice stream. We discuss crystal orientation data to determine the present deformation regimes. A comparison with other deep ice cores shows the unique properties of EastGRIP and that deep ice originates from the Eemian. We further show that the overall plug flow of NEGIS is characterised by many small-scale variations, which remain to be considered in ice-flow models.
Steven Franke, Daniel Steinhage, Veit Helm, Alexandra M. Zuhr, Julien A. Bodart, Olaf Eisen, and Paul Bons
EGUsphere, https://doi.org/10.5194/egusphere-2024-2349, https://doi.org/10.5194/egusphere-2024-2349, 2024
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We use radar technology to study the internal architecture of the ice sheet in western DML, East Antarctica. We identified and dated nine internal reflection horizons (IRHs), revealing important information about the ice sheet's history and dynamics. Some IRHs can be linked to past volcanic eruptions and are of similar age to IRHs detected in other parts of Antarctica. Our findings enhance our understanding of ice sheet behaviour and aid in developing better models for predicting future changes.
Sara Polanco, Mike Blum, Tristan Salles, Bruce C. Frederick, Rebecca Farrington, Xuesong Ding, Ben Mather, Claire Mallard, and Louis Moresi
Earth Surf. Dynam., 12, 301–320, https://doi.org/10.5194/esurf-12-301-2024, https://doi.org/10.5194/esurf-12-301-2024, 2024
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Two-thirds of the world's most populated cities are situated close to deltas. We use computer simulations to understand how deltas sink or rise in response to climate-driven sea level changes that operate from thousands to millions of years. Our research shows that because of the interaction between the outer layers of the Earth, sediment transport, and sea level changes deltas develop a self-regulated mechanism that modifies the space they need to gain or lose land.
Maria-Gema Llorens, Albert Griera, Paul D. Bons, Ilka Weikusat, David J. Prior, Enrique Gomez-Rivas, Tamara de Riese, Ivone Jimenez-Munt, Daniel García-Castellanos, and Ricardo A. Lebensohn
The Cryosphere, 16, 2009–2024, https://doi.org/10.5194/tc-16-2009-2022, https://doi.org/10.5194/tc-16-2009-2022, 2022
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Polar ice is formed by ice crystals, which form fabrics that are utilised to interpret how ice sheets flow. It is unclear whether fabrics result from the current flow regime or if they are inherited. To understand the extent to which ice crystals can be reoriented when ice flow conditions change, we simulate and evaluate multi-stage ice flow scenarios according to natural cases. We find that second deformation regimes normally overprint inherited fabrics, with a range of transitional fabrics.
Paul D. Bons, Tamara de Riese, Steven Franke, Maria-Gema Llorens, Till Sachau, Nicolas Stoll, Ilka Weikusat, Julien Westhoff, and Yu Zhang
The Cryosphere, 15, 2251–2254, https://doi.org/10.5194/tc-15-2251-2021, https://doi.org/10.5194/tc-15-2251-2021, 2021
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The modelling of Smith-Johnson et al. (The Cryosphere, 14, 841–854, 2020) suggests that a very large heat flux of more than 10 times the usual geothermal heat flux is required to have initiated or to control the huge Northeast Greenland Ice Stream. Our comparison with known hotspots, such as Iceland and Yellowstone, shows that such an exceptional heat flux would be unique in the world and is incompatible with known geological processes that can raise the heat flux.
Dan Sandiford and Louis Moresi
Solid Earth, 10, 969–985, https://doi.org/10.5194/se-10-969-2019, https://doi.org/10.5194/se-10-969-2019, 2019
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This study investigates approaches to implementing plate boundaries within a fluid dynamic framework, targeted at the evolution of subduction over many millions of years.
Chao Qi, David J. Prior, Lisa Craw, Sheng Fan, Maria-Gema Llorens, Albert Griera, Marianne Negrini, Paul D. Bons, and David L. Goldsby
The Cryosphere, 13, 351–371, https://doi.org/10.5194/tc-13-351-2019, https://doi.org/10.5194/tc-13-351-2019, 2019
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Ice deformed in nature develops crystallographic preferred orientations, CPOs, which induce an anisotropy in ice viscosity. Shear experiments of ice revealed a transition in CPO with changing temperature/strain, which is due to the change of dominant CPO-formation mechanism: strain-induced grain boundary migration dominates at higher temperatures and lower strains, while lattice rotation dominates at other conditions. Understanding these mechanisms aids the interpretation of CPOs in natural ice.
Jodie Pall, Sabin Zahirovic, Sebastiano Doss, Rakib Hassan, Kara J. Matthews, John Cannon, Michael Gurnis, Louis Moresi, Adrian Lenardic, and R. Dietmar Müller
Clim. Past, 14, 857–870, https://doi.org/10.5194/cp-14-857-2018, https://doi.org/10.5194/cp-14-857-2018, 2018
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Subduction zones intersecting buried carbonate platforms liberate significant atmospheric CO2 and have the potential to influence global climate. We model the spatio-temporal distribution of carbonate platform accumulation within a plate tectonic framework and use wavelet analysis to analyse linked behaviour between atmospheric CO2 and carbonate-intersecting subduction zone (CISZ) lengths since the Devonian. We find that increasing CISZ lengths likely contributed to a warmer Palaeogene climate.
Florian Steinbach, Paul D. Bons, Albert Griera, Daniela Jansen, Maria-Gema Llorens, Jens Roessiger, and Ilka Weikusat
The Cryosphere, 10, 3071–3089, https://doi.org/10.5194/tc-10-3071-2016, https://doi.org/10.5194/tc-10-3071-2016, 2016
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How glaciers or ice sheets flow is a result of microscopic processes controlled by the properties of individual ice crystals. We performed computer simulations on these processes and the effect of air bubbles between crystals. The simulations show that small-scale ice deformation is locally stronger than in other regions, which is enhanced by bubbles. This causes the ice crystals to recrystallise and change their properties in a way that potentially also affects the large-scale flow properties.
D. Jansen, M.-G. Llorens, J. Westhoff, F. Steinbach, S. Kipfstuhl, P. D. Bons, A. Griera, and I. Weikusat
The Cryosphere, 10, 359–370, https://doi.org/10.5194/tc-10-359-2016, https://doi.org/10.5194/tc-10-359-2016, 2016
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In this study we present examples of typical small-scale folds observed in the NEEM ice core, North Greenland, and discuss their characteristics. Numerical modelling of viscoplastic deformation and dynamic recrystallisation was used to improve the understanding of the formation of the observed structures under simple shear boundary conditions. We conclude that the folds originate from bands of grains with a tilted lattice relative to the strong lattice preferred orientation below 1500 m depth.
Z. Zhao, P. D. Bons, G. Wang, A. Soesoo, and Y. Liu
Solid Earth, 6, 457–473, https://doi.org/10.5194/se-6-457-2015, https://doi.org/10.5194/se-6-457-2015, 2015
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The early Mesozoic tectonic history of the Qiangtang terrane in central Tibet is hotly debated. We argue that the north and south Qiangtang terranes were separated by an ocean (Paleo-Tethys) until the late Triassic. Subduction was mainly to the north, underneath the north Qiangtang terrane. The high-pressure rocks were exhumed in a lithospheric-scale core complex. Together with non-metamorphic sedimentary and ophiolitic mélange, these were finally thrust on top of the south Qiangtang.
T. Sachau and D. Koehn
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Niko Schmidt, Angelika Humbert, and Thomas Slawig
Geosci. Model Dev., 17, 4943–4959, https://doi.org/10.5194/gmd-17-4943-2024, https://doi.org/10.5194/gmd-17-4943-2024, 2024
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Jevgenijs Steinbuks, Yongyang Cai, Jonas Jaegermeyr, and Thomas W. Hertel
Geosci. Model Dev., 17, 4791–4819, https://doi.org/10.5194/gmd-17-4791-2024, https://doi.org/10.5194/gmd-17-4791-2024, 2024
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This paper applies a cutting-edge numerical method, SCEQ, to show how uncertain climate change and technological progress affect the future utilization of the world's scarce land resources. The paper's key insight is to illustrate how much global cropland will expand when future crop yields are unknown. The study finds the range of outcomes for land use change to be smaller when using this novel method compared to existing deterministic models.
Yuta Kawai and Hirofumi Tomita
EGUsphere, https://doi.org/10.5194/egusphere-2024-1477, https://doi.org/10.5194/egusphere-2024-1477, 2024
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When considering future high-resolution atmospheric simulations with O(10–100 m) grid spacing, such as global large-eddy simulations, numerical errors with the conventional low-order dynamical cores can contaminate the effects of turbulent parameterization. To achieve high-order discretization, we developed a global atmospheric dynamical core using the discontinuous Galerkin method (DGM). By conducting several validation tests, we discussed the impact of high-order DGM on the atmospheric flows.
Chayan Banerjee, Kien Nguyen, Clinton Fookes, Gregory Hancock, and Thomas Coulthard
EGUsphere, https://doi.org/10.5194/egusphere-2024-1191, https://doi.org/10.5194/egusphere-2024-1191, 2024
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In geosciences, the reliance on numerical models necessitates the precise calibration of their parameters to effectively translate information from observed to unobserved settings. We introduce a generalizable framework for calibrating numerical models, with a case study of the geomorphological model CAESAR-Lisflood. This approach efficiently identifies the optimal set of parameters for a given numerical model, enabling retrospective and prospective analyses at various temporal resolutions.
Gianandrea Mannarini, Mario Leonardo Salinas, Lorenzo Carelli, Nicola Petacco, and Josip Orović
Geosci. Model Dev., 17, 4355–4382, https://doi.org/10.5194/gmd-17-4355-2024, https://doi.org/10.5194/gmd-17-4355-2024, 2024
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Ship weather routing has the potential to reduce CO2 emissions, but it currently lacks open and verifiable research. The Python-refactored VISIR-2 model considers currents, waves, and wind to optimise routes. The model was validated, and its computational performance is quasi-linear. For a ferry sailing in the Mediterranean Sea, VISIR-2 yields the largest percentage emission savings for upwind navigation. Given the vessel performance curve, the model is generalisable across various vessel types.
Soyoung Ha, Jonathan J. Guerrette, Ivette Hernández Baños, William C. Skamarock, and Michael G. Duda
Geosci. Model Dev., 17, 4199–4211, https://doi.org/10.5194/gmd-17-4199-2024, https://doi.org/10.5194/gmd-17-4199-2024, 2024
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To mitigate the imbalances in the initial conditions, this study introduces our recent implementation of the incremental analysis update (IAU) in the Model for Prediction Across Scales – Atmospheric (MPAS-A) component coupled with the Joint Effort for Data assimilation Integration (JEDI) through the cycling system. A month-long cycling run demonstrates the successful implementation of the IAU capability in the MPAS–JEDI cycling system.
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., 17, 4031–4052, https://doi.org/10.5194/gmd-17-4031-2024, https://doi.org/10.5194/gmd-17-4031-2024, 2024
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We introduce SolFinder 1.0, a decision-making tool to select trade-offs between different objective functions for optimal aircraft trajectories, including fuel use, flight time, NOx emissions, contrail distance, and climate impact. The module is included in the AirTraf 3.0 submodel and uses weather conditions simulated by the EMAC atmospheric model. This paper focuses on the ability of SolFinder to identify eco-efficient trajectories, reducing a flight's climate impact at limited cost penalties.
Ali Dashti, Jens C. Grimmer, Christophe Geuzaine, Florian Bauer, and Thomas Kohl
Geosci. Model Dev., 17, 3467–3485, https://doi.org/10.5194/gmd-17-3467-2024, https://doi.org/10.5194/gmd-17-3467-2024, 2024
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This study developed new meshing workflows to enable the automatic generation of meshes that follow geological models. The workflow allows for importing several geological models as input for Gmsh and later exporting the same number of high-quality meshes. This way, geological uncertainty is directly included in the numerical simulations. This study evaluates the impact of the geological uncertainty on thermohydraulic performance of two reservoirs for high-temperature heat storage applications.
Wangbin Shen, Zhaohui Lin, Zhengkun Qin, and Juan Li
Geosci. Model Dev., 17, 3447–3465, https://doi.org/10.5194/gmd-17-3447-2024, https://doi.org/10.5194/gmd-17-3447-2024, 2024
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In this study, a land surface image assimilation system capable of optimizing the spatial structure of the background field is constructed by introducing the curvelet analysis method and taking the similarity of image structure as a weak constraint. The findings demonstrate that the assimilation of surface soil moisture observation images effectively and reasonably enhances the spatial structure of soil moisture analysis field.
Luan Carlos de Sena Monteiro Ozelim, Michéle Dal Toé Casagrande, and André Luís Brasil Cavalcante
Geosci. Model Dev., 17, 3175–3197, https://doi.org/10.5194/gmd-17-3175-2024, https://doi.org/10.5194/gmd-17-3175-2024, 2024
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The paper addresses synthetic dataset challenges in nonlinear constitutive modeling of soils, providing two datasets: one with 2000 soil types, 40 test conditions each (160 000 triaxial tests), and a second with 2048 soil types, 42 test conditions each (172 032 triaxial tests). Each dataset is a 4000×10 matrix applicable for multivariate forecasting and geotechnical simulations. In addition, a new Python code is introduced, empowering researchers to leverage Python packages for NorSand analyses.
Daniel Giles, Matthew M. Graham, Mosè Giordano, Tuomas Koskela, Alexandros Beskos, and Serge Guillas
Geosci. Model Dev., 17, 2427–2445, https://doi.org/10.5194/gmd-17-2427-2024, https://doi.org/10.5194/gmd-17-2427-2024, 2024
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Digital twins of physical and human systems informed by real-time data are becoming ubiquitous across a wide range of settings. Progress for researchers is currently limited by a lack of tools to run these models effectively and efficiently. A key challenge is the optimal use of high-performance computing environments. The work presented here focuses on a developed open-source software platform which aims to improve this usage, with an emphasis placed on flexibility, efficiency, and scalability.
Stefan J. Miller, Paul A. Makar, and Colin J. Lee
Geosci. Model Dev., 17, 2197–2219, https://doi.org/10.5194/gmd-17-2197-2024, https://doi.org/10.5194/gmd-17-2197-2024, 2024
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This work outlines a new solver written in Fortran to calculate the partitioning of metastable aerosols at thermodynamic equilibrium based on the forward algorithms of ISORROPIA II. The new code includes numerical improvements that decrease the computational speed (compared to ISORROPIA II) while improving the accuracy of the partitioning solution.
Fernanda Alvarado-Neves, Laurent Ailleres, Lachlan Grose, Alexander R. Cruden, and Robin Armit
Geosci. Model Dev., 17, 1975–1993, https://doi.org/10.5194/gmd-17-1975-2024, https://doi.org/10.5194/gmd-17-1975-2024, 2024
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Previous work has demonstrated that adding geological knowledge to modelling methods creates more accurate and reliable models. Following this reasoning, we added constraints from magma emplacement mechanisms into existing modelling frameworks to improve the 3D characterisation of igneous intrusions. We tested the method on synthetic and real-world case studies, and the results show that our method can reproduce intrusion morphologies with no manual processing and using realistic datasets.
André R. Brodtkorb, Anna Benedictow, Heiko Klein, Arve Kylling, Agnes Nyiri, Alvaro Valdebenito, Espen Sollum, and Nina Kristiansen
Geosci. Model Dev., 17, 1957–1974, https://doi.org/10.5194/gmd-17-1957-2024, https://doi.org/10.5194/gmd-17-1957-2024, 2024
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It is vital to know the extent and concentration of volcanic ash in the atmosphere during a volcanic eruption. Whilst satellite imagery may give an estimate of the ash right now (assuming no cloud coverage), we also need to know where it will be in the coming hours. This paper presents a method for estimating parameters for a volcanic eruption based on satellite observations of ash in the atmosphere. The software package is open source and applicable to similar inversion scenarios.
Kees Nederhoff, Maarten van Ormondt, Jay Veeramony, Ap van Dongeren, José Antonio Álvarez Antolínez, Tim Leijnse, and Dano Roelvink
Geosci. Model Dev., 17, 1789–1811, https://doi.org/10.5194/gmd-17-1789-2024, https://doi.org/10.5194/gmd-17-1789-2024, 2024
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Forecasting tropical cyclones and their flooding impact is challenging. Our research introduces the Tropical Cyclone Forecasting Framework (TC-FF), enhancing cyclone predictions despite uncertainties. TC-FF generates global wind and flood scenarios, valuable even in data-limited regions. Applied to cases like Cyclone Idai, it showcases potential in bettering disaster preparation, marking progress in handling cyclone threats.
Younghun Kang and Ethan J. Kubatko
Geosci. Model Dev., 17, 1603–1625, https://doi.org/10.5194/gmd-17-1603-2024, https://doi.org/10.5194/gmd-17-1603-2024, 2024
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Models used to simulate the flow of coastal and riverine waters, including flooding, require a geometric representation (or mesh) of geographic features that exhibit a range of disparate spatial scales from large, open waters to small, narrow channels. Representing these features in an accurate way without excessive computational overhead presents a challenge. Here, we develop an automatic mesh generation tool to help address this challenge. Our results demonstrate the efficacy of our approach.
Hui Wan, Kai Zhang, Christopher J. Vogl, Carol S. Woodward, Richard C. Easter, Philip J. Rasch, Yan Feng, and Hailong Wang
Geosci. Model Dev., 17, 1387–1407, https://doi.org/10.5194/gmd-17-1387-2024, https://doi.org/10.5194/gmd-17-1387-2024, 2024
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Sophisticated numerical models of the Earth's atmosphere include representations of many physical and chemical processes. In numerical simulations, these processes need to be calculated in a certain sequence. This study reveals the weaknesses of the sequence of calculations used for aerosol processes in a global atmosphere model. A revision of the sequence is proposed and its impacts on the simulated global aerosol climatology are evaluated.
Christopher J. Vogl, Hui Wan, Carol S. Woodward, and Quan M. Bui
Geosci. Model Dev., 17, 1409–1428, https://doi.org/10.5194/gmd-17-1409-2024, https://doi.org/10.5194/gmd-17-1409-2024, 2024
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Generally speaking, accurate climate simulation requires an accurate evolution of the underlying mathematical equations on large computers. The equations are typically formulated and evolved in process groups. Process coupling refers to how the evolution of each group is combined with that of other groups to evolve the full set of equations for the whole atmosphere. This work presents a mathematical framework to evaluate methods without the need to first implement the methods.
Tom Keel, Chris Brierley, and Tamsin Edwards
Geosci. Model Dev., 17, 1229–1247, https://doi.org/10.5194/gmd-17-1229-2024, https://doi.org/10.5194/gmd-17-1229-2024, 2024
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Jet streams are an important control on surface weather as their speed and shape can modify the properties of weather systems. Establishing trends in the operation of jet streams may provide some indication of the future of weather in a warming world. Despite this, it has not been easy to establish trends, as many methods have been used to characterise them in data. We introduce a tool containing various implementations of jet stream statistics and algorithms that works in a standardised manner.
Amir Golparvar, Matthias Kästner, and Martin Thullner
Geosci. Model Dev., 17, 881–898, https://doi.org/10.5194/gmd-17-881-2024, https://doi.org/10.5194/gmd-17-881-2024, 2024
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Coupled reaction transport modelling is an established and beneficial method for studying natural and synthetic porous material, with applications ranging from industrial processes to natural decompositions in terrestrial environments. Up to now, a framework that explicitly considers the porous structure (e.g. from µ-CT images) for modelling the transport of reactive species is missing. We presented a model that overcomes this limitation and represents a novel numerical simulation toolbox.
Stefan Hergarten
Geosci. Model Dev., 17, 781–794, https://doi.org/10.5194/gmd-17-781-2024, https://doi.org/10.5194/gmd-17-781-2024, 2024
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The Voellmy rheology has been widely used for simulating snow and rock avalanches. Recently, a modified version of this rheology was proposed, which turned out to be able to predict the observed long runout of large rock avalanches theoretically. The software MinVoellmy presented here is the first numerical implementation of the modified rheology. It consists of MATLAB and Python classes, where simplicity and parsimony were the design goals.
Arjun Babu Nellikkattil, Danielle Lemmon, Travis Allen O'Brien, June-Yi Lee, and Jung-Eun Chu
Geosci. Model Dev., 17, 301–320, https://doi.org/10.5194/gmd-17-301-2024, https://doi.org/10.5194/gmd-17-301-2024, 2024
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This study introduces a new computational framework called Scalable Feature Extraction and Tracking (SCAFET), designed to extract and track features in climate data. SCAFET stands out by using innovative shape-based metrics to identify features without relying on preconceived assumptions about the climate model or mean state. This approach allows more accurate comparisons between different models and scenarios.
Mohammad Mortezazadeh, Jean-François Cossette, Ashu Dastoor, Jean de Grandpré, Irena Ivanova, and Abdessamad Qaddouri
Geosci. Model Dev., 17, 335–346, https://doi.org/10.5194/gmd-17-335-2024, https://doi.org/10.5194/gmd-17-335-2024, 2024
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The interpolation process is the most computationally expensive step of the semi-Lagrangian (SL) approach. In this paper we implement a new interpolation scheme into the semi-Lagrangian approach which has the same computational cost as a third-order polynomial scheme but with the accuracy of a fourth-order interpolation scheme. This improvement is achieved by using two third-order backward and forward polynomial interpolation schemes in two consecutive time steps.
Boris Gailleton, Luca C. Malatesta, Guillaume Cordonnier, and Jean Braun
Geosci. Model Dev., 17, 71–90, https://doi.org/10.5194/gmd-17-71-2024, https://doi.org/10.5194/gmd-17-71-2024, 2024
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This contribution presents a new method to numerically explore the evolution of mountain ranges and surrounding areas. The method helps in monitoring with details on the timing and travel path of material eroded from the mountain ranges. It is particularly well suited to studies juxtaposing different domains – lakes or multiple rock types, for example – and enables the combination of different processes.
Denise Degen, Daniel Caviedes Voullième, Susanne Buiter, Harrie-Jan Hendricks Franssen, Harry Vereecken, Ana González-Nicolás, and Florian Wellmann
Geosci. Model Dev., 16, 7375–7409, https://doi.org/10.5194/gmd-16-7375-2023, https://doi.org/10.5194/gmd-16-7375-2023, 2023
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In geosciences, we often use simulations based on physical laws. These simulations can be computationally expensive, which is a problem if simulations must be performed many times (e.g., to add error bounds). We show how a novel machine learning method helps to reduce simulation time. In comparison to other approaches, which typically only look at the output of a simulation, the method considers physical laws in the simulation itself. The method provides reliable results faster than standard.
Carlos Spa, Otilio Rojas, and Josep de la Puente
Geosci. Model Dev., 16, 7237–7252, https://doi.org/10.5194/gmd-16-7237-2023, https://doi.org/10.5194/gmd-16-7237-2023, 2023
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This paper develops a calibration methodology of all absorbing techniques typically used by Fourier pseudo-spectral time-domain (PSTD) methods for geoacoustic wave simulations. The main contributions of the paper are (a) an implementation and quantitative comparison of all absorbing techniques available for PSTD methods through a simple and robust numerical experiment, and (b) a validation of these absorbing techniques in several 3-D seismic scenarios with gradual heterogeneity complexities.
Michael Hillier, Florian Wellmann, Eric A. de Kemp, Boyan Brodaric, Ernst Schetselaar, and Karine Bédard
Geosci. Model Dev., 16, 6987–7012, https://doi.org/10.5194/gmd-16-6987-2023, https://doi.org/10.5194/gmd-16-6987-2023, 2023
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Neural networks can be used effectively to model three-dimensional geological structures from point data, sampling geological interfaces, units, and structural orientations. Existing neural network approaches for this type of modelling are advanced by the efficient incorporation of unconformities, new knowledge inputs, and improved data fitting techniques. These advances permit the modelling of more complex geology in diverse geological settings, different-sized areas, and various data regimes.
Ane Lopez de Gamiz-Zearra, Cecilie Hansen, Xavier Corrales, Iñaki Quincoces, Izaskun Preciado, and Eider Andonegi
EGUsphere, https://doi.org/10.5194/egusphere-2023-1368, https://doi.org/10.5194/egusphere-2023-1368, 2023
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This paper describes the development of the first calibrated end-to-end Atlantis model for the Bay of Biscay that will help us improve the comprehension of the spatial functioning of the Bay of Biscay ecosystem and help establishing management measures of human activities. Our results highlighted the importance of lower trophic levels to the pelagic system and demonstrate the importance of having accurate and precise data for biological processes.
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.
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.
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.
Cited articles
Alley, R. B.: Fabrics in polar ice sheets: development and prediction,
Science, 240, 493–495, 1988
Azuma, N.: A flow law for anisotropic ice and its application to ice sheets,
Earth Planet. Sc. Lett., 128, 601–614,
https://doi.org/10.1016/0012-821X(94)90173-2, 1994.
Bahadori, A., Holt. W. E., Feng, R., Austermann, J., Loughney, K. M., Salles, T., Moresi, L., Beucher, R.,
Lu, N., Flesch, L. M., Calvelage, C. M., Rasbury, E. T. Davis, D. M., Potochnik, A. R., Ward, W. B., Hatton,
K., Haq, S. S. B., Smiley T. M., Wooton, K. M., and Badgley, C.: Coupled influence of tectonics,
climate, and surface processes on landscape evolution in southwestern North
America, Nat. Commun., 13, 4437, https://doi.org/10.1038/s41467-022-31903-2, 2022.
Beucher, R., Giordani, J., Moresi, L., Mansour, J., Kaluza, O., Velic, M., Farrington, R., Quenette, S., Beall, A., Sandiford, D., Mondy, L., Mallard, C., Rey, P., Duclaux, G., Laik, A., Morón, S., Beall, A., Knight, B., and Lu, N.: Underworld2: Python Geodynamics Modelling for Desktop, HPC and Cloud (v2.13.0b), Zenodo [code], https://doi.org/10.5281/zenodo.6820562, 2022a.
Beucher, R., Giordani, J., Moresi, L., Mansour, J., Kaluza, O., Velic, M., Farrington, R., Quenette, S., Beall, A., Sandiford, D., Mondy, L., Mallard, C., Rey, P., Duclaux, G., Laik, A., Morón, S., Beall, A., Knight, B., and Lu, N.: Underworld2: Python Geodynamics Modelling for Desktop, HPC and Cloud (v2.13.0b), Zenodo [code], https://doi.org/10.5281/zenodo.6820562, 2022b.
Blatter, H., Clarke, G., and Colinge, J.: Stress and velocity fields inglaciers: Part
II.sliding and basal stress distribution, J. Glaciol., 44, 457–466, 1998.
Bons, P. D., Jansen, D., Mundel, F., Bauer, C. C., Binder, T., Eisen, O.,
Jessell, M.-G., Llorens, M., Steinbach, F., Steinhage, D., and Weikusat, I.:
Converging flow and anisotropy cause large-scale folding in Greenland's ice
sheet, Nat. Commun., 7, 11427, https://doi.org/10.1038/ncomms11427,
2016.
Bons, P. D., Kleiner, T., Llorens, M.-G., Prior, D. J., Sachau, T.,
Weikusat, I., and Jansen, D.: Greenland Ice Sheet: Higher nonlinearity of ice
flow significantly reduces estimated basal motion, Geophys. Res.
Lett., 45, 6542–6548, https://doi.org/10.1029/2018GL078356, 2018.
Bons, P. D., de Riese, T., Franke, S., Llorens, M.-G., Sachau, T., Stoll, N., Weikusat, I., Westhoff, J., and Zhang, Y.: Comment on “Exceptionally high heat flux needed to sustain the Northeast Greenland Ice Stream” by Smith-Johnsen et al. (2020), The Cryosphere, 15, 2251–2254, https://doi.org/10.5194/tc-15-2251-2021, 2021.
Budd, W. and Jacka, T.: A review of ice rheology for ice sheet modelling,
Cold Reg. Sci. Technol., 16, 107–144, 1989.
Capitanio, F. A., Nebel, O., Cawood, P. A., Weinberg, R. F., and Clos, F.:
Lithosphere differentiation in the early Earth controls Archean tectonics,
Earth Planet. Sc. Lett., 525, 115755,
https://doi.org/10.1016/j.epsl.2019.115755, 2019.
Carluccio, R., Kaus, B., Capitanio, F. A., and Moresi, L. N.: The Impact of a
Very Weak and Thin Upper Asthenosphere on Subduction Motions, Geophys. Res.
Lett., 46, 11893–11905, https://doi.org/10.1029/2019GL085212, 2019.
Cavitte, M. G. P., Blankenship, D. D., Young, D. A., Schroeder, D. M.,
Parrenin, F., Lemeur, E., Macgregor, J. A., and Siegert, M. J.: Deep
radiostratigraphy of the East Antarctic plateau: connecting the Dome C and
Vostok ice core sites, J. Glaciol., 62, 323–334, https://doi.org/10.1017/jog.2016.11, 2016.
Duval, P., Ashby, M. F., and Anderman, I.: Rate-controlling processes in the
creep of polycrystalline ice, J. Phys. Chem., 87, 4066–4074,
https://doi.org/10.1021/j100244a014, 1983.
Ershadi, M. R., Drews, R., Martín, C., Eisen, O., Ritz, C., Corr, H., Christmann, J., Zeising, O., Humbert, A., and Mulvaney, R.: Polarimetric radar reveals the spatial distribution of ice fabric at domes and divides in East Antarctica, The Cryosphere, 16, 1719–1739, https://doi.org/10.5194/tc-16-1719-2022, 2022.
Evans, B. and Kohlstedt, D. L.: Rheology of Rocks, in: Rock Physics and
Phase Relations: a handbook of Physical Constants, Ref. Shelf, vol. 3, edited by:
Ahrens, T. J., 148–165, AGU, Washington D.C., 1995.
Farrington, R. J., Moresi, L. N., and Capitanio, F. A.: The role of
viscoelasticity in subducting plates, Geochem. Geophys. Geosyst.,
15, 4291–4304, 2014.
Gagliardini, O. and Zwinger, T.: The ISMIP-HOM benchmark experiments performed using the Finite-Element code Elmer, The Cryosphere, 2, 67–76, https://doi.org/10.5194/tc-2-67-2008, 2008.
Gagliardini, O., Zwinger, T., Gillet-Chaulet, F., Durand, G., Favier, L., de Fleurian, B., Greve, R., Malinen, M., Martín, C., Råback, P., Ruokolainen, J., Sacchettini, M., Schäfer, M., Seddik, H., and Thies, J.: Capabilities and performance of Elmer/Ice, a new-generation ice sheet model, Geosci. Model Dev., 6, 1299–1318, https://doi.org/10.5194/gmd-6-1299-2013, 2013.
Gillet-Chaulet, f., Gagliardini, O., Meyssonnier, J., Zwinger, T., and
Ruokolainen, J.: Flow-induced anisotropy in polar ice and related ice-sheet
flow modelling, J. Non-Newtonian Fluid Mech., 134, 33–43, 2006.
Glen, J. W.: The Creep of Polycrystalline Ice, P. Roy.
Soc. A, 228, 519–538, https://doi.org/10.1098/rspa.1955.0066, 1955.
Gödert, G.: A Mesoscopic Approach for Modelling Texture Evolution of Polar Ice
Including Recrystallization Phenomena, Ann. Glaciol., 37, 23–28,
https://doi.org/10.3189/172756403781815375, 2003.
Goelzer, H., Robinson, A., Seroussi, H., and van de Wal, R. S. W.:
Recent progress in Greenland Ice Sheet modelling, Current Climate Change
Reports, 3, 291–302, https://doi.org/10.1007/s40641-017-0073-y, 2017.
Goldsby, D. L.: Superplastic flow of ice relevant to glacier and ice-sheet
mechanics, in: Glacier Science and Environmental Change, edited by: Knight, P. G., Blackwell, Oxford,
308–314, https://doi.org/10.1002/9780470750636.ch60, 2006.
Goldsby, D. L. and Kohlstedt, D. L.: Superplastic deformation of ice:
Experimental observations, J. Geophys. Res., 106,
11017–11030, https://doi.org/10.1029/2000JB900336, 2001.
Haefeli, R.: Contribution to the movement and the form of ice sheets in the
Arctic and Antarctic, J. Glaciol., 3, 1133–1151, 1961.
Hindmarsh, R. C. A.: A numerical comparison of approximations to the Stokes
equations used in ice sheet and glacier modeling: HIGHER-ORDER GLACIER
MODELS, J. Geophys. Res.-Earth Surf., 109, F1, https://doi.org/10.1029/2003JF000065, 2004.
Hutter, K. (Ed.): Theoretical glaciology: material science of ice and the
mechanics of glaciers and ice sheets, D. Reidel Publishing Co., Dordrecht,
1983.
Johnson, J. V. and Staiger, J. W.: Modeling long-term stability of the
Ferrar Glacier, East Antarctica: Implications for interpreting cosmogenic
nuclide inheritance, J. Geophys. Res., 112, F03S30,
https://doi.org/10.1029/2006JF000599, 2007.
Kennedy, J. H., Pettit, E. C., and Di Prinzio, C. L.: The evolution of
crystal fabric in ice sheets and its link to climate history, J. Glaciol.,
59, 357–373, https://doi.org/10.3189/2013JoG12J159, 2013.
Korchinski, M., Rey, P. F., Mondy, L., Teyssier, C., and Whitney, D. L.:
Numerical investigation of deep-crust behavior under lithospheric extension,
Tectonophysics, 726, 137–146. https://doi.org/10.1016/j.tecto.2017.12.029,
2018.
Leysinger-Vieli, G. J.-M. C., Martín, C., Hindmarsh, R. C. A., and
Lüthi, M. P.: Basal freeze-on generates complex ice-sheet stratigraphy,
Nat. Commun., 9, 4669, https://doi.org/10.1038/s41467-018-07083-3, 2018.
Llorens, M.-G., Griera, A., Steinbach, F., Bons, P. D., Gomez-Rivas, E.,
Jansen, D., Roessiger, J., Lebensohn, R. A., and Weikusat, I.: Dynamic
recrystallization during deformation of polycrystalline ice: insights from
numerical simulations, Philos. T. R. Soc. Math. Phys. Eng. Sci., 375,
20150346, https://doi.org/10.1098/rsta.2015.0346, 2017.
MacGregor, J. A., Fahnestock, M. A., Catania, G. A., Paden, J. D., Prasad
Gogineni, S., Young, S. K., Rybarski, S. C., Mabrey, A. N., Wagman, B. M.,
and Morlighem, M.: Radiostratigraphy and age structure of the Greenland Ice
Sheet, J. Geophys. Res.-Earth Surf., 120, 212–241,
https://doi.org/10.1002/2014JF003215, 2015.
Mansour, J., Giordani, J., Moresi, L., Beucher, R., Kaluza, O., Velic, M.,
Farrington, R., Quenette, S., and Beall, A.: Underworld2: Python Geodynamics
Modelling for Desktop, HPC and Cloud, JOSS, 5, 1797,
https://doi.org/10.21105/joss.01797, 2020.
Mansour, J., Giordani, J., Moresi, L., Beucher, R., Kaluza, O., Velic, M., Farrington, R., Quenette, S., and Beall, A.: Underworld2: Python Geodynamics Modelling for Desktop, HPC and Cloud (v2.12.0b), Zenodo [code], https://doi.org/10.5281/zenodo.5935717, 2022.
Martín, C., Navarro, F., Otero, J., Cuadrado, M. L., and Corcuera, M.
I.: Three-dimensional modelling of the dynamics of Johnsons Glacier,
Livingston Island, Antarctica, Ann. Glaciol., 39, 1–8,
https://doi.org/10.3189/172756404781814537, 2004.
Martín, C., Gudmundsson, G. H., Pritchard, H. D., and Gagliardini, O.:
On the effects of anisotropic rheology on ice flow, internal structure, and
the age-depth relationship at ice divides, J. Geophys. Res., 114, F04001,
https://doi.org/10.1029/2008JF001204, 2009.
Mather, B., Müller, R.D., O'Neill, C., Beall, A., Vervoort, R. W., and
Moresi, L.: Constraining the response of continental-scale groundwater flow
to climate change, Sci. Rep.-UK, 12, 1–16, 2022.
McConnell, J. C. and Kidd, D. A.: On the plasticity of glacier and other
ice, P. Roy. Soc. London, 44, 331–367,
1888.
Moresi, L. and Mühlhaus, H. B.: Anisotropic viscous models of
large-deformation Mohr–Coulomb failure, Philosophical Magazine, 86,
3287–3305, 2006.
Moresi, L., Dufour, F., and Mühlhaus, H.-B.: A Lagrangian integration
point finite element method for large deformation modeling of viscoelastic
geomaterials, J. Comput. Phys., 184, 476–497,
https://doi.org/10.1016/S0021-9991(02)00031-1, 2003.
Moresi, L., Quenette, S., Lemiale, V., Meriaux, C., and Appelbe, B.:
Computational approaches to studying non-linear dynamics of the crust and
mantle, Phy. Earth Planet. Int., 15, 69–82, 2007.
Mühlhaus, H.-B., Moresi, L., Hobbs, B., and Dufour, F. D. R.: Large
Amplitude Folding in Finely Layered Viscoelastic Rock Structures, Pure Appl.
Geophys., 159, 23, https://doi.org/10.1007/s00024-002-8737-4, 2002.
Mühlhaus, H.-B., Moresi, L., and Cada, M.: Emergent Anisotropy and Flow
Alignment in Viscous Rock, Pure Appl. Geophys., 161, 2451–2463,
https://doi.org/10.1007/s00024-004-2575-5, 2004.
NEEM community members: Eemian interglacial reconstructed from a Greenland
folded ice core, Nature, 493, 489–494,
https://doi.org/10.1038/nature11789, 2013.
Nye, J. F.: The Flow Law of Ice from Measurements in Glacier Tunnels,
Laboratory Experiments and the Jungfraufirn Borehole Experiment, P. Roy. Soc. A,
219, 477–489, https://doi.org/10.1098/rspa.1953.0161, 1953.
Pattyn, F. and Payne, T.: Benchmark experiments for numerical Higher-Order
ice-sheet Models, https://frank.pattyn.web.ulb.be/ismip/welcome.html (last access: 30 May 2022),
2006.
Pattyn, F., Perichon, L., Aschwanden, A., Breuer, B., de Smedt, B., Gagliardini, O., Gudmundsson, G. H., Hindmarsh, R. C. A., Hubbard, A., Johnson, J. V., Kleiner, T., Konovalov, Y., Martin, C., Payne, A. J., Pollard, D., Price, S., Rückamp, M., Saito, F., Souček, O., Sugiyama, S., and Zwinger, T.: Benchmark experiments for higher-order and full-Stokes ice sheet models (ISMIP–HOM), The Cryosphere, 2, 95–108, https://doi.org/10.5194/tc-2-95-2008, 2008.
Ranalli, G.: Rheology of the Earth., 366 pp., Allen and Unwin, Concord,
Mass., 1987.
Ranganathan, M., Minchew, B., Meyer, C. R., and Peč, M.:
Recrystallization of ice enhances the creep and vulnerability to fracture of
ice shelves, Earth Planet. Sc. Lett., 576, 11721, https://doi.org/10.1016/j.epsl.2021.117219, 2021.
Rathmann, N. M. and Lilien, D. A.: Inferred basal friction and mass flux
affected by crystal-orientation fabrics, J. Glaciol., 68, 236–252,
https://doi.org/10.1017/jog.2021.88, 2022.
Richards, D. H. M., Pegler, S. S., Piazolo, S., and Harlen, O. G.: The
evolution of ice fabrics: A continuum modelling approach validated against
laboratory experiments, Earth Planet. Sci. Lett., 556, 116718,
https://doi.org/10.1016/j.epsl.2020.116718, 2021.
Salles, T., Ding, X., and Brocard, G.: pyBadlands: A framework to simulate
sediment transport, landscape dynamics and basin stratigraphic evolution
through space and time, edited by: Borazjani, I., PLoS ONE, 13, e0195557,
https://doi.org/10.1371/journal.pone.0195557, 2018.
Sandiford, D., Moresi, L. M., Sandiford, M., Farrington, R., and Yang, T.:
The Fingerprints of Flexure in Slab Seismicity, Tectonics, 39, e2019TC005894,
https://doi.org/10.1029/2019TC005894, 2020.
Schroeder, D. M., Bingham, R. G., Blankenship, D. D., Christianson, K.,
Eisen, O., Flowers, G. E., Karlsson, N. B., Koutnik, M. R., Paden, J. D., and
Siegert, M. J.: Five decades of radioglaciology, Ann. Glaciol., 61,
1–13, 2020.
Sharples, W., Moresi, L. N., Velic, M., Jadamec, M. A., and May, D. A.:
Simulating faults and plate boundaries with a transversely isotropic
plasticity model, Phys. Earth Planet. Int., 252, 77–90,
2016.
Smith-Johnsen, S., Schlegel, N.-J., Fleurian, B., and Nisancioglu, K. H.:
Sensitivity of the Northeast Greenland Ice Stream to Geothermal Heat, J.
Geophys. Res.-Earth Surf., 125, e2019JF005252, https://doi.org/10.1029/2019JF005252,
2020.
Sugiyama, S., Gudmundsson, G. H., and Helbing, J.: Numerical investigation of
the effects of temporal variations in basal lubrication on englacial
strain-rate distribution, Ann. Glaciol., 37, 49–54,
https://doi.org/10.3189/172756403781815618, 2003.
Sulsky, D., Chen, Z. and Schreyer, H. L.: A particle method for
history-dependent materials, Comput. Meth. Appl. Mech.
Eng., 118, 179–196,
https://doi.org/10.1016/0045-7825(94)90112-0, 1994.
Wolovick, M. J., Creyts, T. T., Buck, W. R., and Bell, R. E.: Traveling
slippery patches produce thickness-scale folds in ice sheets: Traveling
slippery patches, Geophys. Res. Lett., 41, 8895–8901,
https://doi.org/10.1002/2014GL062248, 2014.
Yang, H. and Giordani, J.: underworld-community/sachau-et-al-ice-sheet: v1.1 (v1.1), Zenodo [data set], https://doi.org/10.5281/zenodo.7384424, 2022.
Yang, H., Moresi, L. N., and Mansour, J.: Stress recovery for the
particle-in-cell finite element method, Phys. Earth Planet.
Int., 311, 106637, https://doi.org/10.1016/j.pepi.2020.106637, 2021.
Young, T. J., Schroeder, D. M., Jordan, T. M., Christoffersen, P., Tulaczyk,
S. M., Culberg, R., and Bienert, N. L.: Inferring ice fabric from
birefringence loss in airborne radargrams: Application to the eastern shear
margin of Thwaites Glacier, West Antarctica, J. Geophys.
Res.-Earth Surf., 126, e2020JF006023,
https://doi.org/10.1029/2020JF006023, 2021.
Short summary
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.
Knowledge of the internal structures of the major continental ice sheets is improving, thanks to...
