2D Versus 3D Numerical Simulations of Mantle Plume and Lithosphere Interaction: Quantitative Comparison and Scaling Analysis

25 pages, 14 pages, supporting information https://doi.org/10.1029/2025JB031510.-- Data Availability Statement: All the model results, data processing and plotting scripts relevant to this study have been deposited in the public repository of Zenodo at Zhang and Li (2025) (https://doi.org/10.5281/ze...

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Autores: Zhang, Rui‐Min, Li, Zhong‐Hai, Fu, Hui‐Ying, Leng, Wei, Shi, Ya‐Nan, Morgan, Jason P.
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2025
País:España
Institución:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/400820
Acceso en línea:http://hdl.handle.net/10261/400820
Access Level:acceso abierto
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network_name_str España
repository_id_str
dc.title.none.fl_str_mv 2D Versus 3D Numerical Simulations of Mantle Plume and Lithosphere Interaction: Quantitative Comparison and Scaling Analysis
title 2D Versus 3D Numerical Simulations of Mantle Plume and Lithosphere Interaction: Quantitative Comparison and Scaling Analysis
spellingShingle 2D Versus 3D Numerical Simulations of Mantle Plume and Lithosphere Interaction: Quantitative Comparison and Scaling Analysis
Zhang, Rui‐Min
title_short 2D Versus 3D Numerical Simulations of Mantle Plume and Lithosphere Interaction: Quantitative Comparison and Scaling Analysis
title_full 2D Versus 3D Numerical Simulations of Mantle Plume and Lithosphere Interaction: Quantitative Comparison and Scaling Analysis
title_fullStr 2D Versus 3D Numerical Simulations of Mantle Plume and Lithosphere Interaction: Quantitative Comparison and Scaling Analysis
title_full_unstemmed 2D Versus 3D Numerical Simulations of Mantle Plume and Lithosphere Interaction: Quantitative Comparison and Scaling Analysis
title_sort 2D Versus 3D Numerical Simulations of Mantle Plume and Lithosphere Interaction: Quantitative Comparison and Scaling Analysis
dc.creator.none.fl_str_mv Zhang, Rui‐Min
Li, Zhong‐Hai
Fu, Hui‐Ying
Leng, Wei
Shi, Ya‐Nan
Morgan, Jason P.
author Zhang, Rui‐Min
author_facet Zhang, Rui‐Min
Li, Zhong‐Hai
Fu, Hui‐Ying
Leng, Wei
Shi, Ya‐Nan
Morgan, Jason P.
author_role author
author2 Li, Zhong‐Hai
Fu, Hui‐Ying
Leng, Wei
Shi, Ya‐Nan
Morgan, Jason P.
author2_role author
author
author
author
author
dc.contributor.none.fl_str_mv Agencia Estatal de Investigación (España)
National Natural Science Foundation of China
Fundamental Research Funds for the Central Universities (China)
Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]
description 25 pages, 14 pages, supporting information https://doi.org/10.1029/2025JB031510.-- Data Availability Statement: All the model results, data processing and plotting scripts relevant to this study have been deposited in the public repository of Zenodo at Zhang and Li (2025) (https://doi.org/10.5281/zenodo.14969626). For visualizing the 3D model results, we utilized the open source software Paraview (Ahrens et al., 2005), which can be downloaded from https://www.paraview.org. Figures 2, 10 and 11a were crafted using Adobe Illustrator (https://www.adobe.com/products/illustrator.html). Figure 14 was generated with GMT6 (Wessel et al., 2019) obtained from https://www.generic-mapping-tools.org. The remaining figures were created and composed using Matplotlib (Hunter, 2007) from https://matplotlib.org, with scientific colormaps (Fabio Crameri et al., 2020) sourced from https://www.fabiocrameri.ch/colourmaps/. Curve fitting, optimization, special function calculations, and numerical integration were carried out using SciPy (Virtanen et al., 2020) from https://scipy.org. Array computations and data storage were managed by NumPy from https://numpy.org (Harris et al., 2020). The computer algebra software Wolfram Mathematica (https://www.wolfram.com/mathematica/) was employed to conduct the analytical solution of Equations 15a-16. The I2VIS code could be found in https://doi.org/10.17605/OSF.IO/bnvth (Gerya et al., 2021), and the I3VIS code, with all methods published in Gerya (2019), can be directly requested from the main code developer (taras.gerya@erdw.ethz.ch) or the corresponding author (li.zhonghai@ucas.ac.cn)
publishDate 2025
dc.date.none.fl_str_mv 2025
2025
2025
dc.type.none.fl_str_mv info:eu-repo/semantics/article
http://purl.org/coar/resource_type/c_6501
Publisher's version
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10261/400820
url http://hdl.handle.net/10261/400820
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv https://doi.org/10.1029/2025JB031510
Sí
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv American Geophysical Union
publisher.none.fl_str_mv American Geophysical Union
dc.source.none.fl_str_mv reponame:DIGITAL.CSIC. Repositorio Institucional del CSIC
instname:Consejo Superior de Investigaciones Científicas (CSIC)
instname_str Consejo Superior de Investigaciones Científicas (CSIC)
reponame_str DIGITAL.CSIC. Repositorio Institucional del CSIC
collection DIGITAL.CSIC. Repositorio Institucional del CSIC
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spelling 2D Versus 3D Numerical Simulations of Mantle Plume and Lithosphere Interaction: Quantitative Comparison and Scaling AnalysisZhang, Rui‐MinLi, Zhong‐HaiFu, Hui‐YingLeng, WeiShi, Ya‐NanMorgan, Jason P.25 pages, 14 pages, supporting information https://doi.org/10.1029/2025JB031510.-- Data Availability Statement: All the model results, data processing and plotting scripts relevant to this study have been deposited in the public repository of Zenodo at Zhang and Li (2025) (https://doi.org/10.5281/zenodo.14969626). For visualizing the 3D model results, we utilized the open source software Paraview (Ahrens et al., 2005), which can be downloaded from https://www.paraview.org. Figures 2, 10 and 11a were crafted using Adobe Illustrator (https://www.adobe.com/products/illustrator.html). Figure 14 was generated with GMT6 (Wessel et al., 2019) obtained from https://www.generic-mapping-tools.org. The remaining figures were created and composed using Matplotlib (Hunter, 2007) from https://matplotlib.org, with scientific colormaps (Fabio Crameri et al., 2020) sourced from https://www.fabiocrameri.ch/colourmaps/. Curve fitting, optimization, special function calculations, and numerical integration were carried out using SciPy (Virtanen et al., 2020) from https://scipy.org. Array computations and data storage were managed by NumPy from https://numpy.org (Harris et al., 2020). The computer algebra software Wolfram Mathematica (https://www.wolfram.com/mathematica/) was employed to conduct the analytical solution of Equations 15a-16. The I2VIS code could be found in https://doi.org/10.17605/OSF.IO/bnvth (Gerya et al., 2021), and the I3VIS code, with all methods published in Gerya (2019), can be directly requested from the main code developer (taras.gerya@erdw.ethz.ch) or the corresponding author (li.zhonghai@ucas.ac.cn)Mantle plumes are a key phenomenon in geodynamics, connecting the deep Earth interior with surficial tectonic plates. Numerical simulations are essential for studying plume dynamics and their interactions with overlying lithosphere. While 3D models could better capture the geometric features of plumes, 2D simulations offer superior computational efficiency in large-scale and high-resolution scenarios, particularly when rheologically complex geological processes are involved. Thus, both 2D and 3D models have been widely applied in previous numerical studies. However, due to geometric effects, they may yield different results for the same parameters; we need to know how to build the proper scaling relationship between 2D and 3D models. Here, we systematically compare the 2D versus 3D mantle plume in two different regimes. In the first regime with only a plume head, the 2D plume should have a smaller diameter (65%–100% of the 3D value) and lower temperature (reduced by 0–60 K relative to the 3D case) to best match 3D model result. In the second regime with a continuous plume tail, a much smaller diameter (30%–45%) but counter-intuitively higher temperature (increased by 20–100 K) are needed for the 2D model to best approximate 3D result. Further analytical studies indicate that such discrepancies are mainly controlled by the conservations of area (2D) versus volume (3D) of plume materials. These numerical and analytical results provide quantitative relationships between 2D and 3D plume models, which act as a theoretical reference for interpretation of previous models as well as guidance for future studiesThis work was supported by NSFC projects (42225403, 42241117) and the National Key R&D Program of China (2022YFF0801001), as well as the Fundamental Research Funds for the Central UniversitiesThis work contributes to the Institut de Ciències del Mar "Severo Ochoa Centre of Excellence" accreditation CEX2024-001494-S funded by AEI 10.13039/501100011033 of the Spanish Ministry of Science and InnovationPeer reviewedAmerican Geophysical UnionAgencia Estatal de Investigación (España)National Natural Science Foundation of ChinaFundamental Research Funds for the Central Universities (China)Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]202520252025info:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_6501Publisher's versioninfo:eu-repo/semantics/publishedVersionhttp://hdl.handle.net/10261/400820reponame:DIGITAL.CSIC. Repositorio Institucional del CSICinstname:Consejo Superior de Investigaciones Científicas (CSIC)Ingléshttps://doi.org/10.1029/2025JB031510Síinfo:eu-repo/semantics/openAccessoai:digital.csic.es:10261/4008202026-05-22T06:33:51Z
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