A Bibliometric Analysis of Convection-Permitting Model Research
Convection-permitting models (CPMs) are receiving growing scientific interest for their capability to accurately simulate extreme weather events at a kilometer-scale spatial resolution, offering valuable information for local climate change adaptation. This study employs both qualitative and quantit...
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MDPI AG
2024-11-01
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| Series: | Atmosphere |
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| Online Access: | https://www.mdpi.com/2073-4433/15/12/1417 |
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| author | Xiaozan Lyu Tianqi Ruan Xiaojing Cai |
| author_facet | Xiaozan Lyu Tianqi Ruan Xiaojing Cai |
| author_sort | Xiaozan Lyu |
| collection | DOAJ |
| description | Convection-permitting models (CPMs) are receiving growing scientific interest for their capability to accurately simulate extreme weather events at a kilometer-scale spatial resolution, offering valuable information for local climate change adaptation. This study employs both qualitative and quantitative bibliometric analysis techniques to examine research trends in CPM, utilizing data from 3508 articles published between 2000 and 2023. The annual number of publications exhibits a linear increase, rising from fewer than 50 in 2000 to over 250 after 2020, with the majority of research originating from the US, China, the UK, and Germany. The most productive institutes include the National Oceanic Atmospheric Administration (NOAA) and the National Center for Atmospheric Research (NCAR) in the US, each contributing over 10% of total publications. Title and abstract terms in publications related to keywords such as “scenario”, “climate simulation”, etc., dominate publications from 2018 to 2023, coinciding with advances in computing power. Notably, terms associated with CPM physical processes received the highest citations from 2000 to 2023, underscoring the importance of such these research topics. Given the computational expense of running CPMs and the increasing demand for future predictions using CPMs, novel methods for generating long-term simulations are imperative. |
| format | Article |
| id | doaj-art-ce213ef829094753afc331b53005db0e |
| institution | DOAJ |
| issn | 2073-4433 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Atmosphere |
| spelling | doaj-art-ce213ef829094753afc331b53005db0e2025-08-20T02:55:54ZengMDPI AGAtmosphere2073-44332024-11-011512141710.3390/atmos15121417A Bibliometric Analysis of Convection-Permitting Model ResearchXiaozan Lyu0Tianqi Ruan1Xiaojing Cai2Department of Administrative Management, School of Law, Hangzhou City University, Hangzhou 310015, ChinaDepartment of Energy Technology, KTH Royal Institute of Technology, 100 44 Stockholm, SwedenResearch Center for Government Governance and Public Policy, School of Business, Yangzhou University, Yangzhou 225127, ChinaConvection-permitting models (CPMs) are receiving growing scientific interest for their capability to accurately simulate extreme weather events at a kilometer-scale spatial resolution, offering valuable information for local climate change adaptation. This study employs both qualitative and quantitative bibliometric analysis techniques to examine research trends in CPM, utilizing data from 3508 articles published between 2000 and 2023. The annual number of publications exhibits a linear increase, rising from fewer than 50 in 2000 to over 250 after 2020, with the majority of research originating from the US, China, the UK, and Germany. The most productive institutes include the National Oceanic Atmospheric Administration (NOAA) and the National Center for Atmospheric Research (NCAR) in the US, each contributing over 10% of total publications. Title and abstract terms in publications related to keywords such as “scenario”, “climate simulation”, etc., dominate publications from 2018 to 2023, coinciding with advances in computing power. Notably, terms associated with CPM physical processes received the highest citations from 2000 to 2023, underscoring the importance of such these research topics. Given the computational expense of running CPMs and the increasing demand for future predictions using CPMs, novel methods for generating long-term simulations are imperative.https://www.mdpi.com/2073-4433/15/12/1417convection-permitting modelCPMbibliometric analysisscientific productionresearch trendslocal climate change adaptation |
| spellingShingle | Xiaozan Lyu Tianqi Ruan Xiaojing Cai A Bibliometric Analysis of Convection-Permitting Model Research Atmosphere convection-permitting model CPM bibliometric analysis scientific production research trends local climate change adaptation |
| title | A Bibliometric Analysis of Convection-Permitting Model Research |
| title_full | A Bibliometric Analysis of Convection-Permitting Model Research |
| title_fullStr | A Bibliometric Analysis of Convection-Permitting Model Research |
| title_full_unstemmed | A Bibliometric Analysis of Convection-Permitting Model Research |
| title_short | A Bibliometric Analysis of Convection-Permitting Model Research |
| title_sort | bibliometric analysis of convection permitting model research |
| topic | convection-permitting model CPM bibliometric analysis scientific production research trends local climate change adaptation |
| url | https://www.mdpi.com/2073-4433/15/12/1417 |
| work_keys_str_mv | AT xiaozanlyu abibliometricanalysisofconvectionpermittingmodelresearch AT tianqiruan abibliometricanalysisofconvectionpermittingmodelresearch AT xiaojingcai abibliometricanalysisofconvectionpermittingmodelresearch AT xiaozanlyu bibliometricanalysisofconvectionpermittingmodelresearch AT tianqiruan bibliometricanalysisofconvectionpermittingmodelresearch AT xiaojingcai bibliometricanalysisofconvectionpermittingmodelresearch |