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A Bibliometric Analysis of Convection-Permitting Model Research
Department of Administrative Management, School of Law, Hangzhou City University, Hangzhou 310015, China;.
KTH, School of Industrial Engineering and Management (ITM), Energy Technology.ORCID iD: 0000-0001-6866-3036
Research Center for Government Governance and Public Policy, School of Business, Yangzhou University, Yangzhou 225127, China.
2024 (English)In: Atmosphere, E-ISSN 2073-4433, Vol. 15, no 12, article id 1417Article, review/survey (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
MDPI AG , 2024. Vol. 15, no 12, article id 1417
Keywords [en]
bibliometric analysis, convection-permitting model, CPM, kilometer-scale resolution, local climate change adaptation, research trends, scientific production
National Category
Climate Science
Identifiers
URN: urn:nbn:se:kth:diva-358257DOI: 10.3390/atmos15121417ISI: 001384115600001Scopus ID: 2-s2.0-85213264168OAI: oai:DiVA.org:kth-358257DiVA, id: diva2:1925457
Note

QC 20250117

Available from: 2025-01-08 Created: 2025-01-08 Last updated: 2025-02-07Bibliographically approved

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Ruan, Tianqi

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