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基于文献计量的中国区域极端降水研究现状分析

A Bibliometric analysis of current research status on extreme precipitation in China

  • 摘要: 基于中国知网(CNKI)收录的989篇文献和Web of Science (WOS)收录的995篇文献数据,利用可视化知识图谱分析法(CiteSpace)从发文量、研究团队、热点方向等方面,系统分析了2004-2023年中国区域极端降水研究发展态势。主要结果表明:(1) 2004-2023年中国区域选题为"极端降水"的中英文期刊年发文量均呈现上升趋势,且2018年以后英文论文年发表量超过了中文;(2) 张强、王小军、尹义星、陈晓宏等是该领域的主要贡献学者,以南京信息工程大学、中国科学院大气物理研究所、中国气象科学研究院等为主的科研机构是该选题研究的主力军;(3) 研究热点主要聚焦在极端降水的数据产品评估、时空演变特征和发生机制等三个方面。本领域未来研究可着重关注融合多源数据产品与AI气象大模型开展极端降水时空高精度监测与影响评估,为区域防灾减灾助力。

     

    Abstract: Based on 989 publications indexed in CNKI and 995 publications from the Web of Science (WOS), this study systematically analyzes the development of research on regional extreme precipitation in China from 2004 to 2023 using CiteSpace for visual knowledge mapping. Key aspects such as publication trends, research collaborations, and thematic focuses are examined. The results are as follow: (1) From 2004 to 2023, the annual number of journal articles on “extreme precipitation” in both Chinese and English has shown an increasing trend, with English-language publications surpassing Chinese ones after 2018. (2) The primary contributing scholars in the field included Zhang Qiang, Wang Xiaojun, Yin Yixing, and Chen Xiaohong. For research institutions, Nanjing University of Information Science & Technology, Institute of Atmospheric Physics, Chinese Academy of Sciences, and Chinese Academy of Meteorological Sciences played the main roles. (3) The research hotspots focused on data assessment, spatiotemporal evolutionary characteristics, and occurrence mechanisms of extreme precipitation. Future research should pay more attention to integrating multi-source data products with AI-based meteorological large models for high-precision spatiotemporal monitoring and impact assessment of extreme precipitation, to help regional disaster prevention and mitigation.

     

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