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1945年至2024年气象雷达研究的文献计量分析:形成、发展与趋势

Bibliometric Analysis of Weather Radar Research from 1945 to 2024: Formations, Developments, and Trends.

作者信息

Liu Yin

机构信息

Jiangsu Meteorological Observation Center, Nanjing 210041, China.

College of Atmospheric Sounding, Chengdu University of Information Technology, Chengdu 610225, China.

出版信息

Sensors (Basel). 2024 May 30;24(11):3531. doi: 10.3390/s24113531.

Abstract

In the development of meteorological detection technology and services, weather radar undoubtedly plays a pivotal role, especially in the monitoring and early warning of severe convective weather events, where it serves an irreplaceable function. This research delves into the landscape of weather radar research from 1945 to 2024, employing scientometric methods to investigate 13,981 publications from the Web of Science (WoS) core collection database. This study aims to unravel, for the first time, the foundational structures shaping the knowledge domain of weather radar over an 80-year period, exploring general features, collaboration, co-citation, and keyword co-occurrence. Key findings reveal a significant surge in both publications and citations post-1990, peaking in 2022 with 1083 publications and 13832 citations, signaling sustained growth and interest in the field after a period of stagnation. The United States, China, and European countries emerge as key drivers of weather radar research, with robust international collaboration playing a pivotal role in the field's rapid evolution. Analysis uncovers 30 distinct co-citation clusters, showcasing the progression of weather radar knowledge structures. Notably, deep learning emerges as a dynamic cluster, garnering attention and yielding substantial outcomes in contemporary research efforts. Over eight decades, the focus of weather radar investigations has transitioned from hardware and software enhancements to Artificial Intelligence (AI) technology integration and multifunctional applications across diverse scenarios. This study identifies four key areas for future research: leveraging AI technology, advancing all-weather observation techniques, enhancing system refinement, and fostering networked collaborative observation technologies. This research endeavors to support academics by offering an in-depth comprehension of the progression of weather radar research. The findings can be a valuable resource for scholars in efficiently locating pertinent publications and journals. Furthermore, policymakers can rely on the insights gleaned from this study as a well-organized reference point.

摘要

在气象探测技术与服务的发展过程中,气象雷达无疑发挥着关键作用,尤其是在强对流天气事件的监测与预警方面,具有不可替代的功能。本研究深入探讨了1945年至2024年期间气象雷达的研究概况,运用科学计量学方法对来自科学网(WoS)核心合集数据库的13981篇文献进行了调查。本研究旨在首次揭示80年来塑造气象雷达知识领域的基础结构,探究其一般特征、合作情况、共被引情况以及关键词共现情况。主要研究结果表明,1990年之后文献数量和被引次数均显著激增,在2022年达到峰值,分别为1083篇文献和13832次被引,这表明在经历一段时间的停滞之后,该领域持续增长且受到关注。美国、中国和欧洲国家是气象雷达研究的主要推动力量,强大的国际合作在该领域的快速发展中发挥了关键作用。分析发现了30个不同的共被引聚类,展示了气象雷达知识结构的发展历程。值得注意的是,深度学习成为一个活跃的聚类,在当代研究工作中受到关注并取得了丰硕成果。八十多年来,气象雷达研究的重点已从硬件和软件改进转向人工智能(AI)技术集成以及跨多种场景的多功能应用。本研究确定了未来研究的四个关键领域:利用AI技术、推进全天候观测技术、加强系统优化以及促进网络化协同观测技术。本研究致力于通过深入理解气象雷达研究的进展来支持学术界。研究结果可为学者高效查找相关文献和期刊提供宝贵资源。此外,政策制定者可以将本研究所得的见解作为条理清晰的参考依据。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1ae3/11175257/c6675023fbbf/sensors-24-03531-g001.jpg

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