气象数据存储技术研究进展与方向

Research Progress and Directions in Meteorological Data Storage Technologies

摘要: 随着气象数据规模快速增长，存储技术面临多源异构、高并发、长期保存等多重挑战。文章系统梳理了近年来气象数据存储领域的研究方法、主要创新和不足之处，并展望了未来潜在的热门研究方向。重点分析了数据湖与云原生存储、分布式与混合存储架构、数据智能处理与质量控制、数据安全与传输优化等方面的技术进展，通过性能对比量化分析了不同技术方案的优劣。总结了存储架构、介质优化、智能处理及共享机制等方面的创新成果，指出了标准化不足、系统融合困难、人工智能应用深度有限等现存问题，并从智能分级存储、云边端协同、人工智能赋能、数据要素化支撑及新型存储介质等角度探讨了未来发展趋势。

Abstract: The rapid expansion of meteorological data presents significant challenges for storage technologies, including multi-source heterogeneity, high-concurrency access, and long-term preservation. This paper reviews recent methodologies, innovations, and limitations in meteorological data storage, and prospects potential future research directions. It focuses on analyzing technological advances in data lakes and cloud-native storage, distributed and hybrid storage architectures, intelligent data processing and quality control, as well as data security and transmission optimization, and quantitatively compares the advantages and disadvantages of different technical solutions through performance benchmarking. The study summarizes innovative achievements in storage architecture, media optimization, intelligent processing, and sharing mechanisms, identifies existing problems such as insufficient standardization, difficulties in system integration, and limited depth of artificial intelligence applications, and discusses future development trends from the perspectives of intelligent tiered storage, cloud-edge-device collaboration, AI empowerment, data factorization support, and novel storage media.