欧明,陈龙江,甄卫民,等. 一种近实时全球电离层数据同化和预报系统的构建与实现[J]. 电波科学学报,2024,39(2):1-9. DOI: 10.12265/j.cjors.2023034
      引用本文: 欧明,陈龙江,甄卫民,等. 一种近实时全球电离层数据同化和预报系统的构建与实现[J]. 电波科学学报,2024,39(2):1-9. DOI: 10.12265/j.cjors.2023034
      OU M, CHEN L J, ZHEN W M, et al. Construction and implementation of a near-real-time global ionospheric data assimilation and forecasting system[J]. Chinese journal of radio science,2024,39(2):1-9. (in Chinese). DOI: 10.12265/j.cjors.2023034
      Citation: OU M, CHEN L J, ZHEN W M, et al. Construction and implementation of a near-real-time global ionospheric data assimilation and forecasting system[J]. Chinese journal of radio science,2024,39(2):1-9. (in Chinese). DOI: 10.12265/j.cjors.2023034

      一种近实时全球电离层数据同化和预报系统的构建与实现

      Construction and implementation of a near-real-time global ionospheric data assimilation and forecasting system

      • 摘要: 电离层天气变化正成为目前空间天气预报最重要的内容之一,建立一个可靠的、精确的电离层特征参量现报和预报系统对空间科学研究及军民用无线电信息系统保障均具有重要价值。基于国际GNSS服务组织(International GNSS Service, IGS)的地基GNSS和全球电离层无线电观测站(Global Ionospheric Radio Observatory, GIRO)数字测高仪的实时数据,以国际参考电离层(International Reference Ionosphere, IRI)模型为背景模型,采用高斯-马尔可夫-限带卡尔曼滤波同化技术,结合超大规模矩阵稀疏存储与处理方法,在云计算平台上构建完成了近实时全球电离层数据同化和预报系统(near-Real-Time Global Ionospheric Data AssiMilation and forecasting system, RT-GIDAM)。该系统具备了全球电离层TEC和电子密度的近实时(延时约5 min)、较高空间(5°×2.5°)和时间分辨率(15 min)的同化和预报功能,可为空间物理研究及相关无线电系统应用提供数据支撑。

         

        Abstract: Ionospheric weather changes are becoming one of the most important contents of space weather forecasting. The establishment of a reliable and accurate ionospheric characteristic parameter nowcast and forecast system is of great value to space scientific research and military and civilian radio frequency systems. Based on the real-time ground-based GNSS data and ionosonde data from International GNSS Service (IGS) and Global Ionospheric Radio Observatory (GIRO), taking the International Reference Ionospheric(IRI) as the background model, adopting Gauss-Markov-band-limited Kalman filter assimilation algorithm, combining with ultra-large-scale matrix sparse storage and processing methods, a near-Real-Time Global Ionospheric Data Assimilation and Forecasting System (RT-GIDAM) is built on the cloud computing platform. The system has the ability of specification and prediction of global ionospheric total electron content (TEC) and electron density in near real time (with a delay of about 5 min), higher spatial and temporal resolution (5°×2.5°×15 min). The establishment of RT-GIDAM can provide data support for space physics research and related radiowave system applications.

         

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