由 张 良承 An Improved Ionospheric Tomography Method Based on Adaptive Estimation of the Plasmaspheric Electron Content
基于等离子层电子含量自适应估计的改进型电离层层析成像方法
引文格式 | Citation:
Jiang N, Wu Y H, Li S, Xu Y, Wang Y B, Xu T H. First PWV retrieval using MERSI-LL onboard FY-3E and cross validation with co-platform occultation and ground GNSS[J]. Geophysical Research Letters, 2024, 51(8): e2024GL108681. DOI: 10.1029/2024GL108681.
Geophysical Research Letters（中科院1区Top，IF：4.6）
Computerized ionosphere tomography (CIT)
global navigation satellite systems (GNSS)
NeQuick2 model
plasmasphere
global navigation satellite systems (GNSS)
NeQuick2 model
plasmasphere
Abstract | 摘要
The slant total electron content (STEC) values of signal paths from global navigation satellite system satellites to observation stations are an important data source for voxel-based computerized ionosphere tomography (CIT). However, the height range of the satellite signal rays is much larger than that of the ionospheric-tomography region. Therefore, it is commonly using an empirical model to obtain a fixed proportional coefficient of the STEC of each ray that is outside the tomography region, and then eliminating the influence of the plasmasphere electron content (PEC) to CIT fixed proportional factor for the PEC (CIT-FPPEC); however, it has been found that this is unreasonable and can negatively affect the accuracy of CIT. Herein, we propose an improved CIT method based on adaptive estimation of the PEC (CIT-AEPEC). Numerical experiments were conducted using global positioning system observation data over Europe from May 8 to May 15, 2019, and the inversion results were compared with the electron density profiles from ionosonde data and in situ measurements of Swarm satellites. In contrast to the CIT method without removal of the PEC (CIT-STEC) and CIT-FPPEC, statistical analysis showed that the root-mean-square error (RMSE) values between the CIT-AEPEC and ionosonde observations were improved by 34.54% and 26.78%, and the RMSE values between the CIT-AEPEC and Swarm measurements were improved by 39.77% and 36.97%, respectively. Finally, CIT-AEPEC inversion results were used to detect ionospheric perturbations during two magnetic storms from May 8 May 15, 2019. The effects of negative ionospheric storms and daily variations were clearly visible in peak value maps of the ionospheric electron density (IED). These results reveal that the proposed method is a useful tool for research examining space weather.
全球导航卫星系统信号路径的斜路径总电子含量（STEC）是基于体素的电离层断层成像（CIT）的重要数据源。然而，卫星信号射线的高度范围远大于电离层断层成像区域，传统方法通常采用经验模型固定比例系数（CIT-FPPEC）来估算成像区域外的STEC占比，以消除等离子层电子含量（PEC）的影响；但该方法存在不合理性，会限制CIT反演精度。为此，本文提出一种基于PEC自适应估计的改进CIT方法（CIT-AEPEC）。利用2019年5月8日至15日欧洲地区的全球定位系统观测数据开展数值实验，并将反演结果与电离层测高仪数据、Swarm卫星原位探测的电子密度剖面进行对比。结果表明：相较于未去除PEC的CIT方法（CIT-STEC）和CIT-FPPEC方法，CIT-AEPEC与电离层测高仪观测值的均方根误差分别改善34.54%和26.78%，与Swarm卫星实测值的均方根误差分别提升39.77%和36.97%。进一步利用CIT-AEPEC反演结果探测了该时段内两次磁暴期间的电离层扰动，电离层电子密度峰值分布图清晰显示出负相电离层暴效应及日变化特征。结果表明，该方法可为空间天气研究提供有效技术支持。