基于表面理论的区域电离层 TEC 预测高精度空间重构方法

IF 3.7 2区 地球科学
Space Weather Pub Date : 2023-12-01 DOI:10.1029/2023sw003663
Jian Wang, Yi‐ran Liu, Yanmei Shi
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引用次数: 0

摘要

为了实现更精确的电离层电子总含量(TEC)空间重构,促进卫星定位和测距应用的改进,提出了一种基于表面理论的 TEC 高精度空间重构(HASR)方法。该方法的核心理论如下:(a) 任何曲面都可以由其第一和第二基本量唯一确定;(b) 通过直接差分近似,将微分方程转化为代数方程,从而更快地求解高斯方程。同时,以欧洲部分地区为例,采用所提出的 HASR 方法,以相对均方根误差(RRMSE)为评价标准,确定相关系数和模型的迭代次数。统计结果表明,HASR 方法预测的 TEC 与电离层观测站的实际观测值高度一致,预测 RRMSE 为 9.75%。与带比例因子的克里金插值法相比,HASR 方法的预测精度提高了 8.5%。希望该方法能为其他电离层参数的空间重构提供思路,进一步推动完整准确的空间天气预报的实现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A High Accuracy Spatial Reconstruction Method Based on Surface Theory for Regional Ionospheric TEC Prediction
In order to achieve more accurate spatial reconstruction of ionospheric total electron content (TEC) and promote improved satellite positioning and ranging applications, a high accuracy spatial reconstruction (HASR) method for TEC is proposed based on the surface theory. The core theory of this method is as follows: (a) Any surface can be uniquely determined by its first and second fundamental quantities; (b) By direct difference approximation, differential equations are transformed into algebraic equations to solve Gauss equations faster. At the same time, taking parts of Europe as an example, the proposed HASR method is used to determine the correlation coefficients and the number of iterations of the model by using the relative root mean square error (RRMSE) as the evaluation criterion. The statistical results show that the TEC predicted by the HASR method is highly consistent with the actual observed values of ionospheric observation stations, and the prediction RRMSE is 9.75%. Compared with the Kriging interpolation with scale factor, the prediction accuracy of the HASR method is improved by 8.5%. We hope this method can provide ideas for the spatial reconstruction of other ionospheric parameters and further promote the realization of complete and accurate space weather forecast.
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