A single-station empirical TEC model based on long-time recorded GPS data for estimating ionospheric delay
A single-station empirical TEC model based on long-time recorded GPS data for estimating ionospheric delay
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DOI：
10.1051/swsc/2018047
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发表时间：
2018-12
影响因子：
3.3
通讯作者：
Zhenzhen Zhao;Jiandi Feng;Bao-min Han;Zhengtao Wang
中科院分区：
文献类型：
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作者：
Zhenzhen Zhao;Jiandi Feng;Bao-min Han;Zhengtao Wang
全球分布的GPS（全球定位系统）站已经连续运行了近20年，积累了大量观测数据。这些长时间记录的GPS数据可用于计算单站连续总电子含量（TEC）值，并为建立单站经验TEC模型提供有效的建模数据。本文基于2004 ~ 2015年IONOLAB-TEC应用计算的GPS数据，提出了一种新的单站经验TEC模型SSM-T1。SSM-T1模式由日、季节和太阳相关变化三部分组成，采用非线性最小二乘法拟合18个系数。SSM-T1模型在四个站点进行测试：法国巴黎（opmt）；印度班加罗尔（iisc）；塞杜纳（cedu），澳大利亚；和O 'Higgins （ohi3）在南极半岛上空。4个站点模型残差的均方根值分别为3.22、4.46、3.28和3.83 TECU。评估结果表明，SSM-T1模式与GPS-TEC观测资料吻合较好，在巴黎、班加罗尔和塞杜纳站具有较好的预测能力。然而，在O 'Higgins站，SSM-T1模式与GPS-TEC观测数据偏差严重，不能有效描述中纬度夏夜异常的变化。
Globally distributed GPS (global positioning system) stations have been continuously running for nearly 20 years, thereby accumulating numerous observations. These long-time recorded GPS data can be used to calculate continuous total electron content (TEC) values at single stations and provide an effective modeling dataset to establish single-station empirical TEC models. In this paper, a new empirical TEC model called SSM-T1 for single stations is proposed on the basis of GPS data calculated by IONOLAB-TEC application from 2004 to 2015. The SSM-T1 model consists of three parts: diurnal, seasonal, and solar dependency variations, with 18 coefficients fitted by the nonlinear least-squares method. The SSM-T1 model is tested at four stations: Paris (opmt), France; Bangalore (iisc), India; Ceduna (cedu), Australia; and O’Higgins (ohi3) over the Antarctic Peninsula. The RMS values of the model residuals at these four stations are 3.22, 4.46, 3.28, and 3.83 TECU. Assessment results show that the SSM-T1 model is in good agreement with the observed GPS-TEC data and exhibits good prediction ability at the Paris, Bangalore, and Ceduna stations. However, at the O’Higgins station, the SSM-T1 model seriously deviates from the observed GPS-TEC data and cannot effectively describe the variation of mid-latitude summer night anomaly.