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2014-2019 年日本电离层总电子含量的时空变化研究及 2016 年熊本地震

Study of Spatial and Temporal Variations of Ionospheric Total Electron Content in Japan, during 2014-2019 and the 2016 Kumamoto Earthquake.

机构信息

School of Geodesy and Geomatics, Wuhan University, Wuhan 430079, China.

Chinese Antarctic Center of Surveying and Mapping, Wuhan University, Wuhan 430079, China.

出版信息

Sensors (Basel). 2021 Mar 19;21(6):2156. doi: 10.3390/s21062156.

Abstract

There are a large number of excellent research cases in Global Navigation Satellite System (GNSS) positioning and disaster prediction in Japan region, where the simulation and prediction of total electron content (TEC) is a powerful research method. In this study, we used the data of the GNSS Earth Observation Network (GEONET) established by the Geographical Survey Institute of Japan (GSI) to compare the performance of two regional ionospheric models in Japan, in which the spherical cap harmonic (SCH) model has the best performance. In this paper, we investigated the spatial and temporal variations of ionospheric TEC in Japan and their relationship with latitude, longitude, seasons, and solar activity. The results show that the TEC in Japan increases as the latitude decreases, with the highest average TEC in spring and summer and the lowest in winter, and has a strong correlation with solar activity. In addition, the observation and analysis of ionospheric disturbances over Japan before the 2016 Kumamoto earthquake and geomagnetic storms showed that GNSS observing of ionospheric TEC seems to be very effective in forecasting natural disasters and monitoring space weather.

摘要

日本在全球导航卫星系统(GNSS)定位和灾害预测方面有大量优秀的研究案例,其中总电子含量(TEC)的模拟和预测是一种强大的研究方法。在这项研究中,我们使用了由日本地理调查研究所(GSI)建立的 GNSS 地球观测网络(GEONET)的数据,比较了日本两个区域电离层模型的性能,其中球形谐和(SCH)模型表现最佳。本文研究了日本电离层 TEC 的时空变化及其与纬度、经度、季节和太阳活动的关系。结果表明,日本的 TEC 随纬度降低而增加,春季和夏季的平均 TEC 最高,冬季最低,且与太阳活动有很强的相关性。此外,观测和分析 2016 年熊本地震和地磁暴前日本上空的电离层扰动表明,GNSS 观测电离层 TEC 似乎非常有效地预测自然灾害和监测空间天气。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2882/8003414/d707acdec22e/sensors-21-02156-g001.jpg

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