Forecasting geomagnetic activity Kp index of space environment with Hp
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摘要: 地磁场扰动可以引起近地空间环境(包括电离层和磁层)一系列变化, 地磁Kp指 数是空间天气扰动的重要参考指标. 采用地球同步轨道GOES-8卫星监测到的垂 直于同步卫星轨道平面的地磁分量Hp数据, 分析了地磁Kp指数 与Hp分量波动幅度间的统计关系, 结果显示, Hp分量 的变化与Kp指数具有很好的相关性. 利用回归分析和RBF神经网络方法, 建立了Kp指数现报模型, 根据地球同步轨道地磁场Hp分量的变化, 计算出相同时段的Kp指数. 监测结果表明, 预报方法具有一定的有效性和实 用性, 特别是人工神经网络模式计算的Kp指数与实测结果吻合很好. 利用此 方法能够在不依赖于地面地磁探测数据的情况下, 快速预报地磁扰动, 及时为 空间天气保障提供参考. 同时, 鉴于中国即将发射的风云四号搭载有地磁场探测 仪, 本项研究可为自主数据的应用奠定基础.Abstract: Geomagnetic disturbance can cause a series of changes for near-Earth space environment, including the ionosphere and magnetosphere, and Kp index is the important reference index for disturbance of space weather. Hp component data monitored by GOES-8 satellite of geosynchronous orbit was used in this paper. By analyzing statistical relation between Kp index and Hp component width of fluctuation, it is shown that the change of Hp component and Kp index have good correlation. Based on the change of Hp component, Kp index in the same time interval is calculated, and then Kp index forecast model is established by means of regression analysis and RBF neural networks. Monitoring results show that the prediction method has certain validity and practicability especially that Kp index calculated by artificial neural networks is quite consistent with its measured values. By using this method, it is able to forecast geomagnetic disturbance quickly, and to provide reference in time for space weather guarantee not relying on the data from geomagnetic diction. In addition, China is going to launch FY-4 satellite, on which a magnetic field detector will be carried. Hence, this research will provide the foundation for application using FY-4 data in the future.
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Key words:
- Magnetic field /
- Hp component /
- Kp index /
- Prediction
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