Volume 30 Issue 10 - October 7, 2016 PDF
Ionospheric Space Weather and Aviation
Chia-Hung Chen1*, Charles Lin1, Shau-Shiun Jan2
1Department of Earth Sciences, National Cheng Kung University
2Department of Aeronautics and Astronautics, National Cheng Kung University
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As the typhoon will cause the disaster to endanger our human life, the solar geomagnetic storm will cause the variation of plasma in the high atmosphere region (around 50 ~ 1000 km altitude) to affect the radio communication. For a severe geomagnetic storm event, the satellite communication will further be interfered or broken down and the accuracy of navigation positioning will also be affected by the rapid change of plasma. Recently, the U.S.A. and Japan aggressively develop the landing navigation and positioning system for the aircraft by using the Global Navigation Satellite System (GNSS). The most difficult problem is how to reduce the positioning error. Therefore, how to get the correct variation of plasma, even to forecast, is an important topic and closely related to the people’s livelihood, like the weather prediction.

We have developed an ionospheric plasma forecast system by employing the data assimilation method and assimilating the ground-based GPS total electron content (TEC) observations into a physical model. In this paper, we further discuss the effects of different assimilation cycles and neutral atmosphere on the accuracy of plasma forecast during the geomagnetic storm period. It is shown that the result with shorter assimilation cycle can correctly catch the plasma variations and improve the accuracy of plasma forecast. On the other hand, the neutral parameters, such as neutral wind, neutral temperature, and neutral composition, will also be adjusted and then further alter the trajectory of model forecast, although we only assimilate the TEC observations in the assimilation system. The improvements of neutral atmosphere can be seen in Figure 1, which shows the global distribution of column density ratio of oxygen to nitrogen (O/N2 ratio). It is clearly shown that the results with 60-min assimilation cycle (fig. 1c) has large difference with the satellite observation (fig. 1a), especially around the South America. However, this difference can be greatly mitigated/improved by shorter assimilation cycles (figs. 1d and 1e). This indicates that the shorter assimilation cycles can also significantly improve the neutral parameters during the geomagnetic storm period.

This ionospheric plasma forecast system is still developing and improving. The different kind of observations, such as ground-based radar and satellite observations, will be assimilated in this system to promote the plasma forecast capability. Furthermore, this model will be reconstructed for the operational mission and then automatically prove the forecast information of ionospheric space weather to the applications of radio communication and aviation.
Figure 1. The global distribution of O/N2 ratio. The (a) panel shows the TIMED-GUVI satellite observation. The (b) panel shows the model result without the data assimilation. The (c) panel shows the result with 60-min assimilation cycle. The (d) and (e) panels show the results with 30-min and 10-min assimilation cycles, respectively.
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