JpGU-AGU Joint Meeting 2017

Presentation information

Print

[EE] Poster

P (Space and Planetary Sciences) » P-EM Solar-Terrestrial Sciences, Space Electromagnetism & Space Environment

[P-EM17] [EE] Recent Advances in Ionosphere Observation and Modeling for Monitoring and Forecast

Mon. May 22, 2017 3:30 PM - 5:00 PM Poster Hall (International Exhibition Hall HALL7)

convener:Charles Lin(Department of Earth Science, National Cheng Kung University), Yang-Yi Sun(Kyushu Univsersuty, Department of Earth and Planetary Science), Hidekatsu Jin(National Institude of Information and Communications Technology), Jaeheung PARK(Korea Astronomy and Space Science Institute)

[PEM17-P07] Development of regional ionospheric map and ionospheric prediction over Southeast Asia

*Kornyanat Hozumi1, Noraset Wichaipanich2, Takashi Maruyama1, Takuya Tsugawa1, Mamoru Ishii1 (1.National Institute of Information and Communications Technology, 2.Faculty of Engineering, Rajamangala University of Technology Thanyaburi, No. 39, Moo 1, Rangsit-Nakhonnayok Road, Thanyaburi district,Pathum Thani 12110, Thailand)

Keywords:Ionospheric map, SEALION, Artificial neural network (ANN)

Dates back to 2003, National Institute of Information and Communications Technology (NICT) initiated the ionospheric observation network in Southeast Asia, a so-called Southeast Asia low-latitude ionospheric network (SEALION). Since then, ionospheric data has been collected and researched for a decade for research purpose. Nowadays, ionospheric data users increase. One of the reasons is that ionospheric data will become a must use dataset for air transportation business in the near future. Even though NICT has much data, the data itself is not friendly to non-scientist users. Moreover, there is no effective tool for ionospheric prediction in Southeast Asia yet. Recently we have developed a regional ionospheric map, and a regional ionospheric prediction based on artificial neural network (ANN). This paper introduces progress, success, and problem in the development.