Japan Geoscience Union Meeting 2016

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International Session (Oral)

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

[P-EM04] Space Weather, Space Climate, and VarSITI

Mon. May 23, 2016 9:00 AM - 10:30 AM 103 (1F)

Convener:*Ryuho Kataoka(National Institute of Polar Research), Antti Pulkkinen(NASA GSFC), Yusuke Ebihara(Research Institute for Sustainable Humanosphere, Kyoto University), Yoshizumi Miyoshi(Institute for Space-Earth Environmental Research, Nagoya University), Toshifumi Shimizu(Institute of Space and Astronautical Science, JAXA), Ayumi Asai(Unit for Synergetic Studies of Space, Kyoto University), Hidekatsu Jin(National Institude of Information and Communications Technology), Tatsuhiko Sato(Japan Atomic Energy Agency), Kanya Kusano(Institute for Space-Earth Environmental Research, Nagoya University), Hiroko Miyahara(College of Art and Design, Musashino Art University), Kiminori Itoh(Graduate School of Engineering, Yokohama National University), Kazuo Shiokawa(Institute for Space-Earth Environmental Research, Nagoya University), Takuji Nakamura(National Institute of Polar Research), Shigeo Yoden(Division of Earth and Planetary Sciences, Graduate School of Science, Kyoto University), Kiyoshi Ichimoto(Kwasan and Hida Observatories, Kyoto University), Mamoru Ishii(National Institute of Information and Communications Technology), Chair:Ryuho Kataoka(National Institute of Polar Research)

10:15 AM - 10:30 AM

[PEM04-27] SUSANOO-Aurora Activity Forecast: Forecast of the aurora index with the real time data assimilation

*Yoshizumi Miyoshi1, Ryota Yamamoto1, Genta Ueno2, Daikou Shiota1, Masahito Nose3, Shinobu Machida1 (1.Institute for Space-Earth Environmental Research, Nagoya University, 2.The Institute of Statistical Mathematics, 3.Data Analysis Center for Geomagnetism and Space Magnetism Graduate School of Science, Kyoto University)

Keywords:Data assimilation, Forecast, Auroral activity index

The AU/AL indices are a manifest of the global aurora activity, and their forecast is useful to recognize the future evolution of geospace. In order to forecast the aurora activity, we have developed the forecast system of the aurora index based on the prediction model of Goertz et al.(1992). The model calculates the time evolution of the aurora index using the solar wind electric fields. The real time space weather forecast system SUSANOO (Shiota et al., 2014, http://st4a.stelab.nagoya-u.ac.jp/susanoo/) has provided the next 7 days solar wind parameters at 1 AU, and we calculate the time variations of the aurora indices using the electric fields from the SUSANOO-solar wind simulation. The Goertz model includes several empirical parameters, and the forecast skill depends on the accuracy of these parameters. We have implemented the real-time data assimilation to improve these parameters by comparing the model results and the actual aurora index. The developed system consists of the hindcast and forecast stages. In the hindcast stage, prediction, smoothing and filtering in the data assimilation are performed for the previous 7 days using the data from the SUSANOO-solar wind simulation and the observed aurora index, which improves the parameters for the model. Using the estimated parameters from the hindcast stage, we calculate the time evolution of the aurora index for the next 7 days as the forecast stage. In this presentation, we will present the concept of SUSANOO-aurora activity forecast and initial results from test-operations.