Japan Geoscience Union Meeting 2014

Presentation information

International Session (Oral)

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

[P-EM08_2AM2] Space Weather and Space Climate

Fri. May 2, 2014 10:55 AM - 12:45 PM 411 (4F)

Convener:*Ryuho Kataoka(National Institute of Polar Research), Yusuke Ebihara(Research Institute for Sustainable Humanosphere, Kyoto University), Kanya Kusano(Solar-Terrestrial Environment Laboratory, Nagoya University), Toshifumi Shimizu(Institute of Space and Astronautical Science, JAXA), Yoshizumi Miyoshi(Solar-Terrestrial Environement Laboratory, Nagoya University), Ayumi Asai(Unit for Synergetic Studies of Space, Kyoto University), Tatsuhiko Sato(Japan Atomic Energy Agency), Hidekatsu Jin(National Institude of Information and Communications Technology), Kiminori Itoh(Graduate School of Engineering, Yokohama National University), Hiroko Miyahara(College of Art and Design, Musashino Art University), Chair:Hidekatsu Jin(National Institude of Information and Communications Technology)

10:55 AM - 11:15 AM

[PEM08-15] Ensemble Data Assimilation for Thermospheric Mass Density Specification and Forecasting

*Tomoko MATSUO1, Ite LEE2, Jeffrey ANDERSON3 (1.University of Colorado at Boulder, CO, USA, 2.National Central University, Taiwan, 3.National Center for Atmospheric Research, CO, USA)

Keywords:thermosphere-ionosphere coupling, data assimilation, parameter and state estimation, thermospheric mass density, aerodynamic drag estimation, LEO orbit prediction

Even though the Earth's upper atmosphere density is tenuous, it is substantial enough to exert significant drag on orbiting spacecraft and debris. The largest uncertainty in low-Earth orbit prediction is aerodynamic drag estimation. Thermospheric mass density variation is the major source of drag estimation errors at altitudes below about 700 km. This paper demonstrates how the limit of predictability of thermospheric mass density variability can be extended by means of ensemble data assimilation. To assimilate observations of the thermosphere and ionosphere, we use an ensemble data assimilation procedure constructed with the Data Assimilation Research Testbed and the Thermoshere-Ionosphere Electrodynamics General Circulation Model, two sets of community software offered by NCAR. An important attribute of our approach is that the ionosphere-thermosphere coupling is self-consistently treated in both the forecast model and the assimilation scheme. This enables the inference of unobserved thermospheric states from the relatively plentiful observations of the ionosphere. Given the ever-expanding global navigation satellite infrastructure, this is indeed a promising prospect for upper atmosphere data assimilation. Another relevant strategy is using data assimilation to estimate the model forcing parameters that control states of the thermosphere and ionosphere. In comparison to the lower atmosphere, the upper atmosphere is a dissipative, strongly forced dynamical system, so estimation of model forcing parameters can have a dramatic impact on the quality of ensemble forecasting and assimilation of the upper atmosphere. In this paper, we present results from our ensemble assimilation experiments with thermospheric mass densities obtained from the accelerometer on board the CHAMP satellite, and electron density profiles obtained from the COSMIC/FORMOSAT-3 mission.