[EE] Poster

M (Multidisciplinary and Interdisciplinary) » M-GI General Geosciences, Information Geosciences & Simulations

[M-GI28] [EE] Data assimilation: A fundamental approach in geosciences

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

convener:Shin'ya Nakano(The Institute of Statistical Mathematics), Yosuke Fujii(Meteorological Research Institute, Japan Meteorological Agency), SHINICHI MIYAZAKI(Graduate School of Science, Kyoto University), Takemasa Miyoshi(RIKEN Advanced Institute for Computational Science)

Data assimilation is an inversion approach to estimate the evolution of a system by utilizing a constraint given by a dynamical simulation model. Data assimilation is now widely used not only in meteorology and oceanography but also other fields of geosciences such as hydrology, solid earth science, and space science. This session aims at providing an opportunity for discussion on data assimilation studies among researchers of various field of geosciences. We encourage contributions addressing novel methods and theoretical developments of data assimilation. Contributions dealing with useful applications of data assimilation are also welcome.

[MGI28-P01] Data assimilation for optimal estimation of frictional parameters and prediction of afterslip in the 2003 Tokachi-oki earthquake

*Masayuki Kano¹, SHINICHI MIYAZAKI², Yoichi Ishikawa³, Kosuke Ito⁴, Kazuro Hirahara² (1.Earthquake Research Institute, The University of Tokyo, 2.Department of Geophysics, Graduate School of Science, Kyoto University, 3.Japan Agency for Marine-Earth Science and Technology, 4.Faculty of Science, University of the Ryukyus)

[MGI28-P02] Observation impact on the medium and the long-term range forecast on an eddy-resolving ocean forecast system based on ROMS

*Takashi Setou¹, Hiroshi Kuroda⁵, Daisuke Takahashi⁵, Tomonori Azumaya⁵, Takeshi Okunishi², Daisuke Hasegawa², Shigeho Kakehi², Hitoshi Kaneko², Yugo Shimizu¹, Kiyotaka Hidaka¹, Yutaka HIroe¹, Keiichi Yamazaki¹, Takahiko Kameda¹, kazuhiro aoki¹, Takeshi Taneda³, Kenji Morinaga⁴, Makoto Okazaki⁴, Masachika Masujima⁴, Atsushi Nishimoto¹ (1.National Research Institute of Fisheries Science, Japan Fisheries Research and Education Agency, 2.Tohoku National Fisheries Research Institute, Japan Fisheries Research and Education Agency, 3.Seikai National Fisheries Research Institute, Japan Fisheries Research and Education Agency, 4.National Research Institute of Far Seas Fisheries, Japan Fisheries Research and Education Agency, 5.Hokkaido National Fisheries Research Institute, Japan Fisheries Research and Education Agency)

[MGI28-P03] Development of an operational system for monitoring and forecasting coastal and open ocean states around Japan.

*Nariaki Hirose¹, Norihisa Usui¹, Takahiro Toyoda¹, Yosuke Fujii¹, Yasushi Takatsuki¹, Kei Sakamoto¹, Hiroyuki Tsujino¹ (1.Meteorological Research Institute, Japan Meteorological Agency)

[MGI28-P04] Analysis error estimation in a 4-dimensional variational ocean data assimilation system using a quasi-Newton method

*Yosuke Fujii¹, Yosuke Niwa¹, Norihisa Usui¹ (1.Meteorological Research Institute, Japan Meteorological Agency)

[MGI28-P05] A Reanalysis Experiment using a Coupled Atmosphere-Ocean Data Assimilation System in JMA/MRI

*Yosuke Fujii¹, Toshiyuki Ishibashi¹, Tamaki Yasuda², Yuhei Takaya¹, Takeshi Iriguchi¹, Nariaki Saito¹, Yoshiaki Takeuchi¹ (1.Meteorological Research Institute, Japan Meteorological Agency, 2.Japan Meteorological Agency)

[MGI28-P06] Numerical Weather Prediction Experiments using a Coupled Atmosphere-Ocean Data Assimilation System in JMA/MRI

*Toshiyuki ISHIBASHI¹, Takeshi Iriguchi¹, Yosuke Fujii¹, Tamaki Yasuda², Yuhei Takaya¹, Naoaki Saito¹, Yoshiaki Takeuchi¹ (1.Meteorological Research Institute, 2.Japan Meteorological Agency)

[MGI28-P07] Towards assimilation of aerosol data from an imager of GOSAT into the aerosol transport model SPRINTARS

*Nakamura Haruna¹, Akihide Kamei², Tatsuya Yokota², Masataka Ajiro² (1.Fujitsu FIP Corporation, 2.National Institute for Environmental Studies)

[MGI28-P08] Multi-scale localization with NICAM-LETKF using real observations

*KEIICHI KONDO¹, Takemasa Miyoshi¹ (1.RIKEN Advanced Institute for Computational Science)

[MGI28-P09] Implicit thinning and localization of dense observation data in the LETKF: A case of phased array weather radar

*Guo-Yuan Lien¹, Takemasa Miyoshi¹ (1.RIKEN AICS)

[MGI28-P10] Data assimilation experiment for reproducing the temporal evolution of the inner-magnetospheric environment

*Shin'ya Nakano¹, Pontus Brandt², Mei-Ching Fok³ (1.The Institute of Statistical Mathematics, 2.The Johns Hopkins University Applied Physics Laboratory, 3.NASA Goddard Space Flight Center)

[MGI28-P11] Use of kernel regression in ensemble Kalman filters

*Shin'ya Nakano¹ (1.The Institute of Statistical Mathematics)

Session information