[E] Poster

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

[M-GI33] Data assimilation: A fundamental approach in geosciences

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

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.

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[MGI33-P01] Oceanic iron distribution of the global ocean estimated by data assimilation approach

★Invited Papers

*Toshimasa Doi¹, Satoshi Osafune¹, Shuhei Masuda¹, Hajime Obata⁴, Kazuhiro Misumi³, Jun Nishioka² (1.Japan Agency for Marine-Earth Science and Technology, 2.Hokkaido University, 3.Central Research Institute of Electric Power Industry, 4. The University of Tokyo)

[MGI33-P02] Enhanced correlations between SST and precipitation in the weather time scale represented by a coupled atmosphere-ocean data assimilation system

*Yosuke Fujii¹, Chiaki Kobayashi¹, Ichiro Ishikawa¹, Takaya Yuhei¹ (1.Meteorological Research Institute, Japan Meteorological Agency)

[MGI33-P03] Non-Gaussian statistics in global atmospheric dynamics with a 10240-member ensemble Kalman filter experiment using an intermediate AGCM

★Invited Papers

*Keiichi Kondo^1,2, Takemasa Miyoshi² (1.Meteorological Research Institute, 2.RIKEN Center for Computational Science)

[MGI33-P04] Data assimilation of lightning observation data for global numerical weather prediction

*Toshiyuki Ishibashi¹ (1.Meteorological Research Institute/Japan Meteorological Agency)

[MGI33-P05] Development of a "multilingual" data assimilation library

*Shin ya Nakano¹, Genta Ueno¹, Shunichi Nomura¹, Daisuke Murakami¹ (1.The Institute of Statistical Mathematics)

[MGI33-P06] Observation impact study in global numerical weather prediction

*Toshiyuki Ishibashi¹ (1.Meteorological Research Institute/Japan Meteorological Agency)

Session information

[M-GI33] Data assimilation: A fundamental approach in geosciences

[MGI33-P01] Oceanic iron distribution of the global ocean estimated by data assimilation approach

★Invited Papers

[MGI33-P02] Enhanced correlations between SST and precipitation in the weather time scale represented by a coupled atmosphere-ocean data assimilation system

[MGI33-P03] Non-Gaussian statistics in global atmospheric dynamics with a 10240-member ensemble Kalman filter experiment using an intermediate AGCM

★Invited Papers

[MGI33-P04] Data assimilation of lightning observation data for global numerical weather prediction

[MGI33-P05] Development of a "multilingual" data assimilation library

[MGI33-P06] Observation impact study in global numerical weather prediction