[EE] Oral

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

[M-GI22] Data assimilation: A fundamental approach in geosciences

Sun. May 20, 2018 9:00 AM - 10:30 AM 302 (3F International Conference Hall, Makuhari Messe)

convener:Shin'ya Nakano(The Institute of Statistical Mathematics), Yosuke Fujii(Meteorological Research Institute, Japan Meteorological Agency), SHINICHI MIYAZAKI(京都大学理学研究科, 共同), Takemasa Miyoshi(RIKEN Advanced Institute for Computational Science), Chairperson:Fujii Yosuke

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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9:00 AM - 9:15 AM

[MGI22-01] Assimilation of EUV and ENA measurements for modeling of the inner magnetosphere

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

9:15 AM - 9:30 AM

[MGI22-02] Grad-CAM will tell the important regions to predict the typhoon intensity

*Shinya Tanahara¹, Kosuke Ito^1,2, Hiroyuki Yamada¹, Taiga Shibata¹, Ryota Miyata¹ (1.University of the Ryukyus, 2.Meteorological Research Institute)

9:30 AM - 9:50 AM

[MGI22-03] Development of a storm-scale particle filter for investigating predictability of convection initiation and development

★Invited Papers

*Takuya Kawabata¹, Genta Ueno² (1.Meteorological Research Institute, 2.The Institute of Statistical Mathematics)

9:50 AM - 10:05 AM

[MGI22-04] Toward improved LETKF assimilation of non-local and dense observation by direct covariance localization in model space

*Daisuke Hotta¹ (1.Meteorological Research Institute, Japan Meteorological Agency)

10:05 AM - 10:25 AM

[MGI22-05] Issues regarding maintaining ensemble spreads, balance, and high-resolution information in rapid-update-cycle radar data assimilation with the LETKF

★Invited Papers

*Guo-Yuan Lien¹, Takemasa Miyoshi¹ (1.RIKEN Advanced Institute for Computational Science)

Discussion (10:25 AM - 10:30 AM)

Session information

[M-GI22] Data assimilation: A fundamental approach in geosciences

[MGI22-01] Assimilation of EUV and ENA measurements for modeling of the inner magnetosphere

[MGI22-02] Grad-CAM will tell the important regions to predict the typhoon intensity

[MGI22-03] Development of a storm-scale particle filter for investigating predictability of convection initiation and development

★Invited Papers

[MGI22-04] Toward improved LETKF assimilation of non-local and dense observation by direct covariance localization in model space

[MGI22-05] Issues regarding maintaining ensemble spreads, balance, and high-resolution information in rapid-update-cycle radar data assimilation with the LETKF

★Invited Papers

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