領域外・複数領域(M) | |||
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セッション小記号 | 地球科学一般・情報地球科学(GI) | ||
セッションID | M-GI30 | ||
タイトル | 和文 | Data assimilation: A fundamental approach in geosciences | |
英文 | Data assimilation: A fundamental approach in geosciences | ||
タイトル短縮名 | 和文 | Data assimilation: A fundamental approach in geosciences | |
英文 | Data assimilation | ||
代表コンビーナ | 氏名 | 和文 | 中野 慎也 |
英文 | Shin ya Nakano | ||
所属 | 和文 | 情報・システム研究機構 統計数理研究所 | |
英文 | The Institute of Statistical Mathematics | ||
共同コンビーナ 1 | 氏名 | 和文 | 藤井 陽介 |
英文 | Yosuke Fujii | ||
所属 | 和文 | 気象庁気象研究所 | |
英文 | Meteorological Research Institute, Japan Meteorological Agency | ||
共同コンビーナ 2 | 氏名 | 和文 | 宮崎 真一 |
英文 | SHINICHI MIYAZAKI | ||
所属 | 和文 | 京都大学理学研究科 | |
英文 | Graduate School of Science, Kyoto University | ||
共同コンビーナ 3 | 氏名 | 和文 | 三好 建正 |
英文 | Takemasa Miyoshi | ||
所属 | 和文 | 理化学研究所 | |
英文 | RIKEN | ||
発表言語 | E | ||
スコープ | 和文 | 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. | |
英文 | 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. | ||
発表方法 | 口頭および(または)ポスターセッション | ||
招待講演 | Julien Aubert (Institut de Physique du Globe de Paris) 堀田 大介 (気象庁気象研究所) 荒木田 葉月 (国立研究開発法人理化学研究所 計算科学研究機構) 岡 顕 (東京大学大気海洋研究所) 福田 淳一 (東京大学地震研究所) 大石 俊 (名古屋大学 宇宙地球環境研究所 陸域海洋圏生態研究部) |
時間 | 講演番号 | タイトル | 発表者 | 予稿原稿 |
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口頭発表 5月29日 PM1 | ||||
13:45 - 14:00 | MGI30-01 | Recent progresses and applications of geomagnetic data assimilation | Julien Aubert | 予稿 |
14:00 - 14:15 | MGI30-02 | Accounting for non-locality of vertical error correlation within ETKF through eigen-spectral localization | 堀田 大介 | 予稿 |
14:15 - 14:30 | MGI30-03 | Data assimilation experiments with MODIS LAI observations and the dynamic global vegetation model SEIB-DGVM over Siberia | 荒木田 葉月 | 予稿 |
14:30 - 14:45 | MGI30-04 | アジョイント法による定常トレーサー分布から海洋鉛直拡散係数分布を推定する試み | 岡 顕 | 予稿 |
14:45 - 15:00 | MGI30-05 | Nonlinear data assimilation with 4DEnVar using iterative weather forecast model | 横田 祥 | 予稿 |
15:00 - 15:15 | MGI30-06 | Development of Data Assimilation System for Atmospheric Density to Improve Satellite's Orbit Prediction Accuracy | 加藤 博司 | 予稿 |
口頭発表 5月29日 PM2 | ||||
15:30 - 15:45 | MGI30-07 | An LETKF-based ocean reanalysis for the Asia-Oceania region using Himawari-8 SSTs and SMOS/SMAP SSS | 大石 俊 | 予稿 |
15:45 - 16:00 | MGI30-08 | Validation of JCOPE-T DA ocean assimilation product | 日原 勉 | 予稿 |
16:00 - 16:15 | MGI30-09 | Do surface lateral flows matter for land data assimilation?: Implication for hyper-resolution land modeling and observation | 澤田 洋平 | 予稿 |
16:15 - 16:30 | MGI30-10 | Geodynamo data assimilation for candidate models of IGRF13-SV from Japan team | 南 拓人 | 予稿 |
16:30 - 16:45 | MGI30-11 | A pilot study of geomagnetic data assimilation into a geodynamo model | 中野 慎也 | 予稿 |
16:45 - 17:00 | MGI30-12 | Bayesian parameter estimation of a physics-based model of postseismic crustal deformation | 福田 淳一 | 予稿 |
講演番号 | タイトル | 発表者 | 予稿原稿 |
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ポスター発表 5月29日 AM2 | |||
MGI30-P01 | Superposition of atmospheric states using information redundancy for Numerical Weather Prediction | 石橋 俊之 | 予稿 |
MGI30-P02 | Numerical Weather Prediction Experiments using a Coupled Atmosphere-Ocean Data Assimilation System in JMA/MRI (3) | 石橋 俊之 | 予稿 |
MGI30-P03 | Accurate estimation of posterior error covariance in a 4D-Var inverse analysis | 丹羽 洋介 | 予稿 |
MGI30-P04 | Assimilation CO2 concentration data in the Kanto region using AIST-MM model and for the estimation of CO2 emissions | 新井 豊 | 予稿 |
MGI30-P05 | Application of data assimilation method on parameter estimation of flow and nutrient behavior in watershed model | 堀江 陽介 | 予稿 |
MGI30-P06 | Bayesian inference of grain growth prediction via multi-phase-field models | 伊藤 伸一 | 予稿 |
MGI30-P07 | GNSS data assimilation for the Bungo channel Long-term SSEs using Ensemble Kalman Filter (EnKF) | 藤田 萌実 | 予稿 |
MGI30-P08 | A data assimilation library with Python for parallel computing | 中野 慎也 | 予稿 |