領域外・複数領域(M)
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IDM-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
口頭発表 5月29日 PM1
13:45 - 14:00MGI30-01Recent progresses and applications of geomagnetic data assimilationJulien Aubert予稿
14:00 - 14:15MGI30-02Accounting for non-locality of vertical error correlation within ETKF through eigen-spectral localization堀田 大介予稿
14:15 - 14:30MGI30-03Data 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 - 14:45MGI30-04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 - 15:00MGI30-05Nonlinear data assimilation with 4DEnVar using iterative weather forecast model横田 祥予稿
15:00 - 15:15MGI30-06Development 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 - 15:45MGI30-07An LETKF-based ocean reanalysis for the Asia-Oceania region using Himawari-8 SSTs and SMOS/SMAP SSS大石 俊予稿
15:45 - 16:00MGI30-08Validation of JCOPE-T DA ocean assimilation product日原 勉予稿
16:00 - 16:15MGI30-09Do surface lateral flows matter for land data assimilation?: Implication for hyper-resolution land modeling and observation澤田 洋平予稿
16:15 - 16:30MGI30-10Geodynamo data assimilation for candidate models of IGRF13-SV from Japan team南 拓人予稿
16:30 - 16:45MGI30-11A pilot study of geomagnetic data assimilation into a geodynamo model中野 慎也予稿
16:45 - 17:00MGI30-12Bayesian 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
ポスター発表 5月29日 AM2
MGI30-P01Superposition of atmospheric states using information redundancy for Numerical Weather Prediction石橋 俊之予稿
MGI30-P02Numerical Weather Prediction Experiments using a Coupled Atmosphere-Ocean Data Assimilation System in JMA/MRI (3)石橋 俊之予稿
MGI30-P03Accurate estimation of posterior error covariance in a 4D-Var inverse analysis丹羽 洋介予稿
MGI30-P04Assimilation CO2 concentration data in the Kanto region using AIST-MM model and for the estimation of CO2 emissions新井 豊予稿
MGI30-P05Application of data assimilation method on parameter estimation of flow and nutrient behavior in watershed model堀江 陽介予稿
MGI30-P06Bayesian inference of grain growth prediction via multi-phase-field models伊藤 伸一予稿
MGI30-P07GNSS data assimilation for the Bungo channel Long-term SSEs using Ensemble Kalman Filter (EnKF)藤田 萌実予稿
MGI30-P08A data assimilation library with Python for parallel computing中野 慎也予稿