Multidisciplinary and Interdisciplinary (M)
Session Sub-category General Geosciences, Information Geosciences & Simulations(GI)
Session ID M-GI26
Title Data assimilation: A fundamental approach in geosciences
Short Title Data assimilation
Main Convener Name Shin ya Nakano
Affiliation The Institute of Statistical Mathematics
Co-Convener 1 Name Daisuke Hotta
Affiliation Meteorological Research Institute
Co-Convener 2 Name Shun Ohishi
Affiliation RIKEN Center for Computational Science
Co-Convener 3 Name Masayuki Kano
Affiliation Graduate school of science, Tohoku University
Session Language 
E
Scope 
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.
Presentation Format Oral and Poster presentation
Invited Authors Keiichi Kondo (Meteorological Research Institute)
Jiping Xie (Nansen Environmental and Remote Sensing Center, Norway)
Time Presentation No Title Presenter
Oral Presentation May 30 AM1
9:00 - 9:15 MGI26-01 A hybrid particle filter/ensemble Kalman filter implementation with an intermediate AGCM Keiichi Kondo
9:15 - 9:30 MGI26-02 Ensemble Data Assimilation with Binary Observations: Theory and Application to Urban Flood Monitoring Yohei Sawada
9:30 - 9:45 MGI26-03 Modelling solar energetic particles through satellite data assimilation Takashi Minoshima
9:45 - 10:00 MGI26-04 Ultra-High Spatiotemporal Resolution Reconstruction of the Climate around Japan with Large Ensemble of Climate Simulations and Old Documents Atsushi Okazaki
10:00 - 10:15 MGI26-05 Tsunami data assimilation based on tsunami-induced magnetic fields Zhiheng Lin
10:15 - 10:30 MGI26-06 TOPAZ5: Upgraded the Arctic coupled ocean and sea-ice forecasting system with Ensemble Kalman Filter Jiping Xie
Presentation No Title Presenter
Poster Presentation May 30 PM3
MGI26-P01 Development of LETKF system based on the JMA’s ASUCA-Var Koji Terasaki
MGI26-P02 Using Data Assimilation to Improve Data-Driven Models Michael Goodliff
MGI26-P03 Reduced non-Gaussianity in multi-scale background error by assimilating every-30-second radar observation: a case of idealized deep convection Arata Amemiya
MGI26-P04 Functional data assimilation to make use of high resolution data Shin ya Nakano
MGI26-P05 Assimilation of ionospheric non-Gaussian data into an emulator of a magnetosphere-ionosphere model Shin ya Nakano