JpGU Meeting 2019
Session outline| Multidisciplinary and Interdisciplinary (M) | ||
|---|---|---|
| Session Sub-category | General Geosciences, Information Geosciences & Simulations(GI) | |
| Session ID | M-GI30 | |
| 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 | Yosuke Fujii |
| Affiliation | Meteorological Research Institute, Japan Meteorological Agency | |
| Co-Convener 2 | Name | SHINICHI MIYAZAKI |
| Affiliation | Graduate School of Science, Kyoto University | |
| Co-Convener 3 | Name | Takemasa Miyoshi |
| Affiliation | RIKEN | |
| 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 | Julien Aubert (Institut de Physique du Globe de Paris) Daisuke Hotta (Meteorological Research Institute, Japan Meteorological Agency) Hazuki Arakida (RIKEN Advanced Institute for Computational Science) Akira Oka (Atmosphere and Ocean Research Institute, The University of Tokyo) Jun'ichi Fukuda (Earthquake Research Institute, University of Tokyo) Shun Ohishi (Division for Land-Ocean Ecosystem Research, Institute for Space-Earth Environmental Research, Nagoya University) | |
| Time | Presentation No | Title | Presenter | Abstract |
|---|---|---|---|---|
| Oral Presentation May 29 PM1 | ||||
| 13:45 - 14:00 | MGI30-01 | Recent progresses and applications of geomagnetic data assimilation | Julien Aubert | |
| 14:00 - 14:15 | MGI30-02 | Accounting for non-locality of vertical error correlation within ETKF through eigen-spectral localization | Daisuke Hotta | |
| 14:15 - 14:30 | MGI30-03 | Data assimilation experiments with MODIS LAI observations and the dynamic global vegetation model SEIB-DGVM over Siberia | Hazuki Arakida | |
| 14:30 - 14:45 | MGI30-04 | Inversion of the ocean vertical diffusivity from steady-state tracer distributions by using an adjoint method | Akira Oka | |
| 14:45 - 15:00 | MGI30-05 | Nonlinear data assimilation with 4DEnVar using iterative weather forecast model | Sho Yokota | |
| 15:00 - 15:15 | MGI30-06 | Development of Data Assimilation System for Atmospheric Density to Improve Satellite's Orbit Prediction Accuracy | Hiroshi Kato | |
| Oral Presentation May 29 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 | Shun Ohishi | |
| 15:45 - 16:00 | MGI30-08 | Validation of JCOPE-T DA ocean assimilation product | Tsutomu Hihara | |
| 16:00 - 16:15 | MGI30-09 | Do surface lateral flows matter for land data assimilation?: Implication for hyper-resolution land modeling and observation | Yohei Sawada | |
| 16:15 - 16:30 | MGI30-10 | Geodynamo data assimilation for candidate models of IGRF13-SV from Japan team | Takuto Minami | |
| 16:30 - 16:45 | MGI30-11 | A pilot study of geomagnetic data assimilation into a geodynamo model | Shin ya Nakano | |
| 16:45 - 17:00 | MGI30-12 | Bayesian parameter estimation of a physics-based model of postseismic crustal deformation | Jun'ichi Fukuda | |
| Presentation No | Title | Presenter | Abstract |
|---|---|---|---|
| Poster Presentation May 29 AM2 | |||
| MGI30-P01 | Superposition of atmospheric states using information redundancy for Numerical Weather Prediction | Toshiyuki Ishibashi | |
| MGI30-P02 | Numerical Weather Prediction Experiments using a Coupled Atmosphere-Ocean Data Assimilation System in JMA/MRI (3) | Toshiyuki Ishibashi | |
| MGI30-P03 | Accurate estimation of posterior error covariance in a 4D-Var inverse analysis | Yosuke Niwa | |
| MGI30-P04 | Assimilation CO2 concentration data in the Kanto region using AIST-MM model and for the estimation of CO2 emissions | Yutaka Arai | |
| MGI30-P05 | Application of data assimilation method on parameter estimation of flow and nutrient behavior in watershed model | Yosuke Horie | |
| MGI30-P06 | Bayesian inference of grain growth prediction via multi-phase-field models | Shin-ichi Ito | |
| MGI30-P07 | GNSS data assimilation for the Bungo channel Long-term SSEs using Ensemble Kalman Filter (EnKF) | Megumi Fujita | |
| MGI30-P08 | A data assimilation library with Python for parallel computing | Shin ya Nakano | |