JpGU Meeting 2025
Session Outline| Multidisciplinary and Interdisciplinary (M) | ||||
|---|---|---|---|---|
| Session Sub-category | General Geosciences, Information Geosciences & Simulations (GI) | |||
| Session ID | M-GI26 | |||
| Session Title | Data assimilation: A fundamental approach in geosciences | |||
| Short Title | Data assimilation | |||
| Date & Time | Oral Session |
AM1-AM2 Fri, 30 MAY | ||
| On-site Poster Coretime |
PM3 Fri. 30 MAY | |||
| 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 (Session Description) |
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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| Session Format | Orals and Posters session | |||
| Co-sponsorship | Partner Union(s) | - | ||
| JpGU Society Member(s) | The Oceanographic Society of Japan, Meteorological Society of Japan, The Seismological Society of Japan, Society of Geomagnetism and Earth, Planetary and Space Sciences | |||
| International Collaborative Society | - | |||
| Organizations Other Than JpGU Society Members | - | |||
| 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 |