2010 Fiscal Year Final Research Report
Predictability of atmospheric minor constituents validated by a high-performance data assimilation system
| Project/Area Number |
20740275
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| Research Category |
Grant-in-Aid for Young Scientists (B)
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| Allocation Type | Single-year Grants |
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| Research Field |
Meteorology/Physical oceanography/Hydrology
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| Research Institution | Japan, Meteorological Research Institute |
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Principal Investigator |
SEKIYAMA Tsuyoshi Japan, Meteorological Research Institute, 環境・応用気象研究部, 主任研究官 (90354498)
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| Research Collaborator |
MAKI Takashi 気象庁気象研究所, 環境・応用気象研究部, 主任研究官
TANAKA Taichu 気象庁気象研究所, 環境・応用気象研究部, 主任研究官
DEUSHI Makoto 気象庁気象研究所, 環境・応用気象研究部, 研究官
SHIMIZU Atsushi 国立環境研究所, アジア自然共生研究グループ, 主任研究員
MIYOSHI Takemasa メリーランド大学, 大気海洋科学部, 助教
ARELLANO Avelino F., Jr アリゾナ大学, 大気科学部, 助教
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| Project Period (FY) |
2008 – 2010
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| Keywords | 大気化学 / データ同化 |
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| Research Abstract |
We developed a data assimilation system for atmospheric minor constituents using the Ensemble Kalman filter that is an advanced mathematical statistic scheme. Data assimilation is an informational technology, which merges model simulation results and observation results. The analyses of stratospheric ozone and tropospheric aerosol concentrations were calculated by this data assimilation system. We performed numerical hindcast simulations of the ozone layer and dust aerosol using those analyses as initial conditions. Consequently, the ozone/dust predictability in several hours/several days was evidently improved.
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[Journal Article]2011
Author(s)
Sekiyama, T.T., T.Y. Tanaka, T.Maki, M.Mikami
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Journal Title
Scientific Online Letters on the Atmosphere 7A
Pages: 40-43
Peer Reviewed
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