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タイトル: Non-Gaussian data assimilation of satellite-based leaf area index observations with an individual-based dynamic global vegetation model
著者: Arakida, Hazuki
Miyoshi, Takemasa
Ise, Takeshi  kyouindb  KAKEN_id  orcid https://orcid.org/0000-0003-4331-5144 (unconfirmed)
Shima, Shin-ichiro
Kotsuki, Shunji
著者名の別形: 伊勢, 武史
発行日: Sep-2017
出版者: Copernicus GmbH
誌名: Nonlinear Processes in Geophysics
巻: 24
号: 3
開始ページ: 553
終了ページ: 567
抄録: We developed a data assimilation system based on a particle filter approach with the spatially explicit individual-based dynamic global vegetation model (SEIB-DGVM). We first performed an idealized observing system simulation experiment to evaluate the impact of assimilating the leaf area index (LAI) data every 4 days, simulating the satellite-based LAI. Although we assimilated only LAI as a whole, the tree and grass LAIs were estimated separately with high accuracy. Uncertain model parameters and other state variables were also estimated accurately. Therefore, we extended the experiment to the real world using the real Moderate Resolution Imaging Spectroradiometer (MODIS) LAI data and obtained promising results.
著作権等: © Author(s) 2017. This work is distributed under the Creative Commons Attribution 3.0 License.
URI: http://hdl.handle.net/2433/259312
DOI(出版社版): 10.5194/npg-24-553-2017
出現コレクション:学術雑誌掲載論文等

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