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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 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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