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Nonlinear Processes in Geophysics An interactive open-access journal of the European Geosciences Union
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Volume 24, issue 3 | Copyright
Nonlin. Processes Geophys., 24, 553-567, 2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 06 Sep 2017

Research article | 06 Sep 2017

Non-Gaussian data assimilation of satellite-based leaf area index observations with an individual-based dynamic global vegetation model

Hazuki Arakida1, Takemasa Miyoshi1,2,3, Takeshi Ise4, Shin-ichiro Shima1,5, and Shunji Kotsuki1 Hazuki Arakida et al.
  • 1RIKEN Advanced Institute for Computational Science, Kobe, 650-0047, Japan
  • 2Department of Atmospheric and Oceanic Science, University of Maryland, College Park, MD 20742, USA
  • 3Application Laboratory, Japan Agency for Marine-Earth Science and Technology, Yokohama, 236-0001, Japan
  • 4Field Science Education and Research Center, Kyoto University, Kyoto, 606-8502, Japan
  • 5Graduate School of Simulation Studies, University of Hyogo, Kobe, 650-0047, Japan

Abstract. 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.

Publications Copernicus
Short summary
This is the first study assimilating the satellite-based leaf area index observations every 4 days into a numerical model simulating the growth and death of individual plants. The newly developed data assimilation system successfully reduced the uncertainties of the model parameters related to phenology and carbon dynamics. It also provides better estimates of the present vegetation structure which can be used as the initial states for the simulation of the future vegetation change.
This is the first study assimilating the satellite-based leaf area index observations every 4...