Journal cover Journal topic
Nonlinear Processes in Geophysics An interactive open-access journal of the European Geosciences Union

Journal metrics

  • IF value: 1.329 IF 1.329
  • IF 5-year<br/> value: 1.394 IF 5-year
    1.394
  • CiteScore<br/> value: 1.27 CiteScore
    1.27
  • SNIP value: 0.903 SNIP 0.903
  • SJR value: 0.709 SJR 0.709
  • IPP value: 1.455 IPP 1.455
  • h5-index value: 20 h5-index 20
Nonlin. Processes Geophys., 24, 553-567, 2017
https://doi.org/10.5194/npg-24-553-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
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 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.

Citation: Arakida, H., Miyoshi, T., Ise, T., Shima, S.-I., and Kotsuki, S.: Non-Gaussian data assimilation of satellite-based leaf area index observations with an individual-based dynamic global vegetation model, Nonlin. Processes Geophys., 24, 553-567, https://doi.org/10.5194/npg-24-553-2017, 2017.
Publications Copernicus
Download
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...
Share