Comparing terrestrial carbon fluxes from the scale of a flux tower to the global scale

T. Sasai, K. Okamoto, T. Hiyama, Y. Yamaguchi

Research output: Contribution to journalArticlepeer-review

39 Citations (Scopus)


There are a number of outstanding important issues in terms of estimating terrestrial carbon fluxes; one of these is the spatial scaling issue. The purpose of the present study is to document the spatial scaling effect in terms of the terrestrial carbon flux measured at the point-scale and satellite-driven modeling at the global scale. To achieve this, the biosphere model BEAMS was used at the point, regional, and global scales using the same model conditions and parameters; we then compared the BEAMS output for the three different scales and ground measurements. The three sets of results showed reasonably similar spatial and temporal patterns. Temporal variations in the estimated GPP at point-scale showed good agreement with the ground measurements (R2 = 0.84). The spatial distributions of the annual mean GPP and NPP at the regional-scale revealed high values over hilly areas and plateaus, gradually decreasing toward urban areas and high mountains. Ground-observed, point-scale, and regional-scale GPP values show almost identical seasonal patterns. The correlation coefficient for the regional-scale and global-scale monthly mean NPP values is 0.77. In particular, the NPP calculated at the different scales for three areas showed a strong correlation (R2 = 0.81). As ground measurements are strongly reflected in the output of the global-scale simulation, we conclude that model validation at the point-scale is important when performing global-scale simulations.

Original languageEnglish
Pages (from-to)135-144
Number of pages10
JournalEcological Modelling
Issue number2-4
Publication statusPublished - 2007 Nov 10
Externally publishedYes


  • Biosphere model
  • Carbon cycle
  • GPP
  • Ground measurement
  • NPP
  • Remote sensing
  • Scaling issue
  • Terrestrial carbon flux

ASJC Scopus subject areas

  • Ecological Modelling


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