Comparison of global net primary production trends obtained from satellite-based normalized difference vegetation index and carbon cycle model
Article first published online: 21 SEP 2012
Copyright 2001 by the American Geophysical Union.
Global Biogeochemical Cycles
Volume 15, Issue 2, pages 351–363, June 2001
How to Cite
2001), Comparison of global net primary production trends obtained from satellite-based normalized difference vegetation index and carbon cycle model, Global Biogeochem. Cycles, 15(2), 351–363, doi:10.1029/2000GB001296., , , and (
- Issue published online: 21 SEP 2012
- Article first published online: 21 SEP 2012
- Manuscript Accepted: 21 DEC 2000
- Manuscript Received: 5 MAY 2000
The global terrestrial net primary production (NPP) trend was estimated from two independent methods, satellite observation data and a carbon cycle model, and the results were compared for validation. The satellite-based NPP trend was estimated from the incoming surface solar radiation data set and a National Oceanic and Atmospheric Administration/ Advanced Very High Resolution Radiometer data set that was corrected by normalized difference vegetation index in areas of desert and dense vegetation. The increase in NPP from the Goddard Institute for Space Studies solar radiation data set and from the LaRC solar radiation data set over 10 years in the 1980s was estimated to be 1.8 and 4.4%, respectively. The NPP trend based on a carbon cycle model was estimated from a simple carbon cycle model that was established for the period 1850–1990 with biospheric and oceanic carbon cycle history constraints. The historical trend obtained from the model correlates well with the time variation of not only the observed atmospheric CO2 but also the biospheric and oceanic carbon cycle history. Terrestrial NPP shows an increasing trend beginning in 1930 and is estimated to increase at a rate of 1.1% over the 10-year period in the 1980s. Although all these methods show a recent increase in NPP, satellite-based estimation using the LaRC data set shows a larger trend than the others. A comparison of he trends estimated by these methods indicates that it is necessary to improve the accuracy of incoming surface radiation data, CO2 emission history from changes in land-use change and model structure.