Analysis of a multiyear global vegetation leaf area index data set

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Abstract
The analysis of a global data set of monthly leaf area index (LAI), derived from satellite observations of normalized difference vegetation index (NDVI) for the period July 1981 to September 1994, is discussed in this paper. Validation of this retroactive, coarse resolution (8 km) global multiyear data set is a challenging task because repetitive ground measurements from all representative vegetation types are not available. Therefore the magnitudes and interannual variations in the derived LAI fields were assessed as follows. First, the use of a NDVI‐based algorithm, as opposed to a more physically based approach, is estimated to result in relative errors in LAI of about 10–20%, which is comparable to the mean uncertainty of AVHRR NDVI data. Second, the satellite LAI values compared reasonably well to ground measurements from three field campaigns. Third, comparison with an existing multiyear LAI data set showed qualitative agreement with regards to interannual variability, although the LAI values of the earlier data were consistently larger than those derived here. Fourth, interannual variations in LAI were evaluated through correlations with climate data sets, e.g., sea surface temperatures and precipitation in tropical semiarid regions known for ENSO impacts, temperature dependence of vegetation growth, and therefore LAI, in the northern latitudes. The general consistency between these independent data sets imbues confidence in the LAI data set, at least for use in large‐scale modeling studies. Finally, improvements in near‐surface climate simulation are documented in a companion article when satellite LAI values were used in a global climate model. The data set is available to the community via our Web server (http://cybele.bu.edu).