The FASIR NDVI data set described by Sietse Los was used by Myneni to estimate global gross primary production and to investigate the relationship with El Niño Southern Oscillation (ENSO) induced land precipitation anomalies, using the FASIR NDVI data as a surrogate for precipitation in arid and semi-arid regions of Australia, Africa, and South America. In addition, in an attempt to derive land cover classes consistent with radiative transfer theory, a simplified land cover classification scheme was developed which contained six global classes.
Gross primary production was estimated using the FASIR NDVI to represent Leaf Area Index and coupled with Photosynthetically Active Radiation data set. Assuming net primary production to be proportional to gross primary production (GPP), the results show that heterotrophic respiration and GPP respond similarly to climate, but with different magnitudes.
Significant variations in global GPP were observed for the 1982-1990 time period evaluated, including variations seemingly closely associated with the major 1982-1990 ENSO cycle sea surface temperature (SST) anomalies in the tropical Pacific. This then lead Myneni and co-workers to investigate the possible ENSO-NDVI relationship in order to determine the magnitude of natural variations resulting from SST anomalies on vegetation. There were four major ENSO cycle SST anomalies during the 1982-1990 time period; these two cooling events and two warming events are shown in Figure 9.1.
Spatially-continuous ENSO-precipitation anomalies were investigated for Africa, Australia, and South America using SST data and the GIMMS NDVI continental 7.6 km data for the 1982-1990 time period. The operating assumption is that NDVI data are highly correlated to precipitation data up to ~1000 mm/yr; thus this analysis is restricted to the arid and semi-arid zones of the 3 continents studied. Africa, Australia, and South America were selected for study as they are adjacent to the 5° N to 5° S from 90° W to 150° W SST area of the tropical Pacific (also referred to as the "Niño3" area).
NDVI anomalies were calculated by month from 1982 to 1990 at each 7.6 km pixel for the 3 continents and then correlated with the Niño3 SST anomalies for four 12-month periods during the SST anomalies; each of the 12-month periods corresponded to the Southern Hemisphere summer. The SST-NDVI anomalies were then summarized for the 4 ENSO cycle SST anomalies and represented where they occurred on the 3 continents, as shown in Figure 9.2, as darker areas.
Calculation of the areas affected by the NDVI-ENSO cycle anomalies revealed that sizable areas were affected by the 4 SST anomalies during the 1982-1990 time period (Table 9.1). These included areas of Northeastern Brazil which ranged in area from 360,000 to 1,000,000 km2; an area of 1,700,000 km2 in Southeastern South America which was strongly affected by the 1988 SST cooling; and an area of 1,700000 km 2 in Australia which was heavily affected in the 1982-1983 ENSO cycle SST warming. These results are indicative of the magnitude of impacts natural forcings can have on the global climate system through SST-related precipitation anomalies.
While the areas affected by the ENSO cycle precipitation anomalies always recover within several years following the anomaly, severe drought in Northeastern Brazil is reported to have caused the migration of up to 500,000 people into the Amazon Basin of Brazil. Once in Amazonia, these recent immigrants were responsible for increasing tropical deforestation. Thus, climatic variation in arid and semi-arid areas can indirectly influence human alteration of the natural environment.
This analysis will be extended from 1991-1995 when the processed satellite data become available. At the moment, there is a great deal of confusion in the ENSO cycle modeling community as none of the models can explain what is happening with ENSO cycle anomalies in the 1990s.
The land cover classification described by Myneni is based on radiative transfer theory. Six biome types are defined by the fact that structure is what effects radiation. The biomes are: grasses and cereal crops, broadleaf crops, shrub-desert, savanna, leaf forest, and needle forest. The characteristics of these biomes are as follows:
Biome 1 / grasses and cereal crops
Biome 2 / shrublands
Biome 3 / broadleaf crops
Biome 4 / Savanna (grass cover with tree cover)
Biome 5 / Leaf forests
Biome 6 / Needle forests
A combination of red, near infrared, and NDVI measurements from ±40 degrees can be used to spectrally separate the 6 proposed "radiative transfer biomes."