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NASA NTRS2001

Higher northern latitude normalized difference vegetation index and growing season trends from 1982 to 1999

Normalized difference vegetation index data from the polar-orbiting National Oceanic and Atmospheric Administration meteorological satellites from 1982 to 1999 show significant variations in photosynthetic activity and growing season length at latitudes above 35 degrees N. Two distinct periods of increasing plant growth are apparent: 1982-1991 and 1992-1999, separated by a reduction from 1991 to 1992 associated with global cooling resulting from the volcanic eruption of Mt. Pinatubo in June 1991. The average May to September normalized difference vegetation index from 45 degrees N to 75 degrees N increased by 9% from 1982 to 1991, decreased by 5% from 1991 to 1992, and increased by 8% from 1992 to 1999. Variations in the normalized difference vegetation index were associated with variations in the start of the growing season of -5.6, +3.9, and -1.7 days respectively, for the three time periods. Our results support surface temperature increases within the same period at higher northern latitudes where temperature limits plant growth.

Ecosystem↗

NASA NTRS1999

Sensitivity of Climate to Changes in NDVI

The sensitivity of global and regional climate to changes in vegetation density is investigated using a coupled biosphere-atmosphere model. The magnitude of the vegetation changes and their spatial distribution are based on natural decadal variability of the normalized difference vegetation index (ndvi). Different scenarios using maximum and minimum vegetation cover were derived from satellite records spanning the period 1982-1990. Albedo decreased in the northern latitudes and increased in the tropics with increased ndvi. The increase in vegetation density revealed that the vegetation's physiological response was constrained by the limits of the available water resources. The difference between the maximum and minimum vegetation scenarios resulted in a 46% increase in absorbed visible solar radiation and a similar increase in gross photosynthetic C02 uptake on a global annual basis. This caused the canopy transpiration and interception fluxes to increase, and reduced those from the soil. The redistribution of the surface energy fluxes substantially reduced the Bowen ratio during the growing season, resulting in cooler and moister near-surface climate, except when soil moisture was limiting. Important effects of increased vegetation on climate are : (1) A cooling of about 1.8 K in the northern latitudes during the growing season and a slight warming during the winter, which is primarily due to the masking of high albedo of snow by a denser canopy. and (2) A year round cooling of 0.8 K in the tropics. These results suggest that increases in vegetation density could partially compensate for parallel increases in greenhouse warming . Increasing vegetation density globally caused both evapotranspiration and precipitation to increase. Evapotranspiration, however increased more than precipitation resulting in a global soil-water deficit of about 15 %. A spectral analysis on the simulated results showed that changes in the state of vegetation could affect the low-frequency modes of the precipitation distribution and might reduce its low frequency variability in the tropics while increasing it in northern latitudes.

Bounoua, L.↗

NASA NTRS1991

Mean and inter-year variation of growing-season normalized difference vegetation index for the Sahel 1981-1989

Images are presented that show the mean and coefficient of variation of nine years (1981-1989) of NOAA AVHRR normalized difference vegetation index (NDVI) data for the growing season (July-October) in Africa, north of the equator. The variation in the growing season NDVI is represented by the coefficient of variation image that shows the large variation in the Sahelian growing season between years. It is concluded that these images illustrate some aspects of the perspective being brought to regional and continental scale processes by coarse resolution satellite sensors and the potential of these sensors to provide consistent, long-term datasets.

Tucker, C. J.↗