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TRANSITION
FROM EL NIÑO TO LA NIÑA AFFECTED VEGETATION
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NASA
scientists using satellite data have shown that shifts in
rainfall patterns from one of the strongest El Niño
events of the century in 1997 to a La Niña event in
2000 significantly changed vegetation patterns over Africa.
Assaf
Anyamba and Compton Tucker of NASA's Goddard Space Flight
Center, Greenbelt Md., and Robert Mahoney of Global Science
and Technology Inc (GST) analyzed satellite derived images
of vegetation from 1997 to 2000. They noticed regions of above
normal "greenness" over East Africa associated with
patterns of above normal rainfall during the 1997-1998 El
Niño event. At the same time, they observed below normal
"greenness" over southern Africa associated below
normal rainfall conditions there.
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During
the transition to La Niña, rainfall patterns reversed.
Southern Africa experienced above normal rainfall and East
Africa received below normal rainfall, resulting in a corresponding
reversal of vegetation greenness patterns.
"These
changes vegetation patterns have implications for agriculture,
livestock farming and vector borne disease outbreaks especially
is semi-arid land of Africa," Anyamba said. "Above
normal vegetation conditions are an indicator of improved
pasture conditions which boosts livestock production in these
areas."
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In
addition, it is also an indicator of the likelihood of bumper
harvests. Agricultural production in these areas rises and
wanes to the tune of the El Niño -Southern Oscillation
(ENSO) patterns as revealed here by changes in vegetation
patterns during years of above normal and below normal rainfall.
During above normal rainfall, vegetation conditions provide
habitats necessary for the breeding of vector borne diseases
such as Malaria Rift Valley Fever as was the case in 1997/98
in East Africa.
Satellite
monitoring and mapping the extent of such anomalies in vegetation
conditions can provide useful early warning information for
drought, agriculture and vector borne disease outbreaks to
prevent disaster situations.
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Anyamba
and his colleagues analyzed 20 years of Normalized Difference
Vegetation Index (NDVI) data to determine changes in vegetation
greenness patterns. Tucker, a co-author of the report, developed
the NDVI data to monitor vegetation using orbiting weather
satellites.
The
NDVI data is derived from the Advanced Very High Resolution
Radiometer (AVHRR) instrument flown aboard the National Oceanic
and Atmospheric Administration's (NOAA) polar orbiting satellites.
NDVI
measures vegetation "greenness" or plant health
based on the principle that plants prefer to use (absorb)
visible red colors (wavelengths) of sunlight for photosynthesis
during growth. For example, a healthy plant will absorb more
visible red sunlight for photosynthesis and reflect less back
to space. A plant stressed by drought will photosynthesize
less and reflect more sunlight back to space. A satellite
can measure the amount of sunlight reflected in the red and
near infrared spectrum and the NDVI can be computed to provide
a relative measure of greenness or plant health that can be
displayed as an image.
El
Niño and La Niña events are both part of a cycle
of recurring warmings and coolings of the ocean surface in
the central and eastern Pacific known as the El Niño
Southern Oscillation (ENSO). El Niño refers to the
warm phase of the oscillation and La Niña refers to
the cool phase. Each of these phases affects weather patterns
worldwide and changes in rainfall can impact vegetation patterns.
Above
normal rainfall during the 1997-1998 El Niño in East
Africa and during the 1999-2000 La Niña in southern
Africa improved pasture conditions in those areas, but also
caused widespread flooding and disease outbreaks. The drought
that followed in East Africa during the 1999 to 2000 La Niña
was devastating and caused widespread famine.
This
work was made possible through funding by NASA Headquarters'
Earth Science Enterprise, dedicated to better understanding
and protecting our home planet, as well as the United States
Agency for International Development/Famine Early Warning
System Network programs.
The
findings appear in the November 1 issue of the American Meteorological
Society's Journal of Climate (Vol. 15, Issue 21: 3096-3103,
2002).
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