At international levels, there are groups that alert user communities to environmental changes. For example, the World Meteorological Organization's (WMO) early-warning system (www.wmo.org; chapter 31) is composed of weather satellites and thousands of surface monitors. This system has helped predict long-term droughts and provided information for other human-induced disasters.
Another example of early warning at the international scale is FAO's Global Information and Early Warning System (GIEWS; chapter 32). The GIEWS reports the production, stocks, and trade of cereals and other basic food commodities through an analysis of trends and prospects. These reports vary with need and often contain analysis and statistical information on developments in world cereal markets and export prices. These reports also include the impact of El Niño and La Niña on food grain production and reveal trends in any food emergencies around the world.
GIEWS provides an example of how international early warning systems are ultimately truly interconnected to many other international efforts, many benefiting from the efforts and expertise of other groups. GIEWS maintains connections with many other international bodies: (1) the United Nations High Commissioner for Refugees, which supplies data on refugee numbers, (2) the WMO, which provides climate and weather data, (3) the International Labor Organization, which provides information on unemployment and poverty, (4) the United Nations Children's Fund, (5) the International Grains Council, which provides information on the global market, export prices, and freight rates, (6) the Organization for Economic Co-operation and Development, (7) the World Bank and International Monetary Fund, and (8) UNEP's Global Resource Information Database.
The NOAA Climate Prediction Center/ National Centers for Environmental Prediction takes on the task of monitoring El Nino/Southern Oscillation (ENSO) conditions and passing the results and warnings on to user communities (http://www.cpc.ncep.noaa.gov/index.html). As an example, researchers at Clark University have been using normalized difference vegetation index time-series data in conjunction with ENSO data to help predict drought conditions in eastern Africa (www.clarku.edu). One of the early warning systems that provides crucial information to both countries and large regions is the Famine Early Warning System (chapter 19).
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