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 Uses of Predictions Peru provides a prime example of how even short term El Niņo forecasts can be valuable. There, as in most developing countries in the tropics, the economy (food production, in particular) is highly sensitive to climate fluctuations. Year-to-year swings between above and below normal sea surface temperature along the Peru coast produce a wide range of local impacts. Warm (El Niņo) years tend to be unfavorable for fishing and some of them have been marked by damaging floods along the coastal plain and in the western Andean foothills in the northern part of the country. Cold years are welcomed by fisherman, but not by farmers because there years have frequently been marked by drought and crop failures. Such cold years often come on the heels of strong El Niņo events. Hence, Peruvians have reason to be concerned, not only about El Niņo events, but about both extremes of the El Niņo cycle. Before the flood waters from the record breaking 1982-83 El Niņo event had fully receded, farmers in Peru were already beginning to worry that SST might drop below normal the following year, bringing drought and crop failures. It was at this time that the Peruvian government decided to develop a program to forecast future climate swings.
Heavy rain can cause damages to not only people but also crops. The first task was to make a forecast for the next rainy season, which was expected to occur in early 1984. Information available in early November 1983 indicated that the climatic conditions in the equatorial Pacific were near normal and were likely to remain so through the rainy season, producing favorable conditions for agriculture. This information was conveyed to numerous organizations and to the Minister of Agriculture, who incorporated it into the planning for the 1983-1984 growing season. The forecast proved to be correct, and the harvest was an abundant one. Since that time, forecasts of the upcoming rainy season have been issued each November based on observations of winds and water temperature in the tropical Pacific region and the output of the numerical prediction models. The forecasts are presented in terms of four possibilities: (1) near normal conditions, (2) a weak El Niņo with a slightly wetter than normal growing season, (3) a full blown El Niņo with flooding, and (4) cooler than normal waters offshore, with higher than normal chance of drought. Once the forecast is issued, farmers’ representatives and government officials meet to decide on the appropriate combination of crops to sow in order to maximize the overall yield. Rice and cotton, two of the primary crops grown in northern Peru, are highly sensitive to the quantities and timing of rainfall. Rice thrives on wet conditions during the growing season followed by drier conditions during the ripening phase. Cotton, with its deeper root system, can tolerate drier weather. Hence, a forecast of El Niņo weather might induce farmers to sow more rice and less cotton than in a year without El Niņo.
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