In a natural disaster—a hurricane,flood,tornado,volcanic eruption,or other calamity—minutes and even seconds of warning can be the difference between life and death.Because of this,scientists and government officials are working to use the latest technological advances to predict when and where disasters will happen.They are also studying how best to analyze and communicate this information once it is obtained.The goal is to put technology to effective use in saving lives and property when nature unleashes its power with devastating results. On September 29,1998,Hurricane Georges made landfall in Biloxi,Mississippi,after devastating Haiti,the Dominican Republic,Puerto Rico,and several islands of the Caribbean with torrential rains and winds up to 160 km/h (100 mph).Few people lost their lives along the Gulf Coast of the United States,although hundreds died in the Caribbean. This was a very different outcome from 1900,when a powerful Gulf Coast hurricane made an unexpected direct hit on Galveston,Texas,killing at least 6 000 people.Vastly improved hurricane warnings explain the different circumstances at either end of the 20th century—residents of Galveston had no advance warning that a storm was approaching,while residents of Biloxi had been warned days in advance of Georges’s approach,allowing for extensive safety precautions. At the same time that people in Biloxi were thankful for the advance warning,some residents of New Orleans,Louisiana,120 km to the west,were less satisfied.A day before Georges made landfall,forecasters were predicting that the hurricane had a good chance of striking New Orleans.Because much of New Orleans lies below sea level,the city is at risk for flooding.In addition,because New Orleans has a large population in vulnerable locations,emergency management officials must begin evacuations well before a storm strikes.But evacuation costs money:Businesses close,tourists leave,and citizens take precautionary measures.The mayor of New Orleans estimated that his city’s preparations for Georges cost more than 50 million.After the full fury of Georges missed New Orleans,some residents questioned the value of the hurricane forecasts in the face of such high costs. The differing views on the early warnings for Hurricane Georges illustrate some of the complexities involved in predicting disasters.Disaster prediction is more than just forecasting the future with advanced technology—it is also a process of providing scientific information to the government officials and other decision makers who must respond to those predictions. In general,the process has three phases.First,there is the challenge of forecasting the event itself.In the case of Georges,scientists worked to predict the future direction and strength of the hurricane days in advance. A second important challenge is communicating the forecast to decision-makers.Because forecasts are always uncertain,a central factor in disaster predictions is communicating this uncertainty.Uncertainty is usually described in terms of odds or probabilities,much like daily weather forecasts.The media plays an important role in communicating predictions and their uncertainty to the public. The third part of the process is the use of predictive information by decision makers.Even the most accurate information is of little value if the decision maker does not use it appropriately,for example in deciding whether to order an evacuation.If there is a breakdown in any of these three phases of prediction,the result is increased danger and a higher risk of loss of life. 小题1:The underlined word“calamity”refers to ______.A.nature | B.thunderstorms | C.disaster | D.dangers | 小题2:According the passage,the purpose of disaster prediction is to______.A.demonstrate the power of advanced technology | B.bring out the truth between life and death | C.prevent such natural disasters from happening | D.reduce human casualties and loss of property | 小题3:Which of the following areas suffered the most severe damage?A.Biloxi,Mississippi. | B.Gulf Coast of U. S. | C.Galveston,Texas. | D.New Orleans. |
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