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The means of forecasting natural disasters, such as floods, hurricanes, tornadoes, and tsunamis, and of communicating disaster information to the public, have improved immensely as science and technology have advanced. In this November 1998 Encarta Yearbook article, Roger A. Pielke, Jr., a scientist at the National Center for Atmospheric Research (NCAR) in Boulder, Colorado, warns that although their methods are more reliable now than ever, forecasters will never be able to predict disasters with absolute certainty. Pielke stresses the importance of public awareness and planning in minimizing the havoc that disasters can wreak.
By Roger A. Pielke, Jr.
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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.
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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 6000 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 (75 mi) 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.
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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.
People have always sought to understand what the future might bring, particularly with respect to disasters such as hurricanes, earthquakes, and floods. But only in the 20th century have science and technology systematically provided society with reliable information about impending disasters. Not so long ago, people relied on necromancers (people who claim to tell the future by communicating with the dead), astrologists, and even the casting of oracle bones (equivalent to rolling dice) to prepare for impending catastrophes.
People have been attempting to scientifically predict disasters for many years, however. Flood prediction had its beginnings in the late 18th century. The first official tornado predictions were issued in the United States in 1948. In the 1960s hurricane prediction became reliable with the deployment of geostationary satellites (satellites that remain in constant orbit above the same spot on Earth). Recent years have seen even greater advances in these and other areas of the science behind predicting hurricanes, tornadoes, floods, earthquakes, tsunamis, and volcanoes. Science and technology hold the promise for continued advancements in the 21st century, but learning how to effectively use, and avoid misuse of, predictive information will become increasingly important.
A hurricane is a migratory tropical cyclone that originates over oceans in certain regions near the equator. The modern era of hurricane forecasting began in the 1960s, when satellites allowed continuous monitoring of hurricanes from space. Today, people who live on coastlines and islands vulnerable to the impacts of hurricanes pay close attention to the forecasts of a hurricane's intensity and track, or path. Hurricane forecasts are an important element in decisions to secure property, warn and evacuate populations, and initiate relief operations in affected areas.
In the United States, official hurricane forecasts are issued by the National Hurricane Center, located in south Florida. An official forecast is the result of calculations performed by a number of complex computer models that project the future path and strength of a particular storm. Different computer models will often give differing results. When this occurs, the forecaster draws on individual and collective expertise and experience to arrive at the forecast that is issued to the public.
Over the past 30 years forecasters have seen a slow but steady improvement in the accuracy of hurricane track forecasts, averaging about 1 percent greater accuracy per year. For example, in 1997 the average error—the difference between where a hurricane is forecasted and where it actually goes—in a track forecast made for 24 hours into the future was about 185 km (about 115 mi). At 72 hours in advance, the average forecast error was about 555 km (about 345 mi). The forecasts of hurricane intensity, however, have not improved as much.
Because the predictions are still imprecise and because so many people live along coastlines, it takes considerable time to complete an evacuation before winds begin to get strong. For instance, prior to Hurricane Andrew's 1992 landfall south of Miami, Florida, it was estimated that 25 hours would be needed to clear the vulnerable area in preparation for an approaching storm. Evacuations during that powerful storm probably saved hundreds of lives. Clearance times vary for locations along the coast, depending on the size of the population at risk, the roads on which people will drive to safety, and the willingness of people to evacuate.
The factors of forecast error and evacuation time mean that forecasters must issue hurricane warnings for an area much larger than the storm will actually affect. This policy is known as overwarning. To protect lives, it will always be necessary to overwarn—but how much overwarning is appropriate? The answer depends on society's willingness to balance risks and costs. Improvements in forecasts therefore hold the promise of reducing the need for overwarning and the associated costs and inconveniences.
Computer models are only as good as the data that are fed into them, and scientists expect that hurricane prediction could improve in the future as a result of better data gathered by aircraft reconnaissance. The 53rd Weather Reconnaissance Squadron, a United States Air Force Reserve unit known as the Hurricane Hunters, has flown aircraft into hurricanes since the 1940s to gather data for forecasters to use in their computer models.
In the last several years the Hurricane Research Division of the National Oceanic and Atmospheric Administration (NOAA) has initiated a research project to help predict the behavior of hurricanes. Pilots fly aircraft into and around storms, deploying advanced technologies such as Global Positioning System dropwindsondes, instruments that measure air pressure, temperature, humidity and wind speed and direction. Once dropped into the storm, these instruments send a stream of information back to the aircraft as they fall. Other emerging technologies include remote sensing devices such as airborne Doppler radar, which measures the intensity and direction of precipitation; C-band scatterometer, which measures wind speeds; and stepped frequency microwave radiometer, which takes measurements using microwaves. Scientists expect that the knowledge gained from these technologies will make hurricane prediction even more accurate in the years to come.
Forecasts are also available for seasonal hurricane activity. Seasonal forecasts predict factors such as the overall number of storms. Led by the efforts of atmospheric scientist William Gray and his team at Colorado State University in Fort Collins, scientists are able to make such predictions up to a year in advance using complex statistical models. These models are based on such information as the strong connection between hurricane activity and atmospheric factors such as El Niño (the warming of the Pacific Ocean, typically occurring every three to seven years). Seasonal forecasting of hurricane activity cannot tell scientists where or when a particular storm will strike, but it can project overall features of a hurricane season, providing useful information to officials in such fields as emergency management and insurance.
A look at the last four years of Atlantic Ocean hurricane activity reveals a period more severe than any on record, and scientists predict more such years in the near future. A longer-term vision of scientists is to predict hurricane activity on time scales of decades or even longer. Until such visions become reality, hurricane preparation will continue to rely on the lessons learned from the past.
More lessons were learned in the fall of 1998 when Hurricane Mitch devastated Nicaragua and Honduras, leaving more than 11,000 people dead and as many as 2 million homeless. The storm developed in late October, and Cuba and Jamaica were first alerted for a possible hit. But Mitch, which at one point reached Level 5 status (the highest level of hurricane strength), skirted these countries and instead bore down on Central America. It then stalled just off the coast of Honduras and weakened into a tropical storm.
Tropical Storm Mitch remained dangerous as a powerful rainmaker, however. It dumped precipitation on Nicaragua and Honduras for several days, causing widespread flooding and mudslides that destroyed whole villages. At times communication broke down between emergency and government officials in the affected countries. Mitch also highlighted the problem of focusing on emergency preparations in coastal areas, as mountain villages were among the most devastated in the two countries due to flash floods caused by heavy rains. Some U.S. officials called Mitch the worst disaster ever seen in the western hemisphere, and in the storm's wake experts called for a new hurricane measuring scale to reflect rain levels as well as wind speeds and to better project potential casualties.
A tornado is a highly concentrated vortex of wind that occurs in extreme thunderstorms. Tornadoes occur all over the world, but are most common west of the Appalachian Mountains and east of the Rocky Mountains, especially in the Great Plains of the United States. Tornadoes are often associated with afternoon or evening thunderstorms and can occur as a result of the intense thunderstorms in hurricanes. The most violent tornadoes boast winds of up to 500 km/h (300 mph), powerful enough to lift a car off the ground or demolish a strongly built house. A tornado's winds can wreak tremendous damage and pose a great threat to human life. In the United States, tornadoes cause billions of dollars in damage and kill about 50 people each year.
Because tornadoes have potential for large impacts and because they can occur with little advance warning, many researchers in the scientific community have made tornado prediction a priority. Scientists do not fully understand tornado formation, so prediction of where and when tornadoes will occur remains difficult. For example, it is generally accepted that the “false alarm” rate for tornadoes is around 80 percent. Tornado warnings are generated by a detection system that has both a high-tech and a human component. The human component is a network of volunteer storm spotters—called SKYWARN—who work with their local communities to identify tornadoes when they occur and then communicate this information to emergency officials. The high-tech aspect of tornado warning is the national Doppler radar network that has made it possible, under certain circumstances, for scientists to “see” a tornado's winds with the high-resolution images provided by these radars. The National Weather Service uses the information provided by spotters and the Doppler radars to issue warnings to the general public via television, radio, and, in some places, tornado sirens.
Scientists are seeking to better understand tornadoes. This requires obtaining improved information about what is going on inside a tornadic thunderstorm. In the mid-1980s the National Severe Storms Laboratory pursued a project, called Totable Tornado Observatory (TOTO), much like that featured in the 1996 motion picture Twister. TOTO was a large drum filled with sensors that was to be placed in the path of an approaching tornado. Unlike the device in the movie, TOTO met with limited success.
Today scientists need not depend on placing equipment directly in the path of a tornado. The Doppler On Wheels (DOW) project of the University of Oklahoma in Norman and the National Center for Atmospheric Research is a more advanced high-tech effort that scientists are relying on to learn what happens inside of a tornado. DOW is a team of sturdy trucks, each with a mobile Doppler radar unit mounted on top. The mobility of these trucks gives them a greater ability to get into position near a severe storm, including areas where hurricanes hit land, in order to document the rare and extremely small-scale phenomena that make up tornadoes. Scientists expect that, with the knowledge gained from projects such as DOW, they can provide more lead time and fewer false alarms in tornado prediction.
Two main types of floods impact society and the environment: river floods and flash floods. Large-scale river flooding occurs over a period of weeks or months and can result in the inundation of hundreds or thousands of square miles. A recent example is the great Midwest flood of 1993 that put 3 million hectares (8 million acres) under water and resulted in more than $19 billion in damages. Flash floods occur over a period of hours as the result of extremely heavy rainfall and can affect very small areas. Flash floods pose great risks to human life. In August 1997 a raging wall of water swept down through Antelope Canyon in Arizona, carrying 11 hikers to their deaths. Twenty years earlier, a flash flood in Colorado killed more than 100 people.
Flood prediction involves consideration of many factors. These include the characteristics of a river basin (such as soil type, ability to hold water, and slope), how water behaves in the river, and meteorology. Another important factor in flood prediction, as with hurricanes, is how people respond to warnings.
For flash floods it is important to observe rainfall rates and the flow of water in a river or stream. Increasingly, scientists track rainfall by using advanced radar systems that can measure where the water falls and with what intensity. They monitor river and stream levels using low-tech gauges positioned at key locations along a channel. This information is put into computer models that calculate the future volume and height of a river at particular locations. As with hurricane forecasts, there is an element of uncertainty in flood forecasts, but less so for flash floods since these occur over very short time periods. Emergency officials frequently warn people to seek high ground immediately if a flash flood warning is issued for their location.
The North Dakota floods of 1997 illustrate some of the difficulties involved with communicating and understanding uncertainties in large-scale flood forecasts. In February 1997, in the midst of heavy rains, officials with the National Weather Service warned that, based on the projections of their hydrologic models, flooding along the Red River of the North would exceed record levels. For one town on the river, Grand Forks, the Weather Service predicted a spring flood crest of 15 m (49 ft), a few inches above the record level and 8 m (26 ft) above the community's flood stage.
In issuing this prediction, weather officials wanted to convey a sense of urgency to decision makers and the general public in the region. For some people in the community, the information had the opposite effect—it generated a sense of complacency because they had successfully fought off floods almost as large before. But the prediction underestimated the flood levels, which eventually crested at more than 16 m (54 ft) in mid-April. The shocked community found itself unprepared for this, and almost the entire town was evacuated. The flood caused more than $2 billion in damages, but fortunately there were no deaths.
A hard-earned lesson of this disaster was that even though the forecast was fairly accurate by scientific standards—within 10 percent of actual peak levels two months in advance—many officials misinterpreted the prediction because of miscommunication and misunderstandings of the forecast's level of uncertainty. Although some officials in Grand Forks tried to blame the initial forecast, the issue was not so much the inaccuracy of the forecast but the lack of comprehension about the accuracy that can be expected in flood forecasts. If the scientific community is to influence disaster prediction, more must be done to make sure information is clearly communicated and appropriately used.
A major U.S. effort in flood prediction in the coming years is the Advance Hydrological Prediction System. This program seeks to provide reliable information on the probabilities of different flood levels, using advanced computer models of river channels as well as improved data collection with technologies such as Doppler radar. It hopes to improve flood predictions for days, weeks, and even months in advance. However, much as with hurricanes, scientists are still unable to say exactly when, where, and to what extent nature will unleash major floods.
Unlike the situation with hurricanes, tornadoes, or floods, there are no storm clouds or rising river levels to foretell an earthquake. Because they hit without advance warning, earthquakes are particularly terrifying. When earthquakes strike, they can cause massive human casualties and large amounts of damage. The January 1994 earthquake in Northridge, California, killed 57 people and injured almost 12,000 others while causing more than $25 billion in damages. But these numbers pale in comparison to what happened in Kōbe, Japan, one year later. The Great Hanshin Earthquake there killed more than 5000 people, left more than 300,000 homeless, and resulted in more than $300 billion in damages.
Because earthquakes have the potential to greatly impact society, the U.S. government embarked on an ambitious program in the 1970s to develop methods for predicting earthquakes. The National Earthquake Hazards Reduction Program sought to develop technologies that would allow for earthquake prediction on time scales of hours to days. Such predictions would not necessarily lead to reduced damage, but the hope was that they could reduce injuries and the loss of life suffered in a large quake. Scientists were optimistic in the beginning, in part due to a number of apparent successes in anticipating some earthquakes in the United States and China. However, earthquake prediction has proved more difficult than expected.
One method of earthquake prediction involves studying the geologic history and noting when previous quakes have occurred. One study of a particular segment of the San Andreas Fault near Parkfield, California, noted that it had experienced four earthquakes over the previous 100 years at intervals of roughly 22 years. Based on this information, scientists predicted in 1984 that the area had a 95 percent likelihood of experiencing a moderate earthquake sometime between 1985 and 1993. As part of the Parkfield experiment, steps were taken to prepare for the expected event, including the development of warning strategies and studies of public response.
Through November 1998, however, no earthquake had occurred in Parkfield, leading many people to conclude that the experiment had been a failure. Joanne Nigg, a sociologist who has studied the Parkfield experiment, concluded that the project was at least somewhat successful in forging links between scientific procedures and policy concerns. Much was learned about publicly issuing earthquake predictions; in particular, that earthquake predictions themselves have important impacts on society. If an earthquake does occur in Parkfield, scientists will be prepared with a dense network of scientific instruments to record the quake and improve knowledge about how and why earthquakes occur.
From the perspective of the late 1990s, it is evident that expecting timely and accurate earthquake predictions was too ambitious. In the mid-1980s the National Earthquake Hazards Reduction Program reported to the U.S. Congress that earthquake prediction was more problematic than had been anticipated. Today scientists are more focused on developing improved estimates of long-term earthquake probabilities, measured in decades or centuries.
The program is also working on early warning systems that detect ground motion after an earthquake has started. This information can be used to warn people farther from the epicenter (the point where the earthquake originates). The goal is to create early warning systems to notify people that a large earthquake has begun, from a few seconds to minutes in advance. This warning could allow some useful actions, such as shutting down or backing up systems in a nuclear power plant. In the early 1990s this type of warning system provided Mexico City about 75 seconds of notice that an earthquake had occurred off the coast.
There are two phenomena related to earthquakes for which scientists are able to provide warnings: tsunamis and volcanoes. Tsunamis, sometime called tidal waves, are large waves usually caused by an earthquake under the ocean floor and can bring mass destruction when they strike land. A tsunami at the end of the 19th century killed more than 20,000 people in Japan, and one in July 1998 in Papua New Guinea left at least 2000 dead, making it the deadliest tsunami of the 20th century.
Tsunamis often have impacts thousands of miles from the spot of the seismic event. For example, if a large enough earthquake occurred off the coast of Alaska, communities on the Alaskan coast could experience a tsunami within 15 minutes. The same earthquake could affect the coasts of Hawaii, Washington, Oregon, and California up to five hours later. Although earthquakes themselves cannot be predicted, the lead time between an earthquake and its related tsunami provides an opportunity to warn the general public.
There are three major tsunami warning systems in operation today. The Pacific Tsunami Warning Center, based near Honolulu, Hawaii, can provide warnings of long-distance tsunamis throughout the Pacific Ocean. The second major system comprises five regional warning systems, two in the United States and one each in Japan, Russia, and French Polynesia. The third consists of local warning systems in Chile and Japan. The U.S. systems include 1000 land-based, real-time seismometers (instruments that measure ground vibrations) that cost about $10 million each year to operate. Some experts think that the United States could be better prepared if it added deep-water tsunami gauges to detect tsunamis in the open ocean and if it had better charting of coastal areas vulnerable to tsunamis. In October 1998 a team of Mexican scientists announced that they had devised a mathematical ratio that allows quicker detection of tsunamis based on seismic data, giving affected areas valuable extra minutes of warning. This system needs more testing, however.
Like tsunamis, volcanoes cannot be predicted until some seismic activity has begun. But once a volcano shows signs of life, scientists are able to deploy an impressive range of technologies to monitor its activity. Such monitoring was instrumental in warning people to evacuate from the region around Mount Saint Helens in Washington state. That volcano erupted in May 1980. Several months before the eruption, scientists with the U.S. Geological Survey noticed increased seismic activity under the volcano. Even with the advance warning, more than 50 people lost their lives in the powerful eruption; however, many others were safely evacuated.
To develop new techniques to improve eruption warnings, the scientific community is looking at technologies such as satellite-based thermal alarms, which detect heat building underneath volcanoes; instruments to measure the composition of gases escaping from a volcano; and advanced radar and global positioning systems. These systems can detect changes in the behavior of a volcano—such as land movement, seismic activity, or emissions—that might signal an impending eruption. Both tsunami and volcano prediction offer the hope that not all the devastation of earthquakes will occur without warning.
The costs associated with natural disasters are increasing rapidly. As a result, officials in government and industry have focused more attention on disasters and their effects. The White House Office of Science and Technology Policy has estimated that disasters cost the country about $1 billion per week. Hurricane Andrew, the Midwest flood of 1993, and the Hanshin earthquake have shown that individual disasters can cost tens if not hundreds of billions of dollars. This increasing cost has resulted in greater funding from government and industry for the development of technologies related to disaster prediction, and has led to more research into the effective use of predictive information.
The insurance industry has long been aware of the dangers of natural disasters; the 1906 earthquake in San Francisco, California, bankrupted scores of insurance companies. But the industry has focused particular attention on disaster prediction in recent years, as spiraling costs revealed that many companies had underestimated their financial exposure. For instance, prior to Hurricane Andrew in 1992, many insurance experts thought that the worst hurricane possible would do no more than $8 billion in damages to the industry. The damages caused by Hurricane Andrew, estimated at about $17 billion, shattered these beliefs. Today, estimates of worst-case disaster scenarios approach $100 billion.
The insurance industry has therefore increased its support for research into disaster prediction. One such effort involves a number of companies that have joined together to support the Bermuda-based Risk Prediction Initiative, which funds disaster research. The expectation is that the resulting information will place the industry on a more solid foundation to make decisions about the risk of future disasters. The industry has also lobbied for the government to bear some of the financial burden of disaster insurance. Such a program already exists for flood insurance, set up in the late 1960s by the federal government to insure flood-prone areas. These types of programs, effectively implemented, could be increasingly necessary in the future to make insurance available in areas prone to disasters.
Because the stakes are so high, the science of disaster prediction has a bright future. The various projects and programs illustrate that disaster prediction is a topic of concern to scientists and policy makers alike. Hurricanes, tornadoes, floods, earthquakes, tsunamis, and volcanoes all show that the effective use of disaster predictions not only requires advanced technology but also requires that society consider the entire process of prediction—forecasts, communication, and use of information. Because they cannot predict the future with certainty, and because much remains to be learned, scientists warn that society must understand the limits of scientific predictions and be prepared to employ alternatives. Wisely used, however, disaster prediction has the potential to reduce society's vulnerability to natural disasters.
About the Author: Roger A. Pielke, Jr., is a scientist at the National Center for Atmospheric Research (NCAR) in Boulder, Colorado, and coauthor of the book Hurricanes: Their Nature and Impacts on Society.
Further Reading:
Changnon, Stanley A. The Great Flood of 1993. Westview Press, 1996.
Fisher, Richard V., et al. Volcanoes: Crucibles of Change. Princeton University Press, 1997.
Flaherty, Michael. Tidal Waves and Flooding (Closer Look At). Copper Beech Books, 1998.
Glantz, Michael H. Currents of Change: El Niño's Impact on Climate and Society. Cambridge Press, 1996.
Newson, Lesley. Devastation!: The World's Worst Natural Disasters. DK Publishing, 1998.
Olson, Richard S., and Nigg, Joanne M. The Politics of Earthquake Prediction. Princeton University Press, 1989.
Pielke, Jr., R. A., and Pielke, Sr., R. A. Hurricanes: Their Nature and Impacts on Society. John Wiley and Sons, 1997.
Tufty, Barbara. 1001 Questions Answered About Hurricanes, Tornadoes, and Other Natural Air Disasters. Dover, 1987.
Source: Encarta Yearbook, November 1998.
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Weather; Volcano; Earthquake; Tornado; Tsunami; Meteorology; Hurricane; Flood Control; Disaster
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