In the 1970s, many decision makers became increasingly interested in climate because of numerous weather-related impacts around the world. Events that helped to stimulate this interest included the failed Peruvian anchovy harvest in 1972 and 1973, the 1968 to 1973 drought in the African Sahel, a severe winter freeze in 1972 in the Soviet Union, and in 1974 floods, drought, and early frost in the U.S. Midwest. In 1977, winter in the eastern United States was the coldest ever recorded and summer was one of the three hottest in a century. As a consequence of these extreme events and their impacts, decision makers began paying more attention to the relation of weather and climate to human affairs.
Understanding societal responses to weather and climate requires an understanding of the terms weather and climate. The 1979 World Climate Conference adopted the following definitions of weather and climate:
Weather is associated with the complete state of the atmosphere at a particular instant in time, and with the evolution of this state through the generation, growth and decay of individual disturbances.
Climate is the synthesis of weather events over the whole of a period statistically long enough to establish its statistical ensemble properties (mean value, variances, probabilities of extreme events, etc.) and is largely independent of any instantaneous state.
Handbook of Weather, Climate, and Water: Atmospheric Chembtry, Hydrology, and Societal Impacts, Edited by Thomas D. Potter and Bradley R. Colman. ISBN 0-471-21489-2 © 2003 John Wiley & Sons, Inc.
Climate refers to more than "average weather" (Gibbs, 1987). Climate is, in statistical terminology, the distribution of weather events and their component properties (e.g., rainfall) over some period of time, typically a few months to thousands of years. In general, climate statistics are based on actual (e.g., weather station) or proxy (e.g., ice core) records of weather observations. Such a record of weather events can be used to create a frequency distribution that will have a central tendency, which can be expressed as an average, but it will also have a variance (i.e., spread around an average). Often, variability is more important to decision makers than the average state (Katz and Brown, 1992).
How society thinks about "extreme" weather is, of course, related to what is defined as "normal" weather. What, then, is a "normal" weather event? There are different ways to define normal weather. Of course, it is possible to argue that on planet Earth all weather events are in some sense normal; however, such a definition has little practical utility for decision makers. One way to refine the concept is to define normal weather events as those events that occur within a certain range within a distribution, such as, for instance, all events that fall within one standard deviation of the mean. In practice, historical records of various lengths and reliabilities have been collected around the world for temperature, precipitation, storm events, and others. When data is available, such a statistical definition lends itself to equating normal weather with "expected" weather, where expectations are set according to the amount of the distribution defined as normal. For example, about 68% of all events fall within one standard deviation of the mean of a bell-shaped distribution.
A change in the statistical distribution of a weather variable—such as that associated with a change in climate—is troubling because decision makers may no longer expect that the future will resemble the past. For the insurance industry, as well as other decision makers who rely on actuarial information, such a possibility of a changing climate is particularly troubling. A climate change is thus a variation or change in the shape or location (e.g., mean) of a distribution of discrete events (Katz, 1993).
"Extreme" weather events can simply be defined as those not normal, however normal is chosen to be defined. For instance, if normal weather events are those that occur within 2 standard deviations of the mean, then about 5% of all events will be classified as extreme.
While it is possible to classify hurricanes as either "normal" or "extreme" in this manner, the simple fact is that for most communities any landfalling hurricane would qualify as an extreme event because of their rarity at particular locations along the coast.
From the standpoint of those human activities sensitive to hurricane impacts, it is often the case that decisions are made and decision processes established based on some set of expectations about what future weather or climate will be like. Building codes, land-use regulations, insurance rates, disaster contingency funds are each an example of decisions that are dependent upon an expectation of the frequency and magnitude of future normal and extreme events.
In short, decision makers typically establish policies based upon an expectation of normal weather. Yet for most coastal communities normal weather has historically
(or at least over the time of a human memory) meant no hurricanes! Consequently, people are often surprised when a hurricane does strike and then overwhelms response capabilities. Because decision makers do not always consider the possibility of extreme weather, when such events occur, they often reveal society's vulnerabilities and sometimes lead to human disaster. A fundamental challenge facing society is to incorporate information about weather and climate risks into decision making in order to take advantage of normal weather and to prepare for the extreme. The degree to which society exploits normal weather and reduces its vulnerabilities to extreme weather is a function of how society organizes itself in the face of what is known about various typical and extreme weather events. The challenge is made more difficult by variability at all measurable time scales in the underlying climate, and hence in the frequency, magnitude, and location of various weather events. And, of course, decisions that have a weather or climate component also are laden with all of the political, practical, and social factors that influence policy.
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