2000
DOI: 10.1175/1520-0477(2000)081<0413:aittie>2.3.co;2
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An Introduction to Trends in Extreme Weather and Climate Events: Observations, Socioeconomic Impacts, Terrestrial Ecological Impacts, and Model Projections*

Abstract: Weather and climatic extremes can have serious and damaging effects on human society and infrastructure as well as on ecosystems and wildlife. Thus, they are usually the main focus of attention of the news media in reports on climate. There are some indications from observations concerning how climatic extremes may have changed in the past. Climate models show how they could change in the future either due to natural climate fluctuations or under conditions of greenhouse gas-induced warming. These observed and… Show more

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Cited by 509 publications
(343 citation statements)
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References 13 publications
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“…The vast majority of the change-point tests in the literature is designed to detect abrupt changes in the mean of the distribution of the variable of interest, and only a limited number can detect abrupt changes in variance (Perreault et al, 2000). However, abrupt changes in variance can have a large impact on the frequency of extreme events (Katz and Brown, 1992;Meehl et al, 2000;Ferro et al, 2005), making their detection an important step when examining the stationarity of a time series. The annual maximum discharge time series are tested for abrupt changes in variance by applying the Pettitt test to the squared residuals computed with respect to a line obtained by fitting the time series with a loess function (Cleveland, 1979; span of 0.75), similar to the method suggested by Pegram (2000).…”
Section: Change-point and Trend Analysesmentioning
confidence: 73%
“…The vast majority of the change-point tests in the literature is designed to detect abrupt changes in the mean of the distribution of the variable of interest, and only a limited number can detect abrupt changes in variance (Perreault et al, 2000). However, abrupt changes in variance can have a large impact on the frequency of extreme events (Katz and Brown, 1992;Meehl et al, 2000;Ferro et al, 2005), making their detection an important step when examining the stationarity of a time series. The annual maximum discharge time series are tested for abrupt changes in variance by applying the Pettitt test to the squared residuals computed with respect to a line obtained by fitting the time series with a loess function (Cleveland, 1979; span of 0.75), similar to the method suggested by Pegram (2000).…”
Section: Change-point and Trend Analysesmentioning
confidence: 73%
“…Equally important, the analysis does not apply to extreme precipitation, such as precipitation above the 99.9th percentile (e.g., Groisman et al 2005), for which the theory of statistical extremes more likely provides the appropriate description (e.g., Leadbetter et al 1983;Meehl et al 2000;Wilson and Toumi 2005).…”
Section: Discussionmentioning
confidence: 99%
“…For example, Mearns et al (1984) suggest that with an approximate 2°C warming in Iowa, the probability of summertime heat waves would triple; and Katz and Brown (1992) show that, statistically speaking, a change in variance is more important to the frequency of extreme events than a change in the mean. Therefore, if "extreme" is defined with the current temperature distribution, then shifting the entire distribution by raising the mean value with no change in variance will greatly impact the probability of occurrence of the extreme (Meehl et al 2000), as does an increase in the variance with or without an increase in the mean (Katz and Brown 1992). With this in mind, the purpose of this study is to examine changes in frost days, as defined by days when the minimum temperature is below 0°C, and changes in the frost-free season for the continental United States for the latter half of the twentieth century.…”
mentioning
confidence: 99%