month, season or year) have a strong increasing trend, whereas the highest daily maximum temperatures show little or no trend.
Harvey (2000), Meehl et al. (2000b) and Easterling et al. (2000b) reviewed predicted changes in temperature extremes due to greenhouse gas increases. In many regions, models do indeed predict greater increases in mean (nighttime) minimum temperatures than in mean (daytime) maximum temperatures, with a reduced diurnal range. One reason for this appears to be that cloud reduces the amplitude of the diurnal cycle in regions where cloudiness increases. As expected from statistical considerations (see Section 2.2.3), these type B changes in the mean values are also associated with changes in the frequency of extreme values. This leads to an increase in the frequency of very warm days in summer (as the mean maximum temperature increases), and an even greater decrease in the frequency of very cold days in winter (as the mean minimum temperature increases still more). However, some models show type C changes in the spread of the daily temperature as well as the mean. For example, in northern temperate mid-continental regions, some models predict increases in variance in summer (further increasing the likelihood of very warm days) and decreases in variance in winter (further decreasing the likelihood of very cold days). There are also direct predictions of extreme temperature events. For example, the 20-year return maximum daily temperature values (in summer) show the largest increases where soil moisture is most reduced, and 20-year return minimum daily temperature values (in winter) show the largest increases at high latitudes where snow and ice have retreated. All these predictions also imply that the frequency of cold waves will generally reduce, and the frequency of heatwaves will increase.
A final point of interest regarding weather-related hazards, of particular relevance to precipitation and temperature extremes, is the recent development of the Climate Extremes Index (CEI; Karl et al, 1995a) (Box 3.1). This currently combines indicators of precipitation and temperature extremes for the United States. The century-long record of the CEI for the United States shows large decadal-scale variations, and suggests that the US climate has become more extreme in recent decades. This is probably related to variations in the PNA pattern and ENSO (Karl et al, 1995a). The authors suggested that new indicators relating to other extreme weather (e.g. heatwaves, cold waves, freezes, strong winds, tropical cyclones, hail, tornadoes, etc.) could be added to the CEI as the data improve, particularly with regard to their homogeneity. Easterling and Kates (1995) concluded that the CEI has several of the necessary attributes to become 'usable knowledge', widely understood by users and the general public in the same way as, for example, wind chill factor or the Palmer Drought Severity Index (PDSI). Particularly if extended to other regions and other parameters, the CEI thus promises to be useful for summarising in a quantitative way the results of investigations into the effects of climate change on weather-related hazards, at a time when their impact is increasingly being felt and noted worldwide.
Box 3.1 The Climate Extremes Index (CEI)
The Climate Extremes Index (CEI) was introduced by Karl et al. (1995a) to quantify observed changes in the extremes of climate in the United States. It is based on an aggregate of existing climate extreme indicators, though currently only those concerning temperature and precipitation extremes. The following definition of the CEI was given by Karl et al. (1995a), who also discussed the reasons for the choices of indicator. In each case, occurrences 'much above (below) normal' are defined as those falling above (below) the upper (lower) tenth percentile of the local, century-long period of the record, and the percentages refer to the conterminous US area.
Definition of the United States Climate Extremes Index (CEI)
The US CEI is the annual arithmetic average of the following five indicators:
1. The sum of (a) the percentage of the USA with maximum temperatures much below normal, and (b) the percentage of the USA with maximum temperatures much above normal.
2. The sum of (a) the percentage of the USA with minimum temperatures much below normal, and (b) the percentage of the USA with minimum temperatures much above normal.
3. The sum of (a) the percentage of the USA in severe drought (equivalent to the lowest tenth percentile) based on the Palmer Drought Severity Index (PDSI), and (b) the percentage of the USA with severe moisture surplus (equivalent to the highest tenth percentile) based on the PDSI.
4. Twice the value of the percentage of the USA with a much greater than normal proportion of precipitation derived from extreme (more than 2 in. or 50.8 mm) 1-day precipitation events.
5. The sum of (a) the percentage of the USA with a much greater than normal number of days with precipitation, and (b) the percentage of the USA with a much greater than normal number of days without precipitation.
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