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13.4.2 Temporal Variability
The climate change information most commonly taken from climate modelling experiments
comprises mean monthly, seasonal, or annual changes in variables of importance
to impact assessments. However, changes in climate will involve changes in variability
as well as mean conditions. As mentioned in Section 13.3
on baseline climate, the interannual variability in climate scenarios constructed
from mean changes in climate is most commonly inherited from the baseline climate,
not from the climate change experiment. Yet, it is known that changes in variability
could be very important to most areas of impact assessment (Mearns, 1995; Semenov
and Porter, 1995). The most obvious way in which variability changes affect
resource systems is through the effect of variability change on the frequency
of extreme events. As Katz and Brown (1992) demonstrated, changes in standard
deviation have a proportionately greater effect than changes in means on changes
in the frequency of extremes. However, from a climate scenario point of view,
it is the relative size of the change in the mean versus standard deviation
of a variable that determines the final relative contribution of these statistical
moments to a change in extremes. The construction of scenarios incorporating
extremes is discussed in Section 13.4.2.2.
The conventional method of constructing mean change scenarios for precipitation
using the ratio method (discussed in Section 13.3) results
in a change in variability of daily precipitation intensity; that is, the variance
of the intensity is changed by a factor of the square of the ratio (Mearns et
al., 1996). However, the frequency of precipitation is not changed. Using the
difference method (as is common for temperature variables) the variance of the
time-series is not changed. Hence, from the perspective of variability, application
of the difference approach to precipitation produces a more straightforward
scenario. However, it can also result in negative values of precipitation. Essentially
neither approach is realistic in its effect on the daily characteristics of
the time-series. As mean (monthly) precipitation changes, both the daily intensity
and frequency are usually affected.
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