Climate is the statistical expression of daily weather events; more simply, climate is the expected weather. Naturally, for a particular location, certain weather events will be common (or highly probable); these will lie close to the central tendency or mean of the distribution of weather events. Other types of weather will be more extreme and less frequent; the more extreme the event, the lower the probability of recurrence. Such events would appear at the margins of a distribution of weather events characterizing a particular climate. The overall distribution of climatic parameters defines the climatic variability of the place. If we were to measure temperature in the same location for a finite period of time, the statistical distribution of measured values would reflect the geographical situation of the site (in relation to solar radiation receipts and degree of continentality) as well as the relative frequency of synoptic weather patterns and the associated airflow over the region. Given a long enough period of observations, it would be possible to characterize the temperature of the site in terms of mean and variance. Similarly, observations of other meteorological parameters, such as precipitation, relative humidity, solar radiation, cloudiness, wind speed, and direction, would enable a more comprehensive understanding of the climate of the site to be obtained. However, implicit in such statistics is the element of time. For how long should observations be taken to obtain a reliable picture of the climate at a particular place? The World Meteorological Organization has recommended the adoption of standardized 30-yr periods to characterize climate (Mitchell et al., 1966; Jagannathan et al., 1967). Adoption of a standard reference period is necessary because the statistics that define climate in one area may vary over time so that climate, strictly speaking, should always be defined with reference to the period used in its calculation. Recent studies of global warming express global temperature changes relative to the 1961-1990 mean (Jones, 1994) but most paleoclimate studies rely on climatic data from earlier decades. This becomes important when attempting to compare the fairly subtle climatic variations of the recent past (or general circulation model simulations) with the climate of "today." Presumably, in such a context "today" means the most recent 30-yr mean, but in many areas the last 30 years have been significantly warmer than in previous decades; in fact, on a global scale, 1986-1995 was probably one of the warmest decades for many centuries. The problem is even more difficult in dealing with precipitation, where one 30-yr climatic average may be quite different from another (Bradley, 1991). There is no simple solution, so changes in climate should always be expressed relative to some defined time interval, to allow different reconstructions to be appropriately compared.
Climate may vary in different ways. Some examples of climatic variation are shown in Fig. 2.1. Variations may be periodic (and hence predictable) quasi-periodic (predictable only in the very broadest terms) or non-periodic. Central tendencies
(mean values) may remain more or less constant or exhibit trends or impulsive changes from one mean to another (Hare, 1979). Such occurrences may appear to be random in a time series but this does not necessarily mean they are not predictable. For example, a number of studies have shown that abrupt changes in climate generally result from large explosive volcanic eruptions (e.g., Bradley, 1988). Consequently, the climatic effects of similar eruptions can be anticipated. Hansen et al. (1996), for example, used a general circulation model to estimate the changes in temperature expected from the 1991 eruption of Mount Pinatubo (Philippines). Their estimates tracked very closely observed temperature changes in the years following the eruption. Such studies indicate that in some circumstances reliable climate predictions can be made, even though the eruptions themselves are non-periodic.
A very important aspect of variability in the climate system involves non-linear feedbacks, in which drastic changes may. occur if some critical threshold is exceeded. One example of this is the oceanic thermohaline circulation, which may cease to operate if the salinity-density balance in near-surface waters of the North Atlantic Ocean is disturbed beyond a certain point. The circulation would then cease until salinity increased to the level where density-induced overturning of the water column could resume (see Section 6.9).
Finally, climatic variation may be characterized by an increase in variability without a change in central tendency, though commonly a change in variability accompanies a change in overall mean. Climatic variability is an extremely important characteristic of climate in our increasingly overstressed world. Every year, unexpected weather events (extremes in the climate spectrum) result in hundreds of thousands of deaths and untold economic and social hardships. If climatic variability increases, the unexpected becomes more probable and the strain on social and political systems increases. High resolution paleoclimatic data can shed light on this important aspect of climatic variation.
In the light of these discussions it is appropriate to consider the term climatic change. Clearly, climates may change on different scales of time and in different ways. In paleoclimatic studies, climatic changes are characterized by significant differences in the mean condition between one time period and another. Given enough detail and chronological control, the significance of the change may be calculated from statistics describing the time periods in question. Markedly different climatic conditions between two time periods imply an intervening period of climate characterized by an upward or downward trend, or by an impulsive change in central tendency (see Fig. 2.1). Many paleoclimatic records appear to provide evidence for there being distinct modes of climate, within which short-term variations are essentially stochastic (random). Brief periods of rapid, step-like, climatic change appear to separate these seemingly stable interludes (Bryson et al., 1970). Analysis of several thousand 14C dates on stratigraphic discontinuities (primarily in pollen records from western Europe, but including data from elsewhere) lends some support to this idea (Wendland and Bryson, 1974). Certain periods stand out as having been times of environmental change on a worldwide scale1 (Fig. 2.2). Such widespread discontinuities imply abrupt, globally
1 As discussed in Chapter 3, changes in the 14C content of the atmosphere may result in periods of apparently rapid change, because events which were in reality separate in time appear near synchronous when 14C dated. This effect may have influenced the pattern of change noted by Wendland and Bryson (1974).
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