IPCC Fourth Assessment Report: Climate Change 2007
Climate Change 2007: Working Group I: The Physical Science Basis Temperature Extremes

The TAR concluded that there was a very likely risk of increased high temperature extremes (and reduced risk of low temperature extremes) with more extreme heat episodes in a future climate. The latter result has been confirmed in subsequent studies (Yonetani and Gordon, 2001). Kharin and Zwiers (2005) show in a single model that future increases in temperature extremes follow increases in mean temperature over most of the world except where surface properties change (melting snow, drying soil). Furthermore, they show that in most instances warm extremes correspond to increases in daily maximum temperature, but cold extremes warm up faster than daily minimum temperatures, although this result is less consistent when model parameters are varied in a perturbed physics ensemble where there are increased daily temperature maxima for nearly the entire land surface. However, the range in magnitude of increases was substantial indicating a sensitivity to model formulations (Clark et al., 2006).

Weisheimer and Palmer (2005) examine changes in extreme seasonal (DJF and JJA) temperatures in 14 models for three scenarios. They show that by the end of 21st century, the probability of such extreme warm seasons is projected to rise in many areas. This result is consistent with the perturbed physics ensemble where, for nearly all land areas, extreme JJA temperatures were at least 20 times and in some areas 100 times more frequent compared to the control ensemble mean, making these changes greater than the ensemble spread.

Since the TAR, possible future cold air outbreaks have been studied. Vavrus et al. (2006) analyse seven AOGCMs run with the A1B scenario, and define a cold air outbreak as two or more consecutive days when the daily temperatures are at least two standard deviations below the present-day winter mean. For a future warmer climate, they document a 50 to 100% decline in the frequency of cold air outbreaks in NH winter in most areas compared to the present, with the smallest reductions occurring in western North America, the North Atlantic and southern Europe and Asia due to atmospheric circulation changes associated with the increase in greenhouse gases.

No studies at the time of the TAR specifically documented changes in heat waves (very high temperatures over a sustained period of days, see Chapter 3). Several recent studies address possible future changes in heat waves explicitly, and find an increased risk of more intense, longer-lasting and more frequent heat waves in a future climate (Meehl and Tebaldi, 2004; Schär et al., 2004; Clark et al., 2006). Meehl and Tebaldi (2004) show that the pattern of future changes in heat waves, with greatest intensity increases over western Europe, the Mediterranean and the southeast and western USA, is related in part to base state circulation changes due to the increase in greenhouse gases. An additional factor leading to extreme heat is drier soils in a future warmer climate (Brabson et al., 2005; Clark et al., 2006). Schär et al. (2004), Stott et al. (2004) and Beniston (2004) use the European 2003 heat wave as an example of the types of heat waves that are likely to become more common in a future warmer climate. Schär et al. (2004) note that the increase in the frequency of extreme warm conditions is also associated with a change in interannual variability, such that the statistical distribution of mean summer temperatures is not merely shifted towards warmer conditions but also becomes wider. A multi-model ensemble shows that heat waves are simulated to have been increasing over the latter part of the 20th century, and are projected to increase globally and over most regions (Figure 10.19; Tebaldi et al., 2006), although different model parameters can contribute to the range in the magnitude of this response (Clark et al., 2006).

A decrease in DTR in most regions in a future warmer climate was reported in the TAR, and is substantiated by more recent studies (e.g., Stone and Weaver, 2002; also discussed in relation to Figure 10.11b and in Chapter 11). For a quantity related to the DTR, the TAR concluded that it would be likely that a future warmer climate would also be characterised by a decrease in the number of frost days, although there were no studies at that time from global coupled climate models that addressed this issue explicitly. It has since been shown that there would indeed be decreases in frost days in a future warmer climate in the extratropics (Meehl et al., 2004a), with the pattern of the decreases dictated by the changes in atmospheric circulation due to the increase in greenhouse gases (Meehl et al., 2004a). Results from a nine-member multi-model ensemble show simulated decreases in frost days for the 20th century continuing into the 21st century globally and in most regions (Figure 10.19). A quantity related to frost days in many mid- and high-latitude areas, particularly in the NH, is growing season length as defined by Frich et al. (2002), and this has been projected to increase in future climate (Tebaldi et al., 2006). This result is also shown in a nine-member multi-model ensemble where the simulated increase in growing season length in the 20th century continues into the 21st century globally and in most regions (Figure 10.19). The globally averaged extremes indices in Figures 10.18 and 10.19 have non-uniform changes across the scenarios compared to the more consistent relative increases in Figure 10.5 for globally averaged temperature. This indicates that patterns that scale well by radiative forcing for temperature (e.g., Figure 10.8) would not scale for extremes.

Figure 10.19

Figure 10.19. Changes in extremes based on multi-model simulations from nine global coupled climate models, adapted from Tebaldi et al. (2006). (a) Globally averaged changes in the frost day index (defined as the total number of days in a year with absolute minimum temperature below 0°C) for a low (SRES B1), middle (SRES A1B) and high (SRES A2) scenario. (b) Changes in spatial patterns of simulated frost days between two 20-year means (2080–2099 minus 1980–1999) for the A1B scenario. (c) Globally averaged changes in heat waves (defined as the longest period in the year of at least five consecutive days with maximum temperature at least 5°C higher than the climatology of the same calendar day). (d) Changes in spatial patterns of simulated heat waves between two 20-year means (2080–2099 minus 1980–1999) for the A1B scenario. (e) Globally averaged changes in growing season length (defined as the length of the period between the first spell of five consecutive days with mean temperature above 5°C and the last such spell of the year). (f) Changes in spatial patterns of simulated growing season length between two 20-year means (2080–2099 minus 1980–1999) for the A1B scenario. Solid lines in (a), (c) and (e) show the 10-year smoothed multi-model ensemble means; the envelope indicates the ensemble mean standard deviation. Stippling in (b), (d) and (f) denotes areas where at least five of the nine models concur in determining that the change is statistically significant. Extreme indices are calculated only over land. Frost days and growing season are only calculated in the extratropics. Extremes indices are calculated following Frich et al. (2002). Each model’s time series was centred around its 1980 to 1999 average and normalised (rescaled) by its standard deviation computed (after de-trending) over the period 1960 to 2099. The models were then aggregated into an ensemble average, both at the global and at the grid-box level. Thus, changes are given in units of standard deviations.