TURN DO WN THE H E AT: C L IM AT E E X T RE ME S , R EGION A L IMPA C TS, A N D TH E C A SE FOR R ESILIENCE
or in simulations with a doubling of CO2 (typically resulting in ~3°C global mean warming). Without exception, these show that heat extremes, whether on daily or seasonal time scales, greatly increase under high-emissions scenarios. The intensity of extremely hot days, with a return time of 20 years,15 is expected to increase between 5°C and 10°C over continents, with the larger values over North and South America and Eurasia related to substantial decreases in regional soil moisture there (Zwiers and Kharin 1998). The frequency of days exceeding the present-day 99th percentile could increase by a factor of 20 (D. N. Barnett, Brown, Murphy, Sexton, and Webb 2005). Moreover, the intensity, duration, and frequency of three-day heat events is projected to significantly increase—by up to 3°C in the Mediterranean and the western and southern United States (G. A. Meehl and Tebaldi 2004). Studying the 2003 European heat wave, Schär et al. (2004) project that toward the end of the century approximately every second European summer is likely to be warmer than the 2003 event. On a global scale, extremely hot summers are also robustly predicted to become much more common (D. N. Barnett, Brown, Murphy, Sexton, and Webb 2005b). Therefore, the intensity, duration, and frequency of summer heat waves are expected to be substantially greater over all continents, with the largest increases over Europe, North and South America, and East Asia (Clark, Brown, and Murphy 2006). In this and in the previous report, threshold-exceeding heat extremes are analyzed with the threshold defined by the historical observed variability (see Box 2.2). For this definition of extremes,
regions that are characterized by high levels of warming combined with low levels of historical variability tend to see the strongest increase in extremes (Sillmann and Kharin 2013a). The approach is useful because ecosystems and humans are adapted to local climatic conditions and infrastructure is designed with local climatic conditions and its historic variations in mind. Thus even a relatively small change in temperature in the tropics can have relatively large impacts, for example if coral reefs experience temperatures exceeding their sensitivity thresholds (see, for example, Chapter 4 on “Projected Impacts on Coral Reefs”). An alternative approach would be to study extremes exceeding an absolute threshold, independent of the past variability. This is mostly relevant when studying impacts on specific sectors where the exceedance of some specific threshold is known to cause severe impacts. For example, wheat growth in India has been shown to be very sensitive to temperatures greater than 34°C (Lobell, Sibley, & Ortiz-Monasterio, 2012). As this report is concerned with impacts across multiple sectors, thresholds defined by the local climate variability are considered to be the most relevant index. This report analyzes the timing of the increase in monthly heat extremes and their patterns by the end of the 21st century for both the low-emission (RCP2.6 or a 2°C world) and high-emission (RCP8.5 or a 4°C world) scenarios. In a 2°C world, the bulk of
15 This means that there is a 0.5 probability of this event occurring in any given year.
Box 2.2 Heat Extremes In sections assessing extremes, this report defines two types of extremes using thresholds based on the historical variability of the current local climate (similar to Hansen et al. 2012). The absolute level of the threshold thus depends on the natural year-to-year variability in the base period (1951–1980), which is captured by the standard deviation (sigma).
3-sigma Events – Three Standard Deviations Outside the Normal • Highly unusual at present • Extreme monthly heat • Projected to become the norm over most continental areas by the end of the 21st century
5-sigma Events – Five Standard Deviations Outside the Normal • Essentially absent at present • Unprecedented monthly heat: new class of monthly heat extremes • Projected to become common, especially in the tropics and in the Northern Hemisphere (NH) mid-latitudes during summertime For a normal distribution, 3-sigma events have a return time of 740 years. The 2012 U.S. heat wave and the 2010 Russian heat wave classify as 3-sigma events (Coumou & Robinson, submitted). 5-sigma events have a return time of several million years. Monthly temperature data do not necessarily follow a normal distribution (for example, the distribution can have “long” tails, making warm events more likely) and the return times can be different from the ones expected in a normal distribution. Nevertheless, 3-sigma events are extremely unlikely and 5-sigma events have almost certainly never occurred over the lifetime of key ecosystems and human infrastructure.a a
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Note that the analysis performed here does not make assumptions about the underlying probability distribution.