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IPCC_Managing Risks of Extreme Events.pdf - Climate Access

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Changes in <strong>Climate</strong> <strong>Extreme</strong>s and their Impacts on the Natural Physical EnvironmentChapter 3extremes at the global scale including the reported increase in thenumber <strong>of</strong> warm extremes and decrease in the number <strong>of</strong> cold extremesat that scale (Alexander et al., 2006). Hegerl et al. (2007) also state thatanthropogenic forcing may have substantially increased the risk <strong>of</strong>extreme temperatures (Christidis et al., 2005) and <strong>of</strong> the 2003 Europeanheat wave (Stott et al., 2004).Recent studies on attribution <strong>of</strong> changes in temperature extremes havetended to reaffirm the conclusions reached in the AR4. Alexander andArblaster (2009) found that trends in warm nights over Australia couldonly be reproduced by a coupled model that included anthropogenicforcings. As part <strong>of</strong> the recent report <strong>of</strong> the US <strong>Climate</strong> Change ScienceProgram (CCSP, 2008), Gutowski et al. (2008a) concluded that most <strong>of</strong>the observed changes in temperature extremes for the second half <strong>of</strong>the 20th century over the United States can be attributed to humanactivity. They compared observed changes in the number <strong>of</strong> frost days,the length <strong>of</strong> growing season, the number <strong>of</strong> warm nights, and the heatwave intensity with those simulated in a nine-member multi-modelensemble simulation. The decrease in frost days, an increase in growingseason length, and an increase in heat wave intensity all show similarchanges over the United States in 20th-century experiments thatcombine anthropogenic and natural forcings, though the relativecontributions <strong>of</strong> each are unclear.Results from two global coupled climate models with separateanthropogenic and natural forcing runs indicate that the observedchanges are simulated with anthropogenic forcings, but not with naturalforcings (even though there are some differences in the details <strong>of</strong> theforcings). Zwiers et al. (2011) compared observed annual temperatureextremes including annual maximum daily maximum and minimumtemperatures, and annual minimum daily maximum and minimumtemperatures with those simulated responses to anthropogenic forcing oranthropogenic and natural external forcings combined by multiple GCMs.They fitted probability distributions (Box 3-1) to the observed extremetemperatures with a time-evolving pattern <strong>of</strong> location parameters asobtained from the model simulations, and found that both anthropogenicinfluence and the combined influence <strong>of</strong> anthropogenic and naturalforcing can be detected in all four extreme temperature variables at theglobal scale over the land, and also over many large land areas.Globally, return periods for events that were expected to recur onceevery 20 years in the 1960s are now estimated to exceed 30 years forextreme annual minimum daily maximum temperature and 35 years forextreme annual minimum daily minimum temperature, although theseestimates are subject to considerable uncertainty. Further, return periodswere found to have decreased to less than 10 or 15 years for annualmaximum daily minimum and daily maximum temperatures respectively(Figure 3-2).However, the available detection and attribution studies for extrememaximum and minimum temperatures (Christidis et al., 2011b; Zwierset al., 2011) suggest that the models overestimate changes in themaximum temperatures and underestimate changes in the minimumtemperatures during the late 20th century.Projected Changes and UncertaintiesRegarding projections <strong>of</strong> extreme temperatures, the AR4 (Meehl et al.,2007b) noted that cold episodes were projected to decrease significantlyin a future warmer climate and considered it very likely that heat waveswould be more intense, more frequent, and last longer in a future warmerclimate. Post-AR4 studies <strong>of</strong> temperature extremes have utilized largermodel ensembles (Kharin et al., 2007; Sterl et al., 2008; Orlowsky andSeneviratne, 2011) and generally confirm the conclusions <strong>of</strong> the AR4, whilealso providing more specific assessments both in terms <strong>of</strong> the range <strong>of</strong>considered extremes and the level <strong>of</strong> regional detail (see also Table 3-3).There are few global analyses <strong>of</strong> multi-model projections <strong>of</strong> temperatureextremes available in the literature. The study by Tebaldi et al. (2006),which provided the basis for extreme projections given in the AR4(Figures 10.18 and 10.19 in Meehl et al., 2007b), provided global analyses<strong>of</strong> projected changes (A1B scenario) in several extremes indices basedon nine GCMs (note that not all modelling groups that saved daily dataalso calculated the indices). For temperature extremes, analyses wereprovided for heat wave lengths (using only one index, see discussion inBox 3-1) and warm nights. Stippling was used where five out <strong>of</strong> ninemodels displayed statistically significant changes <strong>of</strong> the same sign.Orlowsky and Seneviratne (2011) recently updated the analysis fromTebaldi et al. (2006) for the full ensemble <strong>of</strong> GCMs that contributed A2scenarios to the CMIP3, using a larger number <strong>of</strong> extreme indices[including several additional analyses <strong>of</strong> daily extremes (see Figures 3-3and 3-4), and three heat wave indices instead <strong>of</strong> one; see also discussion<strong>of</strong> heat wave indices in Box 3-1], using other thresholds for display andstippling <strong>of</strong> the figures (no results displayed if less than 66% <strong>of</strong> themodels agree on the sign <strong>of</strong> change; stippling used only for 90% modelagreement), and providing seasonal analyses. This analysis confirmsthat strong agreement (in terms <strong>of</strong> sign <strong>of</strong> change) exists between thevarious GCM projections for temperature-related extremes, withprojected increases in warm day occurrences (Figure 3-3) and heat wavelength, and decreases in cold extremes (Figure 3-4). Temperatureextremes on land are projected to warm faster than global annual meantemperature in many regions and seasons, implying large changes inextremes in some places, even for a global warming <strong>of</strong> 2 or 3°C (withscaling factors for the SRES A2 scenario ranging between 0.5 and 2 formoderate seasonal extremes; Orlowsky and Seneviratne, 2011). Basedon the analyses <strong>of</strong> Tebaldi et al. (2006) and Orlowsky and Seneviratne(2011), as well as physical considerations, we assess that increases inthe number <strong>of</strong> warm days and nights and decreases in the number <strong>of</strong>cold days and nights (defined with respect to present regional climate,i.e., the 1961-1990 reference period, see Box 3-1) are virtually certain atthe global scale. Further, given the assessed changes in hot and colddays and nights and available analyses <strong>of</strong> projected changes in heatwave length in the two studies, we assess that it is very likely that thelength, frequency, and/or intensity <strong>of</strong> heat waves will increase overmost land areas.Another global study <strong>of</strong> changes in extremes based on the CMIP3ensemble is provided in Kharin et al. (2007), which focuses on changes136

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