IPCC Report.pdf - Adam Curry

Chapter 3Changes in Climate Extremes and their Impacts on the Natural Physical Environmentextremes (Fowler et al., 2007a; Fowler and Ekstrom, 2009). Perhaps themost comprehensive approach to date for quantifying the influence ofthe cascade of uncertainties in regional projections is that used todevelop the recent United Kingdom Climate Projections (UKCP09;Murphy et al., 2009). A complex Bayesian framework is used to combinea perturbed physics ensemble exploring uncertainties in atmosphereand ocean processes, and the carbon and sulfur cycles, with structuraluncertainty (represented by 12 CMIP3 models) and an 11-member RCMperturbed physics ensemble. The published projections provide probabilitydistributions of changes in various parameters including the wettest andhottest days of each season for 25-km grid squares across the UnitedKingdom. These probabilities are conditional on the emissions scenario(low, medium, high) and are described as representing the “relative degreeto which each climate outcome is supported by the evidence currentlyavailable, taking into account our understanding of climate science andobservations, and using expert judgment” (Murphy et al., 2009).Both statistical and dynamical downscaling methods are affected bythe uncertainties that affect the global models, and a further level ofuncertainty associated with the downscaling step also needs to betaken into consideration (see also Sections 3.2.3.1 and 3.2.3.2). Theincreasing availability of coordinated RCM simulations for differentregions permits more systematic exploration of dynamical downscalinguncertainty. Such simulations are available for Europe (e.g., Christensenand Christensen, 2007; van der Linden and Mitchell, 2009) and a fewother regions such as North America (Mearns et al., 2009) and WestAfrica (van der Linden and Mitchell, 2009; Hourdin et al., 2010). RCMintercomparisons have also been undertaken for a number of regionsincluding Asia (Fu et al., 2005), South America (Menendez et al., 2010) andthe Arctic (Inoue et al., 2006). A new series of coordinated simulationscovering the globe is planned (Giorgi et al., 2009). Increasingly, RCMoutput from coordinated simulations is made available at the daily timescale, facilitating the analysis of some extreme events. Nevertheless, itis important to point out that ensemble runs with RCMs currentlyinvolve a limited number of driving GCMs, and hence only subsampleuncertainty space. Ensuring adequate sampling of RCM simulations (bothin terms of the number of considered RCMs and number of considereddriving GCMs) may be more important for extremes than for changes inmean values (Frei et al., 2006; Fowler et al., 2007a). Internal variability,for example, has been shown to make a significant contribution tothe spectrum of variability on at least multi-annual time scales andpotentially up to multi-decadal time scales (Kendon et al., 2008;Hawkins and Sutton, 2009, 2011; Box 3-2).3.3. Observed and Projected Changes inWeather and Climate Extremes3.3.1. TemperatureTemperature is associated with several types of extremes, for example,heat waves and cold spells, and related impacts, for example, on humanhealth, the physical environment, ecosystems, and energy consumption(e.g., Chapter 4, Sections 3.5.6 and 3.5.7; see also Case Studies 9.2.1and 9.2.10). Temperature extremes often occur on weather time scalesthat require daily or higher time scale resolution data to accuratelyassess possible changes (Section 3.2.1). It is important to distinguishbetween daily mean, maximum (i.e., daytime), and minimum (nighttime)temperature, as well as between cold and warm extremes, due to theirdiffering impacts. Spell lengths (e.g., duration of heat waves) arerelevant for a number of impacts. Note that we do not considerhere changes in diurnal temperature range or frost days, which are nottypical ‘climate extremes’. There is an extensive body of literatureregarding the mechanisms of changes in temperature extremes (e.g.,Christensen et al., 2007; Meehl et al., 2007b; Trenberth et al., 2007).Heat waves are generally caused by quasi-stationary anticycloniccirculation anomalies or atmospheric blocking (Xoplaki et al., 2003;Meehl and Tebaldi, 2004; Cassou et al., 2005; Della-Marta et al., 2007b),and/or land-atmosphere feedbacks (in transitional climate regions),whereby the latter can act as an amplifying mechanism through reductionin evaporative cooling (Section 3.1.4), but also induce enhancedpersistence due to soil moisture memory (Lorenz et al., 2010). Also snowfeedbacks (Section 3.1.4), and possibly changes in aerosols (Portmann etal., 2009), are relevant for temperature extremes. Trends in temperatureextremes (either observed or projected) can sometimes be different forthe most extreme temperatures (e.g., annual maximum/minimum dailymaximum/minimum temperature) than for less extreme events [e.g.,cold/warm days/nights; see, for instance, Brown et al. (2008) versusAlexander et al. (2006)]. One reason for this is that ‘moderate extremes’such as warm/cold days/nights are generally computed for each daywith respect to the long-term statistics for that day, thus, for example,an increase in warm days for annual analyses does not necessarily implywarming for the very warmest days of the year.Observed ChangesRegional historical or paleoclimatic temperature reconstructions mayhelp place the recent instrumentally observed temperature extremes inthe context of a much longer period, but literature on this topic is verysparse and most regional reconstructions are for Europe. For exampleDobrovolny et al. (2010) reconstructed monthly and seasonal temperatureover central Europe back to 1500 using a variety of temperature proxyrecords. They concluded that the summer 2003 heat wave and the July2006 heat wave exceeded the +2 standard deviation (associated withthe reconstruction method) of previous monthly temperature extremessince 1500. Barriopedro et al. (2011) showed that the anomalously warmsummers of 2003 in western and central Europe and 2010 in easternEurope and Russia both broke the 500-year long seasonal temperaturerecord over 50% of Europe. The coldest periods within the last fivecenturies occurred in the winter and spring of 1690. Another 500-yeartemperature reconstruction was recently completed for theMediterranean basin by means of documentary data and instrumentalobservations (Camuffo et al., 2010). It suggests strong natural variabilityin the basin, possibly exceeding the recent warming, althoughdiscontinuities in the records limit the interpretation of this finding.133