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IPCC_Managing Risks of Extreme Events.pdf - Climate Access

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<strong>Climate</strong> Change: New Dimensions in Disaster Risk, Exposure, Vulnerability, and ResilienceChapter 1• Participatory and decentralized processes that are linked to higherlevels <strong>of</strong> territorial governance (regions, nation) are a crucial part<strong>of</strong> all the stages <strong>of</strong> risk governance that include identification,choice, and implementation <strong>of</strong> these actions (high confidence).1.3.1. <strong>Climate</strong> Change Will ComplicateManagement <strong>of</strong> Some Disaster <strong>Risks</strong><strong>Climate</strong> change will pose added challenges in many cases for attainingdisaster risk management goals, and appropriately allocating efforts tomanage disaster risks, for at least two sets <strong>of</strong> reasons. First, as discussed inChapters 3 and 4, climate change is very likely to increase the occurrenceand vary the location <strong>of</strong> some physical events, which in turn will affectthe exposure faced by many communities, as well as their vulnerability.Increased exposure and vulnerability would contribute to an increase indisaster risk. For example, vulnerability may increase due to direct climaterelatedimpacts on the development and development potential <strong>of</strong> theaffected area, because resources otherwise available and directedtowards development goals are deflected to respond to those impacts,or because long-standing institutions for allocating resources such aswater no longer function as intended if climate change affects thescarcity and distribution <strong>of</strong> that resource. Second, climate change willmake it more difficult to anticipate, evaluate, and communicate bothprobabilities and consequences that contribute to disaster risk, inparticular that associated with extreme events. This set <strong>of</strong> issues,discussed in this subsection, will affect the management <strong>of</strong> these risksas discussed in Chapters 5, 6, 7, and 8 (high confidence).1.3.1.1. Challenge <strong>of</strong> Quantitative Estimates <strong>of</strong> Changing <strong>Risks</strong><strong>Extreme</strong> events pose a particular set <strong>of</strong> challenges for implementingprobabilistic approaches because their relative infrequency <strong>of</strong>ten makesit difficult to obtain adequate data for estimating the probabilities andconsequences. <strong>Climate</strong> change exacerbates this challenge because itcontributes to potential changes in the frequency and character <strong>of</strong> suchevents (see Section 1.2.2.2).The likelihood <strong>of</strong> extreme events is most commonly described by thereturn period, the mean interval expected between one such event and itsrecurrence. For example, one might speak <strong>of</strong> a 100-year flood or a 50-yearwindstorm. More formally, these intervals are inversely proportional tothe ‘annual exceedance probability,’ the likelihood that an eventexceeding some magnitude occurs in any given year. Thus the 100-yearflood has a 1% chance <strong>of</strong> occurring in any given year (which translatesinto a 37% chance <strong>of</strong> a century passing without at least one such flood((1-0.01) 100 = 37%). Though statistical methods exist to estimatefrequencies longer than available data time series (Milly et al., 2002),the long return period <strong>of</strong> extreme events can make it difficult, if notimpossible, to reliably estimate their frequency. Paleoclimate recordsmake clear that in many regions <strong>of</strong> the world, the last few decades <strong>of</strong>observed climate data do not represent the full natural variability <strong>of</strong>many important climate variables (Jansen et al., 2003). In addition,future climate change exacerbates the challenge <strong>of</strong> non-stationarity(Milly et al., 2008), where the statistical properties <strong>of</strong> weather eventswill not remain constant over time. This complicates an already difficultestimation challenge by altering frequencies and consequences <strong>of</strong>extremes in difficult-to-predict ways (Chapter 3; Meehl et al., 2007; TRB,2008; NRC, 2009).Estimating the likelihood <strong>of</strong> different consequences and their value is atleast as challenging as estimating the likelihood <strong>of</strong> extreme events.Projecting future vulnerability and response capacity involves predictingthe trends and changes in underlying causes <strong>of</strong> human vulnerability andthe behavior <strong>of</strong> complex human systems under potentially stressful andnovel conditions. For instance, disaster risk is endogenous in the sense thatnear-term actions to manage risk may affect future risk in unintendedways and near-term actions may affect perceptions <strong>of</strong> future risks (seeBox 1-3). Section 1.4 describes some <strong>of</strong> the challenges such systemcomplexity may pose for effective risk assessment. In addition, disastersaffect socioeconomic systems in multiple ways so that assigning aquantitative value to the consequences <strong>of</strong> a disaster proves difficult (seeSection 1.2.3.3). The literature distinguishes between direct losses,which are the immediate consequences <strong>of</strong> the disaster-related physicalevents, and indirect losses, which are the consequences that result fromthe disruption <strong>of</strong> life and activity after the immediate impacts <strong>of</strong> theevent (Pelling et al., 2002; Lindell and Prater, 2003; Cochrane, 2004; Rose,2004). Section 1.3.2 discusses some means to address these challenges.1.3.1.2. Processes that Influence Judgmentsabout Changing <strong>Risks</strong>Effective risk governance engages a wide range <strong>of</strong> stakeholder groups– such as scientists, policymakers, private firms, nongovernmentalorganizations, media, educators, and the public – in a process <strong>of</strong>exchanging, integrating, and sharing knowledge and information. Therecently emerging field <strong>of</strong> sustainability science (Kates et al., 2001)promotes interactive co-production <strong>of</strong> knowledge between experts andother actors, based on transdisciplinarity (Jasan<strong>of</strong>f, 2004; Pohl et al.,2010) and social learning (Pelling et al., 2008; Pahl-Wostl, 2009; see alsoSection 1.4.2). The literature on judgment and decisionmaking suggeststhat various cognitive behaviors involving perceptions and judgmentsabout low-probability, high-severity events can complicate the intendedfunctioning <strong>of</strong> such stakeholder processes (see Box 1-3). <strong>Climate</strong> changecan exacerbate these challenges (high confidence).The concepts <strong>of</strong> disaster, risk, and disaster risk management have verydifferent meanings and interpretations in expert and non-expert contexts(Sjöberg, 1999a; see also Pidgeon and Fischh<strong>of</strong>f, 2011). Experts actingin formal private and public sector roles <strong>of</strong>ten employ quantitativeestimates <strong>of</strong> both probability and consequence in making judgmentsabout risk. In contrast, the general public, politicians, and the mediatend to focus on the concrete adverse consequences <strong>of</strong> such events,paying less attention to their likelihood (Sjöberg, 1999b). As described46

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