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IPCC_Managing Risks of Extreme Events.pdf - Climate Access

IPCC_Managing Risks of Extreme Events.pdf - Climate Access

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Chapter 4Changes in Impacts <strong>of</strong> <strong>Climate</strong> <strong>Extreme</strong>s: Human Systems and EcosystemsThe statement about the absence <strong>of</strong> trends in impacts attributableto natural or anthropogenic climate change holds for tropical andextratropical storms and tornados (Boruff et al., 2003; Pielke Jr. et al.,2003, 2008; Raghavan and Rajesh, 2003; Miller et al 2008; Schmidt et al.,2009; Zhang et al., 2009; see also Box 4-2). Most studies related increasesfound in normalized hurricane losses in the United States since the1970s (Miller et al., 2008; Schmidt et al., 2009; Nordhaus, 2010) to thenatural variability observed since that time (Miller et al., 2008; Pielke Jr. etal., 2008). Bouwer and Botzen (2011) demonstrated that other normalizedrecords <strong>of</strong> total economic and insured losses for the same series <strong>of</strong>hurricanes exhibit no significant trends in losses since 1900.The absence <strong>of</strong> an attributable climate change signal in losses also holdsfor flood losses (Pielke Jr. and Downton, 2000; Downton et al., 2005;Barredo, 2009; Hilker et al., 2009), although some studies did find recentincreases in flood losses related in part to changes in intense rainfallevents (Fengqing et al., 2005; Chang et al., 2009). For precipitationrelatedevents (intense rainfall, hail, and flash floods), the picture ismore diverse. Some studies suggest an increase in damages related toa changing incidence in extreme precipitation (Changnon, 2001, 2009),although no trends were found for normalized losses from flash floodsand landslides in Switzerland (Hilker et al., 2009). Similarly, a study <strong>of</strong>normalized damages from bushfires in Australia also shows that increasesare due to increasing exposure and wealth (Crompton et al., 2010).Increasing exposure <strong>of</strong> people and economic assets has been the majorcause <strong>of</strong> long-term increases in economic losses from weather- andclimate-related disasters (high confidence). The attribution <strong>of</strong> economicdisaster losses is subject to a number <strong>of</strong> limitations in studies to date:data availability (most data are available for standard economic sectorsin developed countries); type <strong>of</strong> hazards studied (most studies focus oncyclones, where confidence in observed trends and attribution <strong>of</strong>changes to human influence is low; Section 3.4.4); and the processesused to normalize loss data over time. Different studies use differentapproaches to normalization, and most normalization approaches takeaccount <strong>of</strong> changes in exposure <strong>of</strong> people and assets, but use only limited,if any, measures <strong>of</strong> vulnerability trends, which is questionable. Differentapproaches are also used to handle variations in the quality andcompleteness <strong>of</strong> data on impacts over time. Finding a trend or ‘signal’in a system characterized by large variability or ‘noise’ is difficult andrequires lengthy records. These are all areas <strong>of</strong> potential weakness inthe methods and conclusions <strong>of</strong> longitudinal loss studies and moreempirical and conceptual efforts are needed. Nevertheless, the results <strong>of</strong>the studies mentioned above are strengthened as they show similarresults, although they have applied different data sets and methodologies.A general area <strong>of</strong> uncertainty in the studies concerns the impacts <strong>of</strong>weather and climate events on the livelihoods and people <strong>of</strong> informalsettlements and economic sectors, especially in developing countries.Some one billion people live in informal settlements (UNISDR, 2011),and over half the economy in some developing countries is informal(Schneider et al., 2010). These impacts have not been systematicallydocumented, with the result that they are largely excluded from bothlongitudinal impact analysis and attribution to defined weatherepisodes.Another general area <strong>of</strong> uncertainty comes from confounding factorsthat can be identified but are difficult to quantify, and relates to theusual assumption <strong>of</strong> constant vulnerability in studies <strong>of</strong> loss trends.These include factors that would be expected to increase resilience(Chapters 2 and 5 <strong>of</strong> this report) and thereby mask the influence <strong>of</strong>climate change, and those that could act to increase the impact <strong>of</strong>climate change. Those that could mask the effects <strong>of</strong> change includegradual improvements in warnings and emergency management (Adgeret al., 2005), building regulations (Crichton, 2007), and changinglifestyles (such as the use <strong>of</strong> air conditioning), and the almost instantmedia coverage <strong>of</strong> any major weather extreme that may help reducelosses. In the other direction are changes that may be increasing risk,such as the movement <strong>of</strong> people in many countries to coastal areasprone to cyclones (Pompe and Rinehart, 2008) and sea level rise.4.5.4. Assessment <strong>of</strong> Impact CostsMuch work has been conducted on the analysis <strong>of</strong> direct economic lossesfrom natural disasters. The examples mentioned below mainly focus onnational and regional economic losses from particular climate extremesand disasters, and also discuss uncertainty issues related to the assessment<strong>of</strong> economic impacts.4.5.4.1. Estimates <strong>of</strong> Global and Regional Costs <strong>of</strong> DisastersObserved trends in extreme impacts: Data on global weather- andclimate-related disaster losses reported since the 1960s reflect mainlymonetized direct damages to assets, and are unequally distributed.Estimates <strong>of</strong> annual losses have ranged since 1980 from a few US$billion to above 200 billion (in 2010 dollars) for 2005 (the year <strong>of</strong>Hurricane Katrina) (UNISDR, 2009; Swiss Re 2010; Munich Re, 2011).These estimates do not include indirect and intangible losses.On a global scale, annual material damage from large weather andclimate events has been found to have increased eight-fold between the1960s and the 1990s, while the insured damage has been found to haveincreased by 17-fold in the same interval, in inflation-adjusted monetaryunits (Mechler and Kundzewicz, 2010). Between 1980 and 2004, thetotal costs <strong>of</strong> extreme weather events totaled US$ 1.4 trillion, <strong>of</strong> whichonly one-quarter was insured (Mills, 2005). Material damages caused bynatural disasters, mostly weather- and water-related, have increasedmore rapidly than population or economic growth, so that these factorsalone may not fully explain the observed increase in damage. The loss<strong>of</strong> life has been brought down considerably (Mills, 2005; UNISDR, 2011).Developing regions are vulnerable both because <strong>of</strong> exposure toweather- and climate-related extremes and their status as developingeconomies. However, disaster impacts are unevenly distributed by type <strong>of</strong>269

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