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Changes in Climate Extremes and their Impacts on the Natural Physical EnvironmentChapter 3Overall, though new studies have furthered the understanding of themechanisms leading to drought, there is still relatively limited evidenceto provide an attribution of observed changes, in particular given theissues associated with the availability of observational data (Section 3.2.1)and the definition and computation of drought indicators (Box 3-3). Thislatter point was mostly identified in post-AR4 studies (Box 3-3). Moreover,regions where consistent increases in drought are identified (see ‘ObservedChanges’) are only partly consistent with those where projections indicatean enhancement of drought conditions in coming decades (see nextparagraphs). We thus assess that there is medium confidence (see alsoSection 3.1.5) that anthropogenic influence has contributed to somechanges in the drought patterns observed in the second half of the 20thcentury, based on its attributed impact on precipitation and temperaturechanges (though temperature can only be indirectly related to droughttrends; see Box 3-3). However there is low confidence in the attributionof changes in droughts at the level of individual regions.Projected Changes and UncertaintiesThe AR4 assessed that projections at the time indicated an increase indroughts, in particular in subtropical and mid-latitude areas(Christensen et al., 2007). An increase in dry spell length and frequencywas considered very likely over the Mediterranean region, southernareas of Australia, and New Zealand and likely over most subtropicalregions, with little change over northern Europe. Continental drying andthe associated risk of drought were considered likely to increase insummer over many mid-latitude continental interiors (e.g., central andsouthern Europe, the Mediterranean region), in boreal spring, and dryperiods of the annual cycle over Central America.More recent global and regional climate simulations and hydrologicalmodels mostly support the projections from the AR4, as summarized in thefollowing paragraphs (see also Table 3-3), although we assess the overallconfidence in drought projections as medium given the definitionalissues associated with dryness and the partial lack of agreement inmodel projections when based on different dryness indices (Box 3-3).Indeed, particular care is needed in inter-comparing ‘drought’ projectionssince very many different definitions are employed (corresponding todifferent types of droughts), from simple climatic indices such as CDDto more complex indices of soil moisture and hydrological drought (Box3-3). A distinction also needs to be made between short-term andlonger-term events. Blenkinsop and Fowler (2007a) and Burke et al.(2010), for example, show different trend strength, and sometimes sign(Blenkinsop and Fowler, 2007a), for changes in short- and long-termdroughts with RCM ensembles applied to the United Kingdom(although uncertainties in the latter projections are large; see below).These various distinctions are generally not considered and mostcurrently available studies only assess changes in very few (mostcommonly one or two) dryness indices.On the global scale, Burke and Brown (2008) provided an analysis ofprojected changes in drought based on four indices (SPI, PDSI, PPEA,and SMA; for definitions, see Box 3-3) using two model ensembles: onebased on a GCM expressing uncertainty in parameter space, and a multimodelensemble of 11 GCM simulations from CMIP3. Their analysisrevealed that SPI, based solely on precipitation, showed little change inthe proportion of the land surface in drought, and that all other indices,which include a measure of the atmospheric demand for moisture,showed a statistically significant increase with an additional 5 to 45% ofthe land surface in drought. This study also highlighted large uncertaintiesin regional changes in drought. For reasons highlighted in Box 3-3, usingsimulated soil moisture anomalies from the climate models avoids someshortcomings of other commonly used indices (although the quality ofsimulated soil moisture cannot be well evaluated due to lack ofobservations; Section 3.2 and Box 3-3). In the study of Burke and Brown(2008), this index showed weaker drying compared to PDSI and PPEAindices (but more pronounced drying than the SPI index). In this report,we display projected changes in soil moisture anomalies and CDD(Figure 3-10), this latter index being chosen for continuity with the AR4(see Figure 10.18 of that report). It can be seen that the two indicespartly agree on increased drought in some large regions (e.g., on theannual time scale, in Southern Europe and the Mediterranean region,central Europe, central North America, Central America and Mexico,northeast Brazil, and southern Africa), but some regions where the modelsshow consistent increases in CDD (e.g., southeast Asia) do not showconsistent decreases in soil moisture. Conversely, regions displaying aconsistent decrease in CDD (e.g., in northeastern Asia) do not show aconsistent increase in soil moisture. The substantial uncertainty of droughtprojections is particularly clear from the soil moisture projections, with,for example, no agreement among the models regarding the sign ofchanges in December to February over most of the globe. These resultsregarding changes in CDD and soil moisture are consistent with otherpublished studies (Wang, 2005; Tebaldi et al., 2006; Burke and Brown,2008; Sheffield and Wood, 2008b; Sillmann and Roeckner, 2008) and theareas that display consistent increasing drought tendencies for bothindices have also been reported to display such tendencies for additionalindices (e.g., Burke and Brown, 2008; Dai, 2011; Table 3-3). Sheffield andWood (2008b) examined projections in drought frequency (for droughtsof duration of 4 to 6 months and longer than 12 months, estimated fromsoil moisture anomalies) based on CMIP3 simulations with eight GCMsand the SRES scenarios A2, A1B, and B1. They concluded that drought wasprojected to increase in several regions under these three scenarios(mostly consistent with those displayed in Figure 3-10 for SMA),although the projections of drought intensification were stronger for thehigh CO 2 emissions scenarios (A2 and A1B) than for the more moderatescenario (B1). Regions showing statistically significant increases in droughtfrequency were found to be broadly similar for all three scenarios,despite the more moderate signal in the B1 scenario (their Figures 8 and9). This study also highlighted the large uncertainty of scenarios fordrought projections, as scenarios were found to span a large range ofchanges in drought frequency in most regions, from close to no changeto two- to three-fold increases (their Figure 10).Regional climate simulations and high-resolution global atmosphericmodel simulations over Europe also highlight the Mediterranean region172
Chapter 3Changes in Climate Extremes and their Impacts on the Natural Physical EnvironmentConsecutive dry days (CDD)2046−2065 (ANN)Soil moisture anomalies (SMA)2046−2065 (ANN)2081−2100 (ANN)2081−2100 (ANN)2081−2100 (DJF)2081−2100 (DJF)2081−2100 (JJA)2081−2100 (JJA)−0.6 −0.2 0 0.2 0.6Standard Deviation−0.75 −0.25 0 0.25 0.75Standard DeviationFigure 3-10 | Projected annual and seasonal changes in dryness assessed from two indices for 2081-2100 (bottom three rows, showing the annual time scale and twoseasons, DJF and JJA) and 2046-2065 (top, annual time scale) with respect to 1980-1999. Left column: changes in the maximum number of CDD (days with precipitation
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MANAGING THE RISKS OF EXTREMEEVENTS
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Managing the Risks of Extreme Event
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I Foreword and Preface
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Prefacein understanding and managin
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Summary for PolicymakersBox SPM.1 |
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Summary for PolicymakersB.or sub-na
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Summary for PolicymakersIt is likel
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Summary for Policymakersmicro-insur
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Summary for PolicymakersIt is very
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Summary for PolicymakersOther low-r
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Summary for PolicymakersTable SPM.1
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Summary for PolicymakersBox SPM.2 |
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III Chapters 1 to 9
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Climate Change: New Dimensions in D
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Determinants of Risk: Exposure and
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Changes in Climate Extremes and the
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Changes in Impacts of Climate Extre
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Managing the Risks from Climate Ext
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National Systems for Managing the R
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Managing the Risks: International L
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Toward a Sustainable and Resilient
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Case StudiesChapter 9Table of Conte
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Case StudiesChapter 99.1. Introduct
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Case StudiesChapter 9••••
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Case StudiesChapter 99.2.1.2.3. Hea
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Case StudiesChapter 9CRED, 2009: EM
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Case StudiesChapter 9Hallegatte, S.
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Case StudiesChapter 9O’Neill, M.S
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ANNEXI Authors and Expert Reviewers
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Annex IAuthors and Expert Reviewers
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ANNEXIIGlossary of TermsThis annex
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Annex IIGlossary of Termswater vapo
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Annex IIGlossary of Termsdrought, a
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Annex IIGlossary of TermsImpactsEff
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Annex IIGlossary of Termsforcing is
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ANNEXIIIAcronyms565
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Annex IIIAcronymsNAMNAONAPANaTechND
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ANNEXIVList of Major IPCC Reports56
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Annex IVList of Major IPCC ReportsC
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Index573
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Indexresilience building, 378touris
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IndexEM-DAT database, 364Emissions
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Indextransformation and, 324See als
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IndexRisk sharing, 10-11, 397, 523i
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