IPCC_Managing Risks of Extreme Events.pdf - Climate Access

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Changes in Climate Extremes and their Impacts on the Natural Physical EnvironmentChapter 3bottom drainage (Smith et al., 2005). Overall, increased air temperatureover high latitudes is primarily responsible for the development ofthermokarst terrains and thaw lakes.In summary, it is likely that there has been warming of permafrostin recent decades. There is high confidence that permafrosttemperatures will continue to increase, and that there will beincreases in active layer thickness and reductions in the area ofpermafrost in the Arctic and subarctic.3.5.8. Sand and Dust StormsSand and dust storms are widespread natural phenomena in many partsof the world. Heavy dust storms disrupt human activities. Dust aerosols inthe atmosphere can cause a suite of health impacts including respiratoryproblems (Small et al., 2001). The long-range transport of dust canaffect conditions at long distances from the dust sources, linking thebiogeochemical cycles of land, atmosphere, and ocean (Martin andGordon, 1988; Bergametti and Dulac, 1998; Kellogg and Griffin, 2006).For example, dust from the Saharan region and from Asia may reachNorth America and South America (McKendry et al., 2007). Some climatemodels have representations of dust aerosols (Textor et al., 2006).Climate variables that are most important to dust emission and transportsuch as soil moisture (see also Section 3.5.1), precipitation, wind, andvegetation cover are still subject to large uncertainties in climate modelsimulations. As a result, the sand and dust storm simulations have largeuncertainties as well.The Sahara (especially the Bodélé Depression in Chad) and east Asiahave been recognized as the largest dust sources globally (Goudie,2009). Over the few decades before the 1990s, the frequency of dustevents increased in some regions such as the Sahel zone of Africa(Goudie and Middleton, 1992), and decreased in some other regionssuch as China (Zhang et al., 2003). There seems to be an increase in morerecent years in China (Shao and Dong, 2006). Despite the importance ofAfrican dust, studies on long-term change in Sahel dust are limited.However, dust transported far away from the source region may providesome evidence of long-term changes in the Sahel region. The Africandust transported to Barbados began to increase in the late 1960s andthrough the 1970s; transported dust reached a peak in the early 1980sbut remains high into the present (Prospero and Lamb, 2003; Prosperoet al., 2009).Surface soil dust concentration during a sand and dust storm iscontrolled by a number of factors. The driving force for the productionof dust storms is the surface wind associated with cold frontal systemssweeping across arid and semi-arid regions and lifting soil particles inthe atmosphere. Dust emissions are also controlled by the surfaceconditions in source regions such as the desert coverage distributions,snow cover, and soil moisture. For example, in the Sahel region, theelevated high level of dust emission prior to the 1990s was related tothe persistent drought during that time, and to long-term changes in theNAO (Ginoux et al., 2004; Chiapello et al., 2005; Engelstaedter et al.,2006), and perhaps to North Atlantic SST as well (Wong et al., 2008).Further evidence of the importance of climate on dust emission is thatdespite an increase of approximately 2 to 7% in desert areas in Chinaover the four decades since 1960, dust storm frequency decreased inthat period (Zhong, 1999). Studies on Asian soil dust production from1960 to 2003 suggest that climatic variations have played a major rolein the declining trends in dust emission and storm frequencies in China(Zhang et al., 2003; Zhou and Zhang, 2003; Zhao et al., 2004; Gong etal., 2006). Overall, changes in dust activity are affected by changes inthe climate, such as wind and moisture conditions in the dust sourceregions. Changes in large-scale circulation play an additional role in thelong-distance transport of dust. However, understanding of the physicalmechanisms of the long-term trends in dust activity is not complete; forexample, the relative importance of the various factors affecting dustfrequency as outlined above is uncertain.Future dust activity depends on two main factors: land use in the dustsource regions, and climate both in the dust source region and largescalecirculation that affects long distance dust transport. Studies onprojected future dust activity are very limited. It is difficult to projectfuture land use. Precipitation, soil moisture, and runoff have beenprojected to decrease in major dust source regions (Figure 10.12 in Meehlet al., 2007b). Thomas et al. (2005) suggest that dune fields in southernAfrica can become active again, and sand will become significantlyexposed and move, as a consequence of 21st-century warming. A studybased on simulations from two climate models also suggests increaseddesertification in arid and semi-arid China, especially in the second halfof the 21st century (X.M. Wang et al., 2009). However, confident projectedchanges in wind are lacking (see Section 3.3.3).In summary, there is low confidence in projecting future duststorm changes, although an increase could be expected wherearidity increases. There is a lack of data and studies on pastchanges. There is also a lack of understanding of processes suchas the relative importance of different climate variables affectingdust storms, as well as a high uncertainty in simulating importantclimate variables such as soil moisture, precipitation, and windthat affect dust storms.190
Chapter 3Changes in Climate Extremes and their Impacts on the Natural Physical EnvironmentTable 3-2 | Regional observed changes in temperature and precipitation extremes, including dryness, since 1950 unless indicated otherwise, and using late 20th-century values as reference (see Box 3-1), generally 1961-1990.See Figure 3-1 for definitions of regions. For assessments for small island states refer to Box 3-4.A. North America and Central AmericaRegionsTmax[WD = Warm DaysCD = Cold Days; see Box 3-1] (using late20th-century extreme values as reference,e.g., 90th/10th percentile)Tmin[WN = Warm NightsCN = Cold Nights; see Box 3-1] (usinglate 20th-century extreme values asreference, e.g., 90th/10th percentile)Heat Waves (HW)/Warm Spells (WS)[WSDI = Warm Spell Duration Index,i.e., number or fraction of daysbelonging to spells of at least 6days with Tmax >90th percentile](using late 20th-century extremevalues as reference)Heavy Precipitation (HP)(using late 20th-century extreme valuesas reference, e.g., 90th percentile)Dryness[CDD = Consecutive Dry DaysSMA = (Simulated) Soil MoistureAnomaliesPDSI = Palmer Drought Severity Index;see Box 3-3 for definitions]All NorthAmerica andCentralAmericaW. NorthAmerica(WNA, 3)CentralNorthAmerica(CNA, 4)E. NorthAmerica(ENA, 5)Alaska/N.W. Canada(ALA, 1)E. Canada,Greenland,Iceland(CGI, 2)CentralAmerica andMexico(CAM, 6)High confidence: Likely overall increase in WD,decrease in CD (Aguilar et al., 2005; Alexander etal., 2006).High confidence: Very likely large increases inWD, large decreases in CD (Robeson, 2004;Vincent and Mekis, 2006; Kunkel et al., 2008;Peterson et al., 2008a).Medium confidence: Spatially varying trends.Small increases in WD, decreases in CD in northCNA. Small decreases in WD, increases in CD insouth CNA (Robeson, 2004; Vincent and Mekis,2006; Kunkel et al., 2008; Peterson et al., 2008a).Medium confidence: Spatially varying trends.Overall increases in WD, decreases in CD;opposite or insignificant signal in a few areas(Robeson, 2004; Vincent and Mekis, 2006; Kunkelet al., 2008; Peterson et al., 2008a).High confidence: Very likely large increases inWD, large decreases in CD (Robeson, 2004;Vincent and Mekis, 2006; Kunkel et al., 2008;Peterson et al., 2008a).High confidence: Likely increases in WD in someareas, decrease in others. Decreases in CD insome areas, increase in others (Robeson, 2004;Alexander et al., 2006; Vincent and Mekis, 2006;Trenberth et al., 2007; Kunkel et al., 2008;Peterson et al., 2008a).Medium confidence: Increases in WD, decreasesin CD (Aguilar et al., 2005; Alexander et al.,2006).High confidence: Likely overall decrease inCN, increase in WN (Aguilar et al., 2005;Alexander et al., 2006).High confidence: Very likely large decreasesin CN, large increases in WN (Robeson,2004; Vincent and Mekis, 2006; Kunkel etal., 2008; Peterson et al., 2008a).Medium confidence: Spatially varyingtrends. Small decreases in CN, increases inWN in north CNA. Small increases in CN,decreases in WN in south CNA (Robeson,2004; Vincent and Mekis, 2006; Kunkel etal., 2008; Peterson et al., 2008a).Medium confidence: Weak and spatiallyvarying trends. (Robeson, 2004; Vincentand Mekis, 2006; Kunkel et al., 2008;Peterson et al., 2008a).High confidence: Very likely large decreasesin CN, large increases in WN (Robeson,2004; Vincent and Mekis, 2006; Kunkel etal., 2008; Peterson et al., 2008a).Medium confidence: Small increases inunusually cold nights, decreases in WN innortheastern Canada. Small decreases inCN, increases in WN in southeastern andsouth central Canada. (Robeson, 2004;Vincent and Mekis, 2006; Kunkel et al.,2008; Peterson et al., 2008a).Medium confidence: Decreases in CN,increases in WN (Aguilar et al., 2005;Alexander et al., 2006).Medium confidence: Overall increasesince 1960 (Kunkel et al., 2008). Someareas with significant WSDI increase,others with insignificant WSDI increaseor decrease (Alexander et al., 2006).Medium confidence: Increase in WSDI(Alexander et al., 2006).Medium confidence: Spatially varyingtrends. Some areas with WSDI increase,others with WSDI decrease (Alexander etal., 2006).Medium confidence: Spatially varyingtrends. Many areas with WSDI increase,some areas with WSDI decrease(Alexander et al., 2006).High confidence: Likely increase in manyareas since 1950 (Aguilar et al., 2005;Alexander et al., 2006; Trenberth et al.,2007; Kunkel et al., 2008).Medium confidence: Spatially varyingtrends. General increase, decrease in someareas (Alexander et al., 2006).High confidence: Very likely increase since1950 (Alexander et al., 2006).High confidence: Very likely increase since1950 (Alexander et al., 2006).Low confidence: Insufficient evidence. Medium confidence: Slight tendency forincrease, in southern Alaska; no significanttrend (Kunkel et al., 2008).Medium confidence: Some areas withWSDI increase, most others with WSDIdecrease (Alexander et al., 2006).Low confidence: Spatially varying trends.A few areas increase, a few othersdecrease (Aguilar et al., 2005; Alexanderet al., 2006).Medium confidence: Increase in a few areas(Alexander et al., 2006).Medium confidence: Spatially varyingtrends. Increase in many areas, decrease ina few areas, (Aguilar et al., 2005;Alexander et al., 2006).Medium confidence: Overall slight decreasein dryness (SMA, PDSI, CDD) since 1950;regional variability and 1930s droughtdominate the signal (Aguilar et al., 2005;Alexander et al., 2006; Kunkel et al., 2008;Sheffield and Wood, 2008a; Dai, 2011).Medium confidence: No overall or slightdecrease in dryness (SMA, PDSI, CDD) since1950; large variability, large drought of1930s dominates (Alexander et al., 2006;Kunkel et al., 2008; Sheffield and Wood,2008a; Dai, 2011).Medium confidence: Decrease in dryness(SMA, PDSI, CDD) and increase in meanprecipitation since 1950; large variability,large drought of 1930s dominates(Alexander et al., 2006; Kunkel et al., 2008;Sheffield and Wood, 2008a; Dai, 2011).Medium confidence: Slight decrease indryness (SMA, PDSI, CDD) since 1950, largevariability, large drought of 1930sdominates (Alexander et al., 2006; Kunkelet al., 2008; Sheffield and Wood, 2008a;Dai, 2011).Medium confidence: Inconsistent trends;increase in dryness (SMA, PDSI, CDD) since1950 in part of the region. (Alexander etal., 2006; Kunkel et al., 2008; Sheffield andWood, 2008a; Dai, 2011).Low confidence: Insufficient evidence.Low confidence: Spatially varying trends,inconsistencies in trends in dryness (SMA,PDSI, CDD). (Aguilar et al., 2005; Sheffieldand Wood, 2008a; Dai, 2011).Continued next page191
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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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138much of the continental United S
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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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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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