Seite - 130 - in Loss and Damage from Climate Change - Concepts, Methods and Policy Options

130 R.A. Jameset al. Fig.5.4 Aschematic illustrationof theprobabilitydistributionofaclimatevariable (suchas tem- peratureorprecipitation)with(solidredline)andwithout (greenline)humaninfluenceonclimate. Extremeeventattributionstudiesusestatisticsorclimatemodels toestimatethesedistributionsand then calculate the change inprobability associatedwith anthropogenic forcing (i.e. the difference betweenthegreenhatchedarea—P0—andtheredhatchedarea—P1).Thereddashedlineillustrates howtheprobabilitydistributionof thevariablemight change in future. SourceStott et al. (2016) (see www.climatecentral.org). For example, the flooding in Louisiana in August 2016was attributed to have beenmade twice as likely due to anthropogenic cli- mate change, two weeks after the event occurred (van der Wiel et al. 2017). A large signal from anthropogenic climate change on the early 2017 drought in Kenya could be excluded while the event was still unfolding (Uhe et al. 2017). It is currently not possible to conduct scientifically viable attribution studies for all typesofextremeweatherevents leadingtolossesanddamages(seeFig.5.5),and some specific cases can be particularly difficult tomodel due to rare and complex weatherpatterns,aswasfoundforflooding inPakistan in2010(e.g.Christidisetal. 2013).There are also important variations in the availability andquality of attribu- tion evidencebetween regions.Currently,manymore studies havebeen conducted for developed than developing countries (Otto et al. 2015a). There are efforts to change this (e.g.wwa.climatecentral.org), but limited availability of data in devel- oping countries is a barrier (Huggel et al. 2015a).This is highly relevant forL&D, because itmeans it is challenging tomake attribution statements about losses and damages from some disasters. It is also important to highlight that in some cases anthropogenicclimatechangeisfoundtodecreasetheprobabilityofextremeevents, suchasspringfloodingfromsnowmelt in theUK(Kayetal.2011)ornot toalter the likelihoodof theeventoccurring, as for the2014–15droughts in theSaoPaoloarea (Ottoet al. 2015b). Uncertaintiesassociatedwithevent attributionstudiescanmake the results chal- lengingtocommunicateandapplyinpolicy(Ottoetal.2015a),aswithprojectionsof climatechange(Weaveretal.2013).Theresultsofattributionstudiesalsodependon