Page - 266 - in Loss and Damage from Climate Change - Concepts, Methods and Policy Options

266 A.Lopezet al. 11.2.2 ProjectedChanges inHazard ProjectionsofchangesinfutureclimatearegenerallyderivedusingGeneralCircula- tionModels(GCMs)whichsimulatetheresponseoftheclimatesystemtoascenario offutureemissionsorconcentrationsofgreenhousegasesandaerosols.Eventhough the physical and chemical processes in the climate system followknown physical laws, its complexity implies thatmany simplifications and approximations have to bemadewhenmodelling them.The choice of approximations creates a variety of physical climatemodels (IPCC2013). Therearedifferent sourcesofuncertainties inclimatemodelsimulations, includ- ing(anthropogenicandnatural) forcing, initialconditions,andmodel imperfections (bothmodel uncertainty andmodel inadequacy) (Stainforth et al. 2007). Climate forcingor scenariouncertainty is introducedby the fact that, to simulate future cli- mate, themodels are run using different scenarios of anthropogenic forcings that either representplausiblebut inherentlyunknowablefuturesocioeconomicdevelop- ment,2 or could arise as the result ofmultiplepathwaysof socioeconomicdevelop- ment (Meinshausenetal.2011).Climatemodel imperfectionsand initialconditions uncertainties are due to our incomplete knowledge of the climate system, the lim- itations of computermodels to simulate it, and the system’s non-linearity (Knutti et al. 2007;Stainforth et al. 2007).Toquantify climatemodel uncertainty avariety of climatemodels have been developed around theworld. For instance, the IPCC AR5report (IPCC2013) includesprojections from42climatemodels. Theuncertainty in projections of future climate variability is quantifiedby con- structing,foragivenclimatemodel,asetofprojectionsthatareinitialisedinslightly differentways (see for instanceDeseret al. (2012a,b) for theeffectof initialisation in long termprojections for a single climatemodel, andKirtman et al. (2013) for near termordecadal projections). For eachpossible forcing scenario, ensemblesof different climatemodels that includevariousapproaches to implementing thecom- ponents of the climate system, and,within eachmodel, different parameterisations andinitialisations,areusedtoestimatetheeffectofclimatemodelimperfectionsand initial conditionsuncertainties in theprojectionsofclimatechange. The relative contributions to the total uncertainty from these different sources depend on the spatial scale, the lead-time of the projection, and the variable of interest. For instance for precipitation, at spatial scales of the order of 1000 km, internalvariability is themainsourceofuncertaintyinclimatemodelprojectionsfor many regions in theworld for lead times up to three decades ahead,while forcing uncertainty dominates thereafter (Kirtman et al. 2013;Booth et al. 2013;Hawkins andSutton2009). While GCMs simulate the entire Earth with a relatively coarse spatial resolu- tion (e.g. they can capture featureswith scales of a hundred kilometres or larger), regionalclimateprojectionsdownscaledfromGCMshaveamuchhigher resolution 2This is theapproachusedprior to theIPCCAR5report, see for instanceIPCC(2000),Mossetal. (2008).