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Multi-Criteria AnalysisIn the implementation of MCA it is important toreflect very carefully on how to score thealternatives and which range of scores should beapplied. It is also essential to make sure that theweighted scores can be added, i.e. all criteriashould be formulated in positive terms, or allcriteria should be expressed in negative terms.Usually scores are standardized, so that the highand low levels of the scores represent thejudgement about the performance of thealternatives as precisely as possible. The weightsthen need to be made explicit based on theassessment of the decision makers, or forinstance starting from equal weights and thenaccording to a set of logical and plausibleweights that express the values of variouscategories of stakeholders.This ensures that the impacts of the various setsof weights on the ranking can be assessedtransparently. The process allows decisionmakers to learn about the characteristics of thealternatives and the ranking of the alternativesfor various sets of scores and weights.There are many methods to establish the rankingof the alternatives. The most commonly appliedis the method of weighted summation. However,alternative methods include pair wisecomparison; Analytic Hierarchy Process (AHP) ormore complicated mathematical methods.Detailed descriptions of these methods areavailable from the sources in the further readinglist on Multi Criteria Analysis (e.g. Belton andStewart, 2002).Details of the Analytic Hierarchy Processapproach are provided in a separate PolicyBriefing Note (N o 7).The Application to AdaptationMulti Criteria Analysis has high relevance foradaptation. The criteria can be included toconsider the different aspects of uncertainty aswell as other elements of good adaptation. Asexample, previous adaptation MCAs haveconsidered criteria of robustness, low/no regretcharacteristics or flexibility, as well as cobenefitsand synergies with mitigation.The approach also allows analysis withqualitative information, which is particularlyuseful given there are often data gaps in climatechange adaptation, and/or because there is oftena need to consider additional aspects such asthe acceptability, equity or environmental orsocial performance of options which are difficultto quantify.Applications of MCA to adaptation use some formof climate change information. In more qualitativestudies, this can use climate model information tobuild up indications of the future impacts ofclimate change, e.g. in terms of changes intemperature, weather extremes, runoff and sealevel rise. Similarly the performance of differentadaptation options against these risks can beassessed (i.e. scored). An example of thisqualitative type of approach is included in the casestudy (Van Ierland et al. 2007), which provides anexample of the additional characteristics that canbe included for adaptation, i.e. importance,urgency, no regret characteristics, co-benefits andmitigation synergies.It is also possible to undertake MCA in a morequalitative climate scenario framework, usingclimate model projections and analysis ofoptions (e.g. costs, effectiveness, performanceagainst wider criteria). An example of thisapproach was undertaken within the ThamesEstuary 2100 (TE2100, EA, 2009) project, whichlooked at future flood defences for London usingvarious sea level rise scenarios. This study useda multi-criteria analysis to complement a formaleconomic cost-benefit analysis. The MCA wasused to consider the data collected as part of theStrategic Environmental Assessment andincluded the heritage, recreation and habitatsensitivity criteria, as well as landscapecharacter and capacity assessments, alongsidecosts and benefits within a Multi Criteria Analysis(scoring & weighting).However, MCA does have some limitations inrelation to climate change uncertainty, in that ittends to work with individual scenarios, againstwhich options are assessed. It is more difficult toincorporate the different elements of current andfuture climate risks (the time dimension), and toinclude climate change uncertainty (as well asanalysing how the benefits of differentadaptation options vary against differentscenarios), unless multiple runs of the MCA areconducted. The inclusion of criteria for howoptions perform against uncertainty can beincluded to address this, but this makes theconsideration of uncertainty very qualitative.3