Portraying climate scenario uncertainties in relation to tolerable regional climate change

Analyses of the impacts of future anthropogenic climate change on environmental and social systems have been dominated by a 'top-down' approach. A climate change scenario is defined using output from one or more climate model experiments, the scenario is run through one or more environmental simulation models, and the impacts of the prescribed climate change evaluated. This approach places a considerable burden on the selection of which climate change scenarios should drive the impacts assessment. An alternative approach for assessing possible impacts of climate change follows a 'bottom-up' (or inverse modelling) approach. Here, the sequence of analysis steps is inverted. An assessment is made of what range of magnitudes and/or rates of regional climate change could be adapted to by an environmental or social exposure unit. The question is then asked of the climate scenario developer, how likely is it that future regional climate change will exceed these limits, and by when? Under what scenario or modelling assumptions will these limits be exceeded? And how do these future changes relate to current climate variability? In this paper we present a systematic approach for considering the effect of a set of scenario and modelling uncertainties on the likelihood of critical climate change being exceeded for particular exposure units. We present this assessment in the context of observed climate change over the last 100 yr and illustrate the approach for the UK and for 2 thresholds of climate change. These are defined, very simplistically, in terms of summer mean temperature and rainfall and as such may nominally be regarded as relating to water resources in the UK. We argue that one of the strongest advantages of this approach is that it disarms those who wield climate change scenarios as though they were in some sense 'predictions' of future climate. By visualising the effects on realised future climate of different modelling assumptions and scenario uncertainties, we make more transparent the judgements that must be made in assessing the significance of climate change impacts on different regional exposure units.