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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 ormore 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 theimpacts assessment. An alternative approach for assessing possible impacts of climate change follows a 'bottom-up' (or inverse modeling) 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 modeling assumptions will these limits be exceeded? And how do these future changes relate to current climate variability? In this paper we present a systematicapproach for considering the effect of a set of scenario and modeling 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 relatingto 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 visualizing the effects on realised future climate of different modeling assumptions and scenario uncertainties, we make more [ABSTRACT FROM AUTHOR]