Projected changes in future climate are inherently uncertain. This uncertainty stems largely from the fact that, even for a specified emissions scenario, global climate model (GCM) simulations result in a range of plausible scenarios being modelled. While most models do agree that the globally averaged surface temperature will increase due to increasing atmospheric concentrations of greenhouse gases, there is a significant divergence between models in both the spatial and temporal projections of changes in precipitation. These differences are most pronounced at the regional scale. For example, differences are apparent in the magnitude of projected temperature changes between GCMs; for precipitation projections, both magnitude and direction of change can vary between GCMs. Nonetheless, regional scale climate information is necessary if robust adaptation strategies are to be developed. Until recently, the use of a single climate scenario or climate trajectory was common in the literature. However, reliance on the output from a single GCM means there is significant potential for gross underor over-estimation of the associated risks, which may result in poor decision-making and increase the risk of maladaptation. This report presents an overview of the uncertainties that cascade or propagate through the climate modelling framework – from emissions scenarios to subsequent climate projections. It describes a methodology that has been developed for quantifying such uncertainties at the regional scale. Initially, a methodology adopted from the dynamical modelling community was used to ‘pattern scale’ previously downscaled emissions scenarios for selected locations in Ireland. This enabled the quantification of projected changes in temperature and precipitation for the end of the present century across four marker emissions scenarios. In order to produce probabilistic-based scenarios of temperature and precipitation for the selected station locations, a Monte Carlo analysis was employed in conjunction with three different estimates of future warming. The projected changes in both temperature and precipitation were found to display a considerable spread in values. For example, winter temperature at one location suggested an increase from between 0.6 and 6.6°C by the 2080s’ (2070–2099) period. While the methodology outlined should enable the rapid development of probabilistic climate projections, based on a limited availability of downscaled climate scenarios, caution needs to be expressed in the interpretation of the results outlined in this report. While they provide a basis for assessing the potential risks associated to be quantified, at least one study has illustrated that details of the level of risk are not independent of the methods employed (New et al., 2007).