In this study, we quantify the effect of uncertainties in climate projections on an impact model (IPS) that describes the temperature-dependent swarming and development of Ips typographus. Three forcing climate data sets (ensembles) were used: (1) E-Obs gridded observations, (2) ERA-40 reanalysis data downscaled by eight regional climate models (RCMs) and (3) regional scenarios from one RCM forced by seven GCM simulations representing SRES-A1B, for the period of 1961–2097. The IPS_RCM_ERA40 ensemble members, including IPS_RC3_ERA40, were generally within the IPS_E-Obs confidence limits. The IPS model is however sensitive to the warming during spring and cooling during autumn, and deviations in simulated swarming were related to known climate model biases. The variation between the IPS_RCA3_GCM ensemble members was particularly high in regions where warmer summers (temperature increase from +2 °C to +4 °C) will induce an additional generation per year, for example a shift from one to two generations per year in south Scandinavia, and an increased frequency of three generations per year in central Europe. Impact assessments based on an ensemble of climate data gives more robust decision support than a single climate model approach because it allows a probabilistic assessment of the geographical areas experiencing a transition in biological response.