Abstract/Summary

We evaluate a 12-member perturbed parameter ensemble of regional climate simulations over Europe at 12km resolution, carried out as part of the UK Climate Projections (UKCP) project. This ensemble is formed by varying uncertain parameters within the model physics, allowing uncertainty in future projections due to climate modelling uncertainty to be explored in a systematic way. We focus on present day performance both compared to observations, and consistency with the driving global ensemble. Daily and seasonal temperature and precipitation are evaluated as two variables commonly used in impacts assessments. For precipitation we find that downscaling, even whilst within the convection-parameterised regime, generally improves daily precipitation, but not everywhere. In summer, the underestimation of dry day frequency is worse in the regional ensemble than in the driving simulations. For temperature we find that the regional ensemble inherits a large wintertime cold bias from the global model, however downscaling reduces this bias. The largest bias reduction is in daily winter cold temperature extremes. In summer the regional ensemble is cooler and wetter than the driving global models, and we examine cloud and radiation diagnostics to understand the causes of the differences. We also use a low-resolution regional simulation to determine whether the differences are a consequence of resolution, or due to other configuration differences, with the predominant configuration difference being the treatment of aerosols. We find that use of the EasyAerosol scheme in the regional model, which aims to approximate the aerosol effects in the driving model, causes reduced temperatures by around 0.5K over Eastern Europe in Summer, and warming of a similar magnitude over France and Germany in Winter, relative to the impact of interactive aerosol in the global runs. Precipitation is also increased in these regions. Overall, we find that the regional model is consistent with the global model, but with a typically better representation of daily extremes and consequently we have higher confidence in its projections of their future change.