Assessing natural variability in RCM signals: comparison of a multi model EURO-CORDEX ensemble with a 50-member single model large ensemble

Uncertainties in climate model ensembles are still relatively large. Besides scenario and model response uncertainty, natural variability is another important source of uncertainty. To study regional natural variability on timescales of several decades and more, observations are often too sparse and short. Regional Climate Models (RCMs) can be used to overcome this lack of useful data at high spatial resolutions. In this study, we compare a new 50-member single RCM large ensemble (CRCM5-LE) with an ensemble of 22 EURO-CORDEX models for seasonal temperature and precipitation at 0.11 degrees grid size over Europe-all driven by the RCP 8.5 scenario. This setup allows us to quantify the contribution of natural/model-internal variability on the total uncertainty of a multi-model ensemble. The variability of climate change signals within the two ensembles is compared for three future periods (2020-2049, 2040-069 and 2070-2099). Results show that the single model spread is usually smaller than the multi-model spread for temperature. Similar variabilities can mostly be found in the near future (and to a lesser extent in the mid future) during winter and spring, especially for northern and central parts of Europe. The contribution of internal variability is generally higher for precipitation. In the near future almost all seasons and regions show similar variabilities. In the mid and far future only fall, summer and spring still show similar variabilites. There is a significant decrease of the contribution of internal variability over time for both variables. However, even in the far future for most regions and seasons 25-75% of the overall variability can be explained by internal variability.