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Important discrepancies in the large-scale summer climate change projections were recently detected between the global and regional climate models (RCM/GCM) in the EURO-CORDEX ensemble for several variables including surface temperature, total precipitation, and surface solar radiation. In this study, we use a new experimental framework inspired by the Big-Brother–Little-Brother protocol to explore the mechanisms responsible for generating large-scale discrepancies in future projections between GCM/RCM pairs over Europe in summer. Starting from past and future simulations with a perfect GCM/RCM pair (same resolution, same physics, same forcings), we then disentangle the role of potential sources of GCM/RCM inconsistency by carrying out targeted sensitivity studies. We show that by following such a perfect approach, it is possible to obtain a GCM/RCM pair without statistically significant inconsistencies in projected climate change. Such discrepancies are mainly generated by differences in aerosols representation and atmospheric physics. The role of plant physiology is limited and unlikely to be the dominant factor in the detected discrepancies. Finally, it is unlikely that the discrepancies in the EURO-CORDEX ensemble projections are a result of the upscaled added value, as we show that the effect of increased resolution is not strong enough and mostly limited to areas with complex topography. These findings raise important questions about the current practices in regional climate modelling. In the short term, implementing RCM external forcings consistent with the driving GCM can significantly improve the situation at low cost. In the long term, adopting a seamless strategy in developing the GCM/RCM models should be questioned. [ABSTRACT FROM AUTHOR]

South-East France is a region often affected by heavy precipitating events the characteristics of which are likely to be significantly impacted in the future climate. In this study, cnrm-arome, a Convection-Permitting Regional Climate Model with a 2.5 km horizontal resolution is compared to its forcing model, the Regional Climate Model aladin-climate at a horizontal resolution of 12.5 km, self-driven by the era-interim reanalysis. An hourly observation dataset with a resolution of 1 km, comephore, is used in order to assess simulated surface precipitation from a seasonal to hourly scale. The representation of the spatial pattern of fall precipitation climatology is improved by cnrm-arome. It also shows a clear added value with respect to aladin-climate through the improvement of the localization and intensity of extreme rainfall on a daily and hourly time scale on both fine and coarse spatial scales (2.5, 12.5 and 50 km). cnrm-arome in particular is able to simulate intense rainfall on lowlands and makes sub-daily rainfall events more intense than aladin-climate. cnrm-arome still underestimates very extreme precipitation from above 30 mm/h or 230 mm/day. [ABSTRACT FROM AUTHOR]