Evaluation of the ALARO1-SFX (CY43T2) regional climate model over Belgium across different resolutions

Abstract. Regional climate modelling is essential for providing reliable information to understand localised impacts and guide adaptation strategies in the context of climate change. This study evaluates long-term continuous climate simulations over Belgium performed with the ALARO1-SFX model, a novel version of ALARO-1 that incorporates an advanced surface scheme (SURFEX) and improved physiographic datasets. A scale-selective evaluation setup is introduced, employing a multi-level dynamical downscaling framework to assess the progressive added value of increasing resolution from the mesoscale to convection-permitting scales. The model's performance is evaluated against a gridded observational dataset and precipitation station measurements, focusing on temperature and precipitation biases, diurnal precipitation cycles, and extreme precipitation statistics. Results indicate that the higher resolutions (12.5 and 4 km) improve temperature and precipitation biases relative to the 25 km simulation, with the 4 km resolution providing the best representation of hourly extreme precipitation and its diurnal cycle. A dedicated sensitivity experiment isolates the contribution of the SURFEX land-surface scheme from that of resolution, attributing a substantial part of the improvement in near-surface temperature and precipitation to the introduction of SURFEX. However, all simulations exhibit varying degrees of wet and cold biases. The findings underscore the added value of convection-permitting modelling for improving diurnal precipitation cycles. Furthermore, the study provides evidence that increasing model resolution improves the representation of extreme precipitation.