Dynamic drivers dominate the regionally specific precipitation concentration changes over the Atlantic-European region

Regression modeling and variance partitioning are used to identify drivers of changes in precipitation concentration, represented by the seasonal Gini index (GI). While specific humidity characterizes moisture availability and represents the thermodynamic drivers, four large-scale circulation modes (NAO, SCA, EAWR, EA) constitute the dynamic drivers. The regression model, which uses all drivers, explains a substantial fraction of the GI variability, with the best performance in winter (40% of the mean explained variability) and the worst in summer (22% of the mean explained variability). The unique contribution of the dynamic drivers to the total explained GI variability is, on average, twice that of the specific humidity across all seasons. The GI variability is mostly indirectly linked to atmospheric moisture conditions over Europe, while the circulation modes significantly modulate this relationship regionally. This modulation exhibits strong seasonality and a typical dipole pattern, with regions of significant positive and negative effects on GI variability for individual modes and seasons. Although the analysis of unexplained GI variability cannot be considered direct proof, it suggests that internal variability could contribute significantly to GI variance. The observed and projected trends in the main GI drivers indicate a further increase in precipitation concentration, particularly in southern and central Europe, and a decrease in the northern part of the Atlantic-European region.