Linking torrential events in the Northern French Alps to regional and local atmospheric conditions

Abstract. In this article we study the atmospheric conditions at the origin of damaging torrential events in the Northern French Alps over the long run, using a database of reported occurrence of damaging torrential flooding in the Grenoble conurbation since 1851. We consider seven atmospheric variables that describe the nature of the air masses involved and the possible triggers of precipitation. Using both 20CRv2c and ERA5 reanalyses, we try to isolate the variables associated with torrential events, by objectively determining which of them differ particularly from the climatology at the dates of torrential events. This analysis is done conditionally on the main types of generating atmospheric circulation derived from Lamb weather classes, namely the North-West, Southeast-Southwest and Barometric Swamp classes. Furthermore, the atmospheric variables are considered over two spatial scales – a local scale (the Grenoble conurbation) and a regional scale (the French Alps), in order to study the spatial variability of the atmospheric signature. The results show that all atmospheric variables are less discriminant for torrential events before 1950 according to 20CRv2c – this is likely more linked to 20CRv2c limitations over the remote past than a consequence of climate change. For the post-1950 period, similar atmospheric signatures are found both at local and regional scales in the North-West and Southeast-Southwest classes and for both reanalyses. In the North-West class – which is the best discriminated – humidity and particularly humidity transport (IVT) plays the greatest role. In the Southeast-Southwest class, instability potential (CAPE) is mostly at play. In the Barometric Swamp class both humidity (PWAT) and instability (CAPE) are discriminant – and even more at the local scale –, showing more mixed situations generating torrential events in this class. In total, depending on the class, torrential events are 4 to 14 times more likely when the respective discriminant variables are extreme (typically above their 0.95-quantile).