Atmospheric fronts are fundamental features of the weather variability in the mid‐latitudes and are frequently associated with high‐impact weather events such as hail, wind gusts or precipitation. A method to link precipitation with synoptic‐scale fronts on sub‐daily timescales is developed based on ERA‐Interim data (1979–2016). A case study, a climatology and a trend analysis are presented and discussed. Spatially, an optimal attribution radius is identified based on a random sampling technique. The method is demonstrated using a past weather event that occurred over western Europe. Annual and seasonal cycles are presented and confirm, in agreement with previous studies, that frontal precipitation accounts for a large fraction of all precipitation (up to 80%) in the mid‐latitudes, especially during autumn and winter. Finally, a negative trend in frontal precipitation is identified, mostly affecting the Gulf Stream region. Cold fronts drive most of the observed trends in this region and the trend pattern suggests a polewards displacement of the zone of enhanced precipitation.

The Iberian Peninsula (IP) is often affected by extreme precipitation and severe winds that are mostly associated with extratropical cyclones and their atmospheric fronts. ERA5 reanalysis data are used to revise and update two existing rankings of extreme precipitation and extreme potential wind‐loss days for the extended winter months on the IP. A ranking of concurrent precipitation and wind extreme events is produced by matching the two individual rankings for the IP and for specific IP subregions, including its main river basins. The intensity and the variability at the interannual and decadal scale are evaluated for precipitation, wind and concurrent precipitation and wind events. A systematic analysis of the underlying synoptic conditions is pursued for the top100 most extreme concurrent events including (a) cyclones' trajectories, (b) the presence of an Atmospheric River (AR), (c) recurrent patterns in the locations affected by precipitation and wind extremes and (d) possible long‐term trends. Results show that 85% of concurrent precipitation and wind extreme events are clearly associated with a cyclonic feature and most of these cyclones either cross the IP or pass to the northwest. Concurrent events are more likely occurring in the northwestern sectors of the IP on wintertime as in recent decades a downward trend for the events' frequency is observed in autumn. ARs are more likely associated with the strongest events occurring on the western sector of IP. Accordingly, the areas that mostly experience concurrent precipitation and wind extremes related to those systems are located in the northwestern sector of the peninsula.

The Adriatic basin is regularly affected by cold, strong and gusty bora winds blowing from the northeast, especially during winter. These events are characterized by intense air-sea interactions and produce important meteorological effects not only over the eastern Adriatic basin, where bora originates and attains its maximum intensity, but also downstream over the Italian peninsula where heavy rainfall and snowfall can occur.The present study aims at evaluating the impact of surface fluxes of sensible and latent heat, that characterize air-sea interaction during a bora episode, on wind strength and profiles over the Adriatic Sea, in relation to intense precipitation affecting the Apennines and the Italian coast. High-resolution numerical simulations are used in order to assess the role of surface fluxes in modulating the atmospheric water balance, modifying the thermodynamic characteristic of the boundary layer and, in turn, the dynamics of the orographic flow regime.Results show that while surface evaporation is responsible for a relatively small contribution to the total atmospheric water budget over the Adriatic area, surface fluxes still have a remarkable impact on precipitation via dynamical processes. Both sensible and latent heat fluxes modify the speed, temperature and moisture profiles of the low-level bora wind, sensibly changing the dynamical characteristics of interaction of the flow with the downstream orography. The orographic flow regime determines the intensity and location of orographically induced uplift and hence precipitation. Therefore, the picture that directly associates the precipitation amount upstream and over the Apennines with the degree of moistening of air during its passage over the sea and with orographic uplift is shown to be too simplistic. The variations of the wind speed and static stability due to surface fluxes involve complex and nonlinear effects, changing the flow regime in response to the orographic forcing and thus determining amount and location of heavy precipitation.

An assessment of daily accumulated precipitation during extreme precipitation events (EPEs) occurring over the period 2000–2008 in the Iberian Peninsula (IP) is presented. Different sources for precipitation data, namely ERA-Interim and ERA5 reanalysis by the European Centre for Medium-Range Weather Forecast (ECMWF) and Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA), both in near-real-time and post-real-time releases, are compared with the best ground-based high-resolution (0.2° × 0.2°) gridded precipitation dataset available for the IP (IB02). In this study, accuracy metrics are analysed for different quartiles of daily precipitation amounts, and additional insights are provided for a subset of EPEs extracted from an objective ranking of extreme precipitation during the extended winter period (October to March) over the IP. Results show that both reanalysis and multi-satellite datasets overestimate (underestimate) daily precipitation sums for the least (most) extreme events over the IP. In addition, it is shown that the TRMM TMPA precipitation estimates from the near-real-time product may be considered for EPEs assessment over these latitudes. Finally, it is found that the new ERA5 reanalysis accounts for large improvements over ERA-Interim and it also outperforms the satellite-based datasets.