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This paper analyses the dependency of regional air pollution in Europe on the atmospheric circulation as represented by a set of 8 weather regimes (WRs). For this purpose, daily average PM 2.5 concentrations and daily maximum concentrations of O 3 , NO 2 and CO obtained from an atmospheric composition reanalysis have been used. The results indicate that the pollutant concentrations change substantially with the occurrence of each WR according to the associated circulation patterns. In the extended winter, the responses of PM 2.5 , NO 2 and CO are quite similar, with zonal circulation regimes leading to better air quality than anticyclonic regimes linked to steady flows over Europe. On the other hand, the spatial patterns of O 3 anomalies under most WRs resemble those of temperature in the extended summer as temperature enhancements favour the photochemical production of O 3. The WR characterized by anticyclonic anomalies over Scandinavia leads to the highest concentrations at continental scale and is concurrent with an increased probability of exceeding the poor air quality limits of winter PM 2.5 and summer O 3 in most European countries. It is also found that a multiple linear regression model on the monthly frequency of WRs can explain a considerable fraction of the intermonthly variability of concentration anomalies over large parts of Europe regardless of the pollutant, with R2 values around 0.6–0.8 over large regions. Overall, the application of these models to sub-seasonal weather forecasts does not seem to bring major improvements to the prediction of month-ahead concentration anomalies as compared to the climatology. The poor skill of sub-seasonal forecasts in predicting the WRs for lead times beyond 15 days limits the forecast capability. However, these results open the possibility of extending current air quality forecast to scales of 5–10 days at a low cost in a near future. [Display omitted] • European-wide study of the modulation of air quality by weather regimes (WRs). • WRs explain 60–80% of the monthly variability in air pollution over large regions. • The poorest air quality in most of Europe is associated with Scandinavian blocking. • Evaluation of WRs as a tool to predict month-ahead air pollution anomalies. [ABSTRACT FROM AUTHOR]

Abstract: Forecasting hailstorms is an important challenge. Improving these forecasts is of vital importance to reduce the risks that this phenomenon causes to the environment and the population. This paper presents a methodology for the characterization of hailstorms in different scales by means of: the definition of the synoptic environment favorable to convection, the establishment of mesoscale configurations on hailstorm days, and an analysis of prediction parameters for the presence of hail. Simulations with the WRF model were done for 100 study days in which hailstorms were produced in the Middle Ebro Valley. The synoptic environment was defined from the average geopotential and temperature fields at 500hPa. Using multivariate techniques of the Principal Component Analysis in T-Mode and a Cluster Analysis, four mesoscale configurations were defined for the fields of convective instability, water vapor flux divergence and wind flow and humidity at low layers. Finally, the study included several hail forecast parameters: CAPE, Storm Relative Helicity between 0 and 3km (SRH0–3), Energy–Helicity Index (EHI) and Showalter Index (SI); making a comparison between hail/hail-free grid points, which allowed us to determine their values and thresholds in order to discern the presence of hail within convective precipitation areas. The analysis, along with these three basic ingredients, provides a very useful tool that allows for a good approximation for predicting storms with hail in the study area. [Copyright &y& Elsevier]