Search

When studying hail falls, it is common to mention their variability, but not so much to present results in support of this statement and do so in detail. This is because of the difficulty of accurately understanding hail falls in spatial and temporal terms. It is even more difficult to ascertain the characteristics of hailstones precipitated by storms. In this paper, we use hailpad databases, which are known to give detailed information on hail falls, to determine spatial and temporal variability across two networks in the Middle Ebro Valley (Northeast Spain), just a few tens kilometers apart. These results demonstrate the importance of having sound ground-based information obtained directly. The databases used have 2865 hailpads that measured 197,076 hailstone impacts (≥ 5 mm). When classifying the severity of storms, the maximum hail diameter is typically used. Among all days with hail events, we selected 71 hailstorms that were tracked over their entire duration, having formed and dissipated within either of the two hailpad networks. We present a methodology and application to determine a mathematical equation that expresses the maximum diameter as a function of meteorological variables, analyzing possible uncertainties to make short-term predictions. This equation facilitates improvement of our knowledge of factors that influence the appearance of storms and the classification of predicted severity. • Hailpad databases, to determine spatial and temporal was used. • 71 hailstorms events were tracked over their entire duration • A equation that expresses the maximun diameter as a function of meteorological variables was developed. • The findings improve the knowledge of factors that influence the classification of predicted storms severity. [ABSTRACT FROM AUTHOR]

Abstract One of the main challenges in studies of hail precipitation is the estimation of its trends in the context of global warming. The strong spatiotemporal variability of hailfalls, together with their small scale, makes it difficult to record all such events and build long and homogeneous databases. For this reason, obtaining direct observation trends yields large uncertainties. The study of atmospheric parameters at various scales that influence deep convection and its temporal change has been used to estimate possible trends in the frequency of hailfalls. In this article, we analyze atmospheric variability at synoptic scale during the warm season in Southwest Europe, using empirical orthogonal function analysis and hailfall records from dense hailpad networks in northeastern Spain and southern France. These networks have uninterrupted operation during the warm season and reliable data. This method allowed us to obtain spatial modes of variability and temporal changes, facilitating estimation of changes in hail frequencies. The results show that the main modes of variability of 500-hPa geopotential height facilitate the definition of patterns that favor hailfalls throughout the warm season, whereas lapse-rate patterns between 850 and 500 hPa are shown to be important in the central months of the hail season. In addition, temporal changes in patterns related to hailfall variability suggest changes in the hailfall distribution during the warm season, with a decrease in hail frequency during June and increase during July. Highlights • We analyzed atmospheric variability at synoptic scale during the warm season. • Hailfall records were acquired by hailpad networks in northeastern Spain and southern France. • Empirical orthogonal function (EOF) analysis was used to retrieve the atmospheric variability. • Temporal changes in the patterns related to hailfall variability has been observed. [ABSTRACT FROM AUTHOR]