Rainfall data augmentation in Northern Italy through daily extremes and the Hershfield factor

Abstract

Abstract. The majority of rainfall measurements in the world is at the daily scale, i.e. related to a specific calendar day and measured over fixed 24 h. On these data, daily annual maximum rainfall depths (F-maxima) series are easily obtained. On the other hand, 24 h annual maximum rainfall depths (S-maxima), which refer to a period starting at any instant, are more useful indicators. S-maxima values cannot be less than the F-maxima, and are generally higher. The ratio between these extremes, called Hershfield factor (H), has been studied to move from F-maxima to S-maxima, allowing to take advantage of the relevant amount of information included in historical records of daily extremes. For instance, before 1980, in the Italian Hydrological Yearbooks only a subset (< 50 %) of the rain gauges was equipped with a recording device, from which annual maxima over 1, 3, 6, 12 and 24 consecutive hours can be derived. In this study we investigate the possibility of using F-maxima to complement the S-maxima records related to the Po river basin and the Liguria region (North of Italy). As a first step we retrieved from official databases all the daily rainfall measurements, available over this area, from early 1900 until today and we quality-controlled the measurements. We then computed the annual H for all the stations and all the years where both the F- and S-maxima were available, to obtain data that can be analyzed in their temporal and spatial variability. The spatial distribution of the Hershfield factor shows values similar to the ones suggested in the literature and is related to the geographic position of the stations, allowing the possibility to identify some distinct areas with positive or negative anomalies. The obtained map of the H factor, with interpolated local anomalies, allows to reconstruct the missing S-maxima in stations with only F-maxima, and improve the knowledge of the spatial variability of sub-daily rainfall extremes.