Statistical assessment of trends and oscillations in rainfall dynamics: Analysis of long daily Italian series

Since the 18th century systematic measurements of rainfall have been collected in Italy. The daily rainfall series observed in Milan (1835–2001), Genoa (1833–2000), Bologna (1813–2001) and Palermo (1797–1999) are examples of available long rainfall records. These data series can help analyzing the evolution of precipitation. The present paper deals with long term evolution of: (i) annual rainfall amount; (ii) annual number of rainy events; (iii) intensity of rainfall, (iv) inter-annual rainfall partitioning, i.e. the duration of wet and dry periods, and (v) maximum annual values of daily rainfall amount, duration of wet and dry periods. The evolution is studied analyzing the first two order statistics and the 30-year return period quantiles via moving window analysis. Confidence intervals are introduced to check the statistical significance of the estimated statistics and quantiles. The results are compared with those provided by the traditional Mann-Kendall test. The analysis shows how the annual precipitation exhibits a negative trend in the first half of 20th century, with a subsequent positive trend in northern Italy (Genoa, Milan and Bologna). Conversely, the dataset for Palermo (southern Italy) displays only a negative trend. Because the number of precipitation episodes is found to decrease in the investigated period, the average rain rate is significantly increasing especially in northern Italy. This is also associated with shorter duration of rain episodes with an evident effect on rainfall extremes. Dry periods tend to be longer with increasing variability. The Mann-Kendall test and its progressive form have shown to be well suited for monotonic trend, but the confidence interval analysis, introduced here, is more appropriate if oscillations are significant.