Statistical analysis of inter-arrival times of rainfall events for Italian Sub-Alpine and Mediterranean areas

Abstract. In this work a set of time-series of inter-arrival times of rainfall events, at daily scale, was analysed, with the aim to verify the issue of increasing duration of dry periods. The set consists of 12 time-series recorded at rain gauges in 1926–2005, six of them belong to an Italian Sub-Alpine area (Piedmont) and six to a Mediterranean one (Sicily). In order to overcome the problem related to limited sample size for high values of inter-arrival times, the discrete probability polylog-series distribution was used to fit the empirical data from partial (20 yr) time-series. Moreover, a simple qualitative trend analysis was applied to some high quantiles of inter-arrival times as well as to the average extent of rain clusters. The preliminary analysis seems to confirm the issue of increasing duration of dry periods for both environments, which is limited to the ''cold'' season

Modelling wet and dry spells for daily rainfall data series: an application to irrigation management in North-West Italy

Rainfall time variability is relevant for agricultural production. The daily time scale is often used in modelling crop and soil water balance. In this work a novel statistical analysis of wet and dry spells is presented, together with an application in an Italian area characterised by a relevant climate spatial variability, due to the presence of both high mountains (e.g.: Mont Blanc) and of the Mediterranean Sea. Statistical analysis of the sequences of rainy days, wet spells (WS), and that of no-rainy days, dry spells (DS), could be carried out separately (as widely applied in the past) or jointly, by introducing the inter-arrival time (IT), representing the time elapsed between two subsequent rainy days. Investigating on daily rainfall data series recorded in Sicily, Agnese et al. (2014) found that IT statistics can be described by the 3-parameter Lerch distribution; in turn, WS and DS distributions can be easily derived from IT distribution. Alternatively, the knowledge of both WS and DS distributions allow deriving IT distribution; in this case, WScan be described by the well-accepted geometric distribution, whereas the 2-parameter polylogarithm distribution can be used for DS, as recently suggested (Agnese et al., 2012) in place of the previously used 1-parameter logarithmic distribution (Chatfield, 1966). In this work, by using some daily rainfall data series recorded in Alpine and Sub-Alpine Areas, the equivalence between the above-mentioned approaches is showed. Furthermore, some interesting relationships between respective parameters are also illustrated. A simple soil water model is then used, using this rainfall statistical model, in order to evaluate the irrigation efficiency as a consequence of variations in the timing of surface irrigation, following the approach described in the paper of Canone et al. (2015)

Climate change and glaciers. A didactic link between research and school.

PosterInternational audienceThe legislation regarding the programs of Italian school on the topic of climate change is very deficient. This project is intended to be a didactic tool to deal with this subject - especially with regard to its effects on glaciers - using a specific methodology. Only recently climate change has been mentioned in the programs for the High School (DPR 89, 2010), but no precise indications are given for contents, time and extent in the scheduling, even though a higher level of integration between subjects and topics is aimed for. The aim of this research is to investigate how an innovative approach, which puts in contact research and schools, may allow to improve the knowledge about climate change and glaciers, especially for students living in alpine areas. The experimentation, which is part of a PhD project, will also allow to produce didactic materials and a questionnaire aimed at increasing awareness on climate among students in Italian school

Spatial variability of dry spells duration statistical distributions

Dry spells duration and its extent in space, is a key factor in water resources problems. In order to modelling the empirical distribution of dry spells (DS) frequencies observed in Sicily (i.e. in a typical Mediterranean climate), Agnese et al. (2014) successfully applied the two-parameter polylogarithm-series distribution. Because of the strong seasonality characterising Sicily’s rainfall regime, statistical analysis was separately applied to two data sets, referred to as “dry” and “wet” seasons, respectively. In this work, a similar analysis was carried out for a set of 26 DS time-series recorded in a large area (about 30000 km2), including Piedmont and the Aosta Valley. Area altitude ranges between 100 to almost 5000 m a.s.l., and the Mediterranean sea is at about 20 km distance. Main climate character in the whole area is colder and more humid than that of Sicily, and it varies noticeably within the area itself, likely because of the complex role of geomorphology on rain and snow occurrence. Also, partition between rain and snow is evaluated. A subdivision in homogeneous subareas is found which is related to the main weather types occurring. In this work the focus is on the longer dry spells

Trends of some high quantiles of average and extremes inter-arrival times and rainfall depths at daily scale for an Italian Sub-Alpine area.

Modeling of rainfall statistical structure represents an important research area in hydrology, meteorology, atmospheric physics and climatology, because of the several theoretical and practical implications. The statistical inference of the alternation of wet periods (WP) and dry periods (DP) in daily rainfall records can be achieved through the modelling of inter-arrival time-series (IT), defined as the succession of times elapsed from a rainy day and the one immediately preceding it. It has been shown previously that the statistical structure of IT can be well described by the 3-parameter Lerch distribution (Lch). In this work, Lch was successfully applied to IT data belonging to a sub-alpine area (Piemonte and Valle d\u2019Aosta, NW Italy); furthermore the same statistical procedure was applied to daily rainfall records to ITs associated. The analysis has been carried out for 26 daily rainfall long-series ( 90 yr of observations). The main objective of this work was to detect temporal trends of some features describing the statistical structure of both inter-arrival time-series (IT) and associated rainfall depth (H). Each time-series was divided on subsets of five years long and for each of them the estimation of the Lch parameter was performed, so to extend the trend analysis to some high quantiles