In the present study, an approach for a climate characterization based on a statistical analysis of monthly precipitation and temperature data is presented. First, the original database (1916–2010) was homogenized and a geostatistical analysis was carried out to characterize the monthly mean distribution of the two variables in the study area. Then, temporal change of precipitation and temperature were evaluated through the Mann–Kendall test. Finally, to better assess the climate patterns in Calabria, a climatic characterization was carried out by means of the Péguy climograph. Results have shown a decreasing trend for autumn–winter rainfall and an increasing trend in summer. With respect to the average temperature, the analyses revealed a positive trend in late spring and summer, mainly due to the increase in the minimum values, and a negative trend in the autumn–winter period, mainly due to a decrease in the maximum values. The analysis of the Péguy climographs allowed the dataset to be divided into three groups, depending on the different elevation of the gauges. Moreover, different temporal behaviours were detected by analysing the climographs in three sub-periods.
Spatial and temporal characterization of climate at regional scale using homogeneous monthly precipitation and air temperature data: an application in Calabria (southern Italy)
FERRARI, Ennio
2015-01-01
Abstract
In the present study, an approach for a climate characterization based on a statistical analysis of monthly precipitation and temperature data is presented. First, the original database (1916–2010) was homogenized and a geostatistical analysis was carried out to characterize the monthly mean distribution of the two variables in the study area. Then, temporal change of precipitation and temperature were evaluated through the Mann–Kendall test. Finally, to better assess the climate patterns in Calabria, a climatic characterization was carried out by means of the Péguy climograph. Results have shown a decreasing trend for autumn–winter rainfall and an increasing trend in summer. With respect to the average temperature, the analyses revealed a positive trend in late spring and summer, mainly due to the increase in the minimum values, and a negative trend in the autumn–winter period, mainly due to a decrease in the maximum values. The analysis of the Péguy climographs allowed the dataset to be divided into three groups, depending on the different elevation of the gauges. Moreover, different temporal behaviours were detected by analysing the climographs in three sub-periods.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.