An exhaustive daily rainfall and extreme air temperature series (1883-2000) was reconstructed for Agnone, a small town in Molise (Central Italy). Long-term analysis identified an increasing trend of 1.3 ± 0.4°C per 100 years, statistically confident at the 95% level, only for minimum air temperature, and of a seasonal march, reasonably stationary along the entire investigated interval, explaining more than 50% of the corresponding monthly variance, with maxima in November and July for rainfall and air temperature, respectively. Daily clustering analysis evidenced scale-invariant properties, largely dependent on the threshold value, for all the investigated parameters
Hundred-year trends of mean monthly temperatures and precipitations in Italy are described and analy...
The awareness of the importance of data quality and homogeneity issues in the correct detection of c...
Reliable secular time series of essential climatic variables are a fundamental element for the asses...
An exhaustive daily rainfall and extreme air temperature series (1883-2000) was reconstructed for Ag...
Climate changes has become one of the most analysed subjects from researchers community, mainly beca...
Meteorological variables trend analysis, on different spatial and temporal scales, has been of great...
The Italian monthly temperature (mean, maximum and minimum) and precipitation secular data set was u...
Intensification of heavy precipitation as discussed in climate change studies has become a public co...
Since the 18th century systematic measurements of rainfall have been collected in Italy. The daily r...
We investigate changes in the probability density functions and the probability of moderate extreme...
We investigate changes in the probability density functions and the probability of moderate extremes...
ABSTRACT: Precipitation trend analysis, on different spatial and temporal scales, has been of great ...
The investigation of the statistical links between changes in temperature and rainfall, though not w...
Identifying early signals of climate change and latent patterns of meteorological variability requir...
Agriculture is highly exposed to climate change, as farming activities directly depend on climatic ...
Hundred-year trends of mean monthly temperatures and precipitations in Italy are described and analy...
The awareness of the importance of data quality and homogeneity issues in the correct detection of c...
Reliable secular time series of essential climatic variables are a fundamental element for the asses...
An exhaustive daily rainfall and extreme air temperature series (1883-2000) was reconstructed for Ag...
Climate changes has become one of the most analysed subjects from researchers community, mainly beca...
Meteorological variables trend analysis, on different spatial and temporal scales, has been of great...
The Italian monthly temperature (mean, maximum and minimum) and precipitation secular data set was u...
Intensification of heavy precipitation as discussed in climate change studies has become a public co...
Since the 18th century systematic measurements of rainfall have been collected in Italy. The daily r...
We investigate changes in the probability density functions and the probability of moderate extreme...
We investigate changes in the probability density functions and the probability of moderate extremes...
ABSTRACT: Precipitation trend analysis, on different spatial and temporal scales, has been of great ...
The investigation of the statistical links between changes in temperature and rainfall, though not w...
Identifying early signals of climate change and latent patterns of meteorological variability requir...
Agriculture is highly exposed to climate change, as farming activities directly depend on climatic ...
Hundred-year trends of mean monthly temperatures and precipitations in Italy are described and analy...
The awareness of the importance of data quality and homogeneity issues in the correct detection of c...
Reliable secular time series of essential climatic variables are a fundamental element for the asses...