Understanding climate change–induced variations in daily temperature distributions over Italy.

We investigate changes in the probability density functions and the probability of moderate extremes for maximum and minimum daily temperature anomalies in Italy from 1951 up to 2008. Evaluation of trends in time‐varying percentiles and higher‐moment analysis of empirical density functions give no evidence of long‐term changes in scale or shape of daily anomaly distributions, their temporal evolution being essentially driven by a forward, nonuniform shift in the mean. In this context, on the basis of an appropriate theoretical model for daily anomalies, we provide a realistic representation of the temporal evolution of moderate warm and cold extremes by explicitly considering the inherent nonlinearity between changes in the mean and those in exceedance probabilities. Consistency between expected and observed exceedance probabilities suggests that changes in moderate extremes can be well understood with a simple, rigid shift of the density functions alone, without invoking any change in shape.