Search

We discuss the evolution of summer temperature extremes over Western Europe during 1961–2004 in the context of current climate warming. Using a parametric approach, we investigate the role of properties and changes in probability density functions of daily temperatures in modifying the frequency of severe, isolated events. In this perspective, the recent intensification of extremely warm events over Europe turns out to be well consistent with a pure, nonuniform shift of mean values, with no room for conjectures about increasing temperature variability.

Thirty-arc-second resolution monthly temperature and precipitation climatologies for North Eastern Italy are presented and the procedure we adopted in order to superimpose the information of the secular anomaly records to these climatologies is discussed. Temperature climatologies are obtained by means of a step-wise linear regression method which aims at determining the temperature dependence on geographical and morphological variables. In the first regression (temperature versus elevation) the recorded data are considered; the further regressions concern the residuals obtained after taking into account the effect of each variable, in order of importance. Precipitation climatologies are obtained by means of a procedure which consists in considering each cell of a high-resolution grid and in using the 15 closest stations in order to perform a weighted local linear regression of precipitation versus elevation: the weights are given by the distances of the stations from the grid point and by the level of similarity between the stations cells and the considered grid cell in terms of elevation, slope steepness, slope orientation and distance from the sea. Secular records to be superimposed to the climatologies can be obtained for each grid point by means of a distance-weighted average of the anomaly temperature and precipitation records of the neighbouring stations.

Monthly Northern and Central Italy precipitation climatologies, obtained by means of a procedure aiming at capturing the local dependence of precipitation on elevation, are presented. The procedure consists in considering each cell of a high-resolution grid and in making use of the closest 15 stations in order to perform a weighted linear regression of precipitation versus elevation: the weights are determined by the distances of the stations from the grid point and by the level of similarity between the stations' cells and the considered grid cell in terms of elevation, slope steepness, slope orientation and distance from the sea. The study is based on a dataset of about 3200 1961–1990 monthly precipitation normals. The performance of the procedure is evaluated by reconstructing the monthly precipitation normals of each station and by comparing them with the corresponding observed values. Such comparisons are performed by means of five error estimators: the mean absolute error and the mean error, both evaluated in absolute and relative form, and the root mean squared error. The mean absolute error is slightly more than 10 mm for the monthly precipitation, which turns out to be between 10% and 14% of the monthly precipitation.

The paper presents monthly 30-arc-second-resolution Northern and Central Italy temperature climatologies and discusses the procedure we adopt to superimpose the information of temperature secular records onto these climatologies. The climatologies are obtained by means of a step-wise linear regression method which aims at determining the temperature dependence on geographical and morphological variables. Such a method is applied to a database of about 800 monthly 1961–1990 temperature normals. In the first regression (temperature vs. elevation) the recorded data are considered; the further regressions concern the residuals obtained after taking into account the effect of each variable, in order of importance. An estimated secular anomaly record can be obtained for each point of the climatology grid by means of a distance-weighted average of the temperature anomaly records of the stations surrounding the grid point.

[1] The ongoing increase in extremely warm temperature events across large areas of the globe is generally thought to be a signature of a more extreme climate. However, it is still unclear whether global warming is accompanied by changes in statistical properties beyond the mean, such as an increasing temperature variability. Here we shed light on this issue by uncovering the way probabilities of extremes are being influenced by temperature evolution. Focusing on Europe, we show how the behavior of warm and cold extremes can be determined to a high accuracy by statistically modeling daily temperatures and their changes. Detailed comparison with observations over the past decades puts forward the dominant role of the mean in explaining exceptionally hot events, and rules out contributions from potential changes in second and higher moments.

[1] 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.

[1] The paper investigates precipitation variability in the greater Alpine region (GAR) (4–19°E, 43–49°N) based on 192 instrumental series of homogenized and outlier checked monthly precipitation and on the 1° gridded version of the same data set. Compared to the previous data sets, the one used in this paper adds a full century of data (earliest series starting in 1800) by exploiting the early instrumental period as much as possible in terms of series length and spatial density. The records were clustered into climatically homogeneous subregions, by means of a principal component analysis, and average subregional series were calculated. The principal component analysis was applied also in T-mode to investigate the most recursive precipitation patterns that characterize the examined area. Yearly and seasonal trend analysis was performed both on subregional average series and on the mean GAR series. It was also applied to moving windows, of variable width ranging from 2 decades to 2 centuries, in order to investigate any trends over decadal to secular timescales. Beside trends in total precipitation, precipitation seasonality was also analyzed as an important indicator of climate changes. Links between precipitation variability in the Alpine region and atmospheric circulation, and the North Atlantic Oscillation in particular, were also studied.

[1] A new data set of 45 daily precipitation series, covering quite uniformly Italian territory for the period 1880–2002, was recovered. The series have been homogenized on daily basis, completed by means of statistical methods and grouped into five regions by a Principal Component Analysis. Seasonal and yearly total precipitation, number of wet days, and precipitation intensity were analyzed for each station record and averaged into five regional series for a synthetic description of the results. Proportion and frequency of daily rainfall amounts, belonging to six precipitation class-intervals, defined on the basis of some percentiles of the precipitation distribution, were also analyzed. The results show a negative significant trend in the number of wet days all over Italy, and a positive trend in precipitation intensity, which is significant only in the northern regions. The negative trend in wet days has persisted since the end of 19th century and is due to the marked decrease in the number of low intensity precipitation events. An increase in the number of events belonging to the highest intensity class interval was observed too, but only in northern regions.

Trends in Italian total cloud amount are analysed for the period 1951-1996. The data are a set of 35 station records that were extracted from the 3-hourly Italian Air Force dataset. A method is discussed to obtain daily mean cloud amounts avoiding biases due to missing observations: less than 2 % of the days have no observations, but more than 20 % of them have at least one missing value. Trend analysis is applied to regional Northern and Southern Italy average series. Seasonal and annual trends were estimated by means of least squares linear fitting. Significance was tested using the non parametric Mann-Kendall test. The results show that there is a highly significant negative trend in total cloud amount all over Italy. It is evident in all seasons and is particularly steep in winter where both in Northern and Southern Italy the decrease exceeds 1 okta in 50 years.