ABSTRACT:Daily maximum and minimum temperatures, T max and T min , and diurnal temperature range, DTR, from 37 temperature stations in Catalonia (NE Spain) are analyzed to detect significant daily time trends for the period . The homogeneity of the series is tested by means of the Standard Normal Homogeneity, the Buishand range and the Pettitt tests. The lack of randomness of the series, suggesting time trends, is also investigated by means of the Von Neumann ratio test. The daily time trends obtained and their spatial and temporal patterns are mainly in agreement with overall time trends recently derived for the Northern Hemisphere. The results indicate generalized increasing annual trends of daily T max and T min (0.5°C/decade), especially relevant in spring and summer, with values reaching 0.8-0.9°C/decade, and also remarkable for T max in winter (0.7°C/decade). In autumn, however, average trends point at a decrease in T max (−0.5°C/decade). As a result, an average annual decreasing trend of DTR is found, particularly relevant in autumn (−0.9°C/decade). Several periods with an outstanding number of stations showing significant positive time trends are detected and analyzed during the spring and summer seasons both for daily T max and T min . The only period with a relevant number of significant negative trends is detected in February for daily T min , thus implying a significant increasing trend of DTR during this short winter period. Comparisons are established with large-and regional-scale temperature trends, paying attention to the west Mediterranean atmospheric dynamics change.

Spatial and temporal patterns in the daily rainfall regime of Catalonia (northeastern Spain) recorded for the 1950-2000 period are analysed from several points of view, including the irregularity of the time series in terms of entropy, the Mann-Kendall test for time trends, a principal component analysis (PCA), an average linkage (AL) clustering algorithm and, finally, a power spectrum analysis, which includes a comparison of white-noise and Markovian red-noise hypotheses. The analyses are based on three monthly variables derived from the amounts recorded on a daily basis: the average daily rainfall and the standard deviation of the daily rainfall for each month, together with the corresponding coefficient of variation. The joint spatial-temporal variability is manifested by the irregularity index, which is characterized by relevant values in all cases and gradients from the north (Pyrenees and Pre-Pyrenees mountain ranges) to the south (Ebro Valley) and to the Mediterranean coast. The interpretation of the factor scores derived from the PCA and of the clusters obtained from the AL algorithm also describes the complex spatial distribution of the daily rainfall regime, given that the effects of atmospheric circulation patterns on rainfall regimes are conditioned by the complex orography of Catalonia and its proximity to the Mediterranean Sea. The factor loadings associated with the PCA also suggest a distinction between hot, cold and mild seasons. Finally, it is worth noting that monthly series are usually accompanied by white background noise and, in a few cases, signs of Markovian behaviour and some significant periodicities, which are generally of less than 10 months and which change from one cluster to another.

Statistical distributions of annual extreme and long dry spells for the Iberian Peninsula are investigated by using a daily database compiled from 43 rain gauges, with the recording period extending from 1951 to 1990 and with a minor lack of data. Dry spell lengths are derived for three different daily rainfall thresholds of 0.1, 1.0 and 5.0 mm/day. On one hand, the generalised extreme value (GEV) and generalised Pareto (GP) distributions are considered for modelling the series of annual extreme (AE) dry spells. On the other hand, both theoretical distributions are assumed for the partial duration (PD) series, which are derived from the dry spell lengths exceeding the 95th percentile. In both cases, a robust estimation of the three parameters of the GEV and GP distributions is obtained by L-moments. The fit between empirical and theoretical distributions is evaluated by using the 95% confidence bands of the Kolmogorov-Smirnov test and the L-skewness-kurtosis distance. Even though AE spells are quite well fitted by the GEV model, the GP distribution is a better option for some rain gauges. The PD series are usually better fitted by the GP distribution, only a few cases being better modelled by the GEV distribution. The basis for climatic drought risk assessment in the Iberian Peninsula is then established for dry spell lengths associated with return periods of 2, 5, 10, 25 and 50 years and accurately reviewed by comparing with results deduced from the AE and PD sampling strategies. As a general feature, both the spatial distribution of the statistical parameters and the dry spell lengths for the different return periods depict a north to south gradient. Some local deviations of this behaviour could be due to the vicinity to the Mediterranean Sea and the Atlantic Ocean.

A database of daily rainfall, compiled from 75 gauges covering the period , that was previously considered for analysing spatial and temporal patterns of the daily pluviometric regime in Catalonia is used to obtain new statistical patterns of the daily rain amounts. First, the annual number of rainy days, its coefficient of variation and time trends affecting this number are evaluated for every rain gauge, with the aim of complementing previous analyses concerning the average amount per rainy day and its absolute and relative dispersions. Second, empirical cumulative amount X and time Y distributions are obtained for every rain gauge and fitted with exponential and Weibull models respectively. Third, a normalized rainfall curve is obtained for every rain gauge and modelled in two ways. One of them is based on thec ] and the other on the beta distribution of X given by Y . It is noticeable that there is a relationship between the parameters of both models and the coefficient of variation of the daily rainfall. Additionally, a strong spatial variability is deduced after a review of the results. This variability is characterized by spatial gradients of the parameters of the exponential and Weibull distributions and of the threshold levels that define different percentiles of the X and Y distributions. A more homogeneous spatial behaviour is observed when the contribution to rain amounts of a specific type of daily episode is analysed. Thus, a relatively low ratio of rainy days (25-35%), with daily amounts exceeding average values, generates a good part of the rain amounts (75-85%) for most gauges (80%).

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