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The spatial distribution of precipitation in Xinjiang, China, is extremely heterogeneous due to its complex subsurface, and microphysical studies of cloud precipitation over Xinjiang are severely constrained by observational means. The Global Precipitation Measurement (GPM) dual‐frequency precipitation radar (DPR) provides improved three‐dimensional observation data of strong and weak precipitation and performs effective observations in alpine mountain regions. Therefore, this study used GPM/DPR Level‐3 data from January 2015 to December 2022 to analyze the convective and stratiform precipitation characteristics over Xinjiang. The results showed that (1) the range of maximum precipitation reflectivity factors (PRF_max) near the ground and at different heights were larger in summer and maximum PRF_max values appeared in areas along the Altai, Tianshan, and Kunlun Mountains and plains on the respective mountain slopes. In summer, the PRF_max of stratiform (convective) precipitation nearsurface ranged from 24 to 34 dBZ (28–40 dBZ). (2) The two types of precipitation exhibited the highest storm top heights in summer, with convective precipitation having higher values than stratiform precipitation and mountainous areas having higher values than the surrounding basins due to the effects of topographic uplift. (3) The value domains of the PRF, particle mass‐weighted diameter (Dm), and particle number concentration for stratiform (convective) precipitation were more concentrated (wider), that is, PRF: 14–30 dBZ (12–40 dBZ), Dm: 0.9–1.4 mm (0.7–2.1 mm), and the particle concentration: 29–35 (24–39). The height of the center of the probability density of each variable was higher in the three major mountain ranges than in the two major basins owing to the influence of topography. PRF increased and then decreased with height. Convective raindrops were in an active state of high concentration and exhibited a large scale in the lower layers, whereas the particle spectral parameters of stratiform precipitation showed a more concentrated and symmetric distribution and insignificant changes with height. [ABSTRACT FROM AUTHOR]

In this study, the problem of determining, with an adequate statistical significance, the relationship between teleconnection pattern indices and precipitation at climatological time scales has been addressed through a novel technique based on a rainfall zonation, by means of creating a regional precipitation database for a whole‐region correlation approach. Pearson correlation was performed to evaluate the mesoscale influence on precipitation in the Calabria region over the 1951–2010 time period, by means of a database of 79 rain gauges, divided in five Rainfall Zones (RZs) and seven teleconnection pattern indices relevant to the Mediterranean region, searching where results were significant (significance level < 0.05) and with an absolute correlation value higher than a prefixed threshold equal to 0.2. The Calabria region was chosen as it is located in the centre of the Mediterranean area, which constitutes a hot spot for climate change, and because it is equipped with a high‐density, long‐time series of precipitation gauge network, recently validated and homogenized. Correlation analysis between seasonal teleconnection indices and seasonal cumulated precipitation showed that the Western Mediterranean Oscillation and the East Atlantic/West Russian patterns were the most relevant teleconnections over all Calabria. Correlations of 3‐month averaged teleconnection indices versus monthly precipitation showed that the Mediterranean and Western Mediterranean Oscillations produce most significant results with correlation values higher than 0.2, with East Atlantic pattern a third close. Comparison between monthly teleconnection indices and monthly cumulated precipitation indicate that all modes of variability taken into account share a similarly weak correlation. Comparing the rainfall zone‐based study and the technique of averaging individual stations results post‐correlation, it was shown that on average only 43% of the stations would produce useful correlations, while the novel technique used all the valid and available station data, resulting in statistically more robust findings. [ABSTRACT FROM AUTHOR]

Recent studies evidenced that extreme daily rainfall often increases in spite of a decrease of the total rainfall. For this reason, the analysis of daily precipitation concentration is an important issue in climate research and can be useful to evaluate risks linked to extreme rainfall events. In this paper, an analysis of the spatial and temporal variability of the daily precipitation concentration in the Sardinia region, the second largest island in the Mediterranean Sea, has been performed for the period 1922–2011 by applying the Concentration Index. First, the CI has been evaluated at annual and seasonal scale. Then, the coefficient of variation, and the 5th and 95th percentiles of the annual CI values were calculated and mapped as a set of descriptors of variability and extreme characterization of precipitation concentration across the study area. Finally, in order to evaluate the temporal evolution of the CI, a trend analysis has been also performed using the Mann–Kendall test. Results show CI values ranging from a minimum of 0.477 to a maximum of 0.723. Spatially, the region can be divided in two parts with opposite behaviours: the western side characterized by a more uniform temporal distribution of rainfall intensity and the eastern side with the most critical intensity and aggressiveness of rainfall. From a seasonal point of view, this spatial gradient was evidenced in winter, spring and autumn while summer showed a more homogeneous spatial distribution of CI. The spatial distribution of the coefficient of variation did not show any spatial gradient between the two sides of the region, both at annual and seasonal scale. As regards the trend analysis, a marked positive trend of the CI has been detected, thus indicating a tendency towards more intense and aggressive rainfall. Copyright © 2019 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The present study aims at improving data availability and quality for the last 80-90 years for daily precipitation in the Calabria region (southern Italy). First, the original database was homogenised and the gaps filled in for 129 daily rain gauges for the 1916-2006 period. Then, precipitation variability and change were evaluated at an adequate spatial resolution. Monthly and annual total precipitation (P), number of wet days (WDs), and precipitation intensity (PI) were calculated for each series. With regard to the monthly total precipitation a general negative trend, albeit not everywhere significant, was detected, in particular for the autumn-winter period, while in summer the tendency was toward an increase in total precipitation. The monthly behaviour of WDs was not very different from that observed for P: a diffuse negative trend was detected in most months, particularly evident and significant in January, with the exception of April and the summer months, for which the tendency was toward an increase. Regarding the PI, a general negative and often significant trend was found for the entire region and for almost all the months, except summer. Attention was also focused on tendencies in the different PI categories, revealing negative trends in high-intensity categories, especially coming from the winter season. Finally, running trend analysis revealed that the previously discussed tendencies were not persistent throughout the series length, but depended on the period examined. This important aspect should be taken into account when different results based on different time windows are compared. Copyright © 2010 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

In order to investigate the behaviour of climatic and hydrological variables, several statistical and stochastic techniques are currently applied to time series. In the present study a statistical analysis of annual and seasonal precipitation has been performed over 109 cumulated rainfall series with more than 50 years of data observed in a region of Southern Italy (Calabria). Trend analyses have been made by using both nonparametric (Mann-Kendall test) and parametric (linear regression analysis) procedures. The long historical series of monthly rainfall data employed in this work have been previously processed through a pre-whitening (PW) technique in order to reduce the autocorrelation of rainfall series and its effects on outcomes of trend detection. The application of the above mentioned procedures has shown a decreasing trend for annual and winter-autumn rainfall and an increasing trend for summer precipitation. Moreover the Mann-Whitney test has been used to evidence the possible change points in the data. The higher percentages of rainfall series show possible year changes during decade 1960-1970 for almost all of the temporal aggregation rainfall. Copyright © 2009 Royal Meteorological Society [ABSTRACT FROM AUTHOR]