The spatiotemporal analysis of a region's precipitation climate regime could be particularly interesting for many fields of applied sciences, such as climatology, hydrology and water resources management. In this study, the precipitation trends at seasonal and annual scale, over a large area of the northern Hemisphere have been analysed based on a globally gridded precipitation data sets of monthly observations. In particular, among the several data sets available in literature, with spatial resolutions of 0.5° longitude/latitude, in this work the Global Precipitation Climatology Centre Full Data Reanalysis Version 6 data set has been used. The broad extension of the area under investigation allowed a better understanding of trend precipitation patterns over space. In fact, yearly results evidenced a marked negative rainfall tendency in the eastern Mediterranean (more than −20 mm/10 years) and in North Africa (until −16 mm/10 years), while a relatively large positive trend (more than 20 mm/10 years) in central and northern Europe has been observed.

Abstract:In this study, drought events over a large area of the Northern Hemisphere, including continental Europe, Ireland, the United Kingdom, and the Mediterranean basin, were analyzed using the Standardized Precipitation Index (SPI) at various times scales (3, 6, 12, and 24 months). To this purpose, the Global Precipitation Climatology Centre (GPCC) Full Data Monthly Product Version 2018 data set, with spatial resolutions of 0.5 • longitude/latitude and for the period 1951-2016, has been used. First, the temporal evolution of the percentage of grid points, falling within the severe and extreme drought categories, has been evaluated. Then, a trend analysis has been performed at a seasonal scale, considering the autumn-winter and the spring-summer periods, and at an annual scale. The results of this paper highlight that the Mediterranean basin and North Africa are the most consistently vulnerable areas showing a general reduction in SPI values especially for the long time scale.