A dense daily precipitation data base, extending from 1964 to 1993, has been created for the Mediterranean regions of Spain. It is composed of complete and homogeneous series at 410 raingauge stations (347 in the coastal fringe of peninsular Spain, and 63 in the Balearic Islands). The region offers an interesting scenario for mesoclimatological studies on time and spatial rainfall variability: geomorphologically, it is characterized by important coastal relief units and complex distribution of sea and land masses, leading to different exposures to the rain‐bearing maritime winds; climatically, the western Mediterranean is subject to strong seasonal variability, since it is a transition zone between the midlatitude low pressure belt and the subtropical highs as a result of its latitude (between 36° and 44° N). In this study, we exploit the data base and present a first pluviometric characterization of the area by means of yearly and seasonal mean products. The results reveal clear and coherent spatial patterns that we interpret, based on typical storm tracks and land, sea, and relief distributions. In addition, a partition of the 30‐year period into three decades (1964–1973, 1974–1983, 1984–1993) has been considered in order to assess the possible existence of any trend. A successive drying of the most sensitive areas to the winter Atlantic depressions (western Catalonia, and central and west Andalucía) is observed. In contrast, the second analysed decade is appreciably drier than the other two in the areas more dependent on the Mediterranean disturbances. The occurrence of anomalous autumns being the most responsible. This fact emphasizes the fundamental importance of the autumn season for the pluviometric balance of the considered area, especially in its eastern part where the major amount of precipitation during this season is produced by convective systems. © 1998 Royal Meteorological Society

This paper presents trends in downward surface shortwave radiation (SSR) over Europe, which are based on the 56 longest series available from the Global Energy Balance Archive that are mainly concentrated in central Europe. Special emphasis has been placed on both ensuring the temporal homogeneity and including the most recent years in the data set. We have generated, for the first time, composite time series for Europe covering the period 1939-2012, which have been studied by means of running trend analysis. The mean annual SSR series shows an increase from the late 1930s to the early 1950s (i.e., early brightening), followed by a reduction until mid-1980s (i.e., global dimming) and a subsequent increase up to the early 2000s (i.e., global brightening). The series ends with a tendency of stabilization since the early 21st century, but the short time period is insufficient with regard to establishing whether a change in the trend is actually emerging over Europe. Seasonal and regional series are also presented, which highlight that similar variations are obtained for most of the seasons and regions across Europe. In fact, due to the strong spatial correlation in the SSR series, few series are enough to capture almost the same interannual and decadal variability as using a dense network of stations. Decadal variations of the SSR are expected to have an impact on the modulation of the temperatures and other processes over Europe linked with changes in the hydrological cycle, agriculture production, or natural ecosystems. For a better dissemination of the time series developed in this study, the data set is freely available for scientific purposes.

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Observations are the foundation for understanding the climate system. Yet, currently available land meteorological data are highly fractured into various global, regional, and national holdings for different variables and time scales, from a variety of sources, and in a mixture of formats. Added to this, many data are still inaccessible for analysis and usage. To meet modern scientific and societal demands as well as emerging needs such as the provision of climate services, it is essential that we improve the management and curation of available land-based meteorological holdings. We need a comprehensive global set of data holdings, of known provenance, that is truly integrated both across essential climate variables (ECVs) and across time scales to meet the broad range of stakeholder needs. These holdings must be easily discoverable, made available in accessible formats, and backed up by multitiered user support. The present paper provides a high-level overview, based upon broad community input, of the steps that are required to bring about this integration. The significant challenge is to find a sustained means to realize this vision. This requires a long-term international program. The database that results will transform our collective ability to provide societally relevant research, analysis, and predictions in many weather- and climate-related application areas across much of the globe.

Daily time series from the Climate Prediction Center (CPC) Africa Rainfall Climatology version 2.0 (ARC2), Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS) and Tropical Applications of Meteorology using SATellite (TAMSAT) African Rainfall Climatology And Time series version 2 (TARCAT) high-resolution long-term satellite rainfall products are exploited to study the spatial and temporal variability of East Africa (EA, 5S-20N, 28-52E) rainfall between 1983 and 2015. Time series of selected rainfall indices from the joint CCl/CLIVAR/JCOMM Expert Team on Climate Change Detection and Indices are computed at yearly and seasonal scales. Rainfall climatology and spatial patterns of variability are extracted via the analysis of the total rainfall amount (PRCPTOT), the simple daily intensity (SDII), the number of precipitating days (R1), the number of consecutive dry and wet days (CDD and CWD), and the number of very heavy precipitating days (R20). Our results show that the spatial patterns of such trends depend on the selected rainfall product, as much as on the geographic areas characterized by statistically significant trends for a specific rainfall index. Nevertheless, indications of rainfall trends were extracted especially at the seasonal scale. Increasing trends were identified for the October-November-December PRCPTOT, R1, and SDII indices over eastern EA, with the exception of Kenya. In March-April-May, rainfall is decreasing over a large part of EA, as demonstrated by negative trends of PRCPTOT, R1, CWD, and R20, even if a complete convergence of all satellite products is not achieved.