The availability of quality precipitation records in the current climate situation is of great importance in the scientific-technical field but also for the public institutions that manage the meteorological networks. This work has implemented a comprehensive spatial quality control procedure in the semiarid region of Andalusia (Southern Spain), using precipitation time series from 1947 stations from three meteorological networks: Spanish Meteorological Agency (AEMET), Agroclimatic Information Network of Andalusia (RIA), and Phytosanitary Information Alert Network (RAIF). The method consists of three consecutive steps: basic, absolute, and relative quality control processes. The latter step compares data from neighboring stations taking into account their proximity, height difference, and correlation, leading to a complete evaluation of each daily value. Finally, the quality of each year at each station can be declared as acceptable, good, or excellent. The automatic weather station networks RIA and RAIF gave absolute quality index $$Q$$Q above 85% for almost 87% of their stations, while only 57% of AEMET network reached this percentage. However, one of the longest AEMET datasets, San Fernando-Cádiz, obtained, except for 1 year, $$Q$$Q values over 90% in all available years for more than a century of measurements, since 1870 until 2000. From a total of more than 15 million daily records, almost 82% was flagged as correct. Despite the limitations of Andalusia region (low density of stations and its structural water deficit), the complete quality control procedure has been satisfactorily applied. Finally, related to the number of outliers, no temporal trend was found across the region. Graphical abstract

A simple scaling analysis was performed in Andalusia (Spain) using daily records from 377 selected stations covering the temporal period between 1870 and 2018. Since Andalusia is a region of considerable climatic variety, with notably wet areas as well as extremely dry zones, this study is useful to investigate the relationship between the simple scaling parameter value and the characteristic rainfall regime of a place. Despite the great correspondence with the average annual precipitation (PRCPTOT), a clear dependence on rainfall irregularity was observed, revealed by the ratio of the maximum daily precipitation and PRCPTOT, as well the wet spells frequency index CWD. The spatial distribution of the simple scaling parameter captured the increasing influence of the Mediterranean Sea towards the East. The easternmost dry areas are clearly influenced by Mediterranean disturbances, with a high proportion of convective rainfall and an irregular rainfall pattern. Using a simple scaling parameter, the generalized equations of the intensity-duration-frequency (IDF) curves, of great hydrological interest were calculated for the eight Andalusian provincial capitals. Moreover, the temporal trends of this parameter in the four past decades were studied in the different areas with the aim of determining if changes in their rainfall patterns due to global warming could be detected.

The spatial distribution of rainfall intensity–duration–frequency (IDF) values, essential for hydrological applications, were estimated for Catalunya, Spain. From a larger database managed by the Meteorological Service of Catalunya and after rigorous quality control, 163 high-quality daily series spanning from 1942 to 2016, with an average length of 39.8 years and approximately one station per 200 km², were selected. A monofractal downscaling methodology was applied to derive rainfall intensities for sub-daily durations using the intensities from a reference 24 h duration as the basis, followed by spatial interpolations on a 1 km × 1 km grid. The scaling parameter values have been found to be higher in the northwestern mountainous areas, influenced by Atlantic climate, and lower in the central–western driest zones. A general negative gradient was observed toward the coastline, reflecting the increasing influence of the Mediterranean Sea. The IDF results are presented as spatial distribution maps, providing intensity–frequency estimates for durations between one hour and one day, and return periods between 2 and 200 years, with an estimated uncertainty below 12% for the 200-year return period, and lower for shorter return periods. These findings highlight the need to capture rainfall spatial variations for urban planning, flood control, and climate resilience efforts.