Abstract
Abstract. A high-resolution daily gridded precipitation dataset was built from raw data of 12 858 observatories covering a period from 1950 to 2012 in peninsular Spain and 1971 to 2012 in Balearic and Canary islands. The original data were quality-controlled and gaps were filled on each day and location independently. Using the serially complete dataset, a grid with a 5 × 5 km spatial resolution was constructed by estimating daily precipitation amounts and their corresponding uncertainty at each grid node. Daily precipitation estimations were compared to original observations to assess the quality of the gridded dataset. Four daily precipitation indices were computed to characterise the spatial distribution of daily precipitation and nine extreme precipitation indices were used to describe the frequency and intensity of extreme precipitation events. The Mediterranean coast and the Central Range showed the highest frequency and intensity of extreme events, while the number of wet days and dry and wet spells followed a north-west to south-east gradient in peninsular Spain, from high to low values in the number of wet days and wet spells and reverse in dry spells. The use of the total available data in Spain, the independent estimation of precipitation for each day and the high spatial resolution of the grid allowed for a precise spatial and temporal assessment of daily precipitation that is difficult to achieve when using other methods, pre-selected long-term stations or global gridded datasets. SPREAD dataset is publicly available at https://doi.org/10.20350/digitalCSIC/7393.
Highlights
Precipitation is a key variable to understanding the behaviour of extreme weather events and the severe impacts they cause on hydrological systems, in natural systems and on human societies
Assessing the monthly aggregates of daily precipitation (Table 5), we found the results were very similar to the ratio of means (RM), indicating the absence of systematic biases, with the exception of November and December which showed a slight underestimation
Uncertainty informs in a quantitative way about the reliability of the estimated data, in a way that can be translated to further calculations such as the daily precipitation indices explored in this article
Summary
Precipitation is a key variable to understanding the behaviour of extreme weather events and the severe impacts they cause on hydrological systems, in natural systems and on human societies. These impacts can be considered in regional and local plans which can help to mitigate major disasters if the correct environmental data are available. Quality control and reconstruction processes are in high demand, as well as final products such as serially continuous observational series or gridded datasets. R. Serrano-Notivoli et al.: SPREAD: a high-resolution daily gridded precipitation dataset (Westerling et al, 2003), groundwater recharge Gridded datasets provide valuable products that can be used for both scientific and decision-making policy purposes
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