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Development and Analysis of a 50 year high-resolution daily gridded precipitation dataset over Spain (Spain02)

Journal: International Journal of Climatology
Year: 2012   Volume: 32
Initial page: 74   Last page: 85
Status: Published
In this status since: 9 Dec 2010
PDF file: 2010_herrera_IJC_Spain02_web.pdf
DOI: 10.1002/joc.2256

See the Spain02 dataset web page

In this paper we present a new publicly available high-resolution daily precipitation gridded dataset developed for peninsular Spain and the Balearic islands using 2756 quality-controlled stations (this dataset is referred to as Spain02). The grid has a regular 0.2◦ (aprox. 20km) horizontal resolution and spans the period from 1950 to 2003. Different interpolation methods were tested using a cross-validation approach to compare the resulting interpolated values against station data: Kriging, Angular Distance Weighting, and Thin Plane Splines. The kriging method exhibited the best overall performance and the grid was produced applying this algorithm in a two-step process. First, the occurrence was interpolated using a binary kriging and, in a second step, the amounts were interpolated by applying ordinary kriging to the occurrence outcomes. This procedure is similar to the interpolationmethod used to generate the EOBS gridded data—the state-of-the-art publicly available high-resolution daily dataset for Europe—which was used in this work for comparison purposes.

Climatological statistics and extreme value indicators from the resulting grid were compared to those from the 25km E-OBS dataset using the observed station records as a reference. Spain02 faithfully reproduces climatological features such as annual precipitation occurrence, accumulated amounts and variability whereas E-OBS has some deficiencies in the southern region. When focusing on upper percentiles and other indicators of extreme precipitation regimes, Spain02 accurately reproduces the amount and spatial distribution of the observed extreme indicators, whereas E-OBS
data present serious limitations over Spain due to the sparse data used in this region. Since extreme values are more sensitive to interpolation, the dense station coverage of this new data set was crucial to get an accurate reproduction of the extremes.

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