An assessment of the role of homogenization protocols in the performance of daily temperature series and trends: application to northeastern Spain

Abstract

This paper details a full protocol applied to develop high resolution daily temperature dataset. Our methodology has been tested from a dataset of 1583 temperature observatories over the NE Spain. The raw dataset was initially tested for internal and external consistency and an algorithm was utilized to reconstruct the daily temperature series for selected candidate observatories. Discontinuities in the reconstructed series were determined by combining the results obtained by three homogeneity tests: the Standard Normal Homogeneity Test (SNHT), the Easterling and Peterson two-phased regression method and the Vincent test. To assess the role of data homogenization, a set of selected tests was applied to the temperature trends and the spatial and frequency properties of the series. Results show significant improvement in the spatial dependence of temperature trends at seasonal and annual scales after application of homogeneity correction. However, frequency statistics of the series evidenced no significant impact of the homogenization procedure. From the temporal and spatial perspectives, the new compiled dataset seems to be outstanding in a variety of meteorological, ecological, hydrological and agricultural research applications at local, regional and continental scales.