INTERNATIONAL JOURNAL OF CLIMATOLOGY Int. J. Climatol. 26: 1777–1802 (2006) Published online 5 May 2006 in Wiley InterScience (www.interscience.wiley.com) DOI: 10.1002/joc.1338 THE DEVELOPMENT OF A NEW DATASET OF SPANISH DAILY ADJUSTED TEMPERATURE SERIES (SDATS) (1850–2003) MANOLA BRUNET, a, * OSCAR SALADI ´ E, a PHIL JONES, b JAVIER SIGR ´ O, a ENRIC AGUILAR, a ANDERS MOBERG, c DAVID LISTER, b ALEXANDER WALTHER, d DIEGO LOPEZ a and CARLOS ALMARZA e a Climate Change Research Group, University Rovira i Virgili, Tarragona, 43071, Spain b Climatic Research Unit, University of East Anglia, Norwich, NR4 7TJ, UK c Department of Meteorology, Stockholm University, SE-106 91 Stockholm, Sweden d Earth Sciences Centre, G¨ oteborg University, SE-40530 G¨ oteborg, Sweden e Instituto Nacional de Meteorolog´ ıa, Servicio de Desarrollos Climatol´ ogicos, Leonardo Prieto 8, Madrid, 28040, Spain Received 11 October 2005 Revised 2 March 2006 Accepted 3 March 2006 ABSTRACT Here we present the development of a new adjusted dataset composed of the 22 longest and most reliable Spanish daily temperature records (maximum and minimum temperatures and derived daily mean temperature) covering the period 1850–2003. The paper describes the approaches followed for compiling, controlling the quality and homogenising these 22 daily Spanish records, leading to the creation of a dataset called ‘Spanish Daily Adjusted Temperature Series’ (SDATS). An assessment of the sources of data and metadata used is followed by a reliability assessment of the selected network. Data quality control (QC) procedures applied to raw daily maximum (T max ) and minimum (T min ) temperatures and their results are then considered. For the very first time, an empirical minimisation of the bias related to the impact of changing exposure of thermometers on the records has been undertaken. The application of the Standard Normal Homogeneity Test (SNHT) to check homogeneity of raw T max and T min data on a monthly basis is presented, together with a discussion of the causes, magnitudes and timings of the various inhomogeneities. All 22 records contained a number of inhomogeneities (2.6 on average), mainly associated with documented station relocations confirmed by the metadata available. Monthly adjustments calculated for both screen developments and from the SNHT were linearly interpolated to a daily basis following the Vincent et al. (2002) scheme. Finally, the procedures adopted for creating the regional average, the Spanish Temperature Series (STS), together with an exploratory analysis of long-term trends of each T max and T min records, are provided. The final analysis shows that over mainland Spain highly significant rates of temperature increases have occurred for T max and T min (0.12 ° C/decade and 0.10 ° C/decade, respectively) over 1850–2003. Copyright  2006 Royal Meteorological Society. KEY WORDS: daily temperature series; ‘screen bias’ adjustments; QC; daily data homogeneity; temperature trends; Spain 1. INTRODUCTION High-quality and long-term homogeneous datasets play a pivotal role in ensuring accuracy of many climatic studies, particularly those dealing with climate variability, climate prediction and climate change. Over the last thirty years, much effort has been expended by different research groups to produce high-quality and homogeneous regional to global temperature datasets on different timescales. On a global scale and monthly basis, gridded datasets such like the CRUTEM2v (Jones et al., 2001), the HadCRUT2 (Rayner et al., 2003; Jones and Moberg, 2003) or the Global Historical Climatology Network (GHCN, Vose et al., 1992; Peterson and Vose, 1997) have enabled the documentation and analysis of long-term temperature change at the largest spatial scales (e.g. Jones et al., 1999; Jones and Moberg, 2003). On regional and national scales and also monthly timescales, datasets of higher spatial resolution have been compiled over *Correspondence to: Manola Brunet, Climate Change Research Group, University Rovira i Virgili, Pza. Tarraco, 1, 43071-Tarragona, Spain; e-mail: manola.brunet@urv.net Copyright  2006 Royal Meteorological Society