الفهرس 
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Abstract
from the climatological point of view, northeast Spain is an area of large interest due its varied geographical, topographical and climatic characteristics. In this work, a spatially and temporarily high-resolution daily dataset of temperature was developed for northeastern Spain. Data derived from a high number of observatories (1583) spanning some period between 1900 and 2006 was tested for internal and external consistency to check data quality. To improve data completeness, a linear regression model was then utilized to infill gaps in the daily temperature series using the best correlated data from nearby sites. Discontinuities in the reconstructed series were then determined by combining the results of three homogeneity relative tests:the Standard Normal Homogeneity Test (SNHT), the Easterling and Peterson twophased regression method, and the Vincent test. The newly complied dataset seems to be more robust and reveals more coherent spatial and temporal patterns of temperature compared with the original dataset. This finding was confirmed by means of a suite of statistics (e.g., semivariance models and L-moment statistics).from the temporal and spatial perspectives, the new dataset comprises the most complete register of temperature in northeast Spain (1900-2006), with a reasonably spatial coverage. Therefore, this database provides a more reliable base for studying temperature changes and variability in the region.This thesis analyzed the surface air temperature variability and trends over the study domain for the 20th century based on the new compiled dataset. An assessment of long-term change and variability of temperature was provided using a dataset of 19 observatories from 1920 to 2006. In addition, a more detailed analysis of the spatial and temporal variability of maximum, minimum, and mean temperatures, and the diurnal temperature range (DTR) was also carried out employing 128 observatories spanning the period from 1960 to 2006. In general, maximum, minimum, and mean temperatures increased significantly, mostly from contributions in the late decades of the 20st century. At the seasonal scale, the analysis revealed that the weakest trends (mostly insignificant at the 95% level [p<0.05]) were observed during autumn, while the strongest warming rates were found during summer and spring. Spatially, the observed warming was more robust in the coastal portions compared with mainland observatories.