We investigate the relationships between Spain's electricity load and specific meteorological variables. Spain's electricity data consist of the country's aggregated network daily load for the period of 1993-2010. The meteorological variability is represented by an index based on temperature observations from meteorological stations across Spain. We use a monthly-fixed regression model to characterise the relationships between both indexes and investigate the sensitivity of the relationship. We propose also another regression model based on the relationship between the electricity load index and some indexes that characterize the variability of large scale climate signals. These signals are known to influence the meteorological variability in the Iberian sector, and include the North Atlantic Oscillation, the North Tropical Atlantic, the South Tropical Atlantic and the Pacific Decadal Oscillation, among others. We assess the predictive potential of both models through their monthly hindcast skill values and validate them with some complementary hindcast experiments. (C) 2014 Published by Elsevier Ltd.