Abstract. This paper examines the effect of extreme summer temperatures on daily mortality in two large cities of Iberia: Lisbon (Portugal) and Madrid (Spain). Daily mortality and meteorological variables are analysed using the same methodology based on Box-Jenkins models. Results reveal that in both cases there is a triggering effect on mortality when maximum daily temperature exceeds a given threshold (34 • C in Lisbon and 36 • C in Madrid). The impact of most intense heat events is very similar for both cities, with significant mortality values occurring up to 3 days after the temperature threshold has been surpassed. This impact is measured as the percentual increase of mortality associated to a 1 • C increase above the threshold temperature. In this respect, Lisbon shows a higher impact, 31%, as compared with Madrid at 21%. The difference can be attributed to demographic and socio-economic factors. Furthermore, the longer life span of Iberian women is critical to explain why, in both cities, females are more susceptible than males to heat effects, with an almost double mortality impact value.The analysis of Sea Level Pressure (SLP), 500 hPa geopotential height and temperature fields reveals that, despite being relatively close to each other, Lisbon and Madrid have relatively different synoptic circulation anomalies associated with their respective extreme summer temperature days. The SLP field reveals higher anomalies for Lisbon, but extending over a smaller area. Extreme values in Madrid seem to require a more western location of the Azores High, embracing a greater area over Europe, even if it is not as deep as for Lisbon. The origin of the hot and dry air masses that usually lead to extreme heat days in both cities is located in Northern Africa. However, while Madrid maxima require wind blowing directly from the south, transporting heat from Southern Spain and Northern Africa, Lisbon maxima occur under more easterly conditions, when Northern African air flows over the central Iberian plateau, which had been previously heated.

We present a new approach to improve the reliability of quantifying the impact of a heat wave on mortality rates. We show, for the recent European summer 2003 heat wave, that the use of absolute maximum temperature values, or number of days above a given threshold, can be misleading. Here, we have assessed the impact of the heat wave on Iberian mortality by applying a four step procedure: (1) calculating, for each observatory, the local maximum temperature (T (max)) distributions, (2) calculating the corresponding 95th percentile values (T (threshold)), (3) locally defining extremely hot days (EHD) as those days on which the local threshold of the 95th percentile of the series is exceeded, and (4) calculating the total degrees-days (DD) of exceedance, by calculating the difference T (max)-T (threshold) and summing these values for all days above T (threshold). We show that the relationship between summer mortality rates and the DD index is non-linear and can be described by a logarithmic function, with a correlation coefficient of 0.78, which explains 60.6% of the mortality variance (F value of 24.64, significant at P<0.0001). Using maximum temperatures, no significant relationship is found with mortality, whereas the EHD frequency shows a significant association with mortality, albeit weaker than that obtained with DD.

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The effects of heat waves on the population have been described by different authors and a consistent relationship between mortality and temperature has been found, especially in elderly subjects. The present paper studies this effect in Seville, a city in the south of Spain, known for its climate of mild winters and hot summers, when the temperature frequently exceeds 40 degrees C. This study focuses on the summer months (June to September) for the years from 1986 to 1997. The relationships between total daily mortality and different specific causes for persons older than 65 and 75 years, of each gender, were analysed. Maximum daily temperature and relative humidity at 7.00 a.m. were introduced as environmental variables. The possible confounding effect of different atmospheric pollutants, particularly ozone, were considered. The methodology employed was time series analysis using Box-Jenkins models with exogenous variables. On the basis of dispersion diagrams, we defined extremely hot days as those when the maximum daily temperature surpassed 41 degrees C. The ARIMA model clearly shows the relationship between temperature and mortality. Mortality for all causes increased up to 51% above the average in the group over 75 years for each degree Celsius beyond 41 degrees C. The effect is more noticeable for cardiovascular than for respiratory diseases, and more in women than in men. Among the atmospheric pollutants, a relation was found between mortality and concentrations of ozone, especially for men older than 75.