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Examining Extreme Temperature Events in Mainland Portugal: A Comprehensive Analysis with ERA5-Land Data
* 1 , 1, 2 , 3, 4
1  Instituto Superior Técnico, University of Lisbon (IST/UL), Portugal
2  Civil Engineering Research and Innovation for Sustainability (CERIS), Portugal
3  Civil Engineering Research and Innovation for Sustainability (CERIS), Portugal.
4  Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento (IST-ID), CERIS, Portugal
Academic Editor: ATHANASIOS LOUKAS

Abstract:

This study examines extreme temperature events in mainland Portugal, specifically maximum daily temperatures. The data was obtained from ERA5-Land hourly temperature in the period from Oct/1981 to Sep/2023 (42 hydrological years). The study area comprehends 1012 ERA5-Land grid points, approximately covering mainland Portugal, a country located in the Iberian Peninsula and bordered in the north and east by Spain and in the south and west by the Atlantic Ocean. To identify the extreme events, temperature thresholds were defined based on the empirical quantiles of 90.0, 99.0, and 99.9% of the global set of daily maximum temperatures for the entire country and period of analysis (exceeding 15 million values). The nationwide thresholds ensur the comparability of extreme daily temperatures across all the grid-points. The analysis period was divided into two sub-periods of 21 years each: from 1981/1982 to 2001/2002 (late period) and from 2002/2003 to 2022/2023 (recent period). For each of periods (global and sub-periods) and quantiles, the mean daily temperature above the threshold was computed per grid point and made dimensionless by division by the corresponding nationwide quantile. The mean annual number of days with extreme temperatures was also computed. The t-Student test was applied to compare the mean daily temperatures above the threshold in the sub-periods. Regardless the period, the mean annual number of days with exceptional temperatures was higher for the lowest quantile, up to 90 days/year, while for the highest quantile it was less than 5 days/year. The spatial patterns showed more daily occurrences in the southern regions, and fewer in the northern and coastal ones. The results from the t-Student test revealed a statistically significant increase in the mean daily maximum temperatures above the threshold towards the present for most grid points, especially for the highest quantiles. These findings emphasize the need for effective risk mitigation strategies to adapt to changing climatic conditions.

Keywords: Portugal, Extreme daily temperature, Empirical threshold, Risk management
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