## 3 Results  
### Distribution of Temperature Intervals  
A first inspection at the temperatures recorded at each weather station was carried out, thus providing some basic information regarding their levels of magnitude, temporal variability, and spatial distribution before applying any interpolation approach (Figure 2). The mean temperature over mainland Portugal for the period of 2000-2018 ranges from 9 \({}^{\circ}\)C at the Penhas Douradas, in Serra da Estrela, to 18.2 \({}^{\circ}\)C in Faro. In the NUTS of Alentejo, Lisboa e Vale do Tejo and Algarve, the mean temperature is over 16 \({}^{\circ}\)C in all meteorological stations. The lowest values of mean temperature (<13 \({}^{\circ}\)C) are recorded in the inner-north of the country. The maximum temperature varies from approximately 32 \({}^{\circ}\)C up to 46 \({}^{\circ}\)C, but maximum temperatures below 39 \({}^{\circ}\)C are mostly restricted to high elevation areas or to the western coast, which is significantly influenced by the Atlantic Ocean. The minimum temperatures range between \(-\)13 \({}^{\circ}\)C and 2 \({}^{\circ}\)C. The lowest minimum temperatures are located mainly in the inner-northern Portugal. Figure 2: (**a**) Mean temperature, (**b**) maximum temperature, (**c**) minimum temperature, and (**d**) interquartile ranges (75 th–25 th percentiles) for the period of 2000–2018. The dots are scaled according to the level of magnitude of the temperature. The interquartile range indicates that the regions farthest from the Atlantic Ocean present greater differences between maximum and minimum temperatures, owing to the more continental climatic features. Hence, temperatures tend to decrease from the south to the northeast (higher latitudes and elevations), showing more moderate values in the Atlantic-facing areas. The relevance of each regressor (latitude, elevation, and distance to coastline) depends on the temperature interval. For instance, the distance to coastline is particularly important in the number of hours with temperatures within the intervals of 12-16 \({}^{\circ}\)C and 16-20 \({}^{\circ}\)C, while elevation is important in the number of hours with temperatures in the interval of 4-8 \({}^{\circ}\)C. Despite the differences among temperature intervals, the three regressors are statistically significant according to the Student's t-test at 5% significance level (cf. corresponding 95% confidence intervals in Figure 3). Overall, the regression coefficients are coherent with the corresponding temperature ranges and may thereby be considered reliable, with plausible representations of the spatial variability of temperatures throughout Portugal. The multivariate linear coefficients are positive for the independent variable's latitude, elevation, and distance to the coastline in the dependent variable number of hours within the intervals of 4-8 \({}^{\circ}\)C and 8-12 \({}^{\circ}\)C. The spatial distribution of lower temperatures follows a pattern where the roles of elevation, latitude, and distance to coastline are similar. Temperature usually decreases with elevation and it is therefore more likely to observe lower minimum temperatures in the higher mountains [25]. In addition, there is a general cooling trend in winter as the distance to coastline and latitude increases. The multivariate linear coefficients are negative for elevation and distance to coastline in the number of hours with the temperature ranges of 12-16 \({}^{\circ}\)C, 16-20 \({}^{\circ}\)C, and 20-24 \({}^{\circ}\)C, thus highlighting the predominance of mild temperatures in the coastal regions (Figure 3). The same coefficients are positive for latitude between 4 \({}^{\circ}\)C and 16 \({}^{\circ}\)C, showing the predominance of lower temperatures in the northern region. For the higher temperature intervals (24-28 \({}^{\circ}\)C, 28-32 \({}^{\circ}\)C, and 32-36 \({}^{\circ}\)C), the distance to coastline acquires more relevance, since the highest temperatures are commonly recorded in the interior of the country (Figure 3).