## 4 Discussion and Conclusions  
This study provides an innovative analysis of the near-surface air temperature in mainland Portugal, based on hourly observations over the recent period of 2000-2018 and from a large weather station network (63 meteorological stations). The whole process is fully implemented in a GIS and the final maps are published on Supplementary Material, in a widely used file format (shapefile), thus allowing their future application to a wide range of assessments. Although a longer data period would be preferable, typically 30 years, as is recommended by the WMO (World Meteorological Organization), data prior to 2000 have important gaps and inconsistencies that may strongly limit the statistical robustness of the results. In addition, of the 133 meteorological stations with hourly data available, only 63 are used, due to the significant number of data gaps. The present study is a trade-off between the density and temporal consistency of the meteorological station network. A set of hourly temperature maps is obtained using the most recent data available, thus providing accurate information on the current thermal conditions throughout the country. In the first part of the study, the results allow a detailed geographical characterization of the thermal conditions in mainland Portugal, at a high spatial resolution of 1 km. Such information is of great value to growers and stakeholders in the agrarian sector [30], as it provides a comparison of the different climatic conditions in each agrarian zone. Additionally, the results provide information concerning the relationship between geographical variables and temperature. Thus, final maps can be automatically updated with new hourly temperature data and easily managed within a GIS environment, thus permitting future improvements resulting from new data inputs. Overall, the outcomes highlight a strong spatial variability and strong seasonality of temperatures in mainland Portugal. The NH 4-8 \({}^{\circ}\)C patterns mainly reflect wintertime conditions, whereas the NH 32-36 \({}^{\circ}\)C patterns are a manifestation of summertime conditions. The number of hours in the year with cold conditions (4-12 \({}^{\circ}\)C) is higher in the northern-central regions, mainly in mountainous areas. On the other hand, the number of hours in the year with temperate conditions (12-20 \({}^{\circ}\)C) is largely influenced by the distance to the coastline, presenting much lower values over inner Portugal, mostly  
Figure 9: (**a**) Relative bar chart (in %) for the number of hours by different temperature intervals and for each Protected Designation of Origin (PDO) of olive oil. (**b**) Geographical location of the PDO of olive oil (see the list for their designations). Area-means are computed only over the olive tree land cover areas (source: COS2007). in the northeast. Still, the very warm conditions (number of hours with temperature between 28-36 \({}^{\circ}\)C) are essentially restricted to inner-southern Portugal and to the upper Douro valley. The present study results are also key to understanding climate change impacts on each agriarian region in Portugal. Taking into account previous studies regarding climate change projections for Portugal [7; 12; 21; 31], it is expected that temperatures should increase. It should be noted that extreme temperatures (\(>\)30 \({}^{\circ}\)C) are expected to be more frequent under future climates. Hence, the number of hours in each class of these maps are expected to shift under future climatic conditions. In the second part of the study, some application examples are shown, through the extraction of information for the NUTS level 3 administrative divisions in mainland Portugal. This work may be replicated in the future, in other territorial units up to the local level or other socio-economic sectors. The most striking correspondence between geographical distribution of cool and very warm areas and occurrence of the species is that of chestnut and holm oak (Figure 5a,d and Figure 6).