## 4 Conclusions  
Mean temperature trends that occurred in California during the period 1980-2019 have been analysed in this research. The study has been carried out on a monthly, seasonal and annual basis. Moreover, this study has also analysed the relationship between mean temperatures and up to nine teleconnection patterns that may have an influence on the Californian climate. It is the first time, up to our knowledge, that some patterns (EPO, AAO and WPO) have been considered. In the light of the results some important findings of this research are stated as follows:  
* Trend analysis for the State of California as a whole shows increases in temperature of about +0.01 \({}^{\circ}\)C year\({}^{-1}\). In addition, during that period, southern California, Mojave and Sonora Desert are the regions that have shown the highest statistically significant upsurge (+0.017 \({}^{\circ}\)C year\({}^{-1}\)), while northern areas did to a lesser extent (+0.008 \({}^{\circ}\)C year\({}^{-1}\)). This supports the previous idea that southern California is warming faster than northern California. * According to local trends, it has been shown temperature increases in autumn and summer (+0.06 \({}^{\circ}\)C and +0.035 \({}^{\circ}\)C year\({}^{-1}\) respectively) from 1980 to 2019. These are found in areas such as the Sierra Nevada and Lake Tahoe for autumn and the east part of the state for summer. These seasons are also the ones that show the highest fraction of stations (36%) with statistically significant positive trends. * On the monthly scale, the strongest average warming is found in November at +0.04 \({}^{\circ}\)C/year. January, July, August and November are the months with the highest fraction (25-38%) of significant trends at the individual stations. * The coastal cooling effect in summer gives a trend around zero value, contrary to the results of previous research conducted for this season in different time periods. * As regards the teleconnection patterns, Pacific Decadal Oscillation (PDO) has a positive correlation with average temperatures during the period studied, particularly in coastal areas such as Los Angeles, San Francisco and Monterey. In addition, the highest negative correlations with statistical significance have been noted for the West Pacific Oscillation (WPO) from December to April. Moreover, PDO, WPO, NAO, PNA and EPO are the teleconnection patterns that have shown the highest positive correlation from February to May and might have explanatory potential in mean temperature over those months. Figure 12: Percentage of meteorological stations in the State of California with significant correlations (positive in red, negative in blue) between RMM2 index of MJO and temperature. The Madden-Julian Oscillation (RMM2) is positively correlated with temperature in January and November, with 41.3% of stations have shown a positive correlation in the latter. In November, both EPO and RMM2 have been positively correlated with temperature. On the contrary, Antarctic Oscillation (AAO) and Arctic Oscillation patterns (AO) are unlikely to show great influence on average temperature trends in California. Further investigations on relationships between teleconnection patterns and climate variables are essential to establish cause-effect relationships that help us to predict future changes in average temperatures in California. Knowledge of atmospheric teleconnections provides us with the opportunity to assess interconnection on a planetary scale. Knowing the temperature trends recently occurring in the state of California and the influence of teleconnection patterns on them could help policymakers to implement measures in order to mitigate the possible effects caused by global warming. In that line, the authors consider that this research can contribute to advance that knowledge. [PERSON] and [PERSON] contributed to the study's conception and design. Material preparation and data collection was made by [PERSON]. The statistical analysis was carried out by [PERSON] and [PERSON].