Identification of non-spatial patterns Hourly variations of temperature on a monthly, seasonal and annual basis (Case Study: Synoptic Station of Tabriz)

In this study, in order to determine the variation and temperature trend of 3 hour synop during day and night on monthly, seasonal and annual scale, the hourly data of the synoptic station of Tabriz (with 195768 data) during the statistical period (2017-1951) was extracted and investigated. Using Matlab software, 3-hour data (synops) turned into hourly-monthly, hourly-seasonal, and hourly-annual data. After preparing the desired database, in order to identify the process and the significance of the change process, the nonparametric Mann-Kendall and the slope estimator was also used to determine the slope of each process time line. The results of the study showed that during the day and night, monthly- hourly data has the highest increase at 03:00 in June, with a temperature of 0.71 ° C in every ten years. In the hourly-seasonal view, the summer season at 03:00 increased about 0.66 ° C in per decade. And the highest average annual variation in temperature was observed for synops at 00:00 and 03:00 with an increase of 0.46 degrees Celsius per decade. In general, the results show that the slope of temperature changes in the night synops more than the daily synops and the slope of temperature changes in the warm seasons is more than the cold seasons. According to this trend, energy consumption (cooling) in the next ten years is expected to increase in the summer.