An accurate analysis and modeling of temperature series time series is one of the important challenges in predicting climate behavior and, hence, the impact on future environmental and socioeconomic conditions. Clock time series are complex and non-stationary. In this research, we tried to evaluate and analyze the average long-term (change) and oscillation (temperature variability) of temperature in western Iran. First, modeling in the family of polynomials was used to identify the trend. The results showed that Kermanshah and Ilam stations have linear trend and Kurdistan, Hamadan, and Khorramabad have a significant proportional trend. Using the spatial analysis of the periodologist, the annual temperature with confidence of 99, 95 and 90 percent was extracted. In this research, synoptic stations were selected in the provinces of the western part of the country, all stations showed significant 2-3-year cycles; that is, every recurring temperature event is 2-3 years in one period. In addition, each temperature event is expected to be repeated every two to three years. From the perspective of probability, it can be repeated 0.4 times to repeat the event. This cycle is observed at high temperatures in large areas of the globe and it has been accepted that the biennial cycles are common features of the planet and are the result of a change in orbital flow. In general, with respect to the significance of cycles 2-3, it can be stated that the temperature fluctuations of the west of the country are influenced by large scale models