Classical methods used for predicting temperature as a relevant variable of climate change

Temperature prediction has become a very important area of research in the context of climate change. Classical prediction methods have been highlighted as fundamental tools to address this problem. This work includes a state of the art on temperature prediction as an important variable of climate change, where we seek to identify the strengths and limitations of the methods used such as moving averages, ARIMA, SARIMA, exponential smoothing and linear regression. These methods continue to be valuable tools in temperature prediction, providing a solid basis for analysis and decision making in meteorology and other climate-related areas.