Abstract: The purpose of this study is to analyze climate’s variation trend and forecast the climate. The main methods are known as quantile regression and empirical mode de- composition (EMD). Firstly, a global heat map is utilized for the descriptive statistics of global temperature data. The EMD method is applied for data denoising to analyze global temperature’s variation trend, and the concept of global temperature cycle is introduced. These aim to study the trend of global warming. Secondly, the multivariate linear regres- sion model and the quantile regression model are applied to identify factors influencing global temperature. Then the temperature model is built to predict temperature changes. The findings can provide statistical support for global climate analysis.

Key words: greenhouse effect, global warming, quantile regression, empirical mode de- composition (EMD)