In recent years, global warming and climate extremes have occurred frequently, seriously affecting human life, production and sustainable development.To study the correlation between carbon emissions and climate change, complex networks and big data statistical analysis methods were used to construct a multi-factor climate network of Yunnan carbon emissions and multi-factor climate network by determining the connectivity of edges through Pearson correlation coefficients, and sliding series correlation was used to analyse the effect of carbon emissions on meteorological factors.The results show that carbon emissions show a positive correlation with temperature, wind speed and sunshine, and a negative correlation with air pressure, precipitation and humidity.On long time scales carbon emissions have an impact on changes in meteorological factors, with an immediate effect on wind speed and a trend from lagging to immediate on precipitation.The study provides some theoretical reference for the control of CO 2 emissions in Yunnan Province.