Meteorological conditions may have a great impact on PM_2.5 pollution during the heavy haze winter in Chinese cities. Here, we examined the effects of meteorological factors on PM_2.5 concentrations from December 2013 to February 2014, and from December 2014 to February 2015, in five cities—Shijiazhuang, Xi'an, Beijing, Taiyuan, and Guangzhou exhibiting different levels of PM_2.5. We found (1) meteorological factors affected daily PM_2.5 concentrations, and variables differed in cities with varied pollution levels. Significant positive correlations were obtained between humidity and PM_2.5 concentrations in Shijiazhuang, and a significant negative correlation was also obtained for wind speed. Significant positive correlations were obtained between humidity and PM_2.5 concentrations in Xi'an, and a significant negative correlation was found for wind speed. Significant positive correlations were obtained between humidity/temperature/minimum temperature and PM_2.5 concentrations in Beijing, and a significant negative correlation was found for wind speed. Significant positive correlations were obtained between humidity/temperature/minimum temperature/maximum temperature and PM_2.5 concentrations in Taiyuan, and a negative correlation was found for the maximum sustained wind speed. Significant positive correlations were obtained between humidity/maximum temperature/precipitation and PM_2.5 concentrations in Guangzhou, and a significant negative correlation was found for wind speed. (2) Meteorological factors can explain the smaller variability in PM_2.5 concentration in cities that have heavier PM_2.5 pollution. Shijiazhuang, which represented a severely polluted area, showed meteorological factors of 0.27 after multiple regression analysis (R²). Xi'an, which represents a heavy polluted area, showed meteorological factors of 0.29 (R²). Beijing, which represents a moderately polluted area, showed meteorological factors of 0.46 (R²). Taiyuan, which represents a polluted area, showed meteorological factors of 0.67 (R²). The results provide a scientific basis for regional ecological environment planning and coordinated urban development. Therefore, understanding the main meteorological factors and their impact on urban PM_2.5 in different cities provides a theoretical reference for air pollution control and improvement of prediction accuracy.