Evolution Characteristics of Atmospheric Visibility in the Beijing 

Based on the fine-resolution temporal observation data provided by the auto monitoring stations for road weather information in Beijing airport expressway, the evolution characteristics of atmospheric visibility in the Beijing expressway and the corresponding physical factors are studied. The main conclusions are as follows: (1) It is demonstrated that the visibility in the Beijing expressway has distinct daily and monthly variation features, that is to say, the visibility at 1400 LST is the highest in a day, and the time with the lowest visibility is uncertain in any day. For the seasonal variation, the summer visibility is the highest in a year. (2) Of monthly and daily variation, the relationship between the visibility and the meteorological factors is the complex nonlinear correlation, rather than the simple linear correlation. Through analyzing the lowest monthly visibility with 21-month data, it is shown that the relationship between the visibility and the humidity is in the distribution of power, and is U type between the visibility and the temperature. However, in the highest monthly visibility, the relationship between the visibility and the humidity becomes exponential. (3) From the view of physics, the visibility reduction is affected by humidity through the water vapors Rayleigh scattering and the fog's Mie scattering, is affected by the aerosol through the pressure resistance from the wind, and is affected by the water phase change through the Bergeron three-phase processes when the temperature is around 0℃. (4) It is shown that the visibility below 200 m happens mostly in the conditions that relative humidity of atmosphere is close to 100% (fog weather phenomenon), while the visibility above the 200 m is different. It is found that about 50% of visibility between 200 m and 1000 m happens in the case of fog, and about 30% of 1-4 km visibility is caused by fog. Thus, 1-4 km visibility mainly results from haze, sand storm and other weather phenomena.