1Plateau Atmospheric and Environment Laboratory of Sichuan Province, College of Atmospheric Science, Chengdu University of Information Technology, Chengdu 610225, China
2State Key Laboratory of Severe Weather (LASW), Institute of Atmospheric Composition, Chinese Academy of Meteorological Sciences, Beijing 100081, China
3Center for Environmental Remote Sensing, Chiba University, Chiba, Japan
4National Meteorological Center, CMA, Beijing 100081, China
1Plateau Atmospheric and Environment Laboratory of Sichuan Province, College of Atmospheric Science, Chengdu University of Information Technology, Chengdu 610225, China
2State Key Laboratory of Severe Weather (LASW), Institute of Atmospheric Composition, Chinese Academy of Meteorological Sciences, Beijing 100081, China
3Center for Environmental Remote Sensing, Chiba University, Chiba, Japan
4National Meteorological Center, CMA, Beijing 100081, China
Abstract. This study assesses the performance of SKYNET in comparison to AERONET (Aerosol Robotic Network) for retrieving aerosol optical properties (AOPs) in Beijing, China. The results obtained from simultaneous measurements show high correlation coefficients (> 0.994) for aerosol optical depth (AOD) at each wavelength. The highest correlation coefficient for Ångström exponent is 0.825, at 500–870 nm. The single scattering albedo (SSA) of SKYNET is systematically larger than that of AERONET at each wavelength, and adjusting the SVA (solid view angle) and SA (surface albedo) input values can easily affect the value of SKYNET SSA. The volume size distribution patterns derived from the two networks’ instruments are both bimodal, which is typical, while the coarse-mode volume of SKYNET is larger than that of AERONET on average.
According to the frequency distribution of aerosol particles, coarser aerosol particles often present in autumn and finer particles usually exist in winter, and there are more absorbent aerosol particles in winter. SKYNET data, combined with meteorological data, CALIPSO (Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations) data, backward trajectories, and WPSCF (weighted potential source contribution function) and WCWT (weighted concentrated weighted trajectory) analyses are used to analyze a serious pollution event in winter over Beijing. The results suggest that it was not only affected by local emissions but also by regional transport. The AOPs under three weather conditions (clean, dusty, haze) in Beijing are discussed. The values of AOD on haze days are about 10.3, 10.0, 8.7, 6.3 and 6.2 times larger than those on clean days at 400, 500, 670, 870 and 1020 nm, respectively; and under haze conditions, the PM2.5 (fine particulate matter) is about 7.6 times larger than that under clean conditions. The values of AOD on dusty days are about 7.1, 7.4, 7.0, 5.3 and 5.2 times larger than those on clean days at 400, 500, 670, 870 and 1020 nm, respectively; and under haze conditions, the PM2.5 is about 5.2 times larger than that under clean conditions.
This study assesses the performance of SKYNET in comparison to AERONET (Aerosol Robotic Network) for retrieving aerosol optical properties (AOPs) in Beijing, China. SKYNET data retrieved by SR-CEReS analysis package are used to analyze a serious pollution event in winter over Beijing. The AOPs under three weather conditions (clean, dusty, haze) in Beijing are discussed. Measurements from the SKYNET skyradiometer can be used to analyze the AOPs over Beijing reasonably.
This study assesses the performance of SKYNET in comparison to AERONET (Aerosol Robotic Network)...