At present, few studies have focused on the impact of circulation patterns on aerosol pollution in the Pearl River delta region (PRD) region based on the objective circulation classification method. Based on PM_2.5 observation data, meteorological observation data, Aerosol Robotic Network (AERONET) aerosol observation data and European Center for Medium-Range Weather Forecasting (ECMWF) ERA (European Reanalysis)-Interim data in the PRD during 2013 to 2017, the air pollution level, meteorological conditions, and aerosol optical and radiation characteristics in different circulation patterns are studied in this paper. Using ECMWF ERA-Interim sea level pressure, nine circulation patterns were determined based on the T-mode principal component analysis (PCA) combined with the k-means clustering method. There were significant differences in PM_2.5 values under different circulation patterns, indicating that the change of atmospheric circulation is an important factor driving the change of air quality. The prevailing wind in winter (northerly wind) facilitates the transport of pollutants from the north of the PRD and forms severe air pollution, while the prevailing wind in summer (southerly wind) brings clean air from the South China Sea; additionally, a high frequency of precipitation benefits the wet scavenging of pollutants, resulting in improved air quality in the PRD region. The impact of circulation patterns on the AOD (aerosol optical depth) is basically similar to that of the PM_2.5 concentration. The study also found that the annual average total radiation was negatively correlated with the annual average PM_2.5 concentration. In future, we plan to identify which methods and data are suitable for circulation classification in the PRD region.

In this study, National Centers for Environmental Prediction (NCEP) Final (FNL) operational global analysis data and meteorological observation data from 2013 to 2017 were used to evaluate the impact of seasonal changes and different circulation classifications on the dynamical downscaling simulation results of Weather Research and Forecasting (WRF) in the Pearl River Delta (PRD) region. The results show that the dynamical downscaling method can accurately simulate the time variation characteristics of the near-surface meteorological field and the hit rates of a 2-m temperature, 2-m relative humidity, 10-m wind speed, and 10-m wind direction are 92.66%, 93.98%, 26.78%, and 76.78%, respectively. The WRF model slightly underestimates the temperature and relative humidity, and overestimates the wind speed and precipitation. For precipitation, the WRF model can better simulate the variation characteristics of light rain and heavy rain, with the probability of detection are 0.59 and 0.69, respectively. For seasonal factors, the WRF model can conduct a perfect simulation in autumn and winter, followed by spring, while summer is vulnerable to extreme weather, so the result of the simulation is relatively poor. The circulation type is an important parameter of downscaling assessment. When the PRD is controlled by high pressure, the simulated results of WRF are good, and when the PRD is affected by low pressure or extreme weather, the simulation results are relatively poor.