摘要
A coupled aerosol–cloud model is essential for investigating the formation of haze and fog and the interaction of aerosols with clouds and precipitation. One of the key tasks of such a model is to produce correct mass and number size distributions of aerosols. In this paper, a parameterization scheme for aerosol size distribution in initial emission,which took into account the measured mass and number size distributions of aerosols, was developed in the GRAPES–CUACE [Global/Regional Assimilation and Pr Ediction System–China Meteorological Administration（CMA） Unified Atmospheric Chemistry Environment model]—an online chemical weather forecast system that contains microphysical processes and emission, transport, and chemical conversion of sectional multi-component aerosols. In addition, the competitive mechanism between nucleation and condensation for secondary aerosol formation was improved, and the dry deposition was also modified to be in consistent with the real depositing length. Based on the above improvements, the GRAPES–CUACE simulations were verified against observational data during 1–31 January 2013, when a series of heavy regional haze–fog events occurred in eastern China. The results show that the aerosol number size distribution from the improved experiment was much closer to the observation, whereas in the old experiment the number concentration was higher in the nucleation mode and lower in the accumulation mode. Meanwhile, the errors in aerosol number size distribution as diagnosed by its sectional mass size distribution were also reduced. Moreover, simulations of organic carbon, sulfate, and other aerosol components were improved and the overestimation as well as underestimation of PM2.5 concentration in eastern China was significantly reduced,leading to increased correlation coefficient between simulated and observed PM2.5 by more than 70%. In the remote areas where bad simulation results were produced previously, the correlation coefficient grew from 0.35 to 0.61, and the mean mass concentration went up from 43% to 87.5% of the observed value. Thus, the simulation of particulate matters in these areas has been improved considerably.
A coupled aerosol–cloud model is essential for investigating the formation of haze and fog and the interaction of aerosols with clouds and precipitation. One of the key tasks of such a model is to produce correct mass and number size distributions of aerosols. In this paper, a parameterization scheme for aerosol size distribution in initial emission,which took into account the measured mass and number size distributions of aerosols, was developed in the GRAPES–CUACE [Global/Regional Assimilation and Pr Ediction System–China Meteorological Administration（CMA） Unified Atmospheric Chemistry Environment model]—an online chemical weather forecast system that contains microphysical processes and emission, transport, and chemical conversion of sectional multi-component aerosols. In addition, the competitive mechanism between nucleation and condensation for secondary aerosol formation was improved, and the dry deposition was also modified to be in consistent with the real depositing length. Based on the above improvements, the GRAPES–CUACE simulations were verified against observational data during 1–31 January 2013, when a series of heavy regional haze–fog events occurred in eastern China. The results show that the aerosol number size distribution from the improved experiment was much closer to the observation, whereas in the old experiment the number concentration was higher in the nucleation mode and lower in the accumulation mode. Meanwhile, the errors in aerosol number size distribution as diagnosed by its sectional mass size distribution were also reduced. Moreover, simulations of organic carbon, sulfate, and other aerosol components were improved and the overestimation as well as underestimation of PM2.5 concentration in eastern China was significantly reduced,leading to increased correlation coefficient between simulated and observed PM2.5 by more than 70%. In the remote areas where bad simulation results were produced previously, the correlation coefficient grew from 0.35 to 0.61, and the mean mass concentration went up from 43% to 87.5% of the observed value. Thus, the simulation of particulate matters in these areas has been improved considerably.
基金
Supported by the National Key Project of the Ministry of Science and Technology of China(2016YFC0203306)
National Natural Science Foundation of China(91544232)
National Science and Technology Support Program of China(2014BAC16B03)
China Meteorological Administration Innovation Team Fund for Haze–Fog Monitoring and Forecasts
