| 英文摘要 |
The purpose of this project is to maintain the performance of forecasting systems and to facilitate the daily forecast of air quality over Taiwan region. The main work includes the maintenance and operation of the mesoscale numerical forecasting model, the Mainland China dust dynamic numerical model (TAQM/KOSA), the local riverside mineral dust dynamic model (TAQM/TWKOSA), and the Community Multi-scale Air Quality Model (CMAQ). The characteristics of atmospheric variables and the concentrations of ozone, PM10 and PM2.5 from the model’s outputs and from the observation have been analyzed. To improve the air quality forecasting capability, we have also tried to identify the potential issues leading by the dynamics. In the future, these results can be further used to improve the performance of the dynamic numerical model. Current sensitivity analysis includes comparing the concentrations of O3, PM10 and PM2.5 between the data from EPA monitoring stations and from model simulations. For general pollution analysis, the simulated concentrations, diurnal variations and the seasonal variation of the pollutants are compared with the observation of EPA monitoring stations and seven air quality districts respectively. The poor quality event days in different weather patterns, and a severe local dust event companying with a slight dust originated from the mainland China, and a serious air pollution event due to poor local dispersion, are analyzed. To help the daily forecasting in EPA, special-duty manpower is assigned to work in EPA for organizing and integrating all of the information to support the pre-warning decision. This project also provides the training program to EPA and the expert opinion from project director during the Mainland China severe dust events forecasting meeting.
In this year, the updated initial mode and the adjusted WRF_CMAQ simulation schedule improve the performance of the operation models. Moreover, the air quality forecasting capability is improved, especially for ozone, and PM2.5, after this year’s works. The updated system has been online and started forecasting parallel with the previous system since May 2018, and the original one is used as a backup, which is provided to the forecasters for evaluation.
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