In addition to seasonal transboundary pollution included sandstorm and haze from China, the local pollution also plays an important role in Taiwan. To improve the ability of air quality forecast and provide objective forecast guideline continuously and stably. The following works have been done in the plans, including the maintaining of the statistical correction methods DCA, DMOS, Bayesian model averaging method (BMA) and the automatic forecasting procedures of numerical dynamic air quality forecast model CMAQ-OP1.0 and CMAQ-OP2.0 on high performance computer facility in Central Weather Administration (CWA-HPC).Additionally, we also have been Integrated and updated the three-dimensional meteorological field data of eather Research and Forecasting (WRF) Model, and optimized the air product forecast evaluation platform and the forecast editing system, etc. Following the results of pervious plan, this work continues maintaining and expanding existing automatic forecasting procedures. In this work, we keep maintaining and updating the automatic forecasting procedures, and optimize CMAQ-OP2.0 forecasting procedure simultaneously to make forecast time extend from 84 to 120 hours and forecast times from twice a day to four times a day. Besides, we also develop air quality probability forecast, long-term air quality forecast to improve the existing forecast product.

Community Multi-Scale Air Quality (CMAQ) modeling system, Probability Forecast forecast, Bayesian model averaging (BMA)