WRF-Chem模式降水对上海PM2.5预报的影响

为探讨降水预报准确性对细颗粒物(PM_(2.5))数值预报效果的影响,利用基于WRF-Chem模式构建的华东区域大气环境数值预报系统在2015年1月1日—2016年12月31日期间的业务预报结果,分析了该系统对上海降水和PM_(2.5)的预报能力,探讨了其在不同降水预报准确性下的PM_(2.5)预报效果差异.结果表明,华东区域大气环境数值预报系统对上海的降水和PM_(2.5)都有良好的预报水平,2年平均偏差小于5%;正确预报、空报和漏报较明显降水及准确预报无降水日情况下的PM_(2.5)预报效果差异显著,正确预报降水时有较明显偏高且高估程度随降水的增强而增大,无降水时偏低;正确预报降水时PM_(2.5)预报效果相对较差,其他情况接近.模式湿沉降方案存在不足,需要进一步完善,同时也需要提升模式的降水等气象条件预报能力.

Impact of precipitation on Shanghai PM2.5 forecast using WRF-Chem

The forecast data from the Regional Atmospheric Environmental Modeling System for eastern China (RAEMS) based on WRF-Chem model was employed to investigate the impact of the accuracy of precipitation prediction on particulate matter in numerical modeling. The forecast performance for precipitation and PM_2.5 concentration and the differences of performance for PM_2.5 forecasting under classified precipitation prediction accuracy over Shanghai during Jan. 1, 2015 and Dec. 31, 2016 were analyzed. Possible sources of forecast bias were also discussed to find potential solutions. The results show that the RAEMS has good performance on both precipitation and PM_2.5 prediction during the two years with mean bias of lower than 5%. Performance distinctly differs from each other for categories of correct forecasted (CP), missed, false alarmed precipitation days and correct forecasted clear days. Obvious over-estimating of PM_2.5 concentration is found in CP days and under-estimating is found in clear days. The integrated performance in CP days is relatively worse and those in the other three categories are comparable with each other. The evaluating results also suggest that the over-estimating of PM_2.5 concentration increases with precipitation. Improvements are proposed due to the deficiency of the wet scavenging scheme in the model and the prediction capability on meteorology, such as precipitation.