基于改进的三维变分同化系统对地面细颗粒物浓度 (PM2.5) 与卫星气溶胶光学厚度 (AOD) 进行同化, 评估了同化分析场对 PM2.5 预报的改善效果。研究选定一次持续污染过程, 分别对地面 PM2.5 和 AOD 观测数据进行各自单独同化和两者同时同化。结果表明, 相比于单独同化 PM2.5 , 单独同化 AOD 对 AOD 分析场的精度提升更为有效, 但对 PM2.5 分析场的准确性显著降低。而同时同化 PM2.5 与 AOD 观测时, 分析场对气溶胶的光学-物理特性模拟达到最好的综合效果。同化试验可有效降低模式漏报率, 对于中轻度污染情况, 同化数据的选择对预报影响并不显著; 然而重度污染时, 同时同化近地面 PM2.5 和整层 AOD 的综合预报效果最优。

Based on the improved three-dimensional variational assimilation system, the assimilation of ground fine particulate matter (PM2.5) and satellite aerosol optical depth (AOD) is conducted and the effectof analysis field assimilation on the PM2.5 forecast improvement is evaluated. A continuous pollution process is selected in this study, and the ground PM2.5 and AOD observation data are assimilated individually and simultaneously. The results show that compared with PM2.5 individual assimilation, AOD assimilation alone is more effective in improving the accuracy of the AOD analysis field, but the accuracy of the PM2.5 analysis field is reduced obviously. While simultaneous assimilation of PM2.5 and AOD makes the simulation of aerosol optical-physical properties achieve the best overall effect. Moreover, assimilation tests can effectively reduce the missing report rate. For the case of mild and moderate pollution, the choice of assimilation PM2.5 or AOD does not have a significant impact on the forecast. However, in the case of severe pollution, the comprehensive forecast of PM2.5 is the best when the ground PM2.5 and the whole layer AOD are assimilated simultaneously.