Impacts of meteorological conditions on the NASM pollution data assimilation system

Abstract

Since meteorological conditions are the main factor driving the transport and dispersion of air pollutants, an accurate simulation of the meteorological field will directly affect the accuracy of the atmospheric chemical transport model in simulating PM_2.5. Based on the NASM joint chemical data assimilation system, the authors quantified the impacts of different meteorological fields on the pollutant simulations as well as revealed the role of meteorological conditions in the accumulation, maintenance, and dissipation of heavy haze pollution. During the two heavy pollution processes from 10 to 24 November 2018, the meteorological fields were obtained using NCEP FNL and ERA5 reanalysis data, each used to drive the WRF model, to analyze the differences in the simulated PM_2.5 concentration. The results show that the meteorological field has a strong influence on the concentration levels and spatial distribution of the pollution simulations. The ERA5 group had relatively small simulation errors, and more accurate PM_2.5 simulation results could be obtained. The RMSE was 11.86 μg m⁻³ lower than that of the FNL group before assimilation, and 5.77 μg m⁻³ lower after joint assimilation. The authors used the PM_2.5 simulation results obtained by ERA5 data to discuss the role of the wind field and circulation situation on the pollution process, to analyze the correlation between wind speed, temperature, relative humidity, and boundary layer height and pollutant concentrations, and to further clarify the key formation mechanism of this pollution process.

摘要

气象条件对于污染物的累积, 清除, 传输和扩散有关键的作用. 本文将分别使用FNL 和ERA5再分析资料作为天气模式WRF的初始场, 基于构建的联合数据同化系统, 定量评估气象场对模拟PM_2.5浓度的作用, 同时揭示不同气象要素对于污染物积累, 维持和消散的影响. 研究表明ERA5资料在各个区域的污染模拟结果更接近观测值, 分析了风速, 温度, 相对湿度以及边界层高度与污染物浓度之间的相关性, 并进一步阐明污染过程的形成机制.