Numerical simulation of an extreme haze pollution event over the North China Plain based on initial and boundary condition ensembles

Autor: Xiaobin LI, Hongbo LIU, Ziyin ZHANG, Juanjuan LIU
Jazyk: angličtina
Rok vydání: 2019
Předmět:
Zdroj: Atmospheric and Oceanic Science Letters, Vol 12, Iss 6, Pp 434-443 (2019)
Druh dokumentu: article
ISSN: 1674-2834
2376-6123
16742834
DOI: 10.1080/16742834.2019.1671136
Popis: The North China Plain often suffers heavy haze pollution events in the cold season due to the rapid industrial development and urbanization in recent decades. In the winter of 2015, the megacity cluster of Beijing–Tianjin–Hebei experienced a seven-day extreme haze pollution episode with peak PM2.5 (particulate matter (PM) with an aerodynamic diameter ≤ 2.5 μm) concentration of 727 μg m−3. Considering the influence of meteorological conditions on pollutant evolution, the effects of varying initial conditions and lateral boundary conditions (LBCs) of the WRF-Chem model on PM2.5 concentration variation were investigated through ensemble methods. A control run (CTRL) and three groups of ensemble experiments (INDE, BDDE, INBDDE) were carried out based on different initial conditions and LBCs derived from ERA5 reanalysis data and its 10 ensemble members. The CTRL run reproduced the meteorological conditions and the overall life cycle of the haze event reasonably well, but failed to capture the intense oscillation of the instantaneous PM2.5 concentration. However, the ensemble forecasting showed a considerable advantage to some extent. Compared with the CTRL run, the root-mean-square error (RMSE) of PM2.5 concentration decreased by 4.33%, 6.91%, and 8.44% in INDE, BDDE and INBDDE, respectively, and the RMSE decreases of wind direction (−5.19%, −8.89% and −9.61%) were the dominant reason for the improvement of PM2.5 concentration in the three ensemble experiments. Based on this case, the ensemble scheme seems an effective method to improve the prediction skill of wind direction and PM2.5 concentration by using the WRF-Chem model.
Databáze: Directory of Open Access Journals
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