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

作     者：LI Xiaobin LIU Hongbo ZHANG Ziyin LIU Juanjuan 

作者机构：State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid DynamicsInstitute of Atmospheric PhysicsChinese Academy of SciencesBeijingChina College of Earth and Planetary SciencesUniversity of Chinese Academy of SciencesBeijingChina Institute of Urban MeteorologyChina Meteorological AdministrationBeijingChina 

基　　金：supported by the National Basic Research(973)Program of China [grant number2015CB954102] the National Natural Science Foundation of China [grant number 41475043] the National Key R&D Program of China [grant number 2018YFC1507403] 

出 版 物：《Atmospheric and Oceanic Science Letters》 (大气和海洋科学快报（英文版）)

年 卷 期：2019年第12卷第6期

页      码：434-443页

摘      要：The North China Plain often su ers heavy haze pollution events in the cold season due to the rapid industrial development and urbanization in recent *** 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≤2.5μm)concentration of 727μg m *** the in uence of meteorological conditions on pollu-tant evolution,the e ects 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 difierent initial conditions and LBCs derived from ERA5 reanalysis data and its 10 ensemble *** 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 ***,the ensemble forecasting showed a considerable advantage to some *** 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 *** on this case,the ensemble scheme seems an e ective method to improve the prediction skill of wind direction and PM2.5 concentration by using the WRF-Chem model.

主 题 词：Haze pollution PM 2.5 WRF Chem initial and lateral boundary conditions ensemble forecasting 

学科分类：07[理学] 070602[070602] 0706[理学-大气科学类] 

核心收录：

D　O　I：10.1080/16742834.2019.1671136

馆 藏 号：203858562...