Improvement of the Real-time PM2.5 Forecast over the Beijing-Tianjin-Hebei Region using an Optimal Interpolation Data Assimilation Method | |
Zheng, Haitao1,2,3; Liu, Jianguo1; Tang, Xiao3; Wang, Zifa3; Wu, Huangjian3; Yan, Pingzhong3; Wang, Wei4 | |
刊名 | AEROSOL AND AIR QUALITY RESEARCH |
2018-05-01 | |
卷号 | 18期号:5页码:1305-1316 |
关键词 | Real-time PM2.5 forecast Data assimilation Optimal interpolation Beijing-Tianjin-Hebei Region |
ISSN号 | 1680-8584 |
DOI | 10.4209/aaqr.2017.11.0522 |
英文摘要 | A routine air quality data assimilation (DA) system was established at the China National Environmental Monitoring Center (CNEMC) based on the optimal interpolation (OI) method. The surface observations from more than 1,400 stations across China were assimilated into a real-time air quality forecast system with three nested domains The initial conditions of NO2, SO2 and PM2.5 in the three domains were optimized by the data assimilation system. The impact of the data assimilation on the real-time PM2.5 forecast over the Beijing-Tianjin-Hebei (BTH) Region during the heavy haze season of 2015 was evaluated. The results show that the DA can significantly improve real-time PM2.5 forecasts, reducing the root mean square error (RMSE) by 23%, 8.2% and 4.8% in the forecasts of the first, second and third day, respectively. The mean fractional bias and the mean fractional error of the forecast were reduced from 50.9% and 70.67% to 40% and 62.3%, respectively, and the performance changed from "criteria" to approaching "goal" (as defined by Boylan and Russell, 2006). Additionally, increasing the assimilation frequency can improve the DA system performance for real-time forecasts. As can be seen from the various cases studied here, the improvement in data assimilation is more significant when the bias of the model is higher and there is still much room for correction. The results also show a rapid decay of the DA effects on the PM2.5 forecast, which highlights the limitations of the current routine data assimilation system in which only initial conditions are optimized Further improvements in the data assimilation system with meteorological data assimilation and chemical parameter optimization are needed. |
资助项目 | National Natural Science Foundation[41575128] ; National Natural Science Foundation[91544218] ; National Natural Science Foundation[91644216] |
WOS关键词 | ENSEMBLE KALMAN FILTER ; AEROSOL DATA ASSIMILATION ; AIR-QUALITY ; HETEROGENEOUS CHEMISTRY ; PARTICULATE POLLUTION ; INITIAL CONDITIONS ; HAZE EPISODE ; MODEL ; EMISSIONS ; CHINA |
WOS研究方向 | Environmental Sciences & Ecology |
语种 | 英语 |
出版者 | TAIWAN ASSOC AEROSOL RES-TAAR |
WOS记录号 | WOS:000434011000017 |
内容类型 | 期刊论文 |
源URL | [http://ir.hfcas.ac.cn:8080/handle/334002/36611] |
专题 | 合肥物质科学研究院_中科院安徽光学精密机械研究所 |
通讯作者 | Liu, Jianguo; Wang, Zifa |
作者单位 | 1.Chinese Acad Sci, Key Lab Environm Opt & Technol, Anhui Inst Opt & Fine Mech, Hefei 230031, Anhui, Peoples R China 2.Univ Sci & Technol China, Hefei 230026, Anhui, Peoples R China 3.Chinese Acad Sci, State Key Lab Atmospher Boundary Layer Phys & A, Inst Atmospher Phys, Beijing 100029, Peoples R China 4.China Natl Environm Monitoring Ctr, Beijing 100012, Peoples R China |
推荐引用方式 GB/T 7714 | Zheng, Haitao,Liu, Jianguo,Tang, Xiao,et al. Improvement of the Real-time PM2.5 Forecast over the Beijing-Tianjin-Hebei Region using an Optimal Interpolation Data Assimilation Method[J]. AEROSOL AND AIR QUALITY RESEARCH,2018,18(5):1305-1316. |
APA | Zheng, Haitao.,Liu, Jianguo.,Tang, Xiao.,Wang, Zifa.,Wu, Huangjian.,...&Wang, Wei.(2018).Improvement of the Real-time PM2.5 Forecast over the Beijing-Tianjin-Hebei Region using an Optimal Interpolation Data Assimilation Method.AEROSOL AND AIR QUALITY RESEARCH,18(5),1305-1316. |
MLA | Zheng, Haitao,et al."Improvement of the Real-time PM2.5 Forecast over the Beijing-Tianjin-Hebei Region using an Optimal Interpolation Data Assimilation Method".AEROSOL AND AIR QUALITY RESEARCH 18.5(2018):1305-1316. |
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