Abstract:Based on a 3-DVAR assimilation method of aerosol, this paper developed aerosol assimilation module applied to air quality model in Tianjin, analyzed the influence of observation area on PM2.5 forecasts through data assimilation and prediction experiments during two heavy pollution episodes in Tianjin, and then analyzed the impact of aerosol data assimilation on PM2.5 forecast in Tianjin by conducting experiments with data assimilation over a month, in order to provide support for improving the capability of air quality forecast in Tianjin. The results showed that the attenuation scale of horizontal correlation for background errors was about 50km, and the correlation coefficient between the lowest level of model and the height of 400m decreased to about 0.6. The observation area had a significant impact on the assimilation results. During heavy pollution episodes, the improvement of PM2.5 forecast continued about 12 hours when only observations in Tianjin were used for data assimilation, while the improvement continued above 24 hours when all observations within the model domain were used. 3-DVAR assimilation of surface PM2.5 observations significantly improved PM2.5 numerical forecast over Tianjin. The correlation coefficient between observation and forecast increased from 0.74 to 0.87, the root mean square error decreased from 32.3μg/m3 to 22.4μg/m3, and the mean relative error decreased from 39.9% to 27.1%. The improvement was the most significant at the initial time, and decreased with forecast time increasing. PM2.5 concentration forecasts within 24 hours were improved obviously which were much better within 14hours.
杨旭, 唐颖潇, 蔡子颖, 韩素芹, 董琪如, 杨健博, 朱玉强, 樊文雁. 基于气溶胶三维变分同化天津PM2.5数值预报研究[J]. 中国环境科学, 2021, 41(12): 5476-5484.
YANG Xu, TANG Ying-xiao, CAI Zi-ying, HAN Su-qin, DONG Qi-ru, YANG Jian-bo, ZHU Yu-qiang, FAN Wen-yan. Impact of aerosol data assimilation with 3-DVAR method on PM2.5 forecast over Tianjin. CHINA ENVIRONMENTAL SCIENCECE, 2021, 41(12): 5476-5484.
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