首页|Effect of Meteorological Data Assimilation on Regional Air Quality Forecasts over the Korean Peninsula

Effect of Meteorological Data Assimilation on Regional Air Quality Forecasts over the Korean Peninsula

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The Weather Research and Forecasting model coupled with Chemistry(WRF-Chem),a type of online coupled chemistry-meteorology model(CCMM),considers the interaction between air quality and meteorology to improve air quality forecasting.Meteorological data assimilation(DA)can be used to reduce uncertainty in meteorological field,which is one factor causing prediction uncertainty in the CCMM.In this study,WRF-Chem and three-dimen-sional variational DA were used to examine the impact of meteorological DA on air quality and meteorological fore-casts over the Korean Peninsula.The nesting model domains were configured over East Asia(outer domain)and the Korean Peninsula(inner domain).Three experiments were conducted by using different DA domains to determine the optimal model domain for the meteorological DA.When the meteorological DA was performed in the outer do-main or both the outer and inner domains,the root-mean-square error(RMSE),bias of the predicted particulate mat-ter(PM)concentrations,and the RMSE of predicted meteorological variables against the observations were smaller than those in the experiment where the meteorological DA was performed only in the inner domain.This indicates that the improvement of the synoptic meteorological fields by DA in the outer domain enhanced the meteorological initial and boundary conditions for the inner domain,subsequently improving air quality and meteorological predic-tions.Compared to the experiment without meteorological DA,the RMSE and bias of the meteorological and PM variables were smaller in the experiments with DA.The effect of meteorological DA on the improvement of PM pre-dictions lasted for approximately 58-66 h,depending on the case.Therefore,the uncertainty reduction in the meteor-ological initial condition by the meteorological DA contributed to a reduction of the forecast errors of both meteoro-logy and air quality.

meteorological data assimilationregional air quality forecastparticulate matter concentrationoptimal model domainforecast errorWRF-Chem

Yunjae CHO、Hyun Mee KIM、Eun-Gyeong YANG、Yonghee LEE、Jae-Bum LEE、Soyoung HA

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Department of Atmospheric Sciences,Yonsei University,Seoul 03722,Republic of Korea

University of Maryland Baltimore County,Baltimore,MD 21250,USA

Global Modeling and Assimilation Office,NASA Goddard Space Flight Center,Greenbelt,MD 20771,USA

Air Quality Forecasting Center,National Institute of Environmental Research,Incheon 22689,Republic of Korea

National Center for Atmospheric Research,Boulder,CO 80305,USA

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National Research Foundation of KoreaSouth Korean government(Ministry of Science and ICT)Yonsei Signature Research Cluster Program of 2023National Institute of Environmental ResearchMinistry of Environment(MOE)of the Republic of Korea

2021R1A2C10125722023-22-0009NIER-2022-01-02-076

2024

10.1007/s13351-024-3152-8

气象学报(英文版)
中国气象学会

气象学报(英文版)

CSTPCD
影响因子：0.57
ISSN：0894-0525
年,卷(期)：2024.38(2)
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