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Influence of dense surface meteorological data assimilation on the prediction accuracy of ozone pollution in the southeastern coastal area of the Korean Peninsula

机译:密集表面气象资料同化对朝鲜半岛东南沿海地区臭氧污染预测准确性的影响

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摘要

In order to clarify the influence of surface meteorological data assimilation with various resolutions on the photochemical ozone concentration in the southeastern Korean Peninsula, several numerical experiments were conducted. The meteorological and photochemical reaction models used in this study are the fifth-generation mesoscale model (MM5) and the three-dimensional photochemical urban airshed model (UAM-V), respectively. Dense meteorological data make it easier to obtain accurate estimates and surface characteristics than coarse-resolution data. As a result, the estimated temperature obtained from high resolution surface data assimilation in the Busan and Ulsan metropolitan areas is higher than that obtained from coarse resolution surface data assimilation. These high temperatures resulted in strong winds from the sea and a significant dispersion of ozone. In analyses involving an index of agreement (IOA) and root mean square deviation (RMSD), the temperature and wind speed estimated with dense surface data assimilation agreed well with those obtained from observations. However, the influence of dense surface data assimilation tends to be stronger in the flat Ulsan metropolitan area than in the mountainous Busan metropolitan area. This is caused by the heterogeneity of the surface characteristics, including the topography. If the surface parameters induced by regional circulation, such as the topography and land use, are complex and heterogeneous, the efficiency of observational data on data assimilation has to be verified before air pollution is assessed.
机译:为了阐明不同分辨率的地面气象数据同化对朝鲜半岛东南部光化学臭氧浓度的影响,进行了一些数值实验。本研究中使用的气象和光化学反应模型分别是第五代中尺度模型(MM5)和三维光化学城市空域模型(UAM-V)。密集的气象数据比粗分辨率的数据更容易获得准确的估计和地表特征。结果,从釜山和蔚山市区的高分辨率表面数据同化获得的估计温度高于从粗糙分辨率表面数据同化获得的估计温度。这些高温导致来自大海的强风和臭氧的大量散布。在涉及一致性指数(IOA)和均方根偏差(RMSD)的分析中,通过密集表面数据同化估算的温度和风速与从观测获得的温度和风速非常吻合。但是,平坦的蔚山都市区的密集地表数据同化的影响往往比釜山山区的都市区更强。这是由于表面特征(包括地形)的异质性引起的。如果由区域环流引起的地表参数(例如地形和土地使用情况)复杂且异质,则在评估空气污染之前,必须验证观测数据同化数据的效率。

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