Investigating the behaviour of the CRI-MECH gas-phase chemistry scheme on a regional scale for different seasons using the WRF-Chem model

Investigating the behaviour of the CRI-MECH gas-phase chemistry scheme on a regional scale for different seasons using the WRF-Chem model
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使用 WRF-Chem 模型研究不同季节区域范围内 CRI-MECH 气相化学方案的行为

DOI:
10.1016/j.atmosres.2019.06.021
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发表时间:
2019
影响因子:
5.5
通讯作者:
Khan M
Khan M
中科院分区:
地球科学1区
文献类型:
--
作者:
Khan M

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使用中尺度非静力学3-D气象模式WRF-Chem对2015年西北欧每月第一周的CRI-MECH化学方案的行为进行了研究。将模式模拟的重要痕量气体物种(如臭氧,CO,NO,NO2和SO2)的分布与英国选定的农村和城市地区的地基测量进行了比较。使用英国Defra自动城市和农村网络(AURN)从英国各地测量的数据进行的模型验证显示,(农村地区R= 0.45,城市地区R = 0.34),NO_2(农村R= 0.65,城市R = 0.45)和NO(农村R= 0.35,城市R = 0.22)。然而,模型测量之间的相关性较差,被发现为CO(R= 0.15的城市网站)和SO2(R = 0.1的农村网站andR= 0.27的城市网站)。进一步的研究表明,模式的臭氧,CO,NO和NO2在夏季和秋季的表现较差,冬季相比。模型性能的差异是最明显的臭氧与其他物种有更多的网站和月份之间的差异。分析了模型与实测数据之间存在偏差的可能原因。
The behaviour of the CRI-MECH chemistry scheme was investigated over North-West Europe for the first week of each month for the year of 2015 using the mesoscale non-hydrostatic 3-D meteorological model, WRF-Chem. The model simulations of the distribution of important trace gas species (e.g. ozone, CO, NO, NO2and SO2) were compared with ground-based measurements of selected rural and urban areas in UK. The model validation using the UK Defra Automatic Urban and Rural Network (AURN) measured data from sites across the UK showed a reasonable agreement between model-measurement for ozone (R= 0.45 for rural sites andR= 0.34 for urban sites), for NO2(R= 0.65 for rural sites and R = 0.45 for urban sites) and for NO (R= 0.35 for rural sites andR= 0.22 for urban sites). However, a poor correlation between model-measurement is found for CO (R= 0.15 for urban sites) and for SO2(R = 0.1 for rural sites andR= 0.27 for urban sites). Further investigations showed a poorer performance of the model ozone, CO, NO and NO2during summer and autumn months compared with winter months. The differences in model performance were most noticeable for ozone with the other species having more variance between sites and months. The possible causes for the deviations between the modelled and the measured data are discussed.
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