doi:  10.3878/j.issn.1006-9895.1804.17267
基于京津冀高密度地面观测网络的大气污染地面观测代表性误差估计

Estimating the representative error of surface observations based on a high-density observation network over Beijing-Tianjin-Hebei areas
摘要点击 683  全文点击 65  投稿时间:2017-11-06  修订日期:2018-03-21
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基金:  国家自然科学基金41575128&91644216;国家重点研发计划2016YFC0201802
中文关键词:  地面观测、代表性误差、资料同化、大气污染物
英文关键词:  surface observation  representative error  data assimilation  air pollutants
                          
作者中文名作者英文名单位
李飞Li Fei1. 中国科学院大气物理研究所大气边界层物理与大气化学国家重点实验室
唐晓Tang Xiao1. 中国科学院大气物理研究所大气边界层物理与大气化学国家重点实验室
王自发Wang Zifa
朱莉莉Zhu Lili
王晓彦Wang Xiaoyan
吴煌坚WU Huangjian
卢苗苗LU Miaomiao
李健军LI Jianjun
朱江Zhu Jiang
引用:李飞,唐晓,王自发,朱莉莉,王晓彦,吴煌坚,卢苗苗,李健军,朱江.2018.基于京津冀高密度地面观测网络的大气污染地面观测代表性误差估计[J].大气科学
Citation:Li Fei,Tang Xiao,Wang Zifa,Zhu Lili,Wang Xiaoyan,WU Huangjian,LU Miaomiao,LI Jianjun,Zhu Jiang.2018.Estimating the representative error of surface observations based on a high-density observation network over Beijing-Tianjin-Hebei areas[J].Chinese Journal of Atmospheric Sciences (in Chinese)
中文摘要:
      地面观测提供空间点的浓度信息,三维化学模式提供网格面的浓度信息,两者在进行对比验证或同化融合时会因为空间尺度不匹配引入误差,即观测代表性误差。本研究将大气污染地面国控监测站与区县监测站结合起来,获得了京津冀地区高密度地面观测数据,利用该数据首次对京津冀地区6项常规大气污染物(PM2.5、PM10、SO2、NO2、CO和O3)的地面观测代表性误差进行了客观估计,并与Elbern et al.(2007)方法估计的代表性误差进行了对比。结果发现:两种方法对京津冀地区NO2地面观测代表性误差估计非常接近,但Elbern et al. (2007)方法显著低估了SO2、CO和O3地面观测的代表性误差。在此基础上,我们对Elbern et al. (2007)方法及其误差特征参数进行了本地化修正,并增加了PM2.5和PM10的代表性误差特征参数,建立了京津冀大气污染地面观测代表性误差的客观估计方法。
Abstract:
      Ground station provides the raw monitored point data of air pollutant concentration, and three-dimensional chemical model can simulate the concentrations on grid. While as the former is used to verify or assimilate the later, representative errors would occur due to the mismatch between the spatial scale of discrete monitored point data and the grid simulation. This study employed a high-resolution observation network for Beijing-Tianjin-Hebei area by combining the information obtained from China National Monitoring Center and local Monitoring Center. The combined datasets were used to estimate the representative error of concentration data of 6 typical air pollutants (PM2.5, PM10, SO2, NO2, CO and O3) from ground observation in Beijing-Tianjin-Hebei area. When the results from the aforementioned system is compared with those applying the theory of Elbern et al. (2007), it shows that the two theories are consistent in terms of computing the representative errors of ground observation on NO2, however, the results for SO2, CO and O3 is significantly underestimated in Elbern’s approach. Therefore, this study modifies the characteristic parameters of Elbern’s method on the four air pollutants and introduces new characteristic parameters on PM2.5 and PM10, making the method applied more accurately processing the data of ground observation over Beijing-Tianjin-Hebei area.
主办单位:中国科学院大气物理研究所 单位地址:北京市9804信箱
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