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崔雅琴, 张佃国, 王洪, 刘泉, 张骞, 张洪生. 2015年济南地区雾霾天气过程大气物理量特征初步分析[J]. 大气科学, 2019, 43(4): 705-718. DOI: 10.3878/j.issn.1006-9895.1808.17175
引用本文: 崔雅琴, 张佃国, 王洪, 刘泉, 张骞, 张洪生. 2015年济南地区雾霾天气过程大气物理量特征初步分析[J]. 大气科学, 2019, 43(4): 705-718. DOI: 10.3878/j.issn.1006-9895.1808.17175
CUI Yaqin, ZHANG Dianguo, WANG Hong, LIU Quan, ZHANG Qian, and ZHANG Hongsheng. Preliminary Analysis of Atmospheric Physical Quantity Characteristics during Haze Weather in Jinan Area in 2015[J]. Chinese Journal of Atmospheric Sciences, 2019, 43(4): 705-718. DOI: 10.3878/j.issn.1006-9895.1808.17175
Citation: CUI Yaqin, ZHANG Dianguo, WANG Hong, LIU Quan, ZHANG Qian, and ZHANG Hongsheng. Preliminary Analysis of Atmospheric Physical Quantity Characteristics during Haze Weather in Jinan Area in 2015[J]. Chinese Journal of Atmospheric Sciences, 2019, 43(4): 705-718. DOI: 10.3878/j.issn.1006-9895.1808.17175

2015年济南地区雾霾天气过程大气物理量特征初步分析

Preliminary Analysis of Atmospheric Physical Quantity Characteristics during Haze Weather in Jinan Area in 2015

  • 摘要: 文中对比分析了2015年29个雾、霾及雾霾混合天气过程中,章丘探空站L波段探空雷达和山东省气象局院内德国14通道地基微波辐射计观测的温度资料。对观测数据实施了质量控制,检验了精度和可信度,统计分析了宏观物理参量特征和日变化规律。针对雾、霾及雾霾天气过程各选取了一个个例进行分析,分析了大气中PM2.5、PM10、SO2、NO2、O3、CO含量的变化情况,分析了相对湿度、液态水路径和综合水汽含量等的变化情况。结果表明:两种观测数据一致性较好,拟合优度高于0.97;贴地逆温层存在一定的季节变化,悬垂逆温层存在一定的差异,逆温层的变化、污染参量变化与雾霾的形成有密切关系;不同天气背景对大气物理参量有较大的影响,PM10、AQI(空气质量指数)和CO均在相同时间段出现峰值,有明显的起伏;CO峰值雾霾天气中尤为明显,由早到晚随时间峰值逐渐增大,雾天和霾天峰值较小,雾霾天气明显大于雾天或霾天。

     

    Abstract: This study analyzed the temperature data in the course of 29 mixed fog, haze weather in 2015 from L-band sounding radar at the Zhangqiu sounding station and temperature data from the German 14-channel RPG-HATPRO-G3 microwave radiometer located at the Shandong Meteorological Bureau. The quality analysis of these observation data was performed to determine their accuracy and reliability. In particularly, the macro physical characteristics and diurnal variation of the physical parameters in haze weather were analyzed. The changes of PM2.5, PM10, SO2, NO2, O3, CO in the atmosphere were analyzed for each case of fog, haze, and haze .The changes of relative humidity, liquid water path, and water vapor content were analyzed. The results indicate that data from the two observation instruments have good consistency, with a goodness of fit higher than 0.97 under fog and haze conditions. There are seasonal variations in the surface inversion layer and some differences in the physical parameters of the overhanging inversion layer. The changes in the temperature inversion layer and pollution parameters are closely related to the formation of fog and haze. Different weather backgrounds are determined to have considerable influence on the physical atmospheric parameters, with obvious fluctuations in the PM10, AQI (air quality index), and CO values, which peak during the same time period. The CO peak in fog and haze weather is particularly obvious, CO peak with a gradual increase from the morning to night. The CO peak of the fog and haze days is smaller, and fog and haze weathers are obviously larger than the fog or haze.

     

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