摘要
利用四川盆地2016-2018年的探空资料,估算了3个代表地区(成都、宜宾、达州)最大混合层高度(MMH),运用ERA-interim再分析资料的边界层高度(ERA-PBLH)验证MMH计算结果的可靠性,分析了MMH的概率分布、季节变化特征,并结合同期PM_(2.5)日均浓度资料及地面气象观测资料,探讨了MMH和其他气象因子与PM_(2.5)日均浓度之间的关系。结果表明,四川盆地MMH整体偏低。在季节分布上,成都和宜宾MMH春季的最高,秋季的最低,达州夏季的最高,冬季的最低,这种地区性差异的主要原因来自感热通量及水汽条件的季节变化。总体上PM_(2.5)日均浓度随MMH的升高而逐渐减小。重污染天气多发生在MMH较低、相对湿度较大的情况下,较低的抬升凝结高度限制了混合层的增高,并且气溶胶吸湿增长作用明显,污染物容易聚集。盆地PM_(2.5)浓度的高值主要集中在风速为1.0 m/s左右,盆地内空气流入对当地污染物浓度有明显的增长作用。
The maximum mixed height(MMH)of three representative stations(Chengdu,Yibin,and Dazhou)in Sichuan Basin is estimated using the sounding data from 2016 to 2018.ERA-interim reanalysis data of boundary layer height(ERA-PBLH)is used to evaluate the reliability of MMH.The probability distribution,seasonal variation characteristics of MMH analyzed.Based on the PM_(2.5) average concentration data and surface meteorological observation data,the relationship between MMH,as well as other meteorological factors and PM_(2.5) daily average concentration is analyzed.The results show that the MMH in Sichuan Basin is generally low.In seasonal distribution,the MMH is the highest in spring and lowest in autumn in Chengdu and Yibin,while highest in summer and lowest in winter in Dazhou.The main reasons for this regional difference are the seasonal variations of sensible heat fluxes and water vapor conditions.On the whole,the average PM_(2.5) concentration decreases gradually with the increase of MMH.Heavy polluted weather mostly occurs under the condition of lower MMH and larger relative humidity.The lower lifting condensation level limits the increase of mixing layer height.The aerosol hygroscopic growth is obvious,and the pollutants are easy to accumulate.The high PM_(2.5) concentration in basin usually occurs in the wind speed of about 1.0 m/s,and the air inflow in the basin has an obvious increasing effect on the local pollutant concentration.
作者
刘炜桦
王寅钧
赵晓莉
王敏
罗磊
Liu Weihua;Wang Yinjun;Zhao Xiaoli;Wang Min;Luo Lei(Sichuan Meteorological Disasters Prevention Technology Center(Sichuan Ecological Meteorology and Satellite Remote Sensing Center),Chengdu 610072,China;State Key Laboratory of Severe Weather,Chinese Academy of Meteorological Sciences,Beijing 100081,China;Tianjin Meteorological Information Center,Tianjin 300074,China)
出处
《气象与环境科学》
2024年第2期62-69,共8页
Meteorological and Environmental Sciences
基金
中国气象局预报员专项项目(CMAYBY2019-100)
中国气象科学研究院基本科研业务费项目(2018Y008)
高分辨率数值预报产品在温江大气污染中的应用研究(ERC-21-001)。
