摘要
利用卫星观测的气溶胶光学厚度资料和模式模拟数据,与地面颗粒物观测资料结合,探讨近地面颗粒物质量浓度的估算方法。具体包括:利用区域气侯模式RAMS(Regional Atmospheric Modeling System)模拟的边界层高度对气溶胶光学厚度进行垂直订正,获得近地面颗粒物消光系数;利用模式模拟的相对湿度和颗粒物吸湿增长经验模型对消光系数进行湿度订正,获得近地面颗粒物干消光系数;并基于干消光系数与颗粒物质量浓度地面站点资料建立的统计关系估算获得每个像元的颗粒物质量浓度。利用地面站点观测的颗粒物浓度资料验证表明,基于卫星资料可以获得近地面颗粒物质量浓度,而且细颗粒物质量浓度具有更好的估算精度。
This paper studied the statistic method of particulate matter concentration derived from the combination of the monthly average data of satellite-observed aerosol optical thickness, the predicted data of regional atmospheric model and ground measurement data. Firstly, the simulated Planetary Boundary Layer height was used to correct the monthly average Aerosol Optical Thickness resulting from MODIS data in 2006 in order to get the atmospheric extinction coefficient, which then was further converted to dry extinction coefficient by relative humidity data from RAMS and hygroscopic growth factor. Secondly, the particulate matter PM10 and PM2.5 statistic models were derived by combining the dry extinction coefficients with the ground station measurements in PRD. Finally, the models were validated by using monthly average MODIS AOT data and in situ measurement data from 16 ground stations in 2008 in PRD. The results showed that the predicted particulate matter concentration was consistent with the in situ measurements. It is concluded that the statistic method based on satellite observations combining with ground station measurements can be used to predict particulate matter mass in PRD.
出处
《热带地理》
2015年第1期7-12,共6页
Tropical Geography
基金
广州市科技计划项目(2013J100002)
