大气边界层的垂直分层可以阻碍或改变能量、动量、湿气和微量物质的垂直和水平传输,所以边界层高度对于大气的研究特别重要。探空数据在时间上不能连续给出全天的边界层高度变化,很多情况下边界层顶的气溶胶含量的梯度不明显,所以不能准确给出边界层高度。本文基于拉曼激光雷达的水汽混合比数据,采用斜率法和Douglas-Peucker(DP)算法相结合的方法反演边界层高度,并将其结果与探空数据进行比较,结果表明两者吻合得较好。

Vertical stratification of the atmospheric boundary layer can hinder or change the vertical and horizontal transmission of energy, momentum, moisture, and trace substances. Therefore, the boundary layer height is particularly important for atmospheric research. The continuous changes in boundary layer height throughout the day in time cannot be obtained based on the sounding data. Further, the aerosol content gradient at the top of the boundary layer is not obvious, so the boundary layer height cannot be accurately given. In this paper, based on the water vapor mixing ratio data of Raman lidar, the boundary layer height is inverted by the slope method and the Dougls-Peucker (DP) algorithm, and the results are compared with the sounding data. The results show that the two are in good agreement.