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Raman-Mie Lidar measurements of low and optically thin cloud

机译:低和光学薄云的拉曼-米德激光雷达测量

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摘要

In this paper, we implement and compare two complementary methods for the measurement of low cloud optical depth with a Raman-Mie lidar over the metropolitan area of New York City. The first approach, based on the method of S. Young, determines the cloud optical depth by regressing the elastic signal against a molecular reference signal above and below the cloud. Due to high aerosol loading below and above the low cloud, correction for aerosol influence was necessary and achieved with the combined Raman-elastic returns. The second approach uses N_2-Raman signal to derive cloud extinction profiles and then integrate them to determine optical depth. We find excellent agreements between these two retrievals for cloud optical depths as large as 1.5. Extinction-to-backscatter ratio within the low cloud is obtained and is shown to be consistent to values calculated from liquid water cloud model. The varied lidar ratios at cloud edge may imply the changes of cloud droplet size providing clues to the CCN seeding process. Furthermore, multiple-scattering effects on retrieving cloud optical depths are estimated by using an empirical model and specific lidar parameters.
机译:在本文中,我们实现并比较了两种互补方法,分别使用纽约市大都会区的拉曼-米氏激光雷达测量低云光学深度。第一种方法基于S.Young的方法,通过将弹性信号与云层之上和之下的分子参考信号进行回归来确定云层的光学深度。由于在低云以下和以上的气溶胶负荷较高,因此有必要对气溶胶影响进行校正,并结合拉曼弹性回弹来实现。第二种方法使用N_2-拉曼信号得出云的消光轮廓,然后对其进行积分以确定光学深度。我们发现这两次取回之间对于高达1.5的云光学深度有着极好的协议。获得了低云内的消光与背向散射比,并显示出与从液态水云模型计算出的值一致。云边缘的激光雷达比率的变化可能意味着云滴大小的变化,为CCN播种过程提供了线索。此外,通过使用经验模型和特定的激光雷达参数,估计了对获取云光学深度的多重散射效应。

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