Paper
3 April 2003 Raman lidar multiple scattering
Martin Wengenmayer, Andrew Y.S. Cheng, Peter Voulger, Ulrich G. Oppel
Author Affiliations +
Proceedings Volume 5059, 12th International Workshop on Lidar Multiple Scattering Experiments; (2003) https://doi.org/10.1117/12.512347
Event: 12th International Workshop on Lidar Multiple Scattering Experiments, 2002, Oberpfaffenhofen, Germany
Abstract
We introduce a stochastic corpuscular multiple scttering process including change of frequency to deal with Raman scattering. Based on this stochastic process, we may derive an exact multiple scattering lidar equation with polarization and change of frequency. We used the construction method of this stochastic process to design a variance reduction Monte Carlo code. This construction is based on transitional probabilities for collision, for directional scattering, and for change of frequency. Shortly we recall the necessary basics of Raman scattering and show how to obtain the transition probabilities for change of frequency. The directional scattering and change of polarization are determined by the Mueller matrices belonging to the scattering particles or molecules. We show the form of the Mueller matrices for elastic and inelastic molecular scattering. Roughly we outline our Monte Carlo code pbs3 and its variance reduction technqiues. Finally, we apply this code to check the influence of multiple scattering on the retrieval of the temperature profile.
© (2003) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Martin Wengenmayer, Andrew Y.S. Cheng, Peter Voulger, and Ulrich G. Oppel "Raman lidar multiple scattering", Proc. SPIE 5059, 12th International Workshop on Lidar Multiple Scattering Experiments, (3 April 2003); https://doi.org/10.1117/12.512347
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Raman scattering

Scattering

Multiple scattering

LIDAR

Monte Carlo methods

Raman spectroscopy

Stochastic processes

Back to Top