Abstract
The paper deals with Monte Carlo simulation of polarized radiative transfer and lidar returns in sensing of atmospheric clouds. The Stokes parameters were used to describe the transfer of polarized radiation, and computation of the lidar returns was based on flux-at-point estimators. We consider modifications of the numerical algorithm with scattering according to the phase function for unpolarized light and with scattering depending on polarization. Numerical experiments were performed for lidar sensing of waterdrop clouds.
Funding statement: The research was supported by the Russian Science Foundation (project No. 23–27–00345).
Acknowledgement
The authors are grateful to G. A. Mikhailov, B. F. Kargin, and S. A. Ukhinov for useful remarks.
References
[1] W. Ahmad, K. Zhang, Y. Tong, D. Xiao, L. Wu, and D. Liu, Water cloud detection with circular polarization lidar: A semianalytic Monte Carlo simulation approach. Sensors 22 (2022), No. 4, 1679.10.3390/s22041679Search in Google Scholar PubMed PubMed Central
[2] L. R. Bissonnette, P. Bruscaglioni, A. Ismaelli, G. Zaccanti, A. Cohen, Y. Benayahu, M. Kleiman, S. Egert, C. Flesia, P. Schwendimann, A. Starkov, M. Noormohammadian, U. G. Oppel, E. P. Zege, I. L. Katsev, and I. N. Polonsky, Lidar multiple scattering from clouds. Applied Physics B 60 (1995), 355–362.10.1007/BF01082271Search in Google Scholar
[3] M. Born and E. Wolf, Principles of Optics. Pergamon Press, New York, 1968.Search in Google Scholar
[4] P. Bruscaglioni, C. Flesia, A. Ismaelli, and P. Sansoni, Multiple scattering and lidar returns. Pure Appl. Opt.: J. European Opt. Soc. A 7 (1998), 1273–1287.10.1088/0963-9659/7/6/007Search in Google Scholar
[5] H. C. van de Hulst, Light Scattering by Small Particles. John Wiley & Sons, New York, 1957.10.1063/1.3060205Search in Google Scholar
[6] M. Hess, P. Koepke, and I. Schult, Optical properties of aerosols and clouds: the software package OPAC. Bull. Amer. Meteor. Soc. 79 (1998), 831–844.10.1175/1520-0477(1998)079<0831:OPOAAC>2.0.CO;2Search in Google Scholar
[7] J. W. Hovenier and C. V. M. van der Mee, Testing scattering matrices: a compendium of recipes. J. Quant. Spectrosc. Radiat. Transfer 55 (1996), No. 5, 649–661.10.1016/0022-4073(96)00008-8Search in Google Scholar
[8] Ya. A. Ilyushin, Transient polarized radiative transfer in cloud layers: numerical simulation of imaging lidar returns. J. Optical Soc. America, A 36 (2019), No. 4, 540–548.10.1364/JOSAA.36.000540Search in Google Scholar
[9] M. H. Kalos, On the estimation of flux at a point by Monte Carlo. Nuclear Science and Engineering 16 (1963), 111–117.10.13182/NSE63-A26481Search in Google Scholar
[10] G. W. Kattawar and G. N. Plass, Radiance and polarization of multiple scattered light from haze and clouds. Applied Optics 7 (1968), No. 8, 1519–1527.10.1364/AO.7.001519Search in Google Scholar
[11] K. E. Kunkel and J. A. Weinman, Monte Carlo analysis of multiply scattered lidar returns. J. Atmos. Sci. 33 (1976), 1772–1781.10.1175/1520-0469(1976)033<1772:MCAOMS>2.0.CO;2Search in Google Scholar
[12] G. I. Marchuk, G. A. Mikhailov, M. A. Nazaraliev, R. A. Darbinian, B. A. Kargin, and B. S. Elepov. Monte Carlo Methods in Atmosperic Optics. Springer-Verlag, Berlin–Heidelberg–New York, 1989.Search in Google Scholar
[13] G. A. Mikhailov, Some Problems of the Theory of Monte Carlo Methods, Nauka, Novosibirsk, 1974 (in Russian).Search in Google Scholar
[14] G. A. Mikhailov and V. F. Nazaraliev, Calculation of light polarization in spherical atmosphere by the Monte Carlo method, Physics of Atmosphere and Ocean 7 (1971), No. 4, 385–395.Search in Google Scholar
[15] G. A. Mikhailov, S. M. Prigarin, and S. A. Rozhenko, Comparative analysis of vector algorithms for statistical modelling of polarized radiative transfer process, Russ. J. Numer. Anal. Math. Modelling 33 (2018), No. 4, 253–263.10.1515/rnam-2018-0021Search in Google Scholar
[16] G. A. Mikhailov and A. V. Voitishek, Numerical Statistical Simulation. Monte Carlo Methods. Akademiya, Moscow, 2006 (in Russian).Search in Google Scholar
[17] U. G. Oppel and G. Czerwinski, Multiple scattering LIDAR equation including polarization and change of wavelength. Proc. SPIE 3571 (1998), 14–25.10.1117/12.347604Search in Google Scholar
[18] U. G. Oppel, M. Wengenmayer, and S. M. Prigarin, Monte Carlo simulations of polarized CCD lidar returns. J. Atmospheric and Oceanic Optics 20 (2007), No. 12, 1086–1091.Search in Google Scholar
[19] C. M. R. Platt, Remote sounding of high clouds. III: Monte Carlo calculations of multiple-scattered lidar returns. J. Atmos. Sci. 38 (1981), 156–167.10.1175/1520-0469(1981)038<0156:RSOHCI>2.0.CO;2Search in Google Scholar
[20] S. M. Prigarin, Monte Carlo simulation of the effects caused by multiple scattering of ground-based and spaceborne lidar pulses in clouds. Atmospheric and Oceanic Optics 30 (2017), No. 1, 79–83.10.1134/S1024856017010110Search in Google Scholar
[21] J. C. Ramella-Roman, S. A. Prahl, and S. L. Jacques. Three Monte Carlo programs of polarized light transport into scattering media: Part I. Optics Express 13 (2005), No. 12, 4420–4438.10.1364/OPEX.13.004420Search in Google Scholar
[22] G. H. Ruppersberg, M. Kerscher, M. Noormohammadian, U. G. Oppel, and W. Renger, The influence of multiple scattering on lidar returns by cirrus clouds and an effective inversion algorithm for the extinction coefficient. Contributions to Atmospheric Physics 70 (1997), 93–105.Search in Google Scholar
[23] I. V. Samokhvalov, Double scattering approximation of lidar equation for inhomogeneous atmosphere. Opt. Lett. (1979), No. 5, 12–14.10.1364/OL.4.000012Search in Google Scholar
[24] D. M. Winker and L. R. Poole, Monte-Carlo calculations of cloud returns for ground-based and spacebased LIDARS. Appl. Phys. B: Lasers Opt. 60 (1995), 341–344.10.1007/BF01082269Search in Google Scholar
[25] W. Wiscombe, Improved Mie scattering algorithms. Applied Optics 19 (1980), No. 9, 1505–1509.10.1364/AO.19.001505Search in Google Scholar
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Articles in the same Issue
- Frontmatter
- Simulation algorithms for stationary sequences with distributions in the form of a mixture of Gaussian distributions
- Monte Carlo simulation of polarized lidar returns for atmospheric clouds sensing
- Stochastic simulation of exciton transport in semiconductor heterostructures
- Semi-Lagrangian approximations of the transfer operator in divergent form
- Numerical modelling of large elasto-plastic multi-material deformations on Eulerian grids
Articles in the same Issue
- Frontmatter
- Simulation algorithms for stationary sequences with distributions in the form of a mixture of Gaussian distributions
- Monte Carlo simulation of polarized lidar returns for atmospheric clouds sensing
- Stochastic simulation of exciton transport in semiconductor heterostructures
- Semi-Lagrangian approximations of the transfer operator in divergent form
- Numerical modelling of large elasto-plastic multi-material deformations on Eulerian grids