Articles | Volume 6, issue 11
https://doi.org/10.5194/amt-6-3197-2013
https://doi.org/10.5194/amt-6-3197-2013
Research article
 | 
26 Nov 2013
Research article |  | 26 Nov 2013

Towards an automatic lidar cirrus cloud retrieval for climate studies

E. G. Larroza, W. M. Nakaema, R. Bourayou, C. Hoareau, E. Landulfo, and P. Keckhut

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Cited articles

Ackermann, J.: The extinction-to-backscatter ratio of tropospheric aerosol: a numerical study, J. Atmos. Ocean. Technol., 15, 1043–1050, https://doi.org/10.1175/1520-0426, 1998.
Ansmann, A.: Molecular-Backscatter Lidar Profiling of the Volume-Scattering Coefficient in Cirrus, edited by: Lynch, D. K., Sassen, K., Starr, D.O\textasciiacute C and Stephens, G.: Cirrus, Oxford University Press, London, 197–210, 2002.
Ansmann, A., Riebesell, M., Wandinger, U., Weitkamp, C., Voss, E., Lahmann W., and Michaelis, W.: Combined Raman elastic-backscatter LIDAR for vertical profiling of moisture, aerosol extinction, backscatter, and LIDAR ratio, Appl. Phys., B55, 18–28, https://doi.org/10.1007/BF00348608, 1992.
Barnaba, F. and Gobbi, G. P.: Modeling the aerosol extinction versus backscatter relationship for lidar applications: maritime and continental conditions, J Atmos. Ocean. Technol., 21, 428–442, https://doi.org/10.1175/1520-0426(2004)021<0428:MTAEVB>2.0.CO;2, 2004.
Bissonnette, L. C., Roy, G., and Roy, N.: Multiple-scattering-based lidar retrieval: method and results of cloud probings, Appl. Opt., 44, 5565–5581, https://doi.org/10.1364/AO.44.005565, 2005.
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