Towards an automatic lidar cirrus cloud retrieval for climate studies

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Abstract

<p><strong>Abstract.</strong> This paper presents a methodology to calculate lidar ratios for distinct cirrus clouds that has been developed and implemented for a site located in the Southern Hemisphere. The cirrus cloud lidar data processing aims to consider a large cloud variability and cirrus cloud monitoring through a robust retrieval process. Among cirrus features estimates for complex scenes that lidar systems can provide, we highlight cloud geometrical information and extinction-to-backscatter ratio (known as lidar ratio or LR). In general, direct information on cirrus cloud microphysics is difficult to derive because LR depends on the presence of ice crystals and their properties such as shape, size, composition and orientation of particles. An iterative process to derive a stable LR value has been proposed. One of the keys is to restrict the analysis to conditions allowing accurate multilayer events. This method uses nonparametric statistical approaches to identify stationary periods according to cloud features and variability. Measurements performed in the region of the metropolitan city of São Paulo (MSP) have been used to implement and test the methodology developed for cirrus cloud characterization. Good results are represented by examining specific cases with multilayer cirrus cloud occurrence. In addition to the geometrical parameters obtained, cirrus LR values were calculated for a single day ranging from 19 ± 01 sr to 74 ± 13 sr for 2 observed layers. This large difference in LR can indicate a mixture of ice crystal particles with different sizes and shapes in both layers of the cirrus clouds. Trajectory analyses indicate that both of these cloud layers can be associated with different air mass and should be considered as 2 distinct clouds in climatology.</p>

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APA

Larroza, E. G., Nakaema, W. M., Bourayou, R., Hoareau, C., Landulfo, E., & Keckhut, P. (2013). Towards an automatic lidar cirrus cloud retrieval for climate studies. Atmospheric Measurement Techniques, 6(11), 3197–3210. https://doi.org/10.5194/amt-6-3197-2013

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