19 October 2016 Climate sensitivity characteristics of tropical cirrus clouds using lidar measurements
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Abstract
Cirrus clouds play an important role in the Earth’s radiation budget due to their high frequency of occurrence, nonspherical ice crystal formations, and variability in scattering/absorption characteristics. Mostly, tropical cirrus clouds are considered greenhouse modulators. Thus, the parameterization of tropical cirrus clouds in terms of their microphysical properties and the corresponding radiative effects are highly important for climate studies. For characterizing the radiative properties of cirrus clouds, which depend on the size, shape, and number of ice crystals, knowledge of the extinction coefficient (σ) and optical depth (τ) is necessary. σ provides information needed for understanding the influence of the scatterers on the radiative budget, whereas τ gives an indication of the composition and thickness of the cloud. Extensive research on tropical cirrus clouds has been carried out by using ground-based lidar (GBL) and satellite-based lidar systems. The characteristics of tropical cirrus clouds derived by using the data from the GBL system over the tropical site Gadanki (13.5° N, 79.2° E), India, during 2010 are presented. Some of the results are compared with those obtained by us from satellite-based cloud–aerosol lidar with orthogonal polarization observations of the cloud–aerosol lidar and infrared pathfinder satellite observation mission. It is observed that there is a strong dependence on some of the physical properties, such as occurrence height, cloud temperature, and geometrical thickness, and on the microphysical parameters in terms of extinction coefficient and optical depth. The correlation of both σ and τ with temperature is also observed.
© 2016 Society of Photo-Optical Instrumentation Engineers (SPIE)
Gopinathan Nair S. Motty, Malladi Satyanarayana, Glory Selvan Jayeshlal, Vellara P. M. Pillai, "Climate sensitivity characteristics of tropical cirrus clouds using lidar measurements," Journal of Applied Remote Sensing 10(4), 046005 (19 October 2016). https://doi.org/10.1117/1.JRS.10.046005 . Submission:
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