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Using Lidar Surface Returns to Reduce Uncertainty in Aerosol Retrievals from Elastic Scatter Lidar

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Abstract

Lidar observations obtained from the LITE Mission, GLAS on board ICESat and CALIOP on board CALIPSO have clearly demonstrated the wealth of quantitative information about clouds and aerosols that may be retrieved from spaceborne lidar measurements. All three of these lidars are elastic scatter type lidars. As is well known, backscatter and extinction profiles cannot be unambiguously retrieved from simple elastic scatter lidar returns without an assumption linking extinction and backscatter (e.g., that the extinction-to-backscatter ratio, or lidar ratio is spatially constant through a solution layer) as well as requiring additional boundary value or parameter specification information (e.g., layer optical depth or specification of the lidar ratio). The initial retrieval approach that has been employed for the GLAS and CALIOP observations is to use climatological/geographical based look-up tables for assigning scatterer type and the associated lidar ratio value for 532 nm profile retrievals when alternate, less uncertain methods for either estimating the lidar ratio or providing the needed auxiliary optical depth information are unavailable. Use of depolarization measurement information, as available with the CALIOP lidar, plus assessing the 532 nm to 1064 nm attenuated backscatter signal ratio (color ratio) provides additional information for inferring the scatterer type and associated 532 nm lidar ratio, but this still does not take full advantage of the available dual-wavelength information, or provide a clear consistency check of the lidar ratio assumed in the retrieval. Spectral ratio constraints in the form of the Constrained Ratio Aerosol Model-fit (CRAM) retrieval approach [1,2], which applies aerosol modeling in order to limit the ambiguity inherent in aerosol retrievals from elastic scatter lidar measurements, may be used to further bound/reduce uncertainty in the retrievals and confirm self-consistency in the assumed lidar ratio selection. The CRAM approach has been successfully applied to both GLAS and CALIOP observations [3,4].

© 2010 Optical Society of America

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