Evaluating CALIPSO's 532 nm lidar ratio selection algorithm using AERONET sun photometers in Brazil

Since the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite first began probing the Earth's atmosphere on 13 June 2006, several research groups dedicated to investigating the atmosphere's optical properties have conducted measurement campaigns to validate the CALIPSO data products. Recently, in order to address the lack of CALIPSO validation studies in the Southern Hemisphere, and especially the South American continent, the Lasers Environmental Applications Research Group at Brazil's Nuclear and Energy Research Institute (IPEN) initiated efforts to assess CALIPSO's aerosol lidar ratio estimates using the AERONET sun photometers installed at five different locations in Brazil. In this study we develop a validation methodology to evaluate the accuracy of the modeled values of the lidar ratios used by the CALIPSO extinction algorithms. We recognize that the quality of any comparisons between satellite and ground-based measurements depends on the degree to which the instruments are collocated, and that even selecting the best spatial and temporal matches does not provide an unequivocal guarantee that both instruments are measuring the same air mass. The validation methodology presented in this study therefore applies backward and forward air mass trajectories in order to obtain the best possible match between the air masses sampled by the satellite and the ground-based instruments, and thus reduces the uncertainties associated with aerosol air mass variations. Quantitative comparisons of lidar ratios determined from the combination of AERONET optical depth measurements and CALIOP integrated attenuated backscatter measurements show good agreement with the model values assigned by the CALIOP algorithm. These comparisons yield a mean percentage difference of -1.5% +/- 24 %. This result confirms the accuracy in the lidar ratio estimates provided by the CALIOP algorithms over Brazil to within an uncertainty range of no more than 30 %.