Investigating the Impact of Cloud and Aerosol Contamination in Satellite Products used for Climate Forcing Studies

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Wednesday, 5 February 2014
Hall C3 (The Georgia World Congress Center )
Jianglong Zhang, Univ. of North Dakota, Grand Forks, ND; and J. S. Reid, J. R. Campbell, E. J. Hyer, Y. Shi, and R. Alfaro-Contreras

Cloud and aerosol physical parameters derived from satellite-based measurements are widely used for studying direct and indirect climate forcing. Yet isolating their signals from passive satellite radiances is a difficult task that can easily generate retrieval biases if not properly screened and interpreted. Such uncertainties propagate through solutions for direct and indirect energy budgets that limit their overall fidelity. For example, optically-thin cloud contamination is currently a significant (10-20%) source of error in global aerosol optical depth (i.e., direct forcing) measurements. Similarly, cloud retrievals are contaminated in the presence of absorbing aerosol particles advecting above them, thus weakening our ability to resolve indirect forcing effects and diabatic heating anomalies that impact regional static stability.

In this study, the impact of cloud contamination on Moderate Resolution Imaging Spectroradiometer (MODIS) and Multi-angle Imaging SpectroRadiometer (MISR) aerosol optical depth retrievals, as well as direct aerosol climate forcing estimates based on MODIS and MISR satellite aerosol products, are quantified and described. Collocated MODIS cloud masking data are applied for evaluating the existence of cloud artifacts in MISR aerosol products. The impact of aerosol contamination on cloud property retrievals are also studied for both dust and smoke outflow regions near and off the west coast of Africa, using combined observations from MODIS, Ozone Monitoring Instrument, and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations. Cases depicting above-cloud aerosol particle contamination of cloud property retrievals are identified and their impact quantified for uncertainties relating to cloud optical depth and effective radius.