9.4 Using High-Spatial-Resolution Aircraft Remote Sensing to Explore Aerosols Near Clouds during SEAC4RS

Wednesday, 11 July 2018: 2:15 PM
Regency E/F (Hyatt Regency Vancouver)
Robert Levy, NASA GSFC, Greenbelt, MD; and R. S. Spencer, S. Mattoo, L. Remer, D. L. Hlavka, G. T. Arnold, S. Platnick, and A. Marshak

Aerosols are important components of our climate system, so we must quantify aerosol properties and their interactions with clouds. When applied to the satellite-borne Moderate-resolution Imaging Spectroradiometer (MODIS), the Dark Target (DT) satellite retrieval algorithm provides aerosol optical depth (AOD) and other parameters in cloud-free scenes. However, the coarse resolution (500 m pixels, 3 km or 10 km products) leaves us with significant uncertainty in quantifying aerosol near clouds. Therefore, the DT algorithm was ported to high-resolution data (50 m pixels) obtained from the enhanced-MODIS Airborne Simulator (eMAS), which flew on high altitude aircraft during the Studies of Emissions, Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS) Airborne Science Campaign over the U.S. in 2013. To evaluate the resulting 500 m resolution product, we use collocated observations and retrievals from MODIS, the Cloud Physics Lidar (CPL) and ground-based Aerosol Robotic Network (AERONET). We find that even with aggressive cloud screening, the eMAS AOD is greatly enhanced near clouds. We define spatial metrics to indicate local cloud distributions near each retrieval, and attempt to separate near-cloud and background (far from cloud) AOD. Although the other data suggests some AOD enhancement near clouds, the eMAS enhancement is much greater. This indicates that a 3-D radiation interaction between the clouds and surrounding clear air is the main reason for the high-biased retrieval. The methods and initial results of this paper form a starting point for analyzing aerosol-cloud-interactions (ACI) from high-resolution passive remote sensing measurements, and help interpret more comprehensive global AOD datasets from coarser resolution satellite retrievals.
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