The Influence of Elevated Smoke Layers on Stratocumulus Clouds over the SE Atlantic

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By Sampa Das1, H. Harshvardhan, Peter Colarco2

1. NASA Goddard Space Flight Center/ Purdue University (ex) 2. NASA Goddard Space Flight Center

Data associated with the publication "Influence of Elevated Smoke Layers on Stratocumulus Clouds over the SE Atlantic in the NASA Goddard Earth Observing System (GEOS) Model"

Version 1.0 - published on 09 Jan 2020 doi:10.4231/K195-9C37 - cite this Archived on 13 Feb 2020

Licensed under CC0 1.0 Universal

Description

Previous evaluations of simulated aerosol transport over the South-east Atlantic by global aerosol models, including Goddard Earth Observing System (GEOS) Atmospheric GCM, showed that the bulk of the modeled smoke aerosol layer resided ~1-2 km lower than CALIOP lidar observations over the ocean. Using this finding as the motivation, this study examines the changes in model simulated cloud properties in response to redistributing the aerosol profiles over the ocean. Ten years (2006-15) of CALIOP retrieved smoke aerosol extinction profiles were used to redistribute the model simulated aerosol mass on a monthly mean basis, keeping the column aerosol mass conserved. The results from the model sensitivity experiments show that elevating the aerosol layer to higher levels in agreement with the observations causes an increase in cloud fractions by ~33% for shallow marine boundary layers (MBL), while cloud fractions decrease by ~30% for deeper MBL. We found that aerosol-induced warming within the shallow MBL cloud layers leads to reduced cloud presence due to decrease in relative humidity at these levels. For deeper MBL, increased MBL stability in the lower altitude aerosol case compared to the elevated aerosol layer case suppresses the cloud vertical extent, enhances the cloud cover and delays the stratocumulus to cumulus transition. Finally, aerosol redistribution impacts on radiative forcing are investigated, which appear to be mainly driven by the changes in cloud area fractions rather than in-cloud LWP changes between the model experiments.

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