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Title: Reducing uncertainties in satellite estimates of aerosol–cloud interactions over the subtropical ocean by integrating vertically resolved aerosol observations

Journal Article · · Atmospheric Chemistry and Physics (Online)
 [1];  [1];  [2];  [2];  [1]; ORCiD logo [2]; ORCiD logo [1]; ORCiD logo [3];  [1]
  1. Science Systems and Applications, Inc., Hampton, VA (United States); NASA Langley Research Center, Hampton, VA (United States)
  2. NASA Langley Research Center, Hampton, VA (United States)
  3. Argonne National Lab. (ANL), Lemont, IL (United States)
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Satellite quantification of aerosol effects on clouds relies on aerosol optical depth (AOD) as a proxy for aerosol concentration or cloud condensation nuclei (CCN). However, the lack of error characterization of satellite-based results hampers their use for the evaluation and improvement of global climate models. We show that the use of AOD for assessing aerosol–cloud interactions (ACIs) is inadequate over vast oceanic areas in the subtropics. Instead, we postulate that a more physical approach that consists of matching vertically resolved aerosol data from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite at the cloud-layer height with Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua cloud retrievals reduces uncertainties in satellite-based ACI estimates. Combined aerosol extinction coefficients (σ) below cloud top (σBC) from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and cloud droplet number concentrations (Nd) from MODIS Aqua yield high correlations across a broad range of σBC values, with σBC quartile correlations ≥0.78. In contrast, CALIOP-based AOD yields correlations with MODIS Nd of 0.54–0.62 for the two lower AOD quartiles. Moreover, σBC explains 41% of the spatial variance in MODIS Nd, whereas AOD only explains 17%, primarily caused by the lack of spatial covariability in the eastern Pacific. Compared with σBC, near-surface σ weakly correlates in space with MODIS Nd, accounting for a 16% variance. It is concluded that the linear regression calculated from ln(Nd)–ln(σBC) (the standard method for quantifying ACIs) is more physically meaningful than that derived from the Nd–AOD pair.

Research Organization:
Argonne National Laboratory (ANL), Argonne, IL (United States)
Sponsoring Organization:
USDOE; National Aeronautics and Space Administration (NASA)
Grant/Contract Number:
AC02-06CH11357; NNH16CY04C
OSTI ID:
1833630
Journal Information:
Atmospheric Chemistry and Physics (Online), Vol. 20, Issue 12; ISSN 1680-7324
Publisher:
Copernicus Publications, EGUCopyright Statement
Country of Publication:
United States
Language:
English

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