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Discussion papers
https://doi.org/10.5194/acp-2019-892
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-2019-892
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 06 Nov 2019

Submitted as: research article | 06 Nov 2019

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Atmospheric Chemistry and Physics (ACP).

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

David Painemal1,2, Fu-Lung Chang1,2, Richard Ferrare2, Sharon Burton2, Zhujun Li1,2, William L. Smith Jr.2, Patrick Minnis1,2, Yan Feng3, and Marian Clayton1,2 David Painemal et al.
  • 1Science Systems and Applications Inc., Hampton, Virginia, 23666, U.S.
  • 2NASA Langley Research Center, Hampton, Virginia, 23691 U.S.
  • 3Argonne National Laboratory, Lemont, Illinois, 60439, U.S.

Abstract. 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 (ACI) 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 Aqua Moderate-resolution Imaging Spectroradiometer (MODIS) 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 Aqua-MODIS 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 less than 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 ACI) is more physically meaningful than that derived from the Nd−AOD pair.

David Painemal et al.
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Short summary
Aerosol-cloud interactions (ACI) are the most uncertain aspect of the anthropogenic forcing. Although satellites provide the observational dataset for the global ACI quantification, retrievals are limited to vertically-integrated quantities (e.g. aerosol optical depth, AOD), which are typically used as aerosol proxy. This study demonstrates that matching vertically-resolved aerosol from CALIOP at the cloud-layer height with satellite cloud retrievals reduces uncertainties in ACI estimates.
Aerosol-cloud interactions (ACI) are the most uncertain aspect of the anthropogenic forcing....
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