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

<p>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...

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Main Authors: D. Painemal, F.-L. Chang, R. Ferrare, S. Burton, Z. Li, W. L. Smith Jr., P. Minnis, Y. Feng, M. Clayton
Format: Article
Language:English
Published: Copernicus Publications 2020-06-01
Series:Atmospheric Chemistry and Physics
Online Access:https://www.atmos-chem-phys.net/20/7167/2020/acp-20-7167-2020.pdf
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author D. Painemal
D. Painemal
F.-L. Chang
F.-L. Chang
R. Ferrare
S. Burton
Z. Li
Z. Li
W. L. Smith Jr.
P. Minnis
P. Minnis
Y. Feng
M. Clayton
M. Clayton
author_facet D. Painemal
D. Painemal
F.-L. Chang
F.-L. Chang
R. Ferrare
S. Burton
Z. Li
Z. Li
W. L. Smith Jr.
P. Minnis
P. Minnis
Y. Feng
M. Clayton
M. Clayton
author_sort D. Painemal
collection DOAJ
description <p>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 (<span class="inline-formula"><i>σ</i>)</span> below cloud top (<span class="inline-formula"><i>σ</i><sub>BC</sub>)</span> from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and cloud droplet number concentrations (<span class="inline-formula"><i>N</i><sub>d</sub></span>) from MODIS Aqua yield high correlations across a broad range of <span class="inline-formula"><i>σ</i><sub>BC</sub></span> values, with <span class="inline-formula"><i>σ</i><sub>BC</sub></span> quartile correlations <span class="inline-formula">≥0.78</span>. In contrast, CALIOP-based AOD yields correlations with MODIS <span class="inline-formula"><i>N</i><sub>d</sub></span> of 0.54–0.62 for the two lower AOD quartiles. Moreover, <span class="inline-formula"><i>σ</i><sub>BC</sub></span> explains 41&thinsp;% of the spatial variance in MODIS <span class="inline-formula"><i>N</i><sub>d</sub></span>, whereas AOD only explains 17&thinsp;%, primarily caused by the lack of spatial covariability in the eastern Pacific. Compared with <span class="inline-formula"><i>σ</i><sub>BC</sub></span>, near-surface <span class="inline-formula"><i>σ</i></span> weakly correlates in space with MODIS <span class="inline-formula"><i>N</i><sub>d</sub></span>, accounting for a 16&thinsp;% variance. It is concluded that the linear regression calculated from ln(<span class="inline-formula"><i>N</i><sub>d</sub>)</span>–ln(<span class="inline-formula"><i>σ</i><sub>BC</sub>)</span> (the standard method for quantifying ACIs) is more physically meaningful than that derived from the <span class="inline-formula"><i>N</i><sub>d</sub></span>–AOD pair.</p>
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spelling doaj.art-d00181abde45489ebf0182a66611d2262022-12-21T18:41:40ZengCopernicus PublicationsAtmospheric Chemistry and Physics1680-73161680-73242020-06-01207167717710.5194/acp-20-7167-2020Reducing uncertainties in satellite estimates of aerosol–cloud interactions over the subtropical ocean by integrating vertically resolved aerosol observationsD. Painemal0D. Painemal1F.-L. Chang2F.-L. Chang3R. Ferrare4S. Burton5Z. Li6Z. Li7W. L. Smith Jr.8P. Minnis9P. Minnis10Y. Feng11M. Clayton12M. Clayton13Science Systems and Applications Inc., Hampton, Virginia 23666, USANASA Langley Research Center, Hampton, Virginia 23691 USAScience Systems and Applications Inc., Hampton, Virginia 23666, USANASA Langley Research Center, Hampton, Virginia 23691 USANASA Langley Research Center, Hampton, Virginia 23691 USANASA Langley Research Center, Hampton, Virginia 23691 USAScience Systems and Applications Inc., Hampton, Virginia 23666, USANASA Langley Research Center, Hampton, Virginia 23691 USANASA Langley Research Center, Hampton, Virginia 23691 USAScience Systems and Applications Inc., Hampton, Virginia 23666, USANASA Langley Research Center, Hampton, Virginia 23691 USAArgonne National Laboratory, Lemont, Illinois 60439, USAScience Systems and Applications Inc., Hampton, Virginia 23666, USANASA Langley Research Center, Hampton, Virginia 23691 USA<p>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 (<span class="inline-formula"><i>σ</i>)</span> below cloud top (<span class="inline-formula"><i>σ</i><sub>BC</sub>)</span> from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and cloud droplet number concentrations (<span class="inline-formula"><i>N</i><sub>d</sub></span>) from MODIS Aqua yield high correlations across a broad range of <span class="inline-formula"><i>σ</i><sub>BC</sub></span> values, with <span class="inline-formula"><i>σ</i><sub>BC</sub></span> quartile correlations <span class="inline-formula">≥0.78</span>. In contrast, CALIOP-based AOD yields correlations with MODIS <span class="inline-formula"><i>N</i><sub>d</sub></span> of 0.54–0.62 for the two lower AOD quartiles. Moreover, <span class="inline-formula"><i>σ</i><sub>BC</sub></span> explains 41&thinsp;% of the spatial variance in MODIS <span class="inline-formula"><i>N</i><sub>d</sub></span>, whereas AOD only explains 17&thinsp;%, primarily caused by the lack of spatial covariability in the eastern Pacific. Compared with <span class="inline-formula"><i>σ</i><sub>BC</sub></span>, near-surface <span class="inline-formula"><i>σ</i></span> weakly correlates in space with MODIS <span class="inline-formula"><i>N</i><sub>d</sub></span>, accounting for a 16&thinsp;% variance. It is concluded that the linear regression calculated from ln(<span class="inline-formula"><i>N</i><sub>d</sub>)</span>–ln(<span class="inline-formula"><i>σ</i><sub>BC</sub>)</span> (the standard method for quantifying ACIs) is more physically meaningful than that derived from the <span class="inline-formula"><i>N</i><sub>d</sub></span>–AOD pair.</p>https://www.atmos-chem-phys.net/20/7167/2020/acp-20-7167-2020.pdf
spellingShingle D. Painemal
D. Painemal
F.-L. Chang
F.-L. Chang
R. Ferrare
S. Burton
Z. Li
Z. Li
W. L. Smith Jr.
P. Minnis
P. Minnis
Y. Feng
M. Clayton
M. Clayton
Reducing uncertainties in satellite estimates of aerosol–cloud interactions over the subtropical ocean by integrating vertically resolved aerosol observations
Atmospheric Chemistry and Physics
title Reducing uncertainties in satellite estimates of aerosol–cloud interactions over the subtropical ocean by integrating vertically resolved aerosol observations
title_full Reducing uncertainties in satellite estimates of aerosol–cloud interactions over the subtropical ocean by integrating vertically resolved aerosol observations
title_fullStr Reducing uncertainties in satellite estimates of aerosol–cloud interactions over the subtropical ocean by integrating vertically resolved aerosol observations
title_full_unstemmed Reducing uncertainties in satellite estimates of aerosol–cloud interactions over the subtropical ocean by integrating vertically resolved aerosol observations
title_short Reducing uncertainties in satellite estimates of aerosol–cloud interactions over the subtropical ocean by integrating vertically resolved aerosol observations
title_sort reducing uncertainties in satellite estimates of aerosol cloud interactions over the subtropical ocean by integrating vertically resolved aerosol observations
url https://www.atmos-chem-phys.net/20/7167/2020/acp-20-7167-2020.pdf
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