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Title: Aerosol and cloud microphysics covariability in the northeast Pacific boundary layer estimated with ship-based and satellite remote sensing observations

Abstract

Ship measurements collected over the northeast Pacific along transects between the port of Los Angeles (33.7°N, 118.2°W) and Honolulu (21.3°N, 157.8°W) during May to August 2013 were utilized to investigate the covariability between marine low cloud microphysical and aerosol properties. Ship-based retrievals of cloud optical depth (τ) from a Sun photometer and liquid water path (LWP) from a microwave radiometer were combined to derive cloud droplet number concentration Nd and compute a cloud-aerosol interaction (ACI) metric defined as ACICCN=∂ ln(Nd)/∂ ln(CCN), with CCN denoting the cloud condensation nuclei concentration measured at 0.4% (CCN0.4) and 0.3% (CCN0.3) supersaturation. Analysis of CCN0.4, accumulation mode aerosol concentration (Na), and extinction coefficient (σext) indicates that Na and σext can be used as CCN0.4 proxies for estimating ACI. ACICCN derived from 10 min averaged Nd and CCN0.4 and CCN0.3, and CCN0.4 regressions using Na and σext, produce high ACICCN: near 1.0, that is, a fractional change in aerosols is associated with an equivalent fractional change in Nd. ACICCN computed in deep boundary layers was small (ACICCN = 0.60), indicating that surface aerosol measurements inadequately represent the aerosol variability below clouds. Satellite cloud retrievals from MODerate-resolution Imaging Spectroradiometer and GOES-15 data were compared against ship-based retrievalsmore » and further analyzed to compute a satellite-based ACICCN. Satellite data correlated well with their ship-based counterparts with linear correlation coefficients equal to or greater than 0.78. Combined satellite Nd and ship-based CCN0.4 and Na yielded a maximum ACICCN = 0.88–0.92, a value slightly less than the ship-based ACICCN, but still consistent with aircraft-based studies in the eastern Pacific.« less

Authors:
ORCiD logo [1]; ORCiD logo [2]; ORCiD logo [3]; ORCiD logo [4]; ORCiD logo [5]; ORCiD logo [6]; ORCiD logo [7]; ORCiD logo [8]; ORCiD logo [3]; ORCiD logo [9]
  1. Science Systems and Applications, Inc., Hampton VA (United States); NASA Langley Research Center, Hampton, VA (United States)
  2. Univ. of Reading, Reading (United Kingdom). Dept. of Meteorology
  3. NASA Langley Research Center, Hampton, VA (United States)
  4. Science Systems and Applications, Inc., Hampton VA (United States)
  5. McGill Univ., Montreal, QC (Canada). Dept of Atmospheric and Oceanic Sciences
  6. Argonne National Lab. (ANL), Argonne, IL (United States). Environmental Science Division
  7. Univ. of Wisconsin, Madison, WI (United States). Space Science and Engineering Center
  8. Brookhaven National Lab. (BNL), Upton, NY (United States)
  9. Stony Brook Univ., NY (United States). School of Marine and Atmospheric Sciences
Publication Date:
Research Org.:
Brookhaven National Laboratory (BNL), Upton, NY (United States); NASA Langley Research Center, Hampton, VA (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER); USDOE Office of Science (SC), Basic Energy Sciences (BES)
OSTI Identifier:
1345766
Alternate Identifier(s):
OSTI ID: 1355765; OSTI ID: 1402399
Report Number(s):
BNL-113626-2017-JA
Journal ID: ISSN 2169-897X; R&D Project: 2016-BNL-EE630EECA-Budg; KP1701000
Grant/Contract Number:  
SC0012704; FOA-0000885; SC0011666; AC02-06CH11357; SC0011675
Resource Type:
Accepted Manuscript
Journal Name:
Journal of Geophysical Research: Atmospheres
Additional Journal Information:
Journal Volume: 122; Journal Issue: 4; Journal ID: ISSN 2169-897X
Publisher:
American Geophysical Union
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; 58 GEOSCIENCES; aerosol-cloud interactions; marine boundary layer; remote sensing

Citation Formats

Painemal, David, Chiu, J. -Y. Christine, Minnis, Patrick, Yost, Christopher, Zhou, Xiaoli, Cadeddu, Maria, Eloranta, Edwin, Lewis, Ernie R., Ferrare, Richard, and Kollias, Pavlos. Aerosol and cloud microphysics covariability in the northeast Pacific boundary layer estimated with ship-based and satellite remote sensing observations. United States: N. p., 2017. Web. doi:10.1002/2016JD025771.
Painemal, David, Chiu, J. -Y. Christine, Minnis, Patrick, Yost, Christopher, Zhou, Xiaoli, Cadeddu, Maria, Eloranta, Edwin, Lewis, Ernie R., Ferrare, Richard, & Kollias, Pavlos. Aerosol and cloud microphysics covariability in the northeast Pacific boundary layer estimated with ship-based and satellite remote sensing observations. United States. https://doi.org/10.1002/2016JD025771
Painemal, David, Chiu, J. -Y. Christine, Minnis, Patrick, Yost, Christopher, Zhou, Xiaoli, Cadeddu, Maria, Eloranta, Edwin, Lewis, Ernie R., Ferrare, Richard, and Kollias, Pavlos. Mon . "Aerosol and cloud microphysics covariability in the northeast Pacific boundary layer estimated with ship-based and satellite remote sensing observations". United States. https://doi.org/10.1002/2016JD025771. https://www.osti.gov/servlets/purl/1345766.
@article{osti_1345766,
title = {Aerosol and cloud microphysics covariability in the northeast Pacific boundary layer estimated with ship-based and satellite remote sensing observations},
author = {Painemal, David and Chiu, J. -Y. Christine and Minnis, Patrick and Yost, Christopher and Zhou, Xiaoli and Cadeddu, Maria and Eloranta, Edwin and Lewis, Ernie R. and Ferrare, Richard and Kollias, Pavlos},
abstractNote = {Ship measurements collected over the northeast Pacific along transects between the port of Los Angeles (33.7°N, 118.2°W) and Honolulu (21.3°N, 157.8°W) during May to August 2013 were utilized to investigate the covariability between marine low cloud microphysical and aerosol properties. Ship-based retrievals of cloud optical depth (τ) from a Sun photometer and liquid water path (LWP) from a microwave radiometer were combined to derive cloud droplet number concentration Nd and compute a cloud-aerosol interaction (ACI) metric defined as ACICCN=∂ ln(Nd)/∂ ln(CCN), with CCN denoting the cloud condensation nuclei concentration measured at 0.4% (CCN0.4) and 0.3% (CCN0.3) supersaturation. Analysis of CCN0.4, accumulation mode aerosol concentration (Na), and extinction coefficient (σext) indicates that Na and σext can be used as CCN0.4 proxies for estimating ACI. ACICCN derived from 10 min averaged Nd and CCN0.4 and CCN0.3, and CCN0.4 regressions using Na and σext, produce high ACICCN: near 1.0, that is, a fractional change in aerosols is associated with an equivalent fractional change in Nd. ACICCN computed in deep boundary layers was small (ACICCN = 0.60), indicating that surface aerosol measurements inadequately represent the aerosol variability below clouds. Satellite cloud retrievals from MODerate-resolution Imaging Spectroradiometer and GOES-15 data were compared against ship-based retrievals and further analyzed to compute a satellite-based ACICCN. Satellite data correlated well with their ship-based counterparts with linear correlation coefficients equal to or greater than 0.78. Combined satellite Nd and ship-based CCN0.4 and Na yielded a maximum ACICCN = 0.88–0.92, a value slightly less than the ship-based ACICCN, but still consistent with aircraft-based studies in the eastern Pacific.},
doi = {10.1002/2016JD025771},
journal = {Journal of Geophysical Research: Atmospheres},
number = 4,
volume = 122,
place = {United States},
year = {Mon Feb 27 00:00:00 EST 2017},
month = {Mon Feb 27 00:00:00 EST 2017}
}

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