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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

Journal Article · · Journal of Geophysical Research: Atmospheres
DOI:https://doi.org/10.1002/2016JD025771· OSTI ID:1345766
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
+ Show Author Affiliations

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.

Research Organization:
Brookhaven National Laboratory (BNL), Upton, NY (United States); NASA Langley Research Center, Hampton, VA (United States)
Sponsoring Organization:
USDOE Office of Science (SC), Biological and Environmental Research (BER); USDOE Office of Science (SC), Basic Energy Sciences (BES)
Grant/Contract Number:
SC0012704; FOA-0000885; SC0011666; AC02-06CH11357; SC0011675
OSTI ID:
1345766
Alternate ID(s):
OSTI ID: 1355765; OSTI ID: 1402399
Report Number(s):
BNL-113626-2017-JA; R&D Project: 2016-BNL-EE630EECA-Budg; KP1701000
Journal Information:
Journal of Geophysical Research: Atmospheres, Vol. 122, Issue 4; ISSN 2169-897X
Publisher:
American Geophysical UnionCopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 14 works
Citation information provided by
Web of Science

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Cited By (4)

Spatio-temporal variability of warm rain events over southern West Africa from geostationary satellite observations for climate monitoring and model evaluation
  • Young, Matthew P.; Chiu, J. Christine; Williams, Charles J. R.
  • Quarterly Journal of the Royal Meteorological Society, Vol. 144, Issue 716 https://doi.org/10.1002/qj.3372
journal October 2018
Marine liquid cloud geometric thickness retrieved from OCO-2's oxygen A-band spectrometer journal January 2019
The impact of neglecting ice phase on cloud optical depth retrievals from AERONET cloud mode observations journal January 2019
The Impact of Neglecting Ice Phase on Cloud Optical Depth Retrievals from AERONET Cloud Mode Observations posted_content May 2019

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Related Subjects

54 ENVIRONMENTAL SCIENCES
58 GEOSCIENCES
aerosol-cloud interactions
marine boundary layer
remote sensing