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

Journal Article · Mon Feb 27 04:00:00 EST 2017 · Journal of Geophysical Research: Atmospheres

DOI:https://doi.org/10.1002/2016JD025771· OSTI ID:1376888

Painemal, David ^[1]; Chiu, J. -Y. Christine ^[2]; Minnis, Patrick ^[3]; Yost, Christopher ^[4]; Zhou, Xiaoli ^[5]; Cadeddu, Maria ^[6]; Eloranta, Edwin ^[7]; Lewis, Ernie R. ^[8]; Ferrare, Richard ^[3]; Kollias, Pavlos ^[9]

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1. Science Systems and Applications, Inc., Hampton Virginia USA; NASA Langley Research Center, Hampton Virginia USA
2. Department of Meteorology, University of Reading, Reading UK
3. NASA Langley Research Center, Hampton Virginia USA
4. Science Systems and Applications, Inc., Hampton Virginia USA
5. Department of Atmospheric and Oceanic Sciences, McGill University, Montreal Quebec Canada
6. Environmental Science Division, Argonne National Laboratory, Lemont Illinois USA
7. Space Science and Engineering Center, University of Wisconsin-Madison, Madison Wisconsin USA
8. Brookhaven National Laboratory, Upton New York USA
9. School of Marine and Atmospheric Sciences, Stony Brook University, Stony Brook New York USA

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: Argonne National Laboratory (ANL)
• Sponsoring Organization: USDOE Office of Science - Office of Biological and Environmental Research - Atmospheric Radiation Measurement (ARM) Program; National Aeronautic and Space Administration (NASA)
• DOE Contract Number: AC02-06CH11357
• OSTI ID: 1376888
• Journal Information: Journal of Geophysical Research: Atmospheres, Journal Name: Journal of Geophysical Research: Atmospheres Journal Issue: 4 Vol. 122; ISSN 2169-897X
• Publisher: American Geophysical Union
• Country of Publication: United States
• Language: English