Factors driving the seasonal and hourly variability of sea-spray aerosol number in the North Atlantic

Georges Saliba; Chia-Li Chen; Savannah Lewis; Lynn M Russell; Laura-Helena Rivellini; Alex K Y Lee; Patricia K Quinn; Timothy S Bates; Nils Haëntjens; Emmanuel S Boss; Lee Karp-Boss; Nicholas Baetge; Craig A Carlson; Michael J Behrenfeld

doi:10.1073/pnas.1907574116

Factors driving the seasonal and hourly variability of sea-spray aerosol number in the North Atlantic

Proc Natl Acad Sci U S A. 2019 Oct 8;116(41):20309-20314. doi: 10.1073/pnas.1907574116. Epub 2019 Sep 23.

Authors

Affiliations

¹ Scripps Institution of Oceanography, University of California San Diego, La Jolla, CA 92093.
² Scripps Institution of Oceanography, University of California San Diego, La Jolla, CA 92093; lmrussell@ucsd.edu.
³ Environmental Research Institute, National University of Singapore, 117411, Singapore.
⁴ Department of Civil and Environmental Engineering, National University of Singapore, 117576, Singapore.
⁵ Pacific Marine Environmental Laboratory, National Oceanic and Atmospheric Administration, Seattle, WA 98115.
⁶ Joint Institute for the Study of the Atmosphere and Ocean, University of Washington, Seattle, WA 98195.
⁷ School of Marine Sciences, University of Maine, Orono, ME 04469.
⁸ Department of Ecology, Evolution, and Marine Biology, University of California, Santa Barbara, CA 93106.
⁹ Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR 97331.

Abstract

Four North Atlantic Aerosol and Marine Ecosystems Study (NAAMES) field campaigns from winter 2015 through spring 2018 sampled an extensive set of oceanographic and atmospheric parameters during the annual phytoplankton bloom cycle. This unique dataset provides four seasons of open-ocean observations of wind speed, sea surface temperature (SST), seawater particle attenuation at 660 nm (c_p,660, a measure of ocean particulate organic carbon), bacterial production rates, and sea-spray aerosol size distributions and number concentrations (N_SSA). The NAAMES measurements show moderate to strong correlations (0.56 < R < 0.70) between N_SSA and local wind speeds in the marine boundary layer on hourly timescales, but this relationship weakens in the campaign averages that represent each season, in part because of the reduction in range of wind speed by multiday averaging. N_SSA correlates weakly with seawater c_p,660 (R = 0.36, P << 0.01), but the correlation with c_p,660, is improved (R = 0.51, P < 0.05) for periods of low wind speeds. In addition, NAAMES measurements provide observational dependence of SSA mode diameter (d_m) on SST, with d_m increasing to larger sizes at higher SST (R = 0.60, P << 0.01) on hourly timescales. These results imply that climate models using bimodal SSA parameterizations to wind speed rather than a single SSA mode that varies with SST may overestimate SSA number concentrations (hence cloud condensation nuclei) by a factor of 4 to 7 and may underestimate SSA scattering (hence direct radiative effects) by a factor of 2 to 5, in addition to overpredicting variability in SSA scattering from wind speed by a factor of 5.

Keywords: NAAMES; phytoplankton bloom; radiative impacts; sea spray aerosol.

Publication types

Research Support, U.S. Gov't, Non-P.H.S.