Bioaerosols are the dominant source of warm-temperature immersion-mode INPs and drive uncertainties in INP predictability

Author:

Cornwell Gavin C.12ORCID,McCluskey Christina S.34ORCID,Hill Thomas C. J.3ORCID,Levin Ezra T.3,Rothfuss Nicholas E.5ORCID,Tai Sheng-Lun1ORCID,Petters Markus D.5ORCID,DeMott Paul J.3ORCID,Kreidenweis Sonia3ORCID,Prather Kimberly A.26ORCID,Burrows Susannah M.1ORCID

Affiliation:

1. Atmospheric Science and Global Change Division, Pacific Northwest National Laboratory, Richland, WA 99352, USA.

2. Department of Chemistry and Biochemistry, University of California, San Diego, La Jolla, CA 92093, USA.

3. Department of Atmospheric Science, Colorado State University, Fort Collins, CO 80523, USA.

4. National Center for Atmospheric Research, Boulder, CO 80305, USA.

5. Department of Marine, Earth, and Atmospheric Sciences, North Carolina State University, Raleigh, NC 27605, USA.

6. Scripps Institution of Oceanography, University of California, San Diego, La Jolla, CA 92037, USA.

Abstract

Ice-nucleating particles (INPs) are rare atmospheric aerosols that initiate primary ice formation, but accurately simulating their concentrations and variability in large-scale climate models remains a challenge. Doing so requires both simulating major particle sources and parameterizing their ice nucleation (IN) efficiency. Validating and improving model predictions of INP concentrations requires measuring their concentrations delineated by particle type. We present a method to speciate INP concentrations into contributions from dust, sea spray aerosol (SSA), and bioaerosol. Field campaign data from Bodega Bay, California, showed that bioaerosols were the primary source of INPs between −12° and −20°C, while dust was a minor source and SSA had little impact. We found that recent parameterizations for dust and SSA accurately predicted ambient INP concentrations. However, the model did not skillfully simulate bioaerosol INPs, suggesting a need for further research to identify major factors controlling their emissions and INP efficiency for improved representation in models.

Publisher

American Association for the Advancement of Science (AAAS)

Subject

Multidisciplinary

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