Empirical formulation for multiple groups of primary biological ice nucleating particles from field observations over Amazonia

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  • 1 Department of Physical Geography and Ecosystem Science, Lund University, Lund, Sweden
  • | 2 Université Clermont Auvergne, CNRS, SIGMA Clermont, ICCF, F-63000, Clermont-Ferrand, France
  • | 3 Institute for Atmospheric and Environmental Science, Goethe University of Frankfurt, Frankfurt am Main, Germany
  • | 4 Atmospheric Sciences and Global Change Division, Pacific Northwest National Laboratory, Richland, WA, 99354
  • | 5 Department of Atmospheric Science, Colorado State University, Fort Collins, Colorado, USA
  • | 6 Departamento de Ciências Atmosféricas, Instituto de Astronomia, Geofísica e Ciências Atmosféricas, Universidade de São Paulo, São Paulo, Brazil
  • | 7 Institute for Terrestrial and Planetary Atmospheres, School of Marine and Atmospheric Sciences, Stony Brook University, Stony Brook, New York 11794-5000, USA
  • | 8 INRAE, Pathologie Végétale, 84140, Montfavet, France
  • | 9 Department of Geology, Lund University, Lund, Sweden
  • | 10 Instituto de Física, Universidade de São Paulo, Brazil
  • | 11 Multiphase Chemistry Department, Max Planck Institute for Chemistry, 55128 Mainz, Germany
  • | 12 Institute of Biology, University of Graz, Austria
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Abstract

To resolve the various types of biological ice nuclei (IN) with atmospheric models, an extension of the empirical parameterization (EP) (Phillips et al. 2008; 2013) is proposed to predict the active IN from multiple groups of primary biological aerosol particles (PBAPs). Our approach is to utilize coincident observations of PBAP sizes, concentrations, biological composition, and ice-nucleating ability. The parameterization organizes the PBAPs into five basic groups: fungal spores, bacteria, pollen, viral particles, plant/animal detritus, algae, and their respective fragments. This new biological component of the EP was constructed by fitting predicted concentrations of PBAP IN to those observed at the Amazon Tall Tower Observatory (ATTO) site located in the central Amazon. The fitting parameters for pollen and viral particles, plant/animal detritus, which are much less active as IN than fungal and bacterial groups, are constrained based on their ice nucleation activity from the literature. The parameterization has empirically derived dependencies on the surface area of each group (except algae), and the effects of variability in their mean sizes and number concentrations are represented via their influences on the surface area. The concentration of active algal IN is estimated from literature-based measurements.

Predictions of this new biological component of the EP are consistent with previous laboratory and field observations not used in its construction. The EP scheme was implemented in a 0D parcel model. It confirms that biological IN account for most of the total IN activation at temperatures warmer than −20°C and at colder temperatures dust and soot become increasingly more important to ice nucleation.

Corresponding Author: Dr. Sachin Patade, Lund University, Sweden, email: sachin.patade@nateko.lu.se

Abstract

To resolve the various types of biological ice nuclei (IN) with atmospheric models, an extension of the empirical parameterization (EP) (Phillips et al. 2008; 2013) is proposed to predict the active IN from multiple groups of primary biological aerosol particles (PBAPs). Our approach is to utilize coincident observations of PBAP sizes, concentrations, biological composition, and ice-nucleating ability. The parameterization organizes the PBAPs into five basic groups: fungal spores, bacteria, pollen, viral particles, plant/animal detritus, algae, and their respective fragments. This new biological component of the EP was constructed by fitting predicted concentrations of PBAP IN to those observed at the Amazon Tall Tower Observatory (ATTO) site located in the central Amazon. The fitting parameters for pollen and viral particles, plant/animal detritus, which are much less active as IN than fungal and bacterial groups, are constrained based on their ice nucleation activity from the literature. The parameterization has empirically derived dependencies on the surface area of each group (except algae), and the effects of variability in their mean sizes and number concentrations are represented via their influences on the surface area. The concentration of active algal IN is estimated from literature-based measurements.

Predictions of this new biological component of the EP are consistent with previous laboratory and field observations not used in its construction. The EP scheme was implemented in a 0D parcel model. It confirms that biological IN account for most of the total IN activation at temperatures warmer than −20°C and at colder temperatures dust and soot become increasingly more important to ice nucleation.

Corresponding Author: Dr. Sachin Patade, Lund University, Sweden, email: sachin.patade@nateko.lu.se
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