International Joint Project to Study Effects from Bioaerosols on Clouds

Project leader: Dr V. Phillips, University of Lund, Sweden

Co-Investigator: F. Goncalves (Sao Paulo University, Brazil),

D. Knopf (Stony-Brook University, USA),

S. Burrows (Pacific Northwest National Laboratory, USA),

C. Morris (INRA, PACA Research Center, France),

P. Amato (Institut de Chimie de Clermont-Ferrand, France),

P. DeMott (Colorado State University, USA)

Overview

A project entitled “Impacts on Glaciated Clouds from Biogenic Aerosols Simulated Numerically”, was funded near the end of 2015 by Vetenskapsrådet (VR) in Sweden. It lasted from 2016 to 2020, supporting a postdoctoral scholar.

This joint project involved at least six partner institutions in Brazil, France, Germany and USA:

· Department of Atmospheric Sciences - Institute Astronômical and Geophysical, University of Sao Paulo in Brazil;

· Department of Physical Geography and Ecosystem Science, Lund University, in Sweden;

· Institut de Chimie de Clermont-Ferrand (ICCF), Université Blaise Pascal, in France;

· Department of Atmospheric Science, Colorado State University, in USA;

· Atmospheric Sciences & Global Change, Pacific Northwest National Laboratory, in USA;

· Plant Pathology Unit, INRA, PACA Research Center, in France.

The aim was to predict the separate contributions of ice nucleation by five broad types of primary biological aerosol particle (PBAPs) in an atmospheric model of clouds:

· Bacteria

· Fungal

· Pollen

· Algal

· and animal/plant detritus.

Field and lab observations

We collected aerosol samples from the central Amazon basin at the Amazon Tall Tower Observatory (ATTO; Andreae et al. 2015). The ATTO site is in the middle of the Amazon Rainforest in northern Brazil, 150 km from Manaus.   Our lab observations of the samples used Scanning Electron Microscopy (Fig. 1) and optical microscopy at Lund University, with flow cytometry at Clermont-Ferrand to measure total biological aerosol concentrations. Measurements of ice nucleus activity were made at Clermont-Ferrand with drop-freezing by LINDA (LED-based Ice Nucleation Detection Apparatus) for biological IN and with the Frankfurt Ice Nuclei 219 Deposition Experiment (FRIDGE-IMM) chamber for all IN.

This informed construction of a scheme to resolve the individual IN activities of each of five broad groups of PBAPs. A new version of the ‘empirical parameterization’ (EP) resolving the five bio-IN species is described by a paper from the project (Patade et al. 2021).

Numerical modeling

The new empirical parameterization (EP) scheme resolving the five groups was implemented in an adiabatic parcel model. An idealized simulation of deep ascent of a parcel at water saturation was performed for the Amazon aerosol conditions near Manaus. Biological IN were predicted to prevail in the overall ice nucleation at subzero temperatures warmer than -20 ^oC (Fig. 2).

Cloud modelling

The EP has been implemented in our aerosol-cloud model (AC) for simulations of a deep convective storm observed over Oklahoma in the Spring of 2011. AC predicts the microphysical, dynamical and radiative properties of clouds. AC represents at least 7 chemical species of aerosol: primary biological aerosols, non-biological insoluble organics, soluble organics, sea-salt, ammonium sulphate, mineral dust and soot. Interstitial and immersed/embedded components of each aerosol species are predicted in the air, in the cloud and in the precipitation. AC predicts the active concentrations of ice nuclei (IN) and cloud condensation nuclei (CCN) from the chemistry, sizes and loading of aerosols, which vary with height. There are 5 microphysical species represented, namely cloud-droplets, ice crystals, snow, rain and graupel/hail.

Figure 2: The number concentration of biological ice nuclei predicted by empirical parameterization as a function of supercooling in a water-saturated air parcel. The number concentrations of dust, soot, and biological ice nuclei predicted by the empirical ice nucleation scheme by Phillips et al. (2013) (mentioned as PH13 in the plot) are also shown for comparison. The error bars of observed IN concentrations indicates the standard deviations estimated based on the uncertainties in the measurements. An error bar in bold red on the Biological (model) line indicated uncertainties in the estimated biological IN at a temperature colder than −15^oC. From Patade et al. (2021).

Progress during the Project

The project was completed in 2020. A postdoctoral scholar was hired for all four years of the project. The new EP scheme is described in a paper described at Journal of the Atmospheric Sciences (Patade et al. 2021).

Applying this multi-species approach to treatment of biological ice nucleation in the aerosol-cloud model (AC), a mesoscale storm system observed in USA was simulated. The predicted rain rate at the ground was increased by 10% from inclusion of the PBAPs. The average ice concentration in convective cloud was altered by only a few percent. These changes were found to be scarcely significant, because other sources of ice prevail, such as non-biological ice nucleus aerosols and various types of fragmentation of pre-existing ice precipitation.

During a subsequent project funded by US Department of Energy, via a subaward from University of Oklahoma, these modeling results were published in a sequel paper. Little impact from bioaerosols on the mesoscale multicell convective system was predicted (Patade et al. 2022).

Bibliography

Patade, S., Phillips, V. T. J., Amato, P., Bingemer, H. G., Burrows, S. M., DeMott, P. J., Goncalves, F. L. T., Knopf, D. A., Morris, C. E., Alwmark, C., Artaxo, P., Pöhlker, C., Schrod, J., and B. Weber, 2021: Empirical formulation for multiple groups of primary biological ice nucleating particles from field observations over Amazonia. J. Atmos. Sci., 78, 2195–2220

Patade, S., Waman, D., Deshmukh, A., Gupta, A. K., Jadav, A., Phillips, V. T. J., Bansemer, A., Carlin, J., and A. Ryzhkov, 2022: The influence of multiple groups of biological ice nucleating particles on microphysical properties of mixed-phase clouds observed during MC3E. Atmos. Chem. Phys., 22, 12055–12075