Partitioning ice nucleating particle measurements facilitates improved process-level understanding

Science

Ice nucleating particles (INPs) are a rare subset of particles that can have an outsized impact on the climate. To simulate the effects of INPs, global climate models need to be able to accurately simulate the concentrations of particles known to be good INPs in the ambient atmosphere and include representations of their different ice nucleation efficiencies. Researchers used measurements of aerosol size distributions, INP concentrations, and single-particle composition measurements to identify the different types of, or speciate, INPs at warm and cold temperatures. This novel methodology provides a data set of speciated INPs that can be used to validate simulated INP concentrations.

Impact

Most studies investigating models’ predictive skill for INPs have used total INP concentrations to validate predictions, even though multiple sources of INPs need to be accounted for. The fundamental weakness of these studies is that they cannot determine whether they accurately simulated the component pieces or if multiple errors led to the right answer. To overcome this weakness, this study developed novel methods to speciate INP concentrations into dust, sea spray aerosol (SSA), and bioaerosol. Researchers then used a Lagrangian modeling approach to simulate INP concentrations. They found that the approach adequately simulated dust and SSA INPs, but not bioaerosol. This points to a need for additional research to identify the major factors controlling the emissions and INP efficiency of bioaerosol INPs.

Summary

INPs are a rare subset of atmospheric aerosol that can initiate primary ice formation. There is a significant gap between scientists’ ability to measure INPs and predict their concentrations and variability in large-scale weather and climate models. Accurate simulation of INPs requires representing major particle sources and IN efficiency. Thus, there is a need for measurements of INP concentrations, delineated by particle type, to validate and improve model prediction of INPs.

Speciating INP measurements is technically difficult due to the rarity of these particles. To address this challenge, researchers developed novel methods for speciating INP concentrations into the relative contributions from dust, SSA, and bioaerosol using single-particle measurements. They found that bioaerosols were the primary source of INPs between -12 and -20 °C, while dust was a relatively minor source. They also found that recent simplified model representations of INP activity, known as parameterizations, for dust and SSA accurately predict ambient INP concentrations. Finally, they used the speciated INP concentrations to evaluate INP simulations using a Lagrangian approach, connecting the locally observed aerosol with regionally widespread emissions parameterizations. They were able to skillfully simulate dust and SSA INPs, but not bioaerosol INPs. The inability to simulate bioaerosol INPs was attributed to the lack of a fundamental understanding of bioaerosol types and emission mechanisms as well as the absence of representative INP parameterizations, thereby identifying key areas where model developers can be most impactful.