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Science Areas
Environmental Transformations and Interactions

Airborne Measurements Shed Light on Accuracy of Cloud Physics Theory

A study shows that prevailing theory can predict the number of cloud condensation nuclei under certain conditions.   

airplane flying in sky

Researchers used measurements collected by research aircraft over the Department of Energy’s Southern Great Plains site to assess how closely a widely held cloud physics theory predicted the number and properties of tiny aerosol particles that are the basis for cloud formation.  (Image courtesy of the Atmospheric Radiation Measurement User Facility.)

The Science 

Clouds in the atmosphere form when water vapor condenses around tiny aerosol particles, or nuclei, suspended in the atmosphere. Climate simulations use theoretical models to determine how many of these aerosols and what types are present. But how well does theory match reality? A multi-institutional team of researchers used airborne measurements of aerosols from the Department of Energy (DOE) Southern Great Plains site to assess the differences in what is called a closure study. Their results showed that, under certain conditions, theoretical modeling can accurately predict the number and properties of cloud condensation nuclei with 80 percent certainty. 

The Impact 

Atmospheric aerosol particles that serve as cloud condensation nuclei can influence climate and the water cycle, including how long clouds last and how much precipitation falls. To represent these properties, climate models often use simplified numerical treatments based on cloud physics and one geographic location. These simplifications contribute to uncertainties in predicted aerosol properties. This study is one of the first to use airborne measurements from a wider geographic region that receives both local and long-range transported aerosols. The results can help models better predict the number and properties of cloud condensation nuclei, as well as their impact on climate. 

Summary 

A multi-institutional team of researchers used data taken by a research aircraft from the 2016 Holistic Interactions of Shallow Clouds, Aerosols, and Land Ecosystems (HI-SCALE) field campaign, which was conducted over the Atmospheric Radiation Measurement’s (ARM) Southern Great Plains atmospheric observatory in north-central Oklahoma. ARM is a Department of Energy (DOE), Office of Science User Facility, and the research aircraft was part of the ARM Aerial Facility. Researchers used these facilities and a single-particle mass spectrometer at EMSL, the Environmental Molecular Sciences Laboratory, another DOE Office of Science User Facility, to analyze the size, number, and properties of cloud condensation nuclei using different assumptions. They discovered that if all the particles were composed of 100 percent organic compounds, or if the particle population consisted of three aerosol types, each composed of pure organic compounds, sulfates, and nitrates, then it was possible to theoretically calculate cloud condensation nuclei numbers within an 80 percent certainty under some thermodynamic condition assumptions. The conclusions may help improve modeling of aerosols in climate models. 

Contacts

Gourihar Kulkarni, Pacific Northwest National Laboratory, gourihar.kulkarni@pnnl.gov 

Jerome Fast, Pacific Northwest National Laboratory, jerome.fast@pnnl.gov 

Funding 

This research was supported by the DOE, Office of Science, Biological and Environmental Research, Atmospheric System Research program. The National Oceanic and Atmospheric Administration Air Resources Laboratory provided the transport and dispersion model as well as some data. The HI-SCALE field campaign was supported by the Atmospheric Radiation Measurement User Facility. A portion of the research was conducted at the Environmental Molecular Sciences Laboratory User Facility. 

Publication

G. Kulkarni, et al., “Cloud condensation nuclei closure study using airborne measurements over the Southern Great Plains.” Journal of Geophysical Research: Atmospheres 128, e2022JD037964 (2023). [DOI: 10.1029/2022JD037964]