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Updated: Nov 27, 2025
12:11
Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry
Published on: April 8, 2020
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On the relationship between cloud water composition and cloud droplet number concentration.
Alexander B MacDonald1, Ali Hossein Mardi1, Hossein Dadashazar1
1Department of Chemical and Environmental Engineering, University of Arizona, Tucson, AZ, USA.
Atmospheric Chemistry and Physics
|December 4, 2020
Summary
This study reveals that cloud droplet number concentration (Nd) is best predicted by total sulfate, with ocean tracers like sodium and organic tracers like oxalate also important. Environmental factors like turbulence and smoke influence these relationships, impacting cloud properties.
Area of Science:
- Atmospheric Chemistry
- Cloud Physics
- Aerosol Science
Background:
- Aerosol-cloud interactions are a major source of uncertainty in climate change projections.
- Predicting cloud microphysical parameters, like cloud droplet number concentration (Nd), is challenging.
- Empirical relationships between Nd and aerosol properties are widely used in climate research.
Purpose of the Study:
- To analyze the relationships between cloud droplet number concentration (Nd) and cloud water chemical composition.
- To investigate the influence of environmental factors on these composition-Nd relationships.
- To improve the prediction of cloud microphysical parameters for climate models.
Main Methods:
- Analysis of 385 cloud water samples collected from marine stratocumulus clouds off the California coast.
- Application of single- and multispecies log-log linear regressions to predict Nd using chemical composition.
- Stratification of data based on turbulence, smoke influence, and in-cloud height to assess environmental effects.
Main Results:
- Total sulfate was the single species that best predicted Nd (R^2=0.40).
- Multispecies regressions showed diminishing returns, with six or more species yielding insignificant models.
- The best multispecies models included sulfate, an ocean tracer (e.g., sodium), and an organic tracer (e.g., oxalate).
- Turbulence enhanced the correlation between Nd, sulfate, and sodium.
- Smoke influence improved correlations for biomass burning tracers (oxalate, iron).
- In-cloud height affected correlations: sulfate and sodium best predicted Nd at cloud top, while iron and oxalate correlated best at cloud base.
Conclusions:
- Cloud water chemical composition, particularly sulfate, provides valuable information for predicting cloud droplet number concentration.
- Environmental factors significantly modulate the relationships between cloud composition and Nd.
- These findings can help reduce uncertainties in aerosol-cloud interactions and climate forcing estimations.
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