Parameterizing cloud condensation nuclei concentrations during HOPE

An aerosol model was used to simulate the generation and transport of aerosols over Germany during the HD(CP)2 Observational Prototype Experiment (HOPE) field campaign of 2013. The aerosol number concentrations and size distributions were evaluated against observations, which shows satisfactory agre...

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Bibliographic Details
Published in:Atmospheric chemistry and physics 2016-09, Vol.16 (18), p.12059-12079
Main Authors: Hande, Luke B, Engler, Christa, Hoose, Corinna, Tegen, Ina
Format: Article
Language:English
Subjects:
Aerosol concentrations
Aerosols
Analysis
Carbon
Cloud condensation nuclei
Cloud condensation nuclei concentrations
Clouds
Clouds (Meteorology)
Computer simulation
Condensation
Condensation nuclei
Dust
Nucleus
Parameterization
Physical properties
Precipitation
Prototypes
Regions
Simulation
Spatial variability
Spatial variations
Standard deviation
Temporal variability
Temporal variations
Velocity
Vertical velocities
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Summary:An aerosol model was used to simulate the generation and transport of aerosols over Germany during the HD(CP)2 Observational Prototype Experiment (HOPE) field campaign of 2013. The aerosol number concentrations and size distributions were evaluated against observations, which shows satisfactory agreement in the magnitude and temporal variability of the main aerosol contributors to cloud condensation nuclei (CCN) concentrations. From the modelled aerosol number concentrations, number concentrations of CCN were calculated as a function of vertical velocity using a comprehensive aerosol activation scheme which takes into account the influence of aerosol chemical and physical properties on CCN formation. There is a large amount of spatial variability in aerosol concentrations; however the resulting CCN concentrations vary significantly less over the domain. Temporal variability is large in both aerosols and CCN. A parameterization of the CCN number concentrations is developed for use in models. The technique involves defining a number of best fit functions to capture the dependence of CCN on vertical velocity at different pressure levels. In this way, aerosol chemical and physical properties as well as thermodynamic conditions are taken into account in the new CCN parameterization. A comparison between the parameterization and the CCN estimates from the model data shows excellent agreement. This parameterization may be used in other regions and time periods with a similar aerosol load; furthermore, the technique demonstrated here may be employed in regions dominated by different aerosol species.
ISSN:1680-7324
1680-7316
1680-7324
DOI:10.5194/acp-16-12059-2016