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Volume 16, issue 18
Atmos. Chem. Phys., 16, 12059-12079, 2016
https://doi.org/10.5194/acp-16-12059-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Special issue: HD(CP)2 Observational Prototype Experiment (AMT/ACP...

Atmos. Chem. Phys., 16, 12059-12079, 2016
https://doi.org/10.5194/acp-16-12059-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 27 Sep 2016

Research article | 27 Sep 2016

Parameterizing cloud condensation nuclei concentrations during HOPE

Luke B. Hande1, Christa Engler2, Corinna Hoose1, and Ina Tegen2 Luke B. Hande et al.
  • 1Karlsruhe Institute of Technology, Karlsruhe, Germany
  • 2Leibniz-Institute for Tropospheric Research, Leipzig, Germany

Abstract. 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.

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An aerosol model was used to simulate the concentration of natural and anthropogenic aerosols over Germany. Using a detailed parameterization of CCN activation, which includes information of aerosol chemical and physical properties, CCN concentrations were calculated. Using these results, a series of best fit functions were used to define a new parameterization, which is a simple function of vertical velocity and pressure. The new parameterization is easy to implement in models.
An aerosol model was used to simulate the concentration of natural and anthropogenic aerosols...
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