Abstract
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.
Highlights
The influence that aerosols have on cloud microphysics is relatively well established; clouds and aerosols continue to contribute the largest uncertainty to the Earth’s energy budget in climate simulations (Boucher et al, 2013)
We present a parameterization for estimating cloud condensation nuclei (CCN) concentrations which exploits the complexity of an aerosol model to accurately characterize chemical and physical properties of aerosols
Using the parameterization provided by Abdul-Razzak and Ghan (2000), median CCN number concentrations were calculated at 40 different vertical velocities for each time step of modelled aerosol data
Summary
The influence that aerosols have on cloud microphysics is relatively well established; clouds and aerosols continue to contribute the largest uncertainty to the Earth’s energy budget in climate simulations (Boucher et al, 2013). Several modes can be used to define the aerosol sizes (AbdulRazzak and Ghan, 2000; Fountoukis and Nenes, 2005; Liu et al, 2012; Shipway and Abel, 2010), where the parameters of the size distribution are either calculated from an aerosol model or derived from limited observations from a short time period (Rissler et al, 2004). This sentiment has been echoed by Petters and Kreidenweis (2007) To this end, we present a parameterization for estimating CCN concentrations which exploits the complexity of an aerosol model to accurately characterize chemical and physical properties of aerosols. We present a parameterization for estimating CCN concentrations which exploits the complexity of an aerosol model to accurately characterize chemical and physical properties of aerosols All these detailed properties are represented within a simple mathematical model, which is a function of the vertical velocity and atmospheric pressure. It is suggested the parameterization is suitable for other time periods with a similar aerosol load
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