Master thesis:  Modeled sensitivity of marine background cloud condensation nuclei concentrations to different sea salt aerosol emission parameterizations

Background: Atmospheric aerosols are crucial in cloud formation processes. For a constant liquid water content, an increase in the aerosol concentration, e.g. due to anthropogenic activities, may result in an increase of the cloud droplet number concentration which in turn may alter the cloud radiative properties (first aerosol indirect effect). Model estimates of the global average first indirect aerosol effect are currently highly uncertain. An important factor in determining the magnitude of the first indirect aerosol effect is the natural, background aerosol concentration. Natural aerosols are emitted from a number of sources, for example deserts, oceans and plants. These mechanically generated aerosols are traditionally assumed to be emitted in the coarse aerosol size fraction (diameter > 1mm) and in high mass concentrations, but rather low number concentrations. However, recent investigations have shown sea salt aerosols may actually be emitted in large numbers in the fine aerosol fraction (diameter < 1mm). This is of specific interest for the aerosol indirect effect since the number of aerosols, especially in the size range 0.1mm < diameter < 1mm, is what really matters for cloud droplet formation. In addition, studies have also shown that the magnitude of the sea salt emissions in the fine fraction may be modulated by the sea surface temperature.

Objective: The main aim of this project is to use the ECHAM-HAM global climate model to examine how a “new” sea salt aerosol emission parameterization (including emissions of aerosols smaller than diameter 1 mm) compares to an “old” sea salt aerosol emission parameterization (excluding emissions of aerosols smaller than diameter 1mm) and how the different emission parameterizations impact on the number of available cloud condensation nuclei. The effect of including a temperature dependence of the sea salt emissions will also be studied.

Requirements: Basic knowledge of programming, data analysis and visualization using e.g. Fortran, IDL, MATLAB is necessary.

Contact: Annica Ekman or Ulrike Lohmann