Global models such as the ECHAM5 general circulation model (GCM) are limited to a rather coarse resolution (~100 - 300 km horizontal grid size) so that a process such as precipitation formation can not be resolved. As precipitation is an important process in the hydrological cycle it is important to parameterize the formation process as realistic as possible.
In the standard model version of ECHAM5 the initialization of precipitation is calculated from grid mean quantities, i.e. mass and number of cloud droplets and ice crystals, but even in well mixed clouds it is known that there are regions with more (or less) droplets or ice crystals than represented by the mean, consequently decreasing (or increasing) the local precipitation rate. Furthermore, the liquid water is only categorized into two classes, i.e. cloud water and rain, where the latter is removed from the atmosphere within one time step. Marine stratiform clouds often drizzle. The drizzle may not reach the surface within one time step. Drizzle can also change the stability of the boundary layer. Two PhD projects address these issues and the content of their topics are described below.
The goal is to introduce drizzle (25 - 100 μm) in addition to cloud droplets and rain drops to improve the possible influence of giant CCN (GCCN; e.g. sea salt ≥ 3 μm) on initiating the drizzle process and to study the impact of drizzle on the radiation budget and boundary layer dynamics on a global scale in the ECHAM5 GCM.
Marine stratus (St) and stratocumulus (Sc) cover vast parts of the global oceans and have a substantial role in the Earth's radiative budget, inducing a net cooling. Although they only produce small amounts of precipitation, drizzle has been recognized to have an important impact on both cloud dynamics and microphysics (Feingold et al., JAS 1996).
The formation of drizzle is highly dependent on the onset of the collision-coalescence process, which requires that drops above some critical size are formed. One of the mechanisms leading to these sufficiently large droplets has been perceived to be related to the concentration of GCCN (Posselt & Lohmann, ACP 2008), especially for polluted clouds. Introducing an additional drizzle class in the ECHAM5 will produce a more physical representation of the droplet spectrum (for marine St & Sc) and may improve the representation of drizzle in general.
Figure 3 shows a schematic of the impact of GCCN on non-precipitating clouds
(Courtesy of R. Posselt) and Figure 4 shows a schematic of the introduction of drizzle and the additional microphysical processes, which need
to be accounted for.
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