Comparison of Cloud Droplet Number Concentrations derived from Remote Sensing Observations and Köhler Theory based Activation Parameterizations

In the present research, the activation parameterization method introduced by Nenes and Seinfeld (2003) was compared and evaluated to a remote sensing-based method by Rusli, Donovan & Russchenberg (2017) for determining the cloud drop number concentration. Both methods have fundamentally different approaches for indirectly determining the cloud droplet number concentration. The parameterization method is based on the Köhler Theory, in which the activation process of particles contained in a rising parcel is modelled for predicting the number concentrations of cloud droplets. The remote sensing method, on the other hand, applies theories about particle-light interactions. Since the remote sensing method determines the cloud droplet concentrations in a more direct manner than the parameterization method, it is regarded here as the reference. An agreement was found between the two models, with a relative error of cloud droplet number concentrations between 41.1% and 78.0%, which lead to errors of the cloud’s scattering intensity in the range of 13% and 26%. Despite some discrepancies between the obtained droplet concentrations, the parameterization model shows similar trends to the remote sensing observations. It was found that the updraft velocity that is needed as input variable for the parameterization model has the largest influence on the model’s prediction of droplets concentrations, and that it is likely to be an important cause for the seen discrepancies. Furthermore, the present research shows how assumptions were made on the size distribution input variable used in the parameterization model, which were not available from observations.Additional Master Thesi