A novel method for ground-based remote sensing of profiles of cloud microphysical properties

• Applicant: Professor Dr. Bernhard Mayer
• Subject Area: Atmospheric Science
• Term: from 2014 to 2018
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 256770551

In this project we develop and apply a novel, ground-based combined passive and active remote sensing method to retrieve vertical profiles of microphysical parameters of convective clouds. Deep convection plays an essential role for climate since it has a large influence on the solar radiation budget as well as on the global water cycle. The lifetime and albedo of deep convective clouds are influenced by the interactions between the cloud droplet growth along the cloud profile and the aerosol uptake. As remote sensing applications from space usually can only observe cloud tops, the ground-based remote sensing of cloud sides can be an essential tool for the investigation of cloud droplet growth. Since classical, passive retrievals of the cloud droplet size are commonly based on 1D radiative transfer calculations they fail when faced with complex cloud geometries on a high spatial resolution. In our project we investigate the implications of a inhomogeneous cloud geometry for the remote sensing of cloud droplet profiles and consider the distinct threedimensional nature of convective clouds by extensive 3D radiative transfer calculations. As an essential part of this project we are combining a passive spectrometer with an active cloud radar into a synchronous measurement system. Based on data measured with the passive spectrometer and active cloud radar, we develop a geometry-aware retrieval of cloud microphysics. With this proposal we provide an interim report of the first funding period and apply for one additional year for the PhD candidate in order to enable him to successfully complete this project and to obtain his doctorate degree. In this additional year the methods developed for the spectral imager and the cloud radar will be combined into a geometry-aware retrieval of cloud microphysics. This retrieval will then be tested on measurements and validated with in-situ data gathered during the HDCP2 field campaign.

• DFG Programme: Research Grants
• Participating Person: Dr. Tobias Zinner