Remote Sensing of deep convective clouds - A new satellite view

• Applicant: Dr. Tobias Zinner
• Subject Area: Atmospheric Science
• Term: from 2006 to 2008
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 19002093

Clouds and there evolution in a changing climate are a factor of major importance in the prediction of future climate due to their impact on the radiation budget of the earth. At the same time their variability in time and space is a source of uncertainties. Their global distribution and evolution can only be observed by satellite remote sensing. Thus, the uncertainties of standard remote sensing methods as well as the development of novel methods will be an important research topic for the next decade. The effects on existing methods due to (sub sensor resolution) cloud inhomogeneity have been investigated to some extent for low boundary layer clouds. However, no studies have yet been conducted concerning remote sensing of vertically more complex cloud types, e.g. deep convection, although their distinct three-dimensional structure is likely to introduce large errors into standard remote sensing methods. In this project the potential and the uncertainties of different, standard and novel, methods of remote sensing will be examined for deep convective cloud cases. The satellite observations corresponding to known cloud structures will be simulated and remote sensing techniques will be tested for the simulated data. To achieve this objective, complex cloud structures from physical cloud resolving modeling (CRM) will be used. A state-of-the-art Monte Carlo code for the three-dimensional simulation of radiative transfer will be used to simulate the radiance field. In this context, the Monte Carlo code will be optimized to reduce the extensive computing time necessary for 3D Monte Carlo simulations, in particular in the infra-red spectral range.

• DFG Programme: Research Fellowships
• International Connection: USA
• Host: Dr. Robert Cahalan