Identification of cloud regimes relevant for aerosol-cloud interactions

Project

Cloud are classified into types, classes, or regimes.  The World Meteorological Organisation distinguishes stratus and cumulus clouds and three altitude layers. However, it has proven very  difficult to define cloud regimes objectively. This will be achieved by (1) using high-spatially-, high-spectrally resolved satellite imagery combined with image processing and convolutional neural networks; by (2) combination with available high-resolved simulations for learning cloud types as a function of dynamics and thermodynamics using convolutional neural networks; and by (3) assessing the statistical relationships between cloud properties relevant to quantify and assess cloud adjustments to aerosol cloud interactions.

Supervisors

Johannes Quaas (supervisor), Dino Sejdinovic (co-supervisor), Daniel Klocke (Max-Planck-Institut für Meteorologie, non-academic advisor)

Secondments

3 months at The Alan Turing Institute, 3 months at University of Oxford, 3 months at Max-Planck-Institut für Meteorologie

Enrolment in Doctoral degree

PhD in Meteorology at University of Leipzig