4th workshop on assimilating satellite cloud and precipitation observations for NWP

Visible satellite images provide high-resolution information on
clouds. However, so far they have not been assimilated directly for
operational purposes, as multiple scattering dominates in the visible
spectral range and makes radiative transfer computations with standard
methods complex and slow. Only recently, sufficiently fast and
accurate forward operators have become available. Here we report on
the design of a lookup-table based forward operator and developments
aimed at increasing its accuracy. Approximations for three-dimensional
radiative transfer effects and corrections for mixed-phase clouds are
addressed. Moreover, the potential of alternative approaches based on
machine learning is discussed. These approaches could be competitive
in terms of speed and accuracy and allow for including
additional radiative transfer effects and aerosols.