Remote sensing of clouds and precipitation using active and passive microwave observations

Licentiate thesis, 2019

Global observations of clouds and precipitation are of great importance for weather prediction and the monitoring of the climate. Nonetheless, the currently available record of global observations does not constrain the properties of clouds very well owing to the inherent limitations of the observation systems used to produce them. The upcoming Ice Cloud Imager (ICI) microwave radiometer, which will be launched on the next generation of European weather satellites, will improve this situation by providing observations of clouds at sub-millimeter wavelengths. ICI will be the first sensor of its kind to deliver these observations, which will significantly improve the sensitivity to small ice particles and low mass concentrations compared to currently available microwave observations.
This thesis presents research aimed at developing knowledge and methodology required for the modeling and interpretation of the observations that will be provided by ICI. Two studies are presented which propose a method for measuring distributions of ice hydrometeors from ICI-type sub-millimeter observations combined with radar observations.
The first study uses simulated observations to assess the potential benefits of combin- ing sub-millimeter radiometer observations with radar observations for the retrieval of ice hydrometeors. It is found that the combined observations improve the sensitivity to microphysical properties of clouds, which can help to reduce the error in the retrieved mass concentrations for specific hydrometeor types. Furthermore, improved sensitivity to supercooled liquid cloud is found as an additional synergy between the active and passive observations.
The second study aims to validate the results from the first by applying the synergistic retrieval algorithm to observations from a flight campaign. The retrieval algorithm is found to show overall good agreement with in-situ measured ice concentrations taking into account the sensitivity limits of the sensors. In addition to that, indications of a signal from mixed-phase particles are found in observations of convective updrafts. In the two presented studies, a synergistic retrieval algorithm for ice hydrometeors from radar and passive sub-millimeters has been developed, characterized and vali- dated. The method can be applied in a future satellite mission to reduce uncertainties in global observations of clouds or used to study cloud microphysical properties in field campaigns. In addition to that, the presented application to field campaign data provides one of the rare validation cases for the radiative transfer modeling involving clouds at sub-millimeter wavelengths.