Inferring microstructure and turbulence properties in rain through observations and simulations of signal spectra measured with Doppler–polarimetric radars

Abstract

Doppler radars are able to measure important parameters of the target velocity. In contrast, polarimetric radars are very sensitive to features of the target shape and orientation relative to the radar beam direction. This chapter describes a novel Doppler–polarimetric approach to radar remote sensing. The combination of the Doppler ability and polarization diversity in the radar technology enables more comprehensive investigations of objects and phenomena in radar coverage. The discussion is adapted to the case of atmospheric remote sensing. A special case of cloud and precipitation observations is considered in greater detail. Mathematical models of signals and spectra of Doppler–polarimetric returns are discussed. It is demonstrated (theoretically, by simulation, and by real data processing) that important parameters of dynamic characteristics and microstructure of meteorological objects can be retrieved from Doppler–polarimetric observations. These results lead to new interesting and important applications like turbulence intensity measurement, drop size distribution estimation, recognition of type of scatterers, detection of hail zones, etc.