Applications of Polarized Waves in Radar Sensing of Precipitation: Computational Studies.
The research presented here deals with applications of polarized microwaves in the remote sensing of precipitation. The thesis consists of three distinct works but the extraction of microphysical information acquired from remote measurements of precipitation, i.e. the determination and separation of particle size, shape, and orientation is the common theme. While there are a variety of instruments that can be used in precipitation sensing, this work deals with active sensors in the microwave region, i.e. radars. Technological advances now allow coherent measurements, i.e. the amplitude, relative phase and polarization of the backscattered signals can be obtained. Wave polarization is sensitive to the shape and orientation of scattering objects such as raindrops. For example, it is possible to distinguish between a collection of spheres and a collection of randomly oriented rods by the presence of a cross-polarized return. The use of polarized radar waves to study precipitation microphysics is examined here using computational methods and Monte Carlo simulations. A Random Phase Model is implemented which simulates fluctuating time series of polarimetric radar measurements. Characteristic (optimal) polarizations are then used to extract and separate shape and orientation information of meteorological significance. Of particular note are the parameters asymmetry ratio and optimal tilt which show promise in separating shape and orientation effects.
- Pub Date:
- January 1995
- Physics: Atmospheric Science; Remote Sensing