Scattering in Water Clouds: The Impact of the Spatial Correlation of Particles on The Backscattered Mean Power

In the present work scattering theory in water clouds has been studied. Alternative forms for Maxwell equations have been developed and discretized in order to calculate backscattered mean powers from cloud particles. With simplified discretized equations the backscattered electric field has been approximated for a single particle. This approximation of the electric field is the same as Rayleigh approximation used in meteorological literature. The discretized equations have been implemented in computer code to calculate backscattered power from particles inside a small box, located in the far field of radar. In current radar approach, incoherent Rayleigh approximation is used as the standard scattering theory to retrieve cloud properties. To validate this theory the correlation between particles has been studied. In order to study the influence of inter-particle displacement on correlation between particles, a new idea has been deployed to create turbulence among particles. For different turbulence settings the randomness of the medium has been quantified by the real part of the correlation matrix. In the last chapter both exact and incoherent Rayleigh backscattered mean powers from particles have been calculated. It has been shown that Rayleigh backscattered mean powers are good approximation for uncorrelated particles and both are distributed normally around the same mean value. In case of correlated particles the exact backscattered mean powers have shown to be distributed lognormally. Depending on the degree of correlation their distribution shifts from lognormal to normal, respectively for highly correlated and uncorrelated particles. With statistical results it has been concluded that for correlated water cloud particles, the exact backscattered mean powers will be smaller than the incoherent approximation.Remote sensing of the EnvironmentTelecommunicationsElectrical Engineering, Mathematics and Computer Scienc