The intensity returns obtained by a radar from precipitation are well known to fluctuate violently in space and time. We present a systematic study of the resolution dependence time series with overlapping time resolutions spanning 10 orders of magnitude (0.77 ms to 4 months), of the fluctuating radar echo from precipitation. The results undermine the current assumptions of homogeneity of rainfield at scales smaller than the radar resolution, due to Marshall and Hitschfeld (1953), by showing that the only length scales identifiable in the time series are those of the radar pulse volume, the wavelength, and a very small inner scale of the order of millimeters. An analysis of the multiscaling nature of the time series of echo fluctuations reveals multiscaling behaviour at scales down to the resolution or pulse volume scale. Since there are no a priori scales in the rainfield we proceed to model the fluctuating radar echo by assuming a multiscaling model of rainfield variability which extends to sub-resolution scales. A systematic analysis of the statistical behaviour of computed reflectivities from this variability gives a full statistical description of reflectivity originating from multiscaling variability, and solves the scalar multifractal radar observer's problem. Computation of time series of reflectivities from a time-space representation of this variability reveals quantitative and qualitative behaviours consistent with those of observed echo fluctuation time series. We conclude that a multiscaling model of the rainfield which extends to the smallest scales of the rainfield is consistent with observation.

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Thesis (MEng)--University of South Australia, 2000

Thesis (MEng in Electronics)--University of South Australia, 1996

Bibliography: leaves 106-110. / xii, 110 leaves : ill. ; 30 cm. / Title page, contents and abstract only. The complete thesis in print form is available from the University Library. / Presents a novel system for automated track association, which provides significant improvement on previously proposed methods. The track association system is designed on the premise that the characteristic pattenrs of multimode propagation are a function of the ionospheric conditions. One component of the track association system models the multimode patterns over the radar coverage. An estimated multimode patterns can be compared to the patterns formed by observed tracks, to determine if the observed tracks are multimode tracks from a common target. The comparison of the estimated multimode patterns to be observed track patterns is performed with an association metric. The association metric requires certain parameters of the multimode patterns to be modelled over the radar coverage. / Thesis (Ph.D.)--University of Adelaide, Dept. of Electrical and Electronic Engineering, 1999

Typescript (photocopy) / 1 v. (various paging) : ill., plans ; 30 cm. / Title page, contents and abstract only. The complete thesis in print form is available from the University Library. / Thesis (Ph.D.) Dept. of Electrical Engineering, University of Adelaide, 1981

Bibliography: leaves 106-110. / xii, 110 leaves : ill. ; 30 cm. / Title page, contents and abstract only. The complete thesis in print form is available from the University Library. / Presents a novel system for automated track association, which provides significant improvement on previously proposed methods. The track association system is designed on the premise that the characteristic pattenrs of multimode propagation are a function of the ionospheric conditions. One component of the track association system models the multimode patterns over the radar coverage. An estimated multimode patterns can be compared to the patterns formed by observed tracks, to determine if the observed tracks are multimode tracks from a common target. The comparison of the estimated multimode patterns to be observed track patterns is performed with an association metric. The association metric requires certain parameters of the multimode patterns to be modelled over the radar coverage. / Thesis (Ph.D.)--University of Adelaide, Dept. of Electrical and Electronic Engineering, 1999