Session 8A.2 Radar observations of rainfall variability using non-Rayleigh signal fluctuations

Wednesday, 8 August 2007: 12:00 AM
Hall A (Cairns Convention Center)
A. R. Jameson, RJH Scientific, Inc., Arlington, VA; and A. B. Kostinski and D. A. Brunkow

Presentation PDF (333.1 kB)

The spatial and temporal variability of precipitation is widely recognized. In particular, rainfall rates (R) fluctuate the most in regions where the raindrops are clustered and where mean conditions are changing (statistical heterogeneity). For purposes requiring as quantitative radar measurements as possible, this variability may often challenge our ability to make precise measurements. Indeed, at times the very meaning of an average rainfall rate (whether using conventional or polarimetric radars) is likely to become quite ambiguous. It would, therefore, be useful to identify those locations where this variability may be particularly problematic. In this work a technique is proposed and applied to quantify this variability using deviations from Rayleigh statistics of intensity (I) measurements. Using results from a different paper in this conference, it is shown analytically that in conditions of clustering and statistical heterogeneity, the square of the intrinsic relative dispersion of the radar reflectivity factor, Z, is the clustering index for each component of the heterogeneous rain appropriately weighted by the square of the fractional contribution that each component makes to the reflectivity factor. A technique is described for separating the Rayleigh signal contributions to the observed relative dispersions from those arising from clustering and statistical heterogeneities. Applications to conventional meteorological radar measurements are illustrated. Often, but not always, the greatest ambiguities in estimates of the average rainfall rate occur just where R are the largest and presumably where accurate estimates are most important. This ambiguity is not statistical. Instead these results show precisely where no single average value applies uniformly to the entire domain. These examples also demonstrate that the appropriate observations are feasible using current conventional meteorological radars with adequate processing capabilities. However, changes in radar technology necessary to make such observations more routinely and more precisely are also suggested.
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