Extended Abstract (1.7M)P6B.3
Retrieval of the gross structure of reflectivity: correcting for degraded peak values
Roberto V. Calheiros, São Paulo State University, Bauru, São Paulo, Brazil; and A. B. D'Oliveira
Increasing resolution of atmospheric and hydrological models is prompting the development of efforts to make available radar data matching that demand. The problem represented by the smoothing of the reflectivity structure, imposed by a finite antenna beam, is an old object of concern in radar meteorology. It is a major factor contributing to the ambiguous nature of radar quantitative measurements of precipitation. Such an ambiguity is a most outstanding issue and remains an unsolved problem, challenging the community of the area. The IPMet/UNESP runs an operational program for providing radar observations to a vast region covering most of the State of São Paulo, a highly populated area with strong economic activity. Products made available to users undergo a processing suite, from data acquisition to dissemination, which results in a loss of the native resolution at near radar ranges and a fictitious resolution at mid and far ranges. This is more so when one considers that the two radars operated by IPMet (Bauru/BRU – 22.35º S, 49.03º W, Presidente Prudente/PPR – 22.12º S, 51.38º W) exhibit an antenna beam two degree wide, and observations at far ranges are explored as much as possible. Recent statistics on deterioration of reflectivity gradients with increasing distance of rain cells to the radar, compiled for BRU, have shown the severe negative impact imposed by the beam smoothing on precipitation fields with steep gradients, typical for the coverage area. Within IPMetsx programs of radar product improvement, a research is being conducted in an attempt to retrieve the gross structure of the observed reflectivity distributions. Such research is complementary to the studies on range corrections, since long being developed at the Institute. This paper presents the results already obtained in the exploratory phase now being carried out with the final goal of providing real time operational products with “corrected” reflectivity field structure. Those results refer specifically to the correction of Zmax values within storms. Events from both the “dry-to-wet” season and peak summer were selected, which featured typical convective activity, situated along, or near, the BRU and PPR radar axis. Cross sections through some representative storms, made evident the strong intensity nature of the selected events. They are distributed to the East of BRU, West of PPR and between the radars, at varying distances. Radar data are B scan like matrices, from which fixed range bin azimuth arcs passing through reflectivity maxima were chosen. In this work the theoretical treatment of Donaldson (1965) was adopted. Accordingly, Gaussians functions were fitted to the observed storm structures. From the fitted Gaussians values for the second derivative at maximum reflectivity were obtained. Corrections were then derived for the measured maximum reflectivity. Irrespective of being in between the radars, or at their eastern or western sides, the gaussian functions adjusted to the azimuth storm profiles did not show, in general, significant shape variations. When distance from the respective observing radar is taken into account, range effects are clearly noted. In general, peak corrections provided values compatible with expected reflectivities, for storms at near and mid ranges. At far distances, consistently with the pronounced range effects, the new Zmax values are much below the expected ones, although corrections follows a positive trend being substantially higher than those for the shorter ranges. In an analogous way, second derivative values coherently decreases with increasing distance. Seasonal distribution of corrections are, in general, compatible with the typical intensity of convective activity, and the corresponding gradient steepness. Continuation of this work will focus on the development of algorithms to generate corrected images through approaches like neural network supported Gabor filter banks, in an operational scenario.
Poster Session P6B, Quantitative Precipitation Estimation Forecasting and Hydrological Applications
Tuesday, 7 August 2007, 1:30 PM-3:30 PM, Halls C & D
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