Presently, typical operations of NWP models use horizontal resolutions ranging from approximately 20 to 50 km in the global scale, and around 10 km for limited area in the mesoscale. Towards the end of this decade, plans call for a new generation of atmospheric models, substituting for those running today, which will be non-hydrostatic and will operate in the 1-3 km range of grid sizes. For that, a significantly improved precipitation distribution representation should be achieved. As a matter of fact important programs approaching this issue have been carried out, e. g. the COST-717 European initiative, dedicated to promoting the use of radar data in both NWP and hydrological models. Yet, the modeling of hydrologic models which critically requires an accurate estimate of the spatial distribution of rainfall has driven and ever growing demand for high-resolution rainfall estimates based on radar. In that sense, a recent example emphasizing the relevance of high-resolution radar data is found in Hoblit and Curtis (2001) where it is stated that Gage-adjusted radar rainfall estimates, when used with a GIS, can dramatically improve the rainfall estimate over a study area. As a matter of fact, radar data resolutions for many hydrological applications involve unit cell sizes of less than (1x1) km2. For operational settings where a limited number of radars are available for observations of areas at further ranges, yet demanding relatively better-resolved rainfall fields, the associated loss of definition of the radar derived rain structure is a matter of special concern. Such a situation is experienced in - and around - the State of S.Paulo, where a three-radar network surveys an space-extensive river basin network. This was a major factor prompting research & operations institutions in the State to develop efforts aiming to assess the magnitude of this (old ) problem. In fact, Zawadzki back in 1982 presented a quite comprehensive paper were the precision of radar measurements are dealt with in a particularly appropriate way (Zawadzki, I.,. The quantitative interpretation of weather radar measurements. Atmosphere-Ocean, 20, 158-180, 1982). He points out the effects of the magnitude of gradients in a calculation of the mean rainfall over an area, and approaches the question of the change of the radar reflectivity factor and its spatial variability, with range. Following Zawadzki's work, Torlaschi and Humphries (1983) carried out a research on the statistics of reflectivity gradients, on the grounds of its relevance to improve the precision of radar measurements of the reflectivity patterns, from which the structure of precipitation is obtained. IPMet operates two radars of the S.Paulo network, and tackles the problem of retrieval of the structure of precipitation as a major topic of its research program. The most recent work on this at IPMet approached the representativeness of the rain field as observed by TRMM PR (Calheiros and Machado , 2005). The present paper is a preliminary verification of the distribution with range of reflectivity gradients from the Bauru radar (BRU) observations, centered on a summer season. Statistics are performed using operational products generated from BRU observations, which are available to the users, in an attempt to assess the extent to which they meet finer resolution requirements. Probability distributions of gradients were computed for the whole, and for each month of, the rainy season (October-March) of 2003/2004, and for different range rings. Both along-range and cross-range directions were explored. Range ring stratification of the family of probability curves, for the mid range of gradient values, followed approximately the intra rainy period classification typically applied in the region, i.e. : transition (October), early summer (November & December), peak summer ( January to mid February) and late summer ( mid February to March). In general, stratification among the curves for each range ring is pronounced for the upper half of the range of gradients, for the along range as well the cross range directions. Comparisons with similar statistics from the summer in Alberta, Canada, indicate that the respective coordinate system in which reflectivity data is presented, is playing a major role in the marked differences of range stratification found between probability distributions for each of those, anyhow, different climatic regions. Processing of BRU data in the same coordinate system as that used in the statistics for Alberta will help to clarify that matter and will be performed next. These early results points at a revision of the routine products of both IPMet radars, presently available to the users, under the aspect of the impact of data presentation in the retrieval of the rain structure.