An intelligent system to real time rainfall prediction using radar data

This work presents a new approach for rainfall measurements making use of weather radar data for real time application to the radar systems operated by institute of Meteorological Research (IPMET) - UNESP - Bauru - SP-Brazil. Several real time adjustment techniques has been presented being most of them based on surface rain-gauge network. However, some of these methods do not regard the effect of the integration area, time integration and distance rainfall-radar. In this paper, artificial neural networks have been applied for generate a radar reflectivity-rain relationships which regard all effects described above. To evaluate prediction procedure, cross validation was performed using data from IPMET weather Doppler radar and rain-gauge network under the radar umbrella. The preliminary results were acceptable for rainfalls prediction. The small errors observed result from the spatial density and the time resolution of the rain-gauges networks used to calibrate the radar.

Climatologia de tempestades na área central do Estado de São Paulo usando radar meteorológico

A climatological characterization of storm properties during two summer seasons, viz. 1998-1999 and 1999-2000, based on observations from the Bauru S-band Doppler radar, was obtained from the TITAN Software of the National Center for Atmospheric Research (Boulder, Co), implemented at IPMet. Parameters, such as mean volume, mean area, mean and maximum echo tops, mean and maximum reflectivity, as well as speed and direction of precipitating systems were determined using the reflectivity >25, 30 and 40 dBZ and a volume >30 km3 as thresholds for storm identification. For the first time, the spatial distributions of these parameters were determined in the central State of São Paulo, based on radar observations. It was found that some preferential areas, where most of the convective activity was concentrated during the study period, were located along the Tietê River. The mean maximum reflectivity field has highlighted preferential regions for convection to develop over the metropolitan area of Campinas, which in turn was reinforced by the distribution of the echo tops and reflectivity >40 dBZ.