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.

Fotointerpretacao comparativa de fotografias pancromaticas, imagens de radar e de satelite

Three types of imagery were evaluated for mapping drainage patterns and vegetation in a 100 000 ha area of Sao Paulo State, Brazil. The drainage measurements were drainage density, frequency of channels and texture ratio, studied on circular samples of 10 km2 for panchromatic photography and 100 km2 for radar and satellite images. The vegetation types were forest, pasture, sugar cane and rice, studied on circular samples of 100 km2. Radar images were the most convenient method to study drainage patterns and the land forms of large areas, while Landsat imagery was most efficient for the study of vegetative cover, although panchromatic photographs were the most accurate method.-from Field Crop Abstracts

Mapeamento de solos atraves de imagens de radar e de satelite.

The objective of the present work was the improvement of the methodology for soil mapping through the drainage network with the aid of Landsat data. The drainage network of the area studied was delineated and the soils identified. The main problem of the method has been the characterization of the contact between soil units when it is not abrupt, and in this case field trips and the analysis of the relief has been used to solve doubts.-from English summary

A radar reflectivity-runoff model for use in flood warning

This model connects directly the radar reflectivity data and hydrological variable runoff. The catchment is discretized in pixels (4 Km × 4 Km) with the same resolution of the CAPPI. Careful discretization is made so that every grid catchment pixel corresponds precisely to CAPPI grid cell. The basin is assumed a linear system and also time invariant. The forecast technique takes advantage of spatial and temporal resolutions obtained by the radar. The method uses only the measurements of the factor reflectivity distribution observed over the catchment area without using the reflectivity - rainfall rate transformation by the conventional Z-R relationships. The reflectivity values in each catchment pixel are translated to a gauging station by using a transfer function. This transfer function represents the travel time of the superficial water flowing through pixels in the drainage direction ending at the gauging station. The parameters used to compute the transfer function are concentration time and the physiographic catchment characteristics. -from Authors

The first case study of a thunderstorm in South Africa based on dual- Doppler radar observations

On 27 March 1991, an isolated thunderstorm passed between the two CSIR Doppler radars, spaced about 45km apart. Both radars simultaneously recorded Doppler data of the storm, and a detailed case study during an 11-min period is presented. Air motions synthesized from these data provide the first three-dimensional display of Doppler-derived wind fields within a multicell storm on the Transvaal Highveld. Regions of high divergence values (10 -2s -1) at low levels were found mostly in close proximity to reflectivity maxima (45-51 dBZ), which is consistent with findings from North America, that gravitational loading by the precipitation plays a key role in the initiation and maintenance of downdraughts. -from Authors

Statistics on tropical convective storms observed by radar

Convective storm rainfall is of special importance to urban hydrological studies due to its temporal and spatial variability. Although dense networks of recording rain gauges can be employed to characterize such rainfall, very few investigations of this type have been undertaken due to their prohibitive cost. This paper reports some data on characteristics of tropical convective storms obtained from radar at Bauru in the State of São Paulo, Brazil. Periods of convective precipitation were identified by exclusion of those related to frontal activity with the help of synoptic maps and the radar screen record. The occurrence and evolution of convective storms were observed in two 28 km × 28 km windows obtaining information on the life history of convective cells and the magnitude of rainfall. Frequency distributions of the time of occurrence of convective rainfall, cell size, area covered, life duration and maximum and average rainfall observed in the experimental areas are presented and discussed.

Determination of resonant frequencies of triangular and rectangular microstrip antennas, using artificial neural networks

This paper presents models that can be used in the design of microstrip antennas for mobile communications. The antennas can be triangular or rectangular. The presented models are compared with deterministic and empirical models based on artificial neural networks (ANN) presented in the literature. The models are based on Perceptron Multilayer (PML) and Radial Basis Function (RBF) ANN. RBF based models presented the best results. Also, the models can be embedded in CAD systems, in order to design microstrip antennas for mobile communications.

Análise de superfície de tendência aplicada à chuva, medida por radar meteorológico, nas regiões de Assis e Piracicaba, SP

This paper presents the results from lineal trend surface analysis technique application. The purpose was to detect positive and negative anomalies in the rain measure distribution obtained by the meteorological radar Doppler, band S, located in Bauru, during the period of 21 of October/2004 to 29 of April/2005 in the areas of Assis and Piracicaba. Using three Z-R radar relations for rain quantification was chosen the specific equation Z = 32R1,65, as the best one. The results showed that the applied methodology was able to indicate the space distribution of the rain accumulated, identifying and locating the regions where there was rainy excess and rainy lack during each analyzed period. Such results indicate areas with larger pluvial impact and consequently more favorable for environmental damages.

Weight vector estimation of circular arrays of antennas using Artificial Neural Networks

This paper presents a model for the control of the radiation pattern of a circular array of antennas, shaping it to address the radiation beam in the direction of the user, in order to reduce the transmitted power and to attenuate interference. The control of the array is based on Artificial Neural Networks (ANN) of the type RBF (Radial Basis Functions), trained from samples generated by the Wiener equation. The obtained results suggest that the objective was reached.

New contributions to the determination of resonance frequencies of rectangular microstrip antennas by neural networks

This paper uses artificial neural networks (ANN) to compute the resonance frequencies of rectangular microstrip antennas (MSA), used in mobile communications. Perceptron Multi-layers (PML) networks were used, with the Quasi-Newton method proposed by Broyden, Fletcher, Goldfarb and Shanno (BFGS). Due to the nature of the problem, two hundred and fifty networks were trained, and the resonance frequency for each test antenna was calculated by statistical methods. The estimate resonance frequencies for six test antennas were compared with others results obtained by deterministic and ANN based empirical models from the literature, and presented a better agreement with the experimental values.

Is it possible to make pixel-based radar image classification user-friendly?

In this paper we would like to shed light the problem of efficiency and effectiveness of image classification in large datasets. As the amount of data to be processed and further classified has increased in the last years, there is a need for faster and more precise pattern recognition algorithms in order to perform online and offline training and classification procedures. We deal here with the problem of moist area classification in radar image in a fast manner. Experimental results using Optimum-Path Forest and its training set pruning algorithm also provided and discussed. © 2011 IEEE.

Geoestatística aplicada à acumulação da precipitação pluviométrica com radar meteorológico

Pós-graduação em Agronomia (Energia na Agricultura) - FCA