A combination of weather radar images and electrical discharges using an artificial neural network / Implementação de uma rede neural artificial para associação de imagens de radar meteorológico e dados de descargas elétricas

AUTOR(ES)
DATA DE PUBLICAÇÃO

2003

RESUMO

This work uses radar images together with data of electrical discharges derived from a lightning localization system taken with a Doppler Meteorological Radar as the input to a Neural Network (NN), in order to stablish the non-linear relationship between the reflectivity in the radar images and the atmospheric discharges. Associating these atmospheric discharges to specific storms as for instance the severe thunderstorms where lightning occurrence is higher, we will better be able to understand the physics that governs these meteorological elements and bring better benefits to the society. In this context NNs is a tool that appears as a quite promising alternative that were used in this work to stablish a relationship between meteorological data and the atmospheric discharges. For the development of this work it was necessary a great number of activities, from the acquisition, selection and decoding of the radar images, as well as the geographical position reference of the images with the atmospheric discharges, tests of cases and analysis of results. Basically were selected images from products of CAPPI(Z) with reflectivity at 6 km of altitude, CAPPI(V) with wind speed at an altitude of 1 km and ECHOTOP(Z) cloud vertical profile up to 15 km of altitude, in a total of 1288 images. The obtained results are promising, because in spite of still not to be possible to quantify the intensity of the atmospheric discharges generated by NN is possible to verify an increase or decrease of its intensity, that it can aid it forecast and in a specific case the correlation was obout 80%.

ASSUNTO(S)

meteorologia radar redes neurais neural nets radar meteorológico meteorology raios electric discharges meteorological radar

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