Abstract By using a Doppler Weather Radar (DWR) at Shriharikota (13.66°N & 80.23°E), an Artificial Neural Network (ANN) based technique is proposed to improve the accuracy of rain intensity estimation. Three spectral moments of a Doppler spectra are utilized as an input data to an ANN. Rain intensity, as measured by the tipping bucket rain gauges around the DWR station, are considered as a target values for the given inputs. Rain intensity as estimated by the developed ANN model is validated by the rain gauges measurements. With the help of a developed technique, reasonable improvement in the estimation of rain intensity is observed. By using the developed technique, root mean square error and bias are reduced in the range of 34–18% and 17–3% respectively, compared to Z–R approach.


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    Titel :

    An Artificial Neural Network based approach for estimation of rain intensity from spectral moments of a Doppler Weather Radar


    Beteiligte:
    Dutta, Devajyoti (Autor:in) / Sharma, Sanjay (Autor:in) / Sen, G.K. (Autor:in) / Kannan, B.A.M. (Autor:in) / Venketswarlu, S. (Autor:in) / Gairola, R.M. (Autor:in) / Das, J. (Autor:in) / Viswanathan, G. (Autor:in)

    Erschienen in:

    Advances in Space Research ; 47 , 11 ; 1949-1957


    Erscheinungsdatum :

    2011-02-01


    Format / Umfang :

    9 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch