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.
An Artificial Neural Network based approach for estimation of rain intensity from spectral moments of a Doppler Weather Radar
Advances in Space Research ; 47 , 11 ; 1949-1957
2011-02-01
9 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Doppler Weather Radar. (Video)
NTIS | 1995
Terminal Doppler weather radar
Tema Archiv | 1990
|