Detecting Weather Radar Clutter by Information Fusion With Satellite Images and Numerical Weather Prediction Model Output

A method for detecting clutter in weather radar images by information fusion is presented. Radar data, satellite images, and output from a numerical weather prediction model are combined and the radar echoes are classified using supervised classification. The presented method uses indirect informati...

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Bibliographic Details
Main Authors: Bovith, T., Nielsen, A.A., Hansen, L.K., Overgaard, S., Gill, R.S.
Format: Conference Proceeding
Language:English
Subjects:
Atmospheric modeling
Clutter
Meteorological radar
Numerical models
Predictive models
Radar detection
Radar imaging
Satellites
Spaceborne radar
Weather forecasting
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Description
Summary:A method for detecting clutter in weather radar images by information fusion is presented. Radar data, satellite images, and output from a numerical weather prediction model are combined and the radar echoes are classified using supervised classification. The presented method uses indirect information on precipitation in the atmosphere from Meteosat-8 multispectral images and near-surface temperature estimates from the DMIHIRLAM-S05 numerical weather prediction model. Alternatively, an operational now casting product called 'Precipitating Clouds' based on Meteosat-8 input is used. A scale-space ensemble method is used for classification and the clutter detection method is illustrated on a case of severe sea clutter contaminated radar data. Detection accuracies above 90 % are achieved and using an ensemble classification method the error rate is reduced by 40 %.
ISSN:2153-6996
2153-7003
DOI:10.1109/IGARSS.2006.136