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| Titel |
Rainfall rate retrieval in presence of path attenuation using C-band polarimetric weather radars |
| VerfasserIn |
G. Vulpiani, F. S. Marzano, V. Chandrasekar, A. Berne, R. Uijlenhoet |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1561-8633
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| Digitales Dokument |
URL |
| Erschienen |
In: Natural Hazards and Earth System Science ; 6, no. 3 ; Nr. 6, no. 3 (2006-06-06), S.439-450 |
| Datensatznummer |
250003507
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| Publikation (Nr.) |
 copernicus.org/nhess-6-439-2006.pdf |
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| Zusammenfassung |
| Weather radar systems are very suitable tools for the monitoring
of extreme rainfall events providing measurements with high
spatial and temporal resolution over a wide geographical area.
Nevertheless, radar rainfall retrieval at C-band is prone to
several error sources, such as rain path attenuation which affects
the accuracy of inversion algorithms. In this paper, the so-called
rain profiling techniques (namely the surface reference method FV
and the polarimetric method ZPHI) are applied to correct rain
path attenuation and a new neural network algorithm is proposed to
estimate the rain rate from the corrected measurements of
reflectivity and differential reflectivity. A stochastic model,
based on disdrometer measurements, is used to generate realistic
range profiles of raindrop size distribution parameters while a
T-matrix solution technique is adopted to compute the
corresponding polarimetric variables. A sensitivity analysis is
performed in order to evaluate the expected errors of these
methods. It has been found that the ZPHI method is more reliable
than FV, being less sensitive to calibration errors. Moreover, the
proposed neural network algorithm has shown more accurate rain
rate estimates than the corresponding parametric algorithm,
especially in presence of calibration errors. |
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