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Titel |
Modelling of weather radar echoes from anomalous propagation using a hybrid parabolic equation method and NWP model data |
VerfasserIn |
D. Bebbington, S. Rae, J. Bech, B. Codina, M. Picanyol |
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 ; 7, no. 3 ; Nr. 7, no. 3 (2007-06-08), S.391-398 |
Datensatznummer |
250004543
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Publikation (Nr.) |
copernicus.org/nhess-7-391-2007.pdf |
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Zusammenfassung |
Contamination of weather radar echoes by anomalous propagation (anaprop)
mechanisms remains a serious issue in quality control of radar precipitation
estimates. Although significant progress has been made identifying clutter
due to anaprop there is no unique method that solves the question of data
reliability without removing genuine data. The work described here relates
to the development of a software application that uses a numerical weather
prediction (NWP) model to obtain the temperature, humidity and pressure
fields to calculate the three dimensional structure of the atmospheric
refractive index structure, from which a physically based prediction of the
incidence of clutter can be made. This technique can be used in conjunction
with existing methods for clutter removal by modifying parameters of
detectors or filters according to the physical evidence for anomalous
propagation conditions. The parabolic equation method (PEM) is a well
established technique for solving the equations for beam propagation in a
non-uniformly stratified atmosphere, but although intrinsically very
efficient, is not sufficiently fast to be practicable for near real-time
modelling of clutter over the entire area observed by a typical weather
radar. We demonstrate a fast hybrid PEM technique that is capable of
providing acceptable results in conjunction with a high-resolution terrain
elevation model, using a standard desktop personal computer. We discuss the
performance of the method and approaches for the improvement of the model
profiles in the lowest levels of the troposphere. |
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