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Titel |
Stochastic simulation experiment to assess radar rainfall retrieval uncertainties associated with attenuation and its correction |
VerfasserIn |
R. Uijlenhoet, A. Berne |
Medientyp |
Artikel
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Sprache |
Englisch
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ISSN |
1027-5606
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Digitales Dokument |
URL |
Erschienen |
In: Hydrology and Earth System Sciences ; 12, no. 2 ; Nr. 12, no. 2 (2008-03-19), S.587-601 |
Datensatznummer |
250010578
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Publikation (Nr.) |
copernicus.org/hess-12-587-2008.pdf |
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Zusammenfassung |
As rainfall constitutes the main source of water for the terrestrial
hydrological processes, accurate and reliable measurement and prediction of
its spatial and temporal distribution over a wide range of scales is an
important goal for hydrology. We investigate the potential of ground-based
weather radar to provide such measurements through a theoretical analysis of some
of the associated observation uncertainties. A stochastic model of range profiles
of raindrop size distributions is employed in a Monte Carlo simulation experiment
to investigate the rainfall retrieval uncertainties associated with
weather radars operating at X-, C-, and S-band. We focus in particular on the
errors and uncertainties associated with rain-induced signal attenuation and
its correction for incoherent, non-polarimetric, single-frequency, operational
weather radars. The performance of two attenuation correction schemes, the (forward)
Hitschfeld-Bordan algorithm and the (backward) Marzoug-Amayenc algorithm, is analyzed
for both moderate (assuming a 50 km path length) and intense Mediterranean rainfall
(for a 30 km path). A comparison shows that the backward correction algorithm
is more stable and accurate than the forward algorithm (with a bias in the order
of a few percent for the former, compared to tens of percent for the latter), provided
reliable estimates of the total path-integrated attenuation are available. Moreover,
the bias and root mean square error associated with each algorithm are quantified
as a function of path-averaged rain rate and distance from the radar in order to provide
a plausible order of magnitude for the uncertainty in radar-retrieved rain rates for
hydrological applications. |
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