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| Titel |
Processing polarimetric X-band weather radar data with an Extended Kalman Filter framework |
| VerfasserIn |
Marc Schneebeli, Alexis Berne |
| Konferenz |
EGU General Assembly 2011
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 13 (2011) |
| Datensatznummer |
250053465
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| Zusammenfassung |
| Individual polarimetric quantities measured by weather radar systems are closely related to
each other. Such relations can be used to constrain the estimates of the different
quantities and hence to improve the quality of weather radar data. In the proposed
approach, an extended Kalman filter framework is developed, which takes into account
relations between individual radar variables as well as their spatial structure in order to
simultaneously estimate the specific differential phase shift on propagation Kdp, the
attenuation corrected radar reflectivity at horizontal polarization Zh, the attenuation
corrected differential reflectivity Zdr, and the differential phase shift on backscattering
δhv.
Simulated 2D fields of raindrop size distributions are used to test the proposed algorithm.
In this simulation experiment, it is found that Kdp and δhv are retrieved with an excellent
accuracy, outperforming existing estimators solely based on smoothed measurements of the
total differential phase shift Ïdp. Attenuation corrected reflectivities retrieved with the new
algorithm exhibit an improved accuracy with respect to estimates from the standard ZÏ
algorithm, while the attenuation corrected differential reflectivity is retrieved with a similar
accuracy. By comparing the directly retrieved differential phase shift on propagation Ïdp with
the cumulated Kdp estimate, the algorithm can also be used for radar calibration. The
extended Kalman filter estimation scheme is applied to measurements collected by an
X-band polarimetric radar in the swiss Alps in 2010. The calibration capability of the
algorithm makes possible the estimation of the radome attenuation, which appears to be
significant in moderate and intense rainfall (up to 5Â dB). It is hence crucial to correct for
radome attenuation in order to obtain reliable quantitative rain rate estimates. Once
the radome attenuation has been removed, radar measurements are converted in
to rain rate R using a new functional form of the relation between R, Kdp and
Zdr. The good agreement between radar estimates and ground observations from a
disdrometer indicates the reliability of the proposed radar processing technique. |
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