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| Titel |
Downscaling rainfields in space and time, using the String of Beads model in time series mode |
| VerfasserIn |
G. G. S. Pegram, A. N. Clothier |
| 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 ; 5, no. 2 ; Nr. 5, no. 2, S.175-186 |
| Datensatznummer |
250002406
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| Publikation (Nr.) |
 copernicus.org/hess-5-175-2001.pdf |
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| Zusammenfassung |
| The String of Beads
model is a space-time model of rainfields measured by weather radar. It is here
driven by two auto-regressive time series models, one at
the image scale, the other at the pixel scale, to model the temporal correlation
structure of the wet-period process. The marginal
distribution of the pixel scale intensities on a given radar-rainfall image is
described by a log-normal distribution. The spatial dependence
structure of each image is defined by a power spectrum approximated by a power
law function with a negative exponent. It is demonstrated
that this stochastic modelling approach is valid because the images sampled are
effectively stationary above a scale of 30 km, which is
less than a quarter of the image width. By advecting a simulated sequence of
images along the same cumulative advection vector as the
observed event and matching the image-scale statistics of each simulated image
with those of the corresponding observed image, a simulated
sequence of plausible images is generated which mimics (has the same space-time
statistics as) the observed event but differs from it in
detail. Aggregating the pixel scale intensities in each sequence over a number
of time and space intervals and then comparing their spatial
and temporal statistics, demonstrates that the model captures the intermediate
scale behaviour well, showing satisfactorily its ability to
downscale rainfall in space and time. The model thus has potential as an
operational space-time model of rainfields.
Keywords: Space-time, rainfield modelling, weather radar, multifractals,
Gaussian random fields |
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