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| Titel |
Temporal disaggregation of satellite-derived monthly precipitation estimates and the resulting propagation of error in partitioning of water at the land surface |
| VerfasserIn |
S. A. Margulis, D. Entekhabi |
| 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. 1 ; Nr. 5, no. 1, S.27-38 |
| Datensatznummer |
250002252
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| Publikation (Nr.) |
 copernicus.org/hess-5-27-2001.pdf |
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| Zusammenfassung |
| Global estimates of precipitation can now be
made using data from a combination of geosynchronous and low earth-orbit
satellites. However, revisit patterns of polar-orbiting satellites and the need
to sample mixed-clouds scenes from geosynchronous satellites leads to the
coarsening of the temporal resolution to the monthly scale. There are
prohibitive limitations to the applicability of monthly-scale aggregated
precipitation estimates in many hydrological applications. The nonlinear and
threshold dependencies of surface hydrological processes on precipitation may
cause the hydrological response of the surface to vary considerably based on the
intermittent temporal structure of the forcing. Therefore, to make the monthly
satellite data useful for hydrological applications (i.e. water balance studies,
rainfall-runoff modelling, etc.), it is necessary to disaggregate the monthly
precipitation estimates into shorter time intervals so that they may be used in
surface hydrology models. In this study, two simple statistical disaggregation
schemes are developed for use with monthly precipitation estimates provided by
satellites. The two techniques are shown to perform relatively well in
introducing a reasonable temporal structure into the disaggregated time series.
An ensemble of disaggregated realisations was routed through two land surface
models of varying complexity so that the error propagation that takes place over
the course of the month could be characterised. Results suggest that one of the
proposed disaggregation schemes can be used in hydrological applications without
introducing significant error.
Keywords: precipitation, temporal disaggregation, hydrological modelling,
error propagation |
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