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| Titel |
Cascade-based disaggregation of continuous rainfall time series: the influence of climate |
| VerfasserIn |
A. Güntner, J. Olsson, A. Calver, B. Gannon |
| 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.145-164 |
| Datensatznummer |
250002404
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| Publikation (Nr.) |
 copernicus.org/hess-5-145-2001.pdf |
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| Zusammenfassung |
| Rainfall data of high temporal resolution are
required in a multitude of hydrological applications. In the present paper, a
temporal rainfall disaggregation model is applied to convert daily time series
into an hourly resolution. The model is based on the principles of random
multiplicative cascade processes. Its parameters are dependent on (1) the volume
and (2) the position in the rainfall sequence of the time interval with rainfall
to be disaggregated. The aim is to compare parameters and performance of the
model between two contrasting climates with different rainfall generating
mechanisms, a semi-arid tropical (Brazil) and a temperate (United Kingdom)
climate. In the range of time scales studied, the scale-invariant assumptions of
the model are approximately equally well fulfilled for both climates. The model
parameters differ distinctly between climates, reflecting the dominance of
convective processes in the Brazilian rainfall and of advective processes
associated with frontal passages in the British rainfall. In the British case,
the parameters exhibit a slight seasonal variation consistent with the higher
frequency of convection during summer. When applied for disaggregation, the
model reproduces a range of hourly rainfall characteristics with a high accuracy
in both climates. However, the overall model performance is somewhat better for
the semi-arid tropical rainfall. In particular, extreme rainfall in the UK is
overestimated whereas extreme rainfall in Brazil is well reproduced.
Transferability of parameters in time is associated with larger uncertainty in
the semi-arid climate due to its higher interannual variability and lower
percentage of rainy intervals. For parameter transferability in space, no
restrictions are found between the Brazilian stations whereas in the UK regional
differences are more pronounced. The overall high accuracy of disaggregated data
supports the potential usefulness of the model in hydrological applications.
Keywords: Rainfall, temporal disaggregation, random cascade, scaling,
semi-arid, temperate climate. |
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