Cascade-based disaggregation of continuous rainfall time series: The influence of climate

dc.bibliographicCitation.firstPage145eng
dc.bibliographicCitation.issue2eng
dc.bibliographicCitation.journalTitleHydrology and Earth System Scienceseng
dc.bibliographicCitation.volume5eng
dc.contributor.authorGüntner, A.
dc.contributor.authorOlsson, J.
dc.contributor.authorCalver, A.
dc.contributor.authorGannon, B.
dc.date.accessioned2020-08-07T13:48:33Z
dc.date.available2020-08-07T13:48:33Z
dc.date.issued2001
dc.description.abstractRainfall 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.eng
dc.description.versionpublishedVersioneng
dc.identifier.urihttps://oa.tib.eu/renate/handle/123456789/5412
dc.identifier.urihttps://doi.org/10.34657/4041
dc.language.isoengeng
dc.publisherGöttingen : Copernicus GmbHeng
dc.relation.doihttps://doi.org/10.5194/hess-5-145-2001
dc.relation.issn1027-5606
dc.rights.licenseCC BY-NC-SA 2.5 Unportedeng
dc.rights.urihttps://creativecommons.org/licenses/by-nc-sa/2.5/eng
dc.subject.ddc550eng
dc.subject.otherRainfalleng
dc.subject.otherRandom cascadeeng
dc.subject.otherScalingeng
dc.subject.otherSemi-arideng
dc.subject.otherTemperate climateeng
dc.subject.otherTemporal disaggregationeng
dc.subject.otherdisaggregationeng
dc.subject.othermodel validationeng
dc.subject.otherrainfalleng
dc.subject.othersemiarid regioneng
dc.subject.othertemperate environmenteng
dc.subject.othertime series analysiseng
dc.subject.otherBrazileng
dc.subject.otherUnited Kingdomeng
dc.titleCascade-based disaggregation of continuous rainfall time series: The influence of climateeng
dc.typeArticleeng
dc.typeTexteng
tib.accessRightsopenAccesseng
wgl.contributorPIKeng
wgl.subjectUmweltwissenschafteneng
wgl.typeZeitschriftenartikeleng
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