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dc.contributor.authorSchaer, Christoph
dc.contributor.authorBan, Nikolina
dc.contributor.authorFischer, Erich M.
dc.contributor.authorRajczak, Jan
dc.contributor.authorSchmidli, Juerg
dc.contributor.authorFrei, Christoph
dc.contributor.authorGiorgi, Filippo
dc.contributor.authorKarl, Thomas R.
dc.contributor.authorKendon, Elisabeth J.
dc.contributor.authorKlein Tank, Albert M. G.
dc.contributor.authorO'Gorman, Paul A.
dc.contributor.authorSillmann, Jana
dc.contributor.authorZhang, Xuebin
dc.contributor.authorZwiers, Francis W.
dc.date.accessioned2017-11-13T14:23:39Z
dc.date.available2017-11-13T14:23:39Z
dc.date.created2016-09-02T10:59:39Z
dc.date.issued2016
dc.identifier.citationClimatic Change. 2016, 137 (1), 201-216.nb_NO
dc.identifier.issn0165-0009
dc.identifier.urihttp://hdl.handle.net/11250/2465973
dc.description.abstractMany climate studies assess trends and projections in heavy precipitation events using precipitation percentile (or quantile) indices. Here we investigate three different percentile indices that are commonly used. We demonstrate that these may produce very different results and thus require great care with interpretation. More specifically, consideration is given to two intensity-based indices and one frequency-based index, namely (a) all-day percentiles, (b) wet-day percentiles, and (c) frequency indices based on the exceedance of a percentile threshold. Wet-day percentiles are conditionally computed for the subset of wet events (with precipitation exceeding some threshold, e.g. 1 mm/d for daily precipitation). We present evidence that this commonly used methodology can lead to artifacts and misleading results if significant changes in the wet-day frequency are not accounted for. Percentile threshold indices measure the frequency of exceedance with respect to a percentile-based threshold. We show that these indices yield an assessment of changes in heavy precipitation events that is qualitatively consistent with all-day percentiles, but there are substantial differences in quantitative terms. We discuss the reasons for these effects, present a theoretical assessment, and provide a series of examples using global and regional climate models to quantify the effects in typical applications. Application to climate model output shows that these considerations are relevant to a wide range of typical climate-change applications. In particular, wet-day percentiles generally yield different results, and in most instances should not be used for the impact-oriented assessment of changes in heavy precipitation events.nb_NO
dc.language.isoengnb_NO
dc.relation.urihttp://link.springer.com/article/10.1007/s10584-016-1669-2#enumeration
dc.titlePercentile indices for assessing changes in heavy precipitation eventsnb_NO
dc.typeJournal articlenb_NO
dc.typePeer reviewednb_NO
dc.description.versionsubmittedVersionnb_NO
dc.source.pagenumber201-216nb_NO
dc.source.volume137nb_NO
dc.source.journalClimatic Changenb_NO
dc.source.issue1nb_NO
dc.identifier.doi10.1007/s10584-016-1669-2
dc.identifier.cristin1377544
dc.relation.projectNorges forskningsråd: 229778/E10nb_NO
cristin.unitcode7475,0,0,0
cristin.unitnameCICERO Senter for klimaforskning
cristin.ispublishedtrue
cristin.fulltextpreprint
cristin.qualitycode1


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