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dc.contributor.authorSchär, Christoph
dc.contributor.authorBan, Nikolina
dc.contributor.authorRajczak, Jan
dc.contributor.authorSchmidli, Jürg
dc.contributor.authorFrei, Christoph
dc.contributor.authorGiorgi, Filippo
dc.contributor.authorSillmann, Jana
dc.contributor.authorZhang, Xuebin
dc.contributor.authorFischer, Erich M.
dc.contributor.authorKarl, Thomas R.
dc.contributor.authorKendon, Elizabeth J.
dc.contributor.authorTank, Albert M. G. Klein
dc.contributor.authorZwiers, Francis W.
dc.contributor.authorO'Gorman, Paul
dc.date.accessioned2017-01-12T21:53:18Z
dc.date.available2017-01-12T21:53:18Z
dc.date.issued2016-04
dc.date.submitted2015-05
dc.identifier.issn0165-0009
dc.identifier.issn1573-1480
dc.identifier.urihttp://hdl.handle.net/1721.1/106477
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.en_US
dc.publisherSpringer Netherlandsen_US
dc.relation.isversionofhttp://dx.doi.org/10.1007/s10584-016-1669-2en_US
dc.rightsCreative Commons Attributionen_US
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en_US
dc.sourceSpringer Netherlandsen_US
dc.titlePercentile indices for assessing changes in heavy precipitation eventsen_US
dc.typeArticleen_US
dc.identifier.citationSchär, Christoph, Nikolina Ban, Erich M. Fischer, Jan Rajczak, Jürg Schmidli, Christoph Frei, Filippo Giorgi, et al. “Percentile Indices for Assessing Changes in Heavy Precipitation Events.” Climatic Change 137, no. 1–2 (April 5, 2016): 201–216.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Earth, Atmospheric, and Planetary Sciencesen_US
dc.contributor.mitauthorO'Gorman, Paul
dc.relation.journalClimatic Changeen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2016-08-18T15:19:17Z
dc.language.rfc3066en
dc.rights.holderThe Author(s)
dspace.orderedauthorsSchär, Christoph; Ban, Nikolina; Fischer, Erich M.; Rajczak, Jan; Schmidli, Jürg; Frei, Christoph; Giorgi, Filippo; Karl, Thomas R.; Kendon, Elizabeth J.; Tank, Albert M. G. Klein; O’Gorman, Paul A.; Sillmann, Jana; Zhang, Xuebin; Zwiers, Francis W.en_US
dspace.embargo.termsNen_US
dc.identifier.orcidhttps://orcid.org/0000-0003-1748-0816
mit.licensePUBLISHER_CCen_US


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