Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/113626
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dc.contributor.authorCortés-Hernández, V.-
dc.contributor.authorZheng, F.-
dc.contributor.authorEvans, J.-
dc.contributor.authorLambert, M.-
dc.contributor.authorSharma, A.-
dc.contributor.authorWestra, S.-
dc.date.issued2016-
dc.identifier.citationClimate Dynamics, 2016; 47(5-6):1613-1628-
dc.identifier.issn0930-7575-
dc.identifier.issn1432-0894-
dc.identifier.urihttp://hdl.handle.net/2440/113626-
dc.description.abstractSub-daily rainfall extremes are of significant societal interest, with implications for flash flooding and the design of urban stormwater systems. It is increasingly recognised that extreme subdaily rainfall will intensify as a result of global temperature increases, with regional climate models (RCMs) representing one of the principal lines of evidence on the likely magnitude and spatiotemporal characteristics of these changes. To evaluate the ability of RCMs to simulate subdaily extremes, it is common to compare the simulated statistical characteristics of the extreme rainfall events with those from observational records. While such analyses are important, they provide insufficient insight into whether the RCM reproduces the correct underlying physical processes; in other words, whether the model “gets the right answers for the right reasons”. This paper develops a range of metrics to assess the performance of RCMs in capturing the physical mechanisms that produce extreme rainfall. These metrics include the diurnal and seasonal cycles, relationship between rainfall intensity and temperature, temporal scaling, and the spatial structure of extreme rainfall events. We evaluate a high resolution RCM—the Weather Research Forecasting model—over the Greater Sydney region, using three alternative parametrization schemes. The model shows consistency with the observations for most of the proposed metrics. Where differences exist, these are dependent on both the rainfall duration and model parameterization strategy. The use of physically meaningful performance metrics not only enhances the confidence in model simulations, but also provides better diagnostic power to assist with future model improvement.-
dc.description.statementofresponsibilityVirginia Edith Cortés-Hernández, Feifei Zheng, Jason Evans, Martin Lambert, Ashish Sharma, Seth Westra-
dc.language.isoen-
dc.publisherSpringer-
dc.rights© Springer-Verlag Berlin Heidelberg 2015-
dc.subjectRegional climate models; climate model evaluation; sub-daily extreme rainfall; Weather Research Forecasting (WRF) model; Greater Sydney region-
dc.titleEvaluating regional climate models for simulating sub-daily rainfall extremes-
dc.typeJournal article-
dc.identifier.doi10.1007/s00382-015-2923-4-
pubs.publication-statusPublished-
dc.identifier.orcidLambert, M. [0000-0001-8272-6697]-
dc.identifier.orcidWestra, S. [0000-0003-4023-6061]-
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Civil and Environmental Engineering publications

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