Show simple item record

dc.contributor.authorZulkarnain, Hassan
dc.contributor.authorMohd Faez, Mohd Mansor
dc.contributor.authorAin Nihla, Kamarudzaman
dc.date.accessioned2020-01-23T08:39:03Z
dc.date.available2020-01-23T08:39:03Z
dc.date.issued2019
dc.identifier.citationJournal of Engineering Research and Education, vol.11, 2019, pages 9-14en_US
dc.identifier.issn1823-2981 (print)
dc.identifier.issn2232-1098 (online)
dc.identifier.urihttp://dspace.unimap.edu.my:80/xmlui/handle/123456789/63833
dc.descriptionLink to publisher's homepage at http://jere.unimap.edu.myen_US
dc.description.abstractGeneral Circulation Models (GCMs) are used to modelling the responses of the climate system to different scenarios of greenhouse gas and aerosol. However, the model needs to downscale into a fine resolution daily rainfall series appropriate for local scale hydrological impact studies. In this study, Statistical Down-Scaling Model (SDSM) is used to downscale the GCMs simulations from Hadley Centre 3rd generation (HadCM3) with A2 and B2 scenarios for future rainfall over the area of Perlis, Malaysia. The SDSM model is able to simulate satisfactorily the daily rainfall series by giving the average coefficient of correlation (R2) and standard error (SE) during the validation period are 0.11 and 9.88mm/day respectively. The study area is apparently will gain an increasing trend for annual mean rainfall on the 2020s and show the decreasing trend for annual mean rainfall for period 2050s and 2080s for both scenario emissions.en_US
dc.language.isoenen_US
dc.publisherUniversiti Malaysia Perlis (UniMAP)en_US
dc.subjectGeneral Circulation Modelsen_US
dc.subjectStatistical Down-Scaling Modelen_US
dc.subjectRainfallen_US
dc.subjectHadCM3en_US
dc.titleRainfall projection corresponding to climate scenarios based on Statistical Down-Scaling Model over Perlis, Malaysiaen_US
dc.typeArticleen_US
dc.contributor.urlzulkarnainh@unimap.edu.myen_US


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record