Capability of CORDEX RCMs in simulating extreme rainfall events over South africa

dc.contributor.advisorAbiodun, Babatunde Josephen_ZA
dc.contributor.authorAbba Omar, Sabinaen_ZA
dc.date.accessioned2014-11-05T03:41:28Z
dc.date.available2014-11-05T03:41:28Z
dc.date.issued2014en_ZA
dc.descriptionIncludes bibliographical references.en_ZA
dc.description.abstractIn South Africa, extreme rainfall events often lead to widespread destruction, damage infrastructure, displace communities, strain water management and even destroy lives. Past studies have shown that reliable predictions of extreme rainfall events from regional climate models (RCMs) could help reduce the impact of these events. The present study evaluates the ability of nine RCMs in simulating extreme rainfall events over South Africa, focusing on the Western Cape (WC) and east coast (EC) areas. This study defines an extreme rainfall over a location as rainfall that is equal to or above the 95th percentile of the rainfall distribution at that location, and defines widespread extreme rainfall events (WEREs) over an area as events during which more than 50 of the grid-points in the area experience extreme rainfall. The 95th percentile threshold values were calculated over 11 years (1998-2008) of South Africa’s daily rainfall data from the nine RCMs (CCLM, REMO, PRECIS, CRCM5, ARPEGE, REGCM3, WRF, RACMO and RCA35), which participated in the Coordinated Regional Climate Downscaling Experiment (CORDEX) and used ERA-Interim (ERAINT) as their boundary forcing. The simulations were compared to two observation datasets (TRMM and GPCP), and to ERAINT rainfall data to understand whether these RCMs improve on the results from ERAINT. A self organizing map (SOM) was used to characterize WEREs identified in all the datasets into archetypal groups, and ERAINT data is used to describe the underlying circulations for each archetypal rainfall pattern. The number of WEREs mapped to each rainfall pattern for each dataset allows us to get an idea of whether certain RCMs are more likely to simulate certain rainfall patterns.en_ZA
dc.identifier.apacitationAbba Omar, S. (2014). <i>Capability of CORDEX RCMs in simulating extreme rainfall events over South africa</i>. (Thesis). University of Cape Town ,Faculty of Science ,Department of Environmental and Geographical Science. Retrieved from http://hdl.handle.net/11427/9103en_ZA
dc.identifier.chicagocitationAbba Omar, Sabina. <i>"Capability of CORDEX RCMs in simulating extreme rainfall events over South africa."</i> Thesis., University of Cape Town ,Faculty of Science ,Department of Environmental and Geographical Science, 2014. http://hdl.handle.net/11427/9103en_ZA
dc.identifier.citationAbba Omar, S. 2014. Capability of CORDEX RCMs in simulating extreme rainfall events over South africa. University of Cape Town.en_ZA
dc.identifier.ris TY - Thesis / Dissertation AU - Abba Omar, Sabina AB - In South Africa, extreme rainfall events often lead to widespread destruction, damage infrastructure, displace communities, strain water management and even destroy lives. Past studies have shown that reliable predictions of extreme rainfall events from regional climate models (RCMs) could help reduce the impact of these events. The present study evaluates the ability of nine RCMs in simulating extreme rainfall events over South Africa, focusing on the Western Cape (WC) and east coast (EC) areas. This study defines an extreme rainfall over a location as rainfall that is equal to or above the 95th percentile of the rainfall distribution at that location, and defines widespread extreme rainfall events (WEREs) over an area as events during which more than 50 of the grid-points in the area experience extreme rainfall. The 95th percentile threshold values were calculated over 11 years (1998-2008) of South Africa’s daily rainfall data from the nine RCMs (CCLM, REMO, PRECIS, CRCM5, ARPEGE, REGCM3, WRF, RACMO and RCA35), which participated in the Coordinated Regional Climate Downscaling Experiment (CORDEX) and used ERA-Interim (ERAINT) as their boundary forcing. The simulations were compared to two observation datasets (TRMM and GPCP), and to ERAINT rainfall data to understand whether these RCMs improve on the results from ERAINT. A self organizing map (SOM) was used to characterize WEREs identified in all the datasets into archetypal groups, and ERAINT data is used to describe the underlying circulations for each archetypal rainfall pattern. The number of WEREs mapped to each rainfall pattern for each dataset allows us to get an idea of whether certain RCMs are more likely to simulate certain rainfall patterns. DA - 2014 DB - OpenUCT DP - University of Cape Town LK - https://open.uct.ac.za PB - University of Cape Town PY - 2014 T1 - Capability of CORDEX RCMs in simulating extreme rainfall events over South africa TI - Capability of CORDEX RCMs in simulating extreme rainfall events over South africa UR - http://hdl.handle.net/11427/9103 ER - en_ZA
dc.identifier.urihttp://hdl.handle.net/11427/9103
dc.identifier.vancouvercitationAbba Omar S. Capability of CORDEX RCMs in simulating extreme rainfall events over South africa. [Thesis]. University of Cape Town ,Faculty of Science ,Department of Environmental and Geographical Science, 2014 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/9103en_ZA
dc.language.isoengen_ZA
dc.publisher.departmentDepartment of Environmental and Geographical Scienceen_ZA
dc.publisher.facultyFaculty of Scienceen_ZA
dc.publisher.institutionUniversity of Cape Town
dc.titleCapability of CORDEX RCMs in simulating extreme rainfall events over South africaen_ZA
dc.typeMaster Thesis
dc.type.qualificationlevelMasters
dc.type.qualificationnameMScen_ZA
uct.type.filetypeText
uct.type.filetypeImage
uct.type.publicationResearchen_ZA
uct.type.resourceThesisen_ZA
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