Sea surface temperature trends around Southern Africa (focusing on the Benguela Current system and the Agulhas retroflection area)

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dc.contributor.advisorRouault, Mathieuen_ZA
dc.contributor.authorDlomo, Xolisaen_ZA
dc.date.accessioned2015-05-18T14:25:37Z
dc.date.available2015-05-18T14:25:37Z
dc.date.issued2014en_ZA
dc.descriptionIncludes bibliographical references.en_ZA
dc.description.abstractSea surface temperature (SST) fluctuations and changes around southern Africa have important consequences on regional weather, climate and the marine ecosystem. SST is a good indicator for upwelling strength in the Benguela Current system and therefore is linked to bio logical activity in that region. SS T is an important driver of the air-sea exchange of moisture and energy, especially in the Agulhas Current where high latent and sensible heat fluxes occur. It is important to quantify SST trends with accuracy for the long term monitoring and characterisation of weather, climate and marine ecosystem in southern Africa, especially in the context of climate change. Here various 1° x 1° SST datasets are used to calculate yearly time series, inter-annual fluctuations and trends in key oceanic regions of southern Africa. OI SST, Hadley SST, NOCS SST and ER SST (which has 2° x 2° resolution) are used in this study. I start calculating trends and inter- annual fluctuations for various domains and dataset in the recent satellite era since 1982 to compare the non-satellite products NOCS SST and ER SST with the satellite products Hadley SST and OI SST. The idea is to validate the no n-satellite products since 1982 and then use them to calculate trends around southern Africa before 1982. Trends and inter-annual fluctuation in the Angola Benguela Current system and the Agulhas Current retroflection system are therefore presented for all datasets for the 1982 - 2012 period. The datasets show different trends and different timing or amplitude of inter- annual variability. This prevents the estimation of changes in the region with confidence before the satellite era which was the initial objective of the study. The main reason is that ER SST is a 2° x 2° dataset and maybe not adequate for upwelling region and the Hadley SST 1° x 1° dataset include satellite data from 1980 which creates some non-homogeneity in time and probably an artificial cooling at the coast from the 1980’s when satellite data is introduced in the dataset to patch the observational gaps. It is therefore not advisable to use Hadley SST for trend studies including 1982 onwards. From 1982 to 2012 in the Benguela upwelling system, whereas OI SST and Hadley SST show mainly cooling trends of different magnitude, NOCS SST and ER SST show warming trends with NOCS showing significant (p < 0.05) warming trends which is suspicious. In the Northern Benguela and Retroflection all datasets show warming trends for the 1982 - 2012 period except from NOCS SST.en_ZA
dc.identifier.apacitationDlomo, X. (2014). <i>Sea surface temperature trends around Southern Africa (focusing on the Benguela Current system and the Agulhas retroflection area)</i>. (Thesis). University of Cape Town ,Faculty of Science ,Department of Oceanography. Retrieved from http://hdl.handle.net/11427/12828en_ZA
dc.identifier.chicagocitationDlomo, Xolisa. <i>"Sea surface temperature trends around Southern Africa (focusing on the Benguela Current system and the Agulhas retroflection area)."</i> Thesis., University of Cape Town ,Faculty of Science ,Department of Oceanography, 2014. http://hdl.handle.net/11427/12828en_ZA
dc.identifier.citationDlomo, X. 2014. Sea surface temperature trends around Southern Africa (focusing on the Benguela Current system and the Agulhas retroflection area). University of Cape Town.en_ZA
dc.identifier.ris TY - Thesis / Dissertation AU - Dlomo, Xolisa AB - Sea surface temperature (SST) fluctuations and changes around southern Africa have important consequences on regional weather, climate and the marine ecosystem. SST is a good indicator for upwelling strength in the Benguela Current system and therefore is linked to bio logical activity in that region. SS T is an important driver of the air-sea exchange of moisture and energy, especially in the Agulhas Current where high latent and sensible heat fluxes occur. It is important to quantify SST trends with accuracy for the long term monitoring and characterisation of weather, climate and marine ecosystem in southern Africa, especially in the context of climate change. Here various 1° x 1° SST datasets are used to calculate yearly time series, inter-annual fluctuations and trends in key oceanic regions of southern Africa. OI SST, Hadley SST, NOCS SST and ER SST (which has 2° x 2° resolution) are used in this study. I start calculating trends and inter- annual fluctuations for various domains and dataset in the recent satellite era since 1982 to compare the non-satellite products NOCS SST and ER SST with the satellite products Hadley SST and OI SST. The idea is to validate the no n-satellite products since 1982 and then use them to calculate trends around southern Africa before 1982. Trends and inter-annual fluctuation in the Angola Benguela Current system and the Agulhas Current retroflection system are therefore presented for all datasets for the 1982 - 2012 period. The datasets show different trends and different timing or amplitude of inter- annual variability. This prevents the estimation of changes in the region with confidence before the satellite era which was the initial objective of the study. The main reason is that ER SST is a 2° x 2° dataset and maybe not adequate for upwelling region and the Hadley SST 1° x 1° dataset include satellite data from 1980 which creates some non-homogeneity in time and probably an artificial cooling at the coast from the 1980’s when satellite data is introduced in the dataset to patch the observational gaps. It is therefore not advisable to use Hadley SST for trend studies including 1982 onwards. From 1982 to 2012 in the Benguela upwelling system, whereas OI SST and Hadley SST show mainly cooling trends of different magnitude, NOCS SST and ER SST show warming trends with NOCS showing significant (p < 0.05) warming trends which is suspicious. In the Northern Benguela and Retroflection all datasets show warming trends for the 1982 - 2012 period except from NOCS SST. DA - 2014 DB - OpenUCT DP - University of Cape Town LK - https://open.uct.ac.za PB - University of Cape Town PY - 2014 T1 - Sea surface temperature trends around Southern Africa (focusing on the Benguela Current system and the Agulhas retroflection area) TI - Sea surface temperature trends around Southern Africa (focusing on the Benguela Current system and the Agulhas retroflection area) UR - http://hdl.handle.net/11427/12828 ER - en_ZA
dc.identifier.urihttp://hdl.handle.net/11427/12828
dc.identifier.vancouvercitationDlomo X. Sea surface temperature trends around Southern Africa (focusing on the Benguela Current system and the Agulhas retroflection area). [Thesis]. University of Cape Town ,Faculty of Science ,Department of Oceanography, 2014 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/12828en_ZA
dc.language.isoengen_ZA
dc.publisher.departmentDepartment of Oceanographyen_ZA
dc.publisher.facultyFaculty of Scienceen_ZA
dc.publisher.institutionUniversity of Cape Town
dc.subject.otherOcean and Climate Dynamics.en_ZA
dc.titleSea surface temperature trends around Southern Africa (focusing on the Benguela Current system and the Agulhas retroflection area)en_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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