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dc.contributor.authorSabiiti, Geoffrey
dc.date.accessioned2013-05-10T05:37:13Z
dc.date.available2013-05-10T05:37:13Z
dc.date.issued2008
dc.identifier.citationMaster of Science in Meteorology,en
dc.identifier.urihttp://erepository.uonbi.ac.ke:8080/xmlui/handle/123456789/21018
dc.description.abstractFor any given region to have sustainable development there is need to apply climate change information into its socio-economic strategic plans. The overall objective of the study was to simulate the climate scenarios over the Lake Victoria Basin (LVB) using the Providing Regional Climates for Impacts Studies (PRECIS) Regional Climate Model (RCM) system. This study employed the use of the PRECIS RCM system to downscale the coarse resolution outputs from the General Climate Models (GCMs) to provide fine-scale detailed climate scenarios over the LVB for the period spanning 1961-2030. The methodology involved nesting the RCM within the coarse GCM outputs or reanalysis data over the region of study. The data used in the study consisted of observed rainfall and minimum and maximum temperature from selected synoptic stations over the region. The observed data at stations was complimented with the Climate Research Unit (CRU) rainfall and temperature as an aid to model validation. The initial and lateral boundary datasets that were used to drive the RCM were prepared and provided by the United Kingdom Meteorological Office at the Hadley centre. Analysis of the trends in the observed rainfall records indicated an increase in rainfall variability both in space and time. The observed trend in minimum and maximum temperatures was increasing. The skill for the PRECIS model to simulate the climate of the region was examined. The results showed that the simulated rainfall and temperature climatology were fairly in harmony with both the observed and CRU rainfall and temperature datasets over most of the region of study. This implies that the PRECIS RCM does fairly accurately simulate the observed rainfall and temperature climatology over the region of study. Overall, the model represented the effects of the inland water bodies, orographic features and other features that control the climate of the region of study. The PRECIS RCM was used to project the patterns in rainfall and temperature for the period 2001-2030 using the IPCC SRES scenarios over the region of study. Climate change projections of rainfall over the region indicated that the March to May (MAM) and October to December (aND) seasonal rainfall for the period 2001-2030 will exhibit increasing trends with major peaks in MAM rainfall occurring during 2013, 2017 and 2029 in relation to the B2 SRES scenario. A2 SRES scenario showed increasing rainfall trend with much higher variability than those for B2 SRES scenario over the region of study. Climate change projection of temperature indicated that, both minimum and maximum temperature will exhibit increasing trends during the period 2001-2030 for both A2 and B2 SRES scenarios. While the model was capable of reproducing the general climatological patterns over the region, it did not skillfully capture the effects of the small scale features on the region's climate. There is need for improvement in the model physics and resolution and optimization of the model domain in order to enhance the performance of the PRECIS RCM over the region. The model should be used together with other regional models available for assessing the impacts of climate change and variability over the region. This study provides useful climate change and variability information for regional planning for sustainable development. The results of the study will playa crucial role in enhancing the socio-economic productivity of the region in terms of agriculture and food availability, water resources, transport, fisheries, power production, industry and health.en
dc.description.sponsorshipUniversity of Nairobien
dc.language.isoenen
dc.titleSimulation Of Climate Scenarios Over The Lake Victoria Basin Using The PRECIS Regional Climate Modelen
dc.typeThesisen
local.publisherDepartment of meteorology School of physical sciences University of Nairobien


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