PHD-Department of Environmental Science

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Browsing PHD-Department of Environmental Science by Subject "Climate Change"

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    Intraseasonal Rainfall Variability and Climate Change Adaptation in East Africa
    (Kenyatta University, 2021) Ogega, Obed Matundura; James Koske; James B. Kung’u
    The study assessed historical intraseasonal rainfall variability, generated future intraseasonal rainfall scenarios, and made recommendations to build on climate service foundations for a sustainable climate change adaptation in East Africa. First, an assessment of the performance of regional climate models (RCMs), participating in the Coordinated Regional Climate Downscaling Experiment (CORDEX), in simulating East Africa’s spatio-temporal precipitation characteristics was done. Using a set of eight descriptors of East Africa’s precipitation, the RCM assessment was done to determine the best model runs for evaluating East Africa’s historical and future precipitation characteristics. The descriptors are the consecutive dry days (CDD), consecutive wet days (CWD), simple precipitation intensity index (SDII), mean daily annual (ANN), seasonal (March to May, MAM and October to December, OND) precipitation, and representatives of heavy precipitation (90p) and very intense precipitation (99p) events. Specifically, (i) nine reanalysis data (ERAINT)-driven and (ii) 24 model runs from five general circulation model (GCM)-driven CORDEX-Africa RCMs were analysed. Relatively better performing RCM runs were then used to assess projected precipitation changes (for the period 2071-2099 relative to 1977-2005) over the study domain under the representative concentration pathway (RCP) 8.5 scenario. Results showed the performance of RCMs to be descriptor- and scope- specific. Overall, RCA4 (r1i1p1) forced by CNRM-CERFACS-CNRM-CM5 and MPI-M-MPI-ESM-LR, REMO2009 (r1i1p1) forced by MPI-M-MPI-ESM-LR, and RCA4 (r2i1p1) forced by MPI-M-MPIESM- LR emerged as the top four RCM runs. Further, an ensemble mean of the top four model runs outperformed an ensemble mean of 24 model simulations and ensemble means for all runs in an RCM. An analysis of projections showed a reduction(increase) in mean daily precipitation for MAM(OND), an increase(decrease) in CDD(CWD) events, and a general increase in SDII and the width of the right tail of the precipitation distribution (99p-90p). An increase in SDII and 99p-90p implies a possibility of heavy and extreme precipitation incidences by the end of the 21st century. Examples of how the climate information generated from the analysis could be used in various sectors were made. First, an assessment of historical and future rainfall variability over Kilifi County, a typical coastal community whose primary source of livelihood is rain-fed smallholder farming, was done. Using climate information and data from the social survey on the farmers’ perceptions of climate variability, adaptive capacity, and adaptation activities, an innovative climate change adaptation model was co-developed with smallholder farmers to help build the farmers’ adaptive capacity in Kilifi and beyond. Secondly, the study assessed the potential impacts of global warming scenarios of 1.5 oC and 2 oC on malaria transmission in East Africa. Under the two warming scenarios, results showed an imminent increase in seasons and geographical extents of malaria transmission in East Africa. The study recommended intensification of efforts to sustain the gains made towards malaria elimination. Lastly, a status review (in terms of climate, population, and land-use change over Nairobi metropolis) was done, and recommendations made to help safeguard the future of Nairobi National Park. Overall, the thesis findings provide essential information to support the region’s climate change adaptation and mitigation efforts for sustainability.