Intraseasonal Rainfall Variability and Climate Change Adaptation in East Africa
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Date
2021
Authors
Ogega, Obed Matundura
Journal Title
Journal ISSN
Volume Title
Publisher
Kenyatta University
Abstract
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.
Description
A Research Thesis Submitted in Fulfilment of the Requirements for the Degree of Doctor of Philosophy in Environmental Studies (Climate Change and Sustainability) in the School of Environmental Studies of Kenyatta University, November 2021
Keywords
Intraseasonal, Rainfall, Variability, Climate Change, Adaptation, East Africa