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Spatial and temporal variability of
rainfall offers considerable challenges for assessing and understanding climate
change and variability over East Africa. (Omondi,
et al. 2014). East African rainfall is
characterized by high spatial-temporal variability, and slight variation is
associated with huge socio-economic losses, (Ongoma et al, 2015).

The ‘short rains’ (also referred to
as SON), though the secondary season in the greater eastern equatorial Africa,
exhibit high inter-annual variability. In contrast to the ‘long rains’ (also
referred to as MAM), the short rains have shown a rising trend in recent years
in the equatorial Eastern Africa (Nicholson,
2017). They also exhibit one of the
strongest associations ever demonstrated to global circulation (Nicholson,
2014). Although, for most of the region
the short rains are less intense than the long rains, they provide the maximum
rainfall in some parts of Kenya (Nicholson,

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The rainfall pattern over the region
is highly variable both in space and time because of the diverse topographical
features, such as The Rift-valley, Ethiopian highlands, and the Kenyan highlands
also influence local circulation patterns which in turn influence mesoscale
convection, lakes such as Lake Victoria, Tanganyika and Kyoga as well as the
Indian Ocean along the East African coast causes land-sea contrasts, (Mutai,
et al.,1998). Another feature is the Turkana
Low-Level Jet (LLJ) (Kinuthia
& Asnani, 1982) which forms in the channel created
by the two highland ranges. It affects rainfall of the surrounding area by
alerting moisture, temperature, and vertical velocity fields, thus modulating
mesoscale circulations (Indeje et al., 2001; Nicholson, 2015).


phenomenon which is as a result of the atmospheric and Oceanic interaction in
the Pacific has been established as the dominant mode contributing to east
African rainfall variability (Ogallo, 1988; Hastenrath et al., 1993). With
periodicities ranging from seasonal to about 8 years (Halpert and Ropelewski,

(Nyakwada et
al., 2009) used principal component analysis, composite
analysis and correlation analysis to establish the sea surface temperature
modes that might denote the collective effect of the Atlantic and Indian Oceans
on the seasonal rainfall over East Africa. Most of the first four modes
represented sea surface temperature variability associated with the individual
Oceans, such as basin wide warming/cooling associated with El Nino_Southern
Oscillation, inter-hemispheric SST variability over the Atlantic Ocean and
Indian Ocean Dipole.

In their study
of the relationship between global rainfall and the Southern Oscillation Index
(SOI), (Ropelewski and Halpert 1987) concluded that, although the statistical
association between rainfall over East Africa and the SOI were weak, there was a high probability of
abnormally wet conditions in the region during El Nino years.

The Indian Ocean
Zonal Mode (IOZM), explained by a quasi sea-saw east–west SST gradient reversal
across the Indian Ocean, is also believed to affect the variability of East
African rainfall whereby a positive IOZM indicates warmer and a negative IOZM
indicates cooler than normal SST along equatorial East Africa, which alters the
large-scale wind fields and evaporation, thus higher moisture supply .(Saji, et al. 1999)

(Manatsa et
al., 2014) explored the inter-annual variability of
East African ‘short rains’ (EASR) and the influence of Mascarene High (MH)
variation using Correlation and composite analyses for flood and drought
occasions which revealed that the EASR variability is strongly associated to
the MH zonal movement, in specific, the zonal movement of the MH eastern ridge.

(Oettli &
Camberlin, 2005) compared monthly rainfall distribution with
several topographic parameters, such as slope and the mean and standard
deviation of elevation. The relationships varied seasonally. For example,
east-facing stations were wetter during the boreal autumn but were drier during
the boreal summer and winter seasons. Mean elevation appears to have little
effect on rainfall amount, but it has strong control on the frequency of
rainfall occurrence (Camberlin et al., 2014).

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