Abstract:
The main factor that determines the weather and climate on the surface of the earth is the
time variation of the position of the overhead sun. This single factor determines the time
of the day or night, variation of earth‘s surface temperature, prevailing wind direction
and therefore precipitation, weather and climate. The locus of the overhead sun as
described by the solar-declination from a reference point on the earth surface can be
accurately calculated astronomically at all times. This makes it possible to predict most
weather parameters, using weather and climate models. We have in this study used a
second important factor to account for the natural climate variability as the time variation
of the overhead moon as described in a similar manner by the lunar declination.
This study demonstrates that the presence of enhanced atmospheric tides resulting from
lunar-solar geometry is a key factor when used to predict the temporal distribution of
rainfall amounts. Solar and lunar declination values obtained from ephemeris available
from National Aeronautics Space Agency (NASA) have been used to compute the
relative magnitude and duration of the tidal effect in the atmosphere for the period 1959
to 2005 over Nairobi. The impact of the tidal effect has been assessed by statistical
modeling of Kenya rainfall against the conventional climate variability indices such as
the Southern Oscillation Index (SOI) and Quasi-Biennial Oscillation (QBO) as well as
modeling against parameters derived from the tidal effect. We have found that while
conventional variability indices provide a method to explain past variability, their values
are unknown for the purpose of projection into the future. We have therefore in this
study used statistical modeling technique to obtain future rainfall amounts with
covariates and factors derived from the lunar-solar geometry. The main advantage of lunar-solar parameters is that their values can be calculated accurately at all times and
have therefore been used to carry out a projection of monthly rainfall amounts in Kenya
for the period 1901 to 2020. The statistical model reveals an increase in frequency and
intensity of severe hydrology events for the period 2018 to 2020.
