| dc.description.abstract | Climate variability has significant impact on performance of the economy of a country
especially in a developing country like Kenya. Certain sectors of the economy like
agriculture, manufacturing, transport and communication are vulnerable to unanticipated
weather changes. Thus a good climate and weather forecasting models with high degree
of certainty would playa pivotal role in future planning and policy formulation of any
economy of a developing country.
Climatological weather forecast in Kenya is used to classify amount of rainfall expected
in each of the homogenous climatic zones into three categories: Below Normal, Near
Normal and Above Normal using terciles. These terciles are practical (actual) values
obtained by arranging the rainfall data from a given base period to a specific year into
ascending order anddividing the data into three equal parts. This mode of classifying
rainfall data has been proved to have inconsistencies and in- homogeneities.
This study intends to improve the classifications of rainfall into the above stated
categories by fitting a theoretical probability distribution to the rainfall data and .
determining theoretical values of the terciles using distribution function fitted.
Probability forecasts offer several benefits. They contain more information than weather
forecasts and the uncertainty in the forecast is specifically expressed, thus the user is
madeaware of that uncertainty and can use this information in decision-making.
Probability forecasts can be used with thresholds to make decisions, where the thresholds
canvary from user to user and purpose to purpose. Availability of probability forecasts
would allow users to make decisions based on a quantitative uncertainties and his /her
threshold for making the decision.
Themainobjectives of the study is to determine the distribution ofterciles which are
usedtoclassify the amount of rainfall received in aparticular region into the following
thethree categories: Below normal, Near normal and Above normal in order to improve
Climatological forecasting in Kenya.
Specificobjectives of the study are:
1. To fit the theoretical probability distribution to the cumulative rainfall data for a
season for a given weather station in the country.
2. To find the estimates of the probability distribution.
3. To obtain the theoretical (actual) distribution of the tercilesTI andT2,that is
F (TI, T2) arid find out how this information can be used to improve on the
forecast classification-rainfall data. | en |
