| dc.description.abstract | The homogenization of climate data is of major importance because non-climatic factors make
data unrepresentative of the actual climate variation, and thus the conclusions of climatic and
hydrological studies are potentially biased. A great deal of effort has been made to develop
procedures to identify and remove non-climatic in-homogeneities. This report reviews the
characteristics of several widely used statistical techniques. In this study, the statistical
simulation approach is applied to precipitation data from different monitoring stations located in
Kenya (1950-2006).
The analyses were carried out on several rainfall series inthe 12climatic zones of Kenya. The
results of both the Standard Normal Homogeneity Tests (SNHT) and the Buishand Range Test
(BR) tests show that, atthe 5% significance level, the monthly series have statistically significant
trend.
The findings from the Standard Normal Homogeneity Test (SNHT) showed that allthe monthly
rainfall records from the selected synoptic stations were useful and hence could be used for any
further analysis. From the Buishand Range (BR) Test done, seven out of the twelve stations were
useful while the rest of the stations were doubtful. From the results of the Tests performed it is
clear that the Buishand Range (BR) Test was able to detect breaks at the beginning middle and
the end of the series .It istherefore a rigorous method and hence recommended for homogeneity
testing. | en_US |
