| dc.description.abstract | Most economic activities of African countries, like Ethiopia, such as agriculture,
hydroelectric power, and industry are dependent on the availability of rainfall.
Rainfall monitoring in space and time is therefore a critical aspect for the sustainable
socio-economic development of the country.
Near real time satellite precipitation estimates are becoming increasingly available to
the African countries. These precipitation estimates are potentially useful in order to
augment the rainfall data, which are obtained from relatively sparse rain gauge
network in the country.
It is, therefore, important to understand the accuracy and limitations of satellite
rainfall estimates, such the CPC rainfall estimates, in order to use the products of
these techniques in monitoring rainfall distribution and intensity in the country.
Standard measures, such as the correlation analysis, relative percentage error analysis
and root mean square error analysis have been used in this study to validate the CPC
rainfall estimate.
Users of short-term satellite rainfall estimates need to understand the expected
accuracy and error associated with the estimates. This study discussed the accuracy
or error of the CPC rainfall estimates which gives useful information to help the CPC
algorithm developers to improve their products and to help the users of short-period
satellite rainfall estimates to understand the accuracy and limitations of the CPC
product (estimate).
The results from correlation and root mean square error analyses showed that the
CPC technique fits well for Ethiopia for long-term estimates, but the results from the
graphical and relative percentage error analyses indicated that the CPC rainfall
estimating technique fails to give accurate estimates on short-term basis. | en |
