| dc.description.abstract | Rainfall products from operational algorithms like the TAMSAT and the NOAA CPC
African Rainfall Estimate are being used for many diverse meteorological, climatological,
hydrological, agricultural, and other applications. It is therefore important to have an idea of
their accuracy and expected error characteristics. This is done by validating the satellite
precipitation estimates against "ground truth" from rain gauge observations. One of the
biggest challenges in generating real time climate information for decision support is
monitoring rainfall performance over the western region of Uganda, which is characterized
by a very sparse rainfall observation station network that has continued to degenerate over the
past years. This has resulted into marked inconsistencies and gaps in gauge data. This region
has a marked spatial and temporal rainfall variability which is attributed to its raised terrain,
which is characterizing the western highland region together with the western albertine rift
region. The highly variable rainfall in the tropics directly and indirectly affects different
socio-economic sectors including agricultural production, water resources management,
transport, construction, crop pest monitoring, disaster management, oil exploration among
others. It is therefore essential to measure areal rainfall on real time basis in order to see the
influence of the variable rainfall on such sectors. Remote sensing using satellites has been
found very efficient for this as compared to the in-situ methods of observation. The
comparison of gauge rainfall totals with the satellite estimates, whether on monthly or ten day
temporal scales, remains an essential tool in the validation of satellite products, which may be
used to augment the data gaps or supplement the available scanty data. This study is therefore
to compare satellite derived rainfall estimates from two different operational algorithms, the
NOAA CPC RFE and TAMSAT RFE with gauge data from five stations in western Uganda,
with the main objective of presenting a ground truth and to show the expected errors in the
estimates of the two algorithms. The study shows that both algorithms are in agreement with
the rainfalt climatology patterns for all the five stations in the area of study. The TAMSA T
RFE and the CPC RFE over Arua station showed the highest bias of (15.62 mm) and (7.96
mm) respectively. For both algorithms, Kasese station showed the least bias (-0.71 mm) for
the TAMSAT RFE and (0.87mm) for the CPC RFE. The comparison further shows that the
NOAA CPC RFE reflects a better agreement with the gauge data as compared to the
TAMSAT RFE over the western region of Uganda. The NOAA Cf'C RFEs exhibited smaller
biases as compared to the TAMSAT RFEs. Generally both RFEs exhibit a tendency to under
estimate precipitation for most dekads within the study period for the five stations. | en |
