The tenth IMSC, Beijing, China, 2007 - International Meetings on ...

stations in Iran. <strong>The</strong> amount of seasonal, annual ETo and rainfall trend were determined by
Mann–Kendall test analysis during 1953s–2003. <strong>The</strong> data was then subjected to statistical
tests to determine the probability distributions that best fit them. Suitable probability
distributions were selected from among the Normal, Log-Normal, Gumbel Extreme Value Type
I, Gamma and Logistic distributions. Seasonal and annual rainfall and ETo at 80, 50 and 30
percent probability levels were determined. <strong>The</strong> results showed that there is not any significant
trend for seasonal and annual rainfall and evapotranspiration in all of station. And so, <strong>The</strong>
probability analysis of data shows that variability of evapotranspiration and rainfall are so much,
therefore determining return period of this data are useful for rainfed irrigation. <strong>The</strong> results of
this analysis can be attributed to expansion of irrigation areas and agricultural management.
Keywords: climate change, rainfall, Reference crop evapotranspiration, probability analysis,
trend
Error Detection and Checking of Inhomogenities Basing on the Metadata in Uganda
Climatological Dataset
Lubega N.Fortunata
Department Meteorology Uganda
lubegf@yahoo.com
Majugu Absein
Department Meteorology Uganda
Climate data is a key aspect of statistical climatology, more so, today, when climate
change amplitude is super imposed on climate variability, there is a dire need of well managed
quality data to prove that climate change is not a myth but a reality. WMO together with the
climate scientist are keen to see that artificial deviations within the climate data must be dealt
with, hence the need for data homogenization. In his opening speech, at the FOUTH
SEMINAR ON HOMOGENISATION AND QUALITY CONTROL IN CLIMATOLOGICAL
DATABASES (Budapest Hungary WMO_TD No.1236 2004), Yadowsun Boodhoo observed
that, homogenization of the climate data is not within the reach of all member countries. In this
regard, this paper seeks to address issues pertaining to uncertainties within the climate
datasets which was written out of the quality control work done during the HYDROCLIMATIC
STUDY(2003) in Uganda. <strong>The</strong> detection of errors in climatological data sets, the checking of
inhomogenities basing on metadata and design of quality control measures were undertaken
during an inter-disciplinary study carried out by Uganda Meteorological Department (UMD) in
collaboration with the Water Resource Management Department (WRMD). <strong>The</strong>re were 597
rainfall and 50 temperature stations which were digitized using CLICOM software that
generated 16,363 and 1,500 records of rainfall and temperatures respectively, spanning the
years 1902 to 2003.Different types of errors and their relationship were identified. Checking
logics (nature of checking algorithm) were employed both by automatic computer programs
and manual checks. <strong>The</strong> check tests used varied in accordance with the characteristic of
logical operations, the element and the type of data being checked, daily, monthly or annual
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