1. Technical Conference on Meteorological and Environmental Instruments and Methods of Observation TECO Geneva, 4th – 6th December 2006.
Validation of Automatic weather observation system Data in Uganda. By
Lawrence Aribo, Eliphaz Bazira

2. Introduction
Lives and livelihoods of most communities in Uganda depends on:
-Agriculture
-Determined by climate as one of the key factors.
Frequent occurrence of extreme climatic events of recent has had adverse effects
-food insecurity and famine
-property and economic losses
-pests and disease epidemics
Hence, public outcry for reliable meteorological and environmental information.
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3. Objectives and hypothesis
General: a contribution towards provision of timely and reliable meteorological information.
Specifically: to investigate the relationship between AWOS and Conventional (surface) observation RF data.
Hypothesis: significant relationship between AWOS and conventional observation RF data
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4. Methods
Daily RF data (2005) for Namulonge Agro-met station, obtained from Dept. of Meteorology Uganda
Subjected to quality control and consistency checks
Data grouped into pentads for MAM and SON rainy seasons
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5. Methods cont.. Data sets normalised; ((Ii - ī)/σ)
Time series graphs drawn for actual RF (mm) and RF indices (MAM and SON seasons)
Scatter diagrams plotted
Correlation analysis performed
ANOVA F-test of significance then carried out.
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6. Result 1: actual MAM RF time series
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7. Result 2: MAM RF indices time series
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8. Result 3: actual SON RF time series
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9. Result 4: SON RF indices time series
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10. Result 5: correlation and significance test
Season r2 r F p
MAM
SON
Confidence level = 95%
P critical = 0.05
MAM correlation moderately strong and statistically significant
SON correlation moderately strong and not statistically significant.
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11. Conclusion
Some variability between RF data recorded by AWOS and human observers
Similar trends of RF for the two observation methods (AWOS and Conventional)
Moderately strong relationship between data sets from the two observation methods
Statistically significant for MAM season
Not significant for SON season
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12. Recommendation
Up-scaling the research to national and regional levels (Spatio - temporal)
Motivation and refresher training for observers to avoid observer biases
Adequate and regular funding for inspection of instruments
Regular calibration of instruments
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13. Thank you for me listening to me
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