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

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. 16/01/2019

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 16/01/2019

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 16/01/2019

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. 16/01/2019

Result 1: actual MAM RF time series 16/01/2019

Result 2: MAM RF indices time series 16/01/2019

Result 3: actual SON RF time series 16/01/2019

Result 4: SON RF indices time series 16/01/2019

Result 5: correlation and significance test Season r2 r F p MAM 0.34 0.59 1.22 0.009 SON 0.25 0.5 1.72 0.06 Confidence level = 95% P critical = 0.05 MAM correlation moderately strong and statistically significant SON correlation moderately strong and not statistically significant. 16/01/2019

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 16/01/2019

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 16/01/2019

Thank you for me listening to me 16/01/2019