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The refractivity profile variation in troposphere is one of the aspects that influences long-distance terrestrial electromagnetic wave propagation and performance of communication systems. This study is aimed at calculating and estimating radio refractivity at Makurdi with tropospheric parameters of relative humidity, absolute temperature and atmospheric pressure using ITU-R and artificial neural network models. Validation results are thus, absolute temperature = 0.4313 K, relative humidity = 0.9989 %, pressure = 0.0201 (hpa) respectively. The validation of the correlation coefficient results shows that all the tropospheric parameters have effects on radio refractivity, but relative humidity has more effect which is attributed to the large quantity of moisture at the troposphere. From the estimation results, it is clear that artificial neural network has the capacity of estimating tropopheric refractivity since the estimated values has close agreement with the calculated values.

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