This research paper evaluates the variations in radio refractivity in Calabar, Cross River State, Nigeria. The research work was carried out from data obtained from the Nigeria Meteorological Agency (NIMET) for a period of 10 years (2010 to 2019) within the rainy season from March to October. The yearly averages of refractivity were calculated from meteorological parameters provided. The analysis carried out generally shows slight variations in refractivity during this period with the highest value occurring during the wet season in 2016 and the least value occurring in 2014. The study also showed a linear relationship between water vapour pressure and refractivity, with an R 2 value of 0.9902 while the relationship between refractivity and temperature had an R 2 value of 0.8442.

It is common knowledge that tropospheric variables affect signals, thereby distorting coverage. Since the major factor affecting dropped calls is coverage and the penetration depth of the signal strength transmitted by a wireless system determines its coverage, therefore, there is a tendency for tropospheric variables to affect dropped calls. This research investigates the effects of relative humidity, wind speed, rainfall and temperature on dropped calls for four mobile networks (MTN, Airtel, Globacom and 9mobile) in Cross River State, Nigeria. Six years data of weather variables collected from the Nigerian Meteorological Agency (NiMet), Cross River State and six years Drop Call Rate (DCR) data obtained from the telecommunications regulatory body, Nigerian Communication Commission (NCC), was used for this study, both spanning from January 2015 to December 2020. From the collected data, graphs were plotted and, in each case, the DCR of the mobile networks were the dependent variables while the tropospheric variables were the independent variables. Also, regression models were obtained to forecast the DCR of each network, provided the tropospheric variable at each given period is known. Finally, the variables were correlated to give a picture of how each tropospheric variable related to the DCR of the mobile networks. For MTN and 9mobile networks, a low positive correlation was obtained for rainfall and relative humidity, a highly positive correlation was obtained for wind speed while a lowly negative correlation was obtained for temperature. For Airtel network, a moderately negative correlation exists between DCR and relative humidity/temperature while a low positive relationship existed for rainfall. However, a low negative relationship was observed for wind speed. For Globacom network, a moderately negative and a moderately positive relationship was obtained for rainfall and relative humidity respectively while a highly positive and a lowly negative correlation was obtained for temperature/wind speed against DCR. This result will be very useful to the meteorologist, mobile network planners and the network operators.