Meteorological Models for Determination of Surface Radio Refractivity over Nigeria

Abstract

Previous studies showed that linear meteorological expressions obtained were localized and could not be generally applied. It is therefore required that more locations should be investigated to deduce new linear meteorological models best suitable for estimation of surface refractivity. Surface meteorological data, including pressure, temperature and relative humidity, was downloaded from Modern-Era Retrospective analysis for Research and Application (MERRA - 2) for six locations defined by different climatic conditions over Nigeria, namely Yenagoa, Abakaliki, Ibadan, Anyigba, Jalingo and Sokoto for a period of 40 years partitioned into two periods of 20 years each. The 1979 – 1998 dataset of atmospheric temperature, T (K), atmospheric pressure, P (hPa) and relative humidity, Rh (%) were extracted using text import wizard to calculate surface refractivity using existing model (Nitu-r). Regression analysis was carried out to obtain new linear meteorological expressions as function of temperature (Nt), relative humidity (Nrh), and combination of relative humidity and temperature (Nrh,t). The new expressions were tested using 1999 – 2018 meteorological dataset and the results of surface refractivity from the new linear expressions were compared with values from existing equations.
 It was observed that high relative humidity and low temperature values prevalent in the three southern stations – Yenagoa, Abakaliki and Ibadan – significantly enhanced the suitability of Nrh,t linear meteorological model for estimation of surface refractivity values comparable toNitu-r. Contrary to the observations in the southern stations, in the northern stations, relative humidity contributions (Nrh) had the best linear correlation of 0.96 at Anyigba, 0.98 at Jalingo and Sokoto. Estimation of surface refractivity from the new linear meteorological models was found to be best as a function of temperature and relative humidity in the south and a function of relative humidity in the north. Linear meteorological models as a function of relative humidity and temperature were best suitable for stations in the south with minimum correlation of 0.98 while linear expressions as a function of relative humidity only were best suitable for the stations in the north with minimum correlation of 0.96.

The Role of Statistical Methods and Tools for Weather Forecasting and Modeling

“…(8) shows the relationship between refractivity (dependent variable) and meteorological parameters (ambient temperature, atmospheric pressure, and vapor pressure) which are all independent variables. This has been applied in [7] modeling the meteorological parameters for the accurate determination of refractivity. These meteorological parameters (Ambient Temperature, Atmospheric Pressure and Relative Humidity) have been obtained from the Nigeria meteorological Agency (NiMet), Calabar.…”