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Radio refractivity estimation is paramount in the planning and design of radio link/systems for the purpose of achieving optimal performances. In this study, the monthly average daily atmospheric pressure, relative humidity and temperature data obtained from the National Aeronautics and Space Administration (NASA) during the period of twenty two years (July 1983 -June 2005 for Osogbo (Latitude 7.47 0 N, Longitude 4.29 0 E, and 302.0 m above sea level) were used to estimate the monthly tropospheric radio refractivity and to investigate its variation with other meteorological parameters of monthly average daily atmospheric pressure, relative humidity, absolute temperature, saturation vapour pressure and radio refractive index. The field strength variability (FSV) and the radio horizon distance were also computed. The monthly variation of FSV using two years data (2003 -2004) was also investigated. The results of this study revealed that the values of radio refractivity are more during the rainy season than in the dry season. It was found that the maximum average value of tropospheric radio refractivity of 370.98 N-units and minimum average value of 332.36 N-units occurred in the months of May and January during the rainy and dry seasons respectively. 71.45 % of the total value of the radio refractivity was contributed by the dry term while the major variation is by the wet term radio refractivity. The average refractivity gradient computed for the study area under investigation was −42.69 Nunits/km and the average effective earth radius (kfactor) was 1.37 which corresponds to the conditions of super refraction. The annual maximum mean value of FSV is 7.72 dB and minimum monthly mean value of 0.07 dB was obtained for the study area. The implication of this FSV values is that the output of a receiving antenna in Osogbo may generally be subjected to changes not less than 0.07 dB in a year and not greater than 7.72 dB. The descriptive statistical analysis shows that the radio refractivity, relative humidity, absolute temperature and radio refractive index data spread out more to the left of their mean value (negatively skewed), while the atmospheric pressure data spread out more to the right of their mean value (positively skewed). The radio refractivity, relative humidity and radio refractive index data have positive kurtosis which indicates a relatively peaked distribution and possibility of a leptokurtic distribution. The atmospheric pressure and absolute temperature data have negative kurtosis which indicates a relatively flat distribution and possibility of platykurtic distribution.

In this paper, the monthly variation of Surface Water Vapour Density (SWVD) with meteorological parameters of monthly average daily mean temperature, relative humidity, surface pressure, cloud cover and sunshine hours during the period of sixteen years (2000-2015) for Owerri (Latitude 5.48°N, Longitude 7.00°E, and 91m above sea level) were investigated. The daily variation of surface water vapour density for the two distinct seasons considering two typical months in each during the period of year 2015 was examined. The results showed fluctuation in the amount of surface water vapour density in each day of the month for the period under investigation. The monthly average daily values indicated that the surface water vapour densities are greater during the raining season than in the dry season. It was observed that the maximum average value of surface water vapour density of 21.002gm-3 occurred in the month of June during the raining season and minimum value of 14.653gm-3 in the month of January during the dry season. The highest value of surface water vapour density was observed on 9 th May, 2015 and the lowest on 14 th January, 2015. The comparison assessment of the developed SWVD based models was carried out using statistical indices of coefficient of determination (R 2), Mean Bias Error (MBE), Root Mean Square Error (RMSE), Mean Percentage Error (MPE), Nash-Sutcliffe Equation (NSE) and Index of Agreement (IA). The developed multivariate correlation regression model that relates temperature and relative humidity with R 2 =99.9% MBE=0.1259 RMSE=0.1462 MPE=-0.6739 NSE=99.8402% and IA=99.9611% was found more suitable for surface water vapour density estimation with good fitting and therefore can be used for estimating surface water vapour density in the location under investigation and region with similar climatic information. The results of the descriptive statistical analysis revealed that the surface water vapour density, mean temperature, relative humidity, cloud cover and sunshine hours data spread out more to the left of their mean value (negatively skewed), while the surface pressure data spread out more to the right of their mean value (positively skewed). The surface water vapour density data have positive kurtosis which indicates a relatively peaked distribution and possibility of a leptokurtic distribution while the mean temperature, relative humidity, surface pressure, cloud cover and sunshine hours data have negative kurtosis which indicates a relatively flat distribution and possibility of platykurtic distribution.

In this study, the measured monthly average daily global solar radiation and extraterrestrial solar radiation using the generalized 45% and 40% dataset was utilized to estimate the photosynthetically active radiation (PAR) and extraterrestrial photosynthetically active radiation (PAR 0 ) for Akure (Latitude 7.17 0 N, Longitude 5.18 0 E, and 375.0 m above sea level) Ondo State located in South Western, Nigeria. The monthly average daily sunshine hours, maximum and minimum temperature data were used to develop nine (9) new PAR sunshine based models and three (3) PAR temperature based models. The meteorological parameters used in this study covered a period of thirty one years (1980 -2010). The newly developed models were tested using statistical indicators of coefficient of determination (R 2 ), Mean Bias Error (MBE), Root Mean Square Error (RMSE), Mean Percentage Error (MPE), ttest, Nash -Sutcliffe Equation (NSE) and Index of Agreement (IA). The PAR sunshine based models that took a quadratic form and the linear logarithmic PAR temperature based models were found more suitable for estimating PAR for the location under study. Comparing the PAR sunshine based and temperature based models indicated that the PAR sunshine based model is more suitable for PAR estimation in Akure. Furthermore, the results showed that the PAR is high during the dry season and low during the rainy season. Based on the measured and estimated PAR models; the minimum values was found in July and August while the maximum values in February, March and November. The descriptive statistical analysis shows that the PAR and all the estimated sunshine based PAR data spread out more to the left of their mean value (negatively skewed). Similarly, they have negative kurtosis which indicates a relatively flat distribution and possibility of platykurtic distribution. The PAR and the PAR logarithmic temperature based model (equation 17a) data spread out more to the left of their mean value (negatively skewed), while the PAR linear exponent and linear temperature based models (equation 17b and 17c) data spread out more to the right of their mean value (positively skewed). The PAR and all the estimated PAR temperature based data have negative kurtosis which indicates a relatively flat distribution and possibility of platykurtic distribution.

Precipitable water vapour (PWV) is a vital component of the atmosphere and appreciably controls many atmospheric processes. The PWV is not easy to measure with sufficient spatial and time resolution under all weather conditions. In this paper, three precipitable water vapour models; the Smith, Won and Leckner's models were evaluated and compared for Owerri (Latitude 5.48°N, Longitude 7.00°E, and 91 m above sea level) using meteorological parameters of monthly average daily maximum temperature, minimum temperature and relative humidity during the period of sixteen years (2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015). The Leckner's model was found most suitable and therefore recommended for estimating PWV for the location with range between 3.253 and 4.662 cm. The highest PWV occurred in June for Won and Leckner's models while for Smith's model it occurred in September; the lowest PWV occurred in January for all the evaluated models. The result showed that high values of dew point temperature (T dew ), PWV and relative humidity (RH) were observed during the raining season and low values in the dry season; this is an indication that the dew point temperature is a reflection of the PWV and RH. The dew point temperature is an opposite reflection of the virtual temperature (T virtual ), potential temperature (T potential ) and mean temperature (T mean ). The dew point temperature increases and decreases with mean temperature in the months from January to March and in July respectively for the location under investigation. The values of the dew point temperature indicated that the air is stable signifying no development of severe weather condition like thunderstorms. The maximum and minimum virtual temperature correction of 3.3246°C and 2.3371°C occurred in June and January respectively while for the dew point depression, it occurred in the months of January and September with 8.7514°C and 2.1094°C. The descriptive statistical analysis shows that the dew point temperature, potential temperature, mean temperature and virtual temperature correction data spread out more to the left of their mean value (negatively skewed), while the virtual temperature and dew point depression data spread out more to the right of their mean value (positively skewed). The dew point temperature and the virtual temperature correction data have positive kurtosis which indicates a relatively peaked distribution and possibility of a leptokurtic distribution while the virtual temperature, potential temperature, mean temperature and dew point depression data have negative kurtosis which indicates a relatively flat distribution and possibility of platykurtic distribution.