A study of the long-term variability; trend and characteristics of visibility in four zones of Nigeria was carried out. Visibility and other meteorological data from NOAA-NCDC and aerosol index data over Nigeria during 1984-2013 are analyzed using time series and simple regression model. There are significant decreasing trends for every region and season during the 30-years period; the fluctuations exhibited nearly similar pattern. The 30-year mean visibilities for the four zones (Sahel; North Central; Southern; and Coastal) were 13.8 ± 3.9; 14.3 ± 4.2; 13.6 ± 3.5 and 12.8 ± 3.1 km with decreasing trends at the rates of 0.08; 0.06; 0.02 and 0.02 km/year. In all the zones; visibilities were better in summer while worse in Harmattan (dry season). During summer visibility was best in Sahel and North-central; however; in Harmattan visibility was best in southern and coastal zones. It was best between May and June (17.6; 18.9; 16.6 and 15.1 km) with a second peak in September. The 30-year seasonal averages were 16.2 ± 2.1; 16.8 ± 2.4; 15.4 ± 1.8 and 14.0 ± 2.2 km in summer; and 10.2 ± 2.5; 10.9 ± 2.9; 11.0 ± 3.3 and 11.4 ± 3.0 km in Harmattan for the respective zones. Sahel and North Central had the worse visibility reduction during Harmattan compared with Southern and coastal areas. An analysis based on simple regression equation reveals a strong and negative relationship between visibility on one hand; AI; and AOD on the other hand. The analysis also discusses the variability regarding the frequency of occurrence of a dust storm; dust haze; and good visibility over the period of study.

The uncertainty in the quantification of aerosol properties such as concentration, size, and composition, spatially and temporally makes regional studies important. Therefore, this study presents seasonal variations of aerosol optical properties over Ilorin (8˚32'N, 4˚34'E), Nigeria. Long-term (1998-2013) records of aerosol optical depth (AOD) and angstrom exponent α, from ground-based Aerosol Robotic Network (AERONET) are used to study the seasonal variability, characteristics and types of aerosol. The study showed that seasonal variations (Harmattan and Summer) result in different aerosol concentration, characteristics, and types. The magnitude and sensitivity of AOD to wavelength are found low in Summer with significant increase during Saharan dust transport season (Harmattan). The average mean AODs are 0.73 ± 0.50, 0.97 ± 0.52 and 0.46 ± 0.29 with corresponding mean angstrom of 0.66 ± 0.36, 0.68 ± 0.34, and 0.64 ± 0.37 for the entire period, Harmattan and Summer seasons. High frequency of occurrence of angstrom exponent below 1 (78% and 81%) which were observed during Harmattan and Summer indicates that the particles are generally coarse in mode. The results revealed that for both Harmattan and Summer seasons, the dominant aerosol was dust (DA) with frequency of occurrence of 82% and 79%. However, mixed aerosol (MIXA) (14.4%) is the second dominant case during Harmattan while in Summer maritime aerosol (MA) (9.1%) associated with transport due to southwesterly trade wind is the second dominant aerosol. This conclusion is supported by size distribution data for the study site which showed that large volume of aerosol particle size are enclosed in largely coarse mode range in all seasons. A 7-day back trajectory seasonal frequency plot sourced from the Hysplit Single Particles Lagrangian Integrated Trajectory model (Hysplit_4 model) shows that dust are transported from the Saha-* Corresponding author. ra during north-easterly trade wind flow while the observed marine aerosols are conveyed by the southwesterly trade wind influences to the study site.

The objective of this work is to analyze the temporal and spatial variability of the monthly mean aerosol index (AI) obtained from the Total Ozone Mapping Spectrometer (TOMS) and Ozone Monitoring Instrument (OMI) in comparison with the available ground observations in Nigeria during 1984-2013. It also aims at developing a regression model to allow the estimation of the values of AI in Nigeria based on the data from ground observations. TOMS and OMI data are considered and treated separately to provide continuity and consistency in the long-term data observations, together with the meteorological variable such as wind speed, visibility, air temperature and relative humidity that can be used to characterize the dust activity in Nigeria. The results revealed a strong seasonal pattern of the monthly distribution and variability of absorbing aerosols along a north to south gradient. The monthly mean AI showed higher values during the dry months (Harmattan) and lower values during the wet months (Summer) in all zones. From December to February, higher AI values are observed in the southern region, decreasing progressively towards the north, while during March-October, the opposite pattern is observed. The AI showed clear maximum values of 2.06, 1.93, and 1.87 (TOMS) and 2.32, 2.27 and 2.24 (OMI) in the month of January and minimum values in September over the north-central, southern and coastal zones, while showing maximum values of 1.76 (TOMS) and 2.10 (OMI) during March in the Sahel. New empirical algorithms for predicting missing AI data were proposed using TOMS data and multiple linear regression, and the model co-efficient was determined. The generated coefficients were applied to another dataset for cross-validation. The accuracy of the model was determined using the coefficient of determination R 2 and the root mean square error (RMSE) calculated at the 95% confidence level. The AI values for the missing years were retrieved, plotted and compared with the * Corresponding author. M. Balarabe et al.426 measured monthly AI cycle. It is concluded that the meteorological variables can significantly explain the AI variability and can be used efficiently to predict the missing AI data.

The variation of climate in the past on different time scale in Nigeria has generated a lot of concern and is still posing a threat to life and properties. Meteorologist and climatologist in Nigeria are working hard to address this problem. This study assessed the recent trend and variability of summer season`s visibility and temperature for Sahel zone of Nigeria. The long-term (1988-2017) summer seasons meteorological data derived from National Oceanic Atmospheric Agency-National Climate Data Centre (NOAA-NCDC) were used. A significant decreasing trend in visibility and increasing trend in temperature were detected during the entire period of study. The overall averages were 14.71 ± 4.17 km and 24.54 ± 4.19  respectively. The trends were found more significance in the last ten years. The Decades` means are 19.38± 3.05, 13.76 ± 2.09, 10.98 ± 1.28 km  and 20.60 ± 4.72◦C, 25.78 ± 2.54 ◦C and 27.25 ± 0.79  ◦C for the first, second and third decades respectively. Standardize anomaly chart revealed that over the period of study, positive visibility anomaly correspond to negative temperature anomaly and vice visa. Their correlation at p< 0.05 significant level showed a negative relationship of 0.54 over the thirty years period. However, decade analysis showed a positive correlation of 0.47 and negative correlations of 0.61 and 0.74 for the first, second and third decades respectively. These suggest that summer season of the recent decades are dustier than the previous ones and that, summer season of the recent decades become hotter than the previous decades