SPATIO-TEMPORAL VARIATIONS OF WIND SPEED DURING HARMATTAN SEASON IN NORTHEASTERN NIGERIA

Wind speed is the principal climatic element that drives the Marmaton season in West African sub region. It drives the season by conveying huge amount of dust across the Northeastern Nigeria. The presence of dust in the atmosphere brought by the Northeast trade winds during the Harmattan season plays a vital role in absorbing and scattering solar radiation. The study examines the spatial and temporal variations of wind speed in Northeastern Nigeria during the Harmattan season with the sole aim of ascertaining its variability, patterns and trends from1984 to 2014. Descriptive and statistics such as mean, standard deviation, coefficient of variation, and time series analysis with ArcGIS 10.3 was used in examine the temporal and spatial variations of wind speed from 1984–2014 in six synoptic stations of Northeastern Nigeria. The findings show that wind speed varied both temporally and spatially in the last three decades. The pattern of variations in the six synoptic stations shows rising trends within the study years. It was also found that latitude playing a crucial role in determining the speed of the wind in the study area and as the speed of the wind increases with increasing latitude. 
Keywords: Wind speed, Harmattan, Season, Northeast, Variation and ITD. 
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area of high pressure to area of low pressure system.The movement of the wind in the first place is determined by pressure gradient in the Sahara Desert during the period of the low sun (winter period in the Northern hemisphere) and the greater the pressure of the air, the faster the wind moves. There is no gainsaying that the speed of the wind determines the amount of dust that is seasonally or annually brought into the region. Therefore, assessing the speed at which this climatic parameter moves across the study area during Harmattan season will go a long way in making sense out of its Spatio-temporal variations in last three decades.
Wind speed is an environmental resource that facilitate the generation of wind energy.
Due to recent development in wind energy mostly in developed countries (especially in Europe) with desire to reduce environmental impacts of the conventional energy resources, there is a general growing interest in the wind energy development in Nigeria (Adaramola and Oyewola 2011). It is against this background this research examines the Spatio-temporal variations of wind speed during Harmattan season in Northeastern Nigeria by assessing its variability, patterns and trends from 1984 to 2014.The Northeast trade wind controls the Harmattan season in West African sub region; it drives the season by conveying huge amount of dust across the region (Danlami, 2017). This wind advances into the savannah belts of Nigeria due to the seasonal migrations of the Inter-Tropical Discontinuity (ITD). The ITD attains its southernmost position around latitude 6 0 .00 1 N in January. This marks the peak of the dry season in West Africa with all the areas with the exception of the coastal areas under the influence of the dry Northeasterly from the Sahara Desert (Ayoade, 2004). The North east trade wind commonly referred to as the Harmattan wind; arise due to synoptic-scale of pressure gradients that align north-south across the Saharan desert.
High pressure to the north of the Bodele intensifies the NE trade winds, leading to an increased entrainment of dust in the Bodele Depression. In summer, dust mobilization cannot be explained by the large scale meteorological conditions. This highlights the importance of local to regional wind systems linked to the northernmost position of the inter-tropical convergence zone (ITCZ) during this time (Schwanghart and Schutt, 2007).Harmattan season is highly dependent on air pressure variability in the Mediterranean area (Schwanghart and Schutt, 2007). When the northeast trade wind covers substantial parts of West African countries towards the coast and that is when the dry season is experienced. During the months of November and December to the months of January, February and March, the climate of the West African region is dominated by Dantata Danlami, et al/ GEOSI Vol. 4 No. 2 (2019) [105][106][107][108][109][110][111][112][113][114][115][116][117][118][119][120][121][122][123] northeasterly trade winds. The subtropical pressure belt system over North Africa near latitude 30 0 north is responsible for the movement of the NE trade wind. The deflecting force of the earth's rotation known as the corilis force is responsible for the Northeast direction of this trade wind. Winds are caused by pressure differences that induce airflow from zones of high pressure to zones of low pressure (Getis el at., 2011). In other words, wind originates from region of high pressure belt and move to the region of low pressure belt. This trade wind that originates from the subtropical high pressure belt in the northern hemisphere plays a key role in influencing the climate of West Africa. It is this wind that blows and pick up fine dust and sand particles otherwise known as crustal materials from the Sahara Desert and produce the Harmattan season across West African sub region.

The Methods
The study area in this article is Northeastern Nigeria. It comprises Adamawa, Bauchi, Borno, Gombe and Yobe states. It is approximately located between latitudes 9 0 30 1 N and 14 0 .00 1 N and longitudes 9 0 14 1 E and 15 0 .00 1 N. It shares border with Niger Republic to the North, Lake Chad to the North-east, and Cameroon Republic to the East. Plateau and Taraba states to the South and Jigawa state to the West. The locations of the synoptic stations can be seen in table From the table, it is glaring that Bauchi station has the highest elevation in the Western part of the study area and Yola station with the lowest elevation in the Southern part of the study area The Meteorological data used for the trend-surface analysis in this study was obtained from the Nigerian Meteorological Agency (NIMET). The quantitative data covered a period of 30 years (1984 -2014). In an attempt to analyze the temporal variations and trends of wind speed in the six synoptic stations (Bauchi, Gombe, Maiduguri, Nguru, Potiskum and Yola) in the study area, mean monthly and mean seasonal data were plotted for each station so as to depict the variations and trends in the last three decades.

Results and Discussion
The raw wind speed data was subjected to the statistical tools of Mean, Standard Deviation, Coefficient of Variation; Time Series through the use of the statistical package for the Dantata Danlami, et al/ GEOSI Vol. 4 No. 2 (2019)  From the table, it is glaring that Bauchi station has the highest elevation in the Western part of the study area and Yola station with the lowest elevation in the Southern part of the study area The Meteorological data used for the trend-surface analysis in this study was obtained from the Nigerian Meteorological Agency (NIMET). The quantitative data covered a period of 30 years (1984 -2014). In an attempt to analyze the temporal variations and trends of wind speed in the six synoptic stations (Bauchi, Gombe, Maiduguri, Nguru, Potiskum and Yola) in the study area, mean monthly and mean seasonal data were plotted for each station so as to depict the variations and trends in the last three decades.

Results and Discussion
The raw wind speed data was subjected to the statistical tools of Mean, Standard Deviation, Coefficient of Variation; Time Series through the use of the statistical package for the Dantata Danlami, et al/ GEOSI Vol. 4 No. 2 (2019)  From the table, it is glaring that Bauchi station has the highest elevation in the Western part of the study area and Yola station with the lowest elevation in the Southern part of the study area The Meteorological data used for the trend-surface analysis in this study was obtained from the Nigerian Meteorological Agency (NIMET). The quantitative data covered a period of 30 years (1984 -2014). In an attempt to analyze the temporal variations and trends of wind speed in the six synoptic stations (Bauchi, Gombe, Maiduguri, Nguru, Potiskum and Yola) in the study area, mean monthly and mean seasonal data were plotted for each station so as to depict the variations and trends in the last three decades.

Results and Discussion
The raw wind speed data was subjected to the statistical tools of Mean, Standard Deviation, Coefficient of Variation; Time Series through the use of the statistical package for the social sciences (SPSS) to show the variations and trends of wind speedin the last three decades.
Also, the study mapped out the spatial patterns over the six different synoptic stations to observe the spatial patterns over time in the ArcGIS 10.3 environment. The trend equations were also superimposed on the seasonal mean variations of each synoptic station so as to establish their trends over the years in the study area.The trends and variations of wind speed in all the six synoptic stations of the study area were determined by their monthly and seasonal means in the last three decades. The Figures 1.2 to 1.8 show clearly the variations in wind speed in all synoptic stations of the study area. It is also glaring from the figures (1.3 to 1.8) that the speed of wind diminishes as it travels southward across the study area. Danlami et al (2018) pointed out that the Biu plateau is the most important geomorphologic formation in the study area and the strategic location of the Biu plateau on the path of the Harmattan wind is responsible for the reduction in the speed of the wind thus reducing the amount of dust reaching the extreme south of the study area resulting to moderate visibility in areas around Yolastation.They opined that the Plateau is a structural and topographical divide between the Upper Benue Basin to the south and the Chad Basin to the north.

Monthly Distribution of Wind Speed
The speed of the Northeast trade wind that brings the Harmattan dust from the Sahara Desert and engulfs the whole of West African sub region varies with time and across space.
There are slight variations in the speed of wind during the five (5) months of the Harmattan season. The speed of the wind is higher at the source region and decreases as it advances towards the Gulf of Guinea in the South. The validity of this statement can be seen in the sizes of dust particles that are blown by the wind. Larger dust particles are usually dropped along the way and the finer particles are moved further down south (De Longueville et al., 2010). This is because at the dust source region, the high velocity of the wind could carry larger dust particles but as the wind grows weak in the course of its journey down south, the larger dust particles are dropped and finer ones are moved further into the Gulf of Guinea and beyond. The speed of the wind therefore, decreases with increase in distance (space) from its source. The wind speed variations can be clearly seen on ( Fig. 1.2) across the six synoptic stations of the study area. Yola station that is located in lowest latitude has the lowest wind speed with long-term monthly mean between 1.00 to 2.00 Knots. Maiduguri and Potiskum stations with the highest mean monthly Dantata Danlami,et al/ GEOSI Vol. 4 No. 2 (2019) 105-123 110 wind speed between 5.00 to 6.00 Knots. Gombe, Bauchi and Nguru fall between 3.00 to 5.00 Knots during the Harmattan season. The mean monthly wind speeds for the whole stations fluctuate between 2.00 to 7.00 Knots throughout the Harmattan seasons (November, December, January, February and March) in the study area. Wind speed is measured in Knot in which one knot of wind speed is equal to one nautical mile or one thousand eight hundred and fifty-two meters (1852m) per hour. The International Organization of standardization (ISO) standard symbol for knot is Kn.

Spatial Interpolation of Sub Periods Mean of Wind Speed
The surface visibility degradation experienced in the study area is caused by the arrival of the dust brought by the north east trade wind from the Bodele depression at the heart of the Sahara Desert (Danlami et al 2018). The arrival of this dust that usually engulfs the region is the most conspicuous sign of Harmattan season and therefore, responsible for the degraded visibility.
The Northeast trade wind that seasonally conveys huge amount of dust across the West African sub region that produces the Harmattan season between November and December of one year and January, February and March of the subsequent year (Danlami, 2017) plays a crucial role in regulating the climatic condition of the region. Wind speed which is translated as its capacity for rapid motion, plays a very remarkable role in influencing the Harmattan season variations in northeastern Nigeria. It is important to note that, the variation in wind speed distribution is also important with respect to the impacts of climate variability and change (Karabulut al.,2012;Amadiet al.,2014).
The movement of the wind in the first place is determined by pressure gradient in the Sahara Desert during the period of the low sun (winter period in the Northern hemisphere). The greater the pressure of the air, the faster the wind moves from the region of high pressure to the region of low pressure system. There is therefore, no gainsaying that the speed of the wind determines the amount of dust that is seasonally or annually brought into the region. Therefore, assessing the rate at which this climatic parameter moves across the study area during Harmattan season will go a long way in making sense out of the spatial variations of the season in last three decades. The spatial variations and distributions of wind speed in Northeastern Nigeria can be seen in the six sub periods in (Fig. 1.9 to 1.14).
The sub period of wind speed distribution for 1984 /1985 -1988/1989 in (Fig. 1.9) shows variations between 2.27kn in south to 5.79kn in the north of the study area. Maiduguri shows the highest wind speed followed by areas around Nguru and Potiskum. Areas around Bauchi, Gombe and Yola in the south show relatively low wind speed in this sub period.
The variations in (Fig. 10) and (Fig. 11) cover between 1.98kn -8.78kn and 1.79kn -7.40kn respectively. Potiskum area in both the sub periods show the highest wind speed followed by  (Fig. 14) shows relatively high wind speed across the study area. It varies between 3.56kn in the south and 6.62 kn in the north. Maiduguri areas witnessed high wind speed followed by Nguru, Potiskum and Gombe while Bauchi and Yola were low. It is important to know that the speed of the wind decreases as it moves southwards due to distance (latitudes) and friction generated by the earth-bound materials carried by the wind in the study area (Danlami, 2017). Moreover, the undulating plains in the Chad basin formation in Maiduguri and Potiskum are responsible for high speed of the wind experienced in the region. It is important to state here that wind speed tends to be higher in areas where there are no barriers like shelter belts and highlands.  (Fig. 14) shows relatively high wind speed across the study area. It varies between 3.56kn in the south and 6.62 kn in the north. Maiduguri areas witnessed high wind speed followed by Nguru, Potiskum and Gombe while Bauchi and Yola were low. It is important to know that the speed of the wind decreases as it moves southwards due to distance (latitudes) and friction generated by the earth-bound materials carried by the wind in the study area (Danlami, 2017). Moreover, the undulating plains in the Chad basin formation in Maiduguri and Potiskum are responsible for high speed of the wind experienced in the region. It is important to state here that wind speed tends to be higher in areas where there are no barriers like shelter belts and highlands.  (Fig. 14) shows relatively high wind speed across the study area. It varies between 3.56kn in the south and 6.62 kn in the north. Maiduguri areas witnessed high wind speed followed by Nguru, Potiskum and Gombe while Bauchi and Yola were low. It is important to know that the speed of the wind decreases as it moves southwards due to distance (latitudes) and friction generated by the earth-bound materials carried by the wind in the study area (Danlami, 2017). Moreover, the undulating plains in the Chad basin formation in Maiduguri and Potiskum are responsible for high speed of the wind experienced in the region. It is important to state here that wind speed tends to be higher in areas where there are no barriers like shelter belts and highlands. The spatial analysis of the wind speed in the last couple of decades has shown that it is on the rise which agrees with the temporal analysis. This sends a signal that the desert is vigorously advancing into the savannah belts of Nigeria because the northeast trade wind is responsible for the desert-like conditions in the Sudano-sahelian ecological zone of the study area. The spatial analysis also agrees with what (Dahuwa el at., 2018) where they reported that The wind speeds for Azare, Bauchi State, are high enough to support wind power generation in all strong wind regions of the country. The speed of the wind during the Harmattan season is seen to be stronger in the months of December and January and this conforms to what was reported by (Waewsak et al., 2011). They opined that wind speedanalysis showed strong and sufficient wind for power generation occurred during the months of January to July and in the month of October 2008 in Thasala district in the southern province of Thailand where the south east Asian Monsoon is experienced which is similar to West African Monsoon. Fagbenle et al., (1980) reported that average wind speed across Nigeria is about 3 m/s.
In addition, they found that wind speeds are generally higher in the northern part of Nigeria than in the southern part of the country. Ojosu and Salawu (1990a)