the effect of mean annual rain days on mean annual rain totals

International Journal of Health and Medical Information, Vol. 4, No. 3, December 2015 18ISSN: 2350-2150

The Effect of Mean Annual Rain Days on Mean AnnualRain Totals in the Middle Belt Region of Nigeria

Mage, J. O.

ABSTRACT

This study correlates the occurrence of annual rain days and annual raintotals in the Middle Belt region (MBR) of Nigeria from 1961 to 2006. Dailyrainfall data are collected from eight synoptic weather stations in the studyarea. To compute the annual rain days, the population of rain days is firstextracted then summed and divided by the number of years and the mean gotfor each station. The mean annual rain fall total was also got by summingthe annual totals for each station and dividing by 46. Product momentcorrelation coefficient is applied to the values to establish a relationshipbetween the two variables. The result is tested using the t test. The associationbetween mean number of rain days and mean annual rain totals is significantat 0.5 levels, meaning that annual totals are dependent on the number ofrain days. This indicates a general increasing light rains in the MBR sinceonly heavy events result to few numbers of rain days with high annual totalsalthough there are variations within specific areas in the region.Keywords: Annual rain days, mean annual rain totals, Middle Belt region

INTRODUCTION

Rainfall is the main form of precipitation in the tropics and as a result it is most timesused synonymously as precipitation. The variability of rainfall is an importantconsideration in the tropics where rainfall not only tends to be variable than in thetemperate but is also more seasonal in its incidences within the year (Ayoade, 2004).This variability affects characteristics of rainfall including frequency, intensity, amountsand numbers of rain days for a month, season or year. Changes in global temperaturehave tremendous impact on global climate system. As global temperature changes,atmospheric moisture, precipitation and atmospheric circulation also changes as thewhole system is affected. Radioactive forcing alters heating, and at the earth surfacethis directly affects evaporation as well as sensible heating. Further increases intemperature lead to increase in the moisture holding capacity of the atmosphere at arate of about 7% per degree centigrade (Trenberth and Stepaniak, 2003). As theclimate changes and Sea Surface Temperatures (SSTs) continue to increase, theenvironment in which tropical storms forms changes. SSTs are generally accompaniedby increased water vapours in the lower troposphere, thus the moist static energy thatfuels convection and thunder storm also increases. Together, these effects alter the

Mage, J. O. is a Lecturer in the Department of Geography, Benue State University, P. M. B.102119, Makurdi, Nigeria. E-mail: [email protected].


hydrological circle, especially characteristics of precipitation, that is to say, amounts,frequentcy, intensity, duration and type as well as precipitation extremes (IPCC, 2007).In weather systems, convergence of increased water vapour lead to more intenseprecipitation, but reduction in duration and/or frequency (Trenberth and Stepaniak,2003). Because precipitation comes mainly from weather systems that feed on thewater stored in the atmosphere, this has generally increased precipitation intensity andrisk of heavy rain and snow events (Trenberth and Stepaniak, 2003). Basic theory,climate model simulation and empirical evidence all confirm that warmer climates, owingto increase water vapour lead to more intense storm activity and frequency. With theenergy of global warming powering the system, the resultant effect is increased dailyrainfall intensity and frequency with prospect for even stronger events when the overallprecipitation amounts increases (IPPC, 2007).

It is reasonable for a higher number of rain days to amount to higher rainfalltotals but this simple assumption becomes erroneous and intricately complicated bysituation whereby many of the rainfall events are occurring at varying intensity categories.Expressing as a global average, surface temperature has increase by about 0.740 Cover the past hundred years (1906 and 2007) however, the warming has been neithersteady nor the same in different season or in different locations (IPPC, 2007). Thisdifferential spatial warming will result to differential response by rainfall characteristics.

Bosch and Davis (2008) study on rainfall variability and spatial patterns forsouth eastern region of the United States observe that rainfall patterns although highlyvariable from year to year, show rainfall to be the greatest in the mid summer monthwith high intensity convective thunder storms, Thirty years of rainfall data from the littleriver watershed near Tifton, Georgia were analyzed. The summer storms were foundto be more intense, shorter, yield less volume and occur more frequently. For summerstorms, gauges separated by 1.9km or less are likely to be highly correlated (r > 0.9)while this increase to (r > 9.2) for the winter. They opine that the extrapolation ofprecipitation data collected at off site locations will have little utility for prediction onmodeling purposes unless the off- site gauges is located closer than 2km to the site ofinterest.

Ayansina (2009) uses geographic information system Kriging InterpolationTechnique to examine and map spatiotemporal variation in rainfall in Guinea Savannahof Nigeria. Rainfall data for the period between 1970 and 2000 were collected fromarchives of the Nigeria meteorological services, Oshiodi, Lagos. The result of theanalysis shows that rainfall varies both in time and space. Rainfall variability was observedto be high in most of Northern Guinea Savanna (Yola, Minna and Ilorin) with variedcoefficient of variation (CV) between 26% and 49% while in southern Guinea Savannah,the coefficient of variation is very low especially in Enugu (9%) and Shaki (8%).

Tyubee (2006) analyses the persistence and periodicity of rainfall characteristicsin the middle belt of Nigeria and concluded that significant cycles and periodicitiesexist in the series of rainfall characteristics range between 2.5 to 20.0 years while nosignificant cycle was detected in annual rainfall. The study opines that the middle belt is


located several hundreds of kilometers from the coast and that the short periodicitymay not be associated with the oceanic atmospheric interactions as noted by Lough(1980); Olugunorisa and Adejuwon (2013), but may be as a result of the complexeffects of topography on the speed, direction, vertical height and moisture content ofthe south west monsoon during the rainy season (Tyubee, 2006). This work seeks toestablish the relationship between rain days and rain totals in the Middle Belt Region(MBR) of Nigeria to show what category (heavy or light) most of the rainfall eventsare occurring. The Middle Belt region is a unique geographical and climatologicalregion of central Nigeria (Anyadike, 1987). It is a transitional region between southernand Northern Nigeria. In this study, the middle belt region is defined to cover the sixStates within the north central geo-political zone and Adamawa and Taraba States.This definition uses the northern States boundary of Niger, FCT, Nasarawa, Plateau,Taraba and Adamawa as the northern limit of the region. The Middle Belt Region asdefined is located within Latitude 60241 to 110 301N and longitude 20 421 to 15 000 1E.This covers the total land area of about 333 815km2. The area occupies about 36.14%of the total land area of Nigeria (Figure 1).

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NIGERIA

Figure 1: The location of the Middle Belt Region of NigeriaSource: Longman School Atlas (2009)

The Middle Belt Region is a multi-ethnic and multi-religious area. Unlike the dominanceof the Hausa - Fulani in the north, Yoruba in the southwest and Igbos in the southeast,the Middle Belt is populated largely by minority ethnic groups including Tiv, Nupe,Gwari, Angas, Idoma, Igala, Birom, Igede, Jukum, Mumuye. The total population ofthe region has increased from 18,169, 128, in 1991 to 24,437,467 people in 2006(National Population Commission, 2006) representing 42% increase with an average


annual growth rate of 2.8%. The population constitutes about 17.4% of the totalpopulation of Nigeria and is unevenly distributed within the study area. The majorsocio-economic activity in the Middle Belt region is farming. Being an Ecologicaltransition zone between Sahel and southern forest region, the moderate and variableclimate support the cultivation of various cereals, root and tuber crops in commercialquantities with rainfed moisture. In Benue State and parts of Nassarawa as well asTaraba States, yam is cultivated in large quantity such that it is commercially transportedto other parts of the country, cereals such as maize, millet, guinea corn, rice, sesame(Benniseed), soya beans as well as other roots and tubers such as cassava and potatoesare commonly grown.

On the north central plateau, around Jos town, Irish potatoes are commerciallygrown in large quantity because of the cooler condition due to the elevation. TheMiddle belt region is underline by two major contrasting geological formations namelybasement complex rocks and sedimentary rocks which give rise to the highlands andthe valleys along the Niger-Benue trough respectively. The region is drained by riversNiger and Benue; the major drainage system in the country and perennial tributariesincluding rivers Gongola, Taraba, Donga and Katsina-ala (for river Benue) and riversGurave Kaduna, Kontagora, Awun, Moshi (for river Niger) respectively.

The Middle Belt Region is found within the tropical wet and dry climatedesignated as Aw by Koppen’s (1930) climatic classification (Tyubee, 2006). The Awclimate lies between the Af (Tropical wet climate) on its equator ward side and theBSh (Tropical Steppe) on its polar ward side. It is a zone of gradual change in climatecharacter from the wetter equatorial margin towards the drier polar ward regions.Two seasons are experienced in the region. The dry season which start from lateNovember, last till March, the wet season prevails from April to October. It ischaracterized by the tropical maritime air mass which brings rainfall and wet conditionto the region. The annual amount of rainfall of Aw region ranges from 1000mm to2100mm (40 to 60 inches), although years with extreme conditions exceed these values.The rainfall declines with increasing latitude.

MATERIALS AND METHOD

The data used for the study are daily rainfall data. Daily rainfall data are obtained from8 synoptic weather stations in the Middle Belt Region for 46 years period (1961 -2006). The data are acquired at the Nigerian Meteorological Agency OperationalHeadquarters, Oshodi, Lagos. The eight Synoptic weather stations are selected becauseof data availability covering the study period (Table 1 and figure 2). The number of raindays for each of the eight stations was extracted then summed and divided by thestudy period (46 years) to get the mean annual number of the rain days. The meanannual rain total was gotten by also summing the annual totals for each station anddividing by 46.


Table 1: Meteorological stations selected for the study.Station Code Latitude (N) Longitude (E) Elevation (m)Bida 65112 9o061 6o011 142Ibi 65145 8o 111 9o451 108Ilorin 65101 8o291 4o351 307Jos 65134 9o381 8o521 1286Makurdi 65271 7o451 8o321 92Minna 65123 9o371 6o321 259Yola 65167 9o141 12o281 186Source: Nigerian Meteorological Agency, Lagos (2011)

The correlation between mean annual rain days and mean annual rain totalwas analyzed using product moment correlation coefficient given by:

The result was tested using t test given by:

RESULTS AND DISCUSSION

Correlation of Mean Annual Rain days and Mean Annual Rain Totals in theMiddle Belt RegionAn analysis of the occurrence of rain days in the study region shows that Jos has thehighest mean number of rain days (105) within the region followed by IIorin with (90)mean rain days. Ibi and Yola have the least mean number of rain days in the region with(70) each. The highest number of rain days in Jos is due to its location on a summit ofa plateau and the associated orogragrphic effect while IIorin is located at the southwestwhere the rain bearing winds that bring rainfall into Nigeria advects thus the windsbeen more moisture laden give rise to more rain events and subsequent more numberof rain days. Ibi is located in the valley of River Benue and experience air descentinhibiting the occurrence of rainfall. A correlation of mean annual rain days and meanannual rain totals shows that at 0.05 significant level and 6 degrees of freedom, criticalvalue of t is 2.45 while the calculated value of t is 2.95 (table 2). The calculated valueof t 2.95 is greater than the critical value 2.45. The correlation is thus significant at 0.05levels; i.e. the effect between mean number of rain days and mean annual rainfall totalsis significant, meaning that annual totals are dependent on number of rain days. Thisindicates increasing light rains in the MBR since only heavy events result to few numberof rain days with high annual totals.

Effects of variation in daily Rainfall intensity categories on rainfall totalsA correlation of daily rainfall intensity categories on rainfall totals shows that for


extremely light categories, only northwestern and northeastern areas of the MBR haveinsignificant positive correlation. The other regions have negative correlation and noneof the areas show a significant relationship. Light intensity categories has only Makurdiregion with significant positive correlation. The correlation for the moderate intensitycategories show only Ibi with positive significant relationship in the moderately lightcategory while central areas have negative correlations for both moderately light andmoderately heavy categories. Heavy intensity category has north central areas withpositive significant correlations while northeastern areas show negative correlations.

Extremely heavy intensity category indicates that central areas and northeasternareas have significant positive correlations (table 3). The result implies that lighter rainscontribute only small to the overall rainfall amount whereas heavier rain events increasesrainfall amount respectively. However there are observed variations to the generalpattern. As shown on table 3, only the north eastern and north western areas receivesignificant contribution to the rainfall totals by extreme light events. Light events do notcontribute significantly to rainfall total in the study areas except in Makurdi regionwhere a significant contribution to the rainfall total is from light events. The moderateintensity categories contribute significantly to rain totals only in south eastern areas.

Rainfall total of central areas are least affected by moderate intensity categories.North central and western areas within the Middle Belt have their rainfall totals mostlyaffected by extremely heavy events. It therefore means that these areas may have fewrainy days but more rainfall totals because of the influence from heavy events.

Table 2: Mean annual rain days and mean annual rain totalStation Mean number of raindays Mean annual rainfall totalBida 81 1151Ibi 70 930Ilorin 90 1152Jos 105 1201Lokoja 79 1104Makurdi 81 993Minna 70 831Yola 81 909Source: Fieldwork, 2012

Table 3: Correlation of daily rainfall intensity categories and rainfall totalsStation Extremely light Light Moderately light Moderately heavy Heavy Extremely heavy

Bida -0.223 -0.382 0.226 0.269 0.085 0.365*Ibi -0.132 -0.214 0.379* -0.208 0.175 -0.276Ilorin -0.161 -0.120 0.228 0.075 0.290 0.293Jos -0.209 0.290 -0.271 0.046 0.350* 0.529*Lokoja -0.071 0.043 -0.002 0.060 -0.015 0.217Makurdi -0.243 0.403* 0.033 0.004 0.044 0.015Minna 0.179 0.082 0.151 -0.055 0.154 0.329*Yola 0.055 0.044 0.068 0.160 -0.050 0.224* Correlation significant at 95% significance level.Source: Fieldwork, 2012


Table 4: Correlation of Mean Annual Rain Days and Mean Annual Rainfall TotalMean No. of Mean No. of AnnualRain days (x) rainfall Total (Y) X2 Y2 XY

Bida 81 1151 6561 1,324,801 93,231Ibi 70 930 4900 864,900 65,100Ilorin 90 1152 8100 1,327,104 103,680Jos 105 1201 11025 1,442,401 126,105Lokoja 79 1104 6241 1,218,816 87,216Makurdi 81 993 6561 986,049 80,433Minna 70 831 4900 690,561 58,170Yola 81 909 6561 826,281 73,629Total 657 8271 54849 8,680,913 687,564

At 0.05 level and 6 degrees of freedom, critical value of t is 1.94. Since the calculated value oft 4.61 is greater than the critical value 1.94, the null hypothesis is rejected. The correlation issignificant at 0.05, i.e. the association between mean number of rain days and mean annualtotal is significant.

CONCLUSION

With increasing global temperatures, characteristics of rainfall are observed to bechanging. There are prospects for heavy events even where the overall rainfall totalsare decreasing (Trenberth and Stepaniak, 2013). This calls for analysis of regionalrainfall intensity pattern and how these intensity categories impinge on the rainfall totals.In the Middle Belt region (MBR) of Nigeria, rainfall totals are determine by the numbersof rain days, meaning lesser of the events are of the heavy intensity though variationsexist within specific areas in the region.

REFERENCES

Ayansina, A. (2009). Seasonal Rainfall Variability in Guinea Savannah, Nigeria: A GIS Approach.International Journal of Climate Change Strategies and Management, 1, 3.

Anyadike, R. N. C. (1987). A Multivariate Classification and Regionalization of West AfricanClimates. Journal of Climatology, 7, 157- 164.

Ayoade, J. O. (2004). Introduction to Climatology for the Tropics. Ibadan: Spectrum BooksLimited, Nigeria.

Bosch and Davis (2008). Rainfall Variability and Spatial Patterns for the Southeastern Region ofthe United States.

Intergovernmental Panel on Climate Change (IPCC) (2007). Climate Change 2007; SynthesisReport. Contribution of Working Groups I, II and III to the Fourth Assessment Report ofthe Intergovernmental Panel on Climate Change (Core Writing Team et al. (eds.)). IPCCGeneva, Switzerland.

Longman School Atlas (2009). Map of Gwer West Local Government Area, Benue State.Lough, J. M. (1980). West Africa rainfall variations and the tropical Atlantic Sea surface

temperature. Climate Monitor 9: 150 -157 in Tyubee (2006). Persistence and Periodicity inRainfall Characteristics in the Middle Belt of Nigeria. Journal of Geography andDevelopment, 1, 1.

National Population Commission (2006). Nigeria Population Census Figures. Lagos: NPCNigerian Meteorological Society (2011). Data on daily rainfall records. Lagos: Operational

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Trenberth, K. E. and Stepaniak, D. P. (2003). The Changing Character of Precipitation. AmericanMeteorological Society, 84, 1205-1217.

Tyubee, T. B. (2006). Persistence and Periodicity in Rainfall Characteristics in the Middle Belt ofNigeria. Journal of Geography and Development, 1, 1.

the effect of mean annual rain days on mean annual rain totals

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