Modeled Implications of Global Warming Conditions on Precipitation Totals in Valley and Highland Areas of Nigeria

Johnson Orfega Mage; Rhoda Mojisola Olanrewaju; Ifeanyi Chris Onwuadiochi

doi:10.4236/ajcc.2023.123022

American Journal of Climate Change > Vol.12 No.3, September 2023

Modeled Implications of Global Warming Conditions on Precipitation Totals in Valley and Highland Areas of Nigeria

Johnson Orfega Mage¹, Rhoda Mojisola Olanrewaju², Ifeanyi Chris Onwuadiochi^3*
¹Department of Geography, Benue State University, Makurdi, Nigeria.
²Department of Geography and Environmental Management, University of Ilorin, Ilorin, Nigeria.
³Department of Geography and Meteorology, Nnamdi Azikiwe University, Awka, Nigeria.
DOI: 10.4236/ajcc.2023.123022 PDF HTML XML 94 Downloads 455 Views

Abstract

Global temperature has been increasing causing differences in precipitation response in different physiographic regions as feedback mechanism. The aim of this work is to model the implications of the global warming conditions on precipitation occurrences in the valley and highland areas of Nigeria. Harmonic analysis on the average monthly rainfall observations was performed for 56 years (1961-2016) using the Turbo Pascal for windows programming language in order to implement the computation. This was carried out by fitting a periodic function of sinusoidal character to enhance the determination of the contribution of each harmonic, the amplitude of each harmonic and the time at which each harmonic is maximum. The result of harmonic plots of the grand average monthly rainfall for the valley area of Makurdi and highland area of Jos shows that there exists a similarity in the trend of variations of harmonic series plots of the data as either plots exhibit single rainfall maxima or peak, meaning that rainfall patterns are mono-modal in nature. Modeled result of average monthly rainfall for the valley area of Makurdi shows an increase in rainfall occurrences from the month of January to August but a decrease from September to December, meaning an expectation of more rains immediately after onsets and lesser rains before cessations. The modeled result for the highland area of Jos however shows a decrease in the occurrence of rainfall in the months of January and February but an increase from the month of March to December. The implication is that there will be water deficiency for late crops and aquifer recharge in the valley areas while highland areas will experience delayed onset of agricultural calendar. The study recommends timely release and adherence to weather/climate forecasts.

Keywords

Physiographic, Regions, Harmonics, Rainfall, Patterns

Share and Cite:

Mage, J. , Olanrewaju, R. and Onwuadiochi, I. (2023) Modeled Implications of Global Warming Conditions on Precipitation Totals in Valley and Highland Areas of Nigeria. American Journal of Climate Change, 12, 489-503. doi: 10.4236/ajcc.2023.123022.

1. Introduction

The study on rainfall response to global warming in low and highland areas of Nigeria is significant because these marginal areas are important agricultural zones of the country; hence an understanding of the variation in rainfall behaviour is vital for agricultural development of the physiographic regions. Agricultural practices in Nigeria are predominantly rain-fed and rainfall characteristics determine the agricultural calendar ( Olayide et al., 2016 ). Changing rainfall totals as a response to global warming will affect agricultural activities and production. The valley areas are flood plains which are used for the cultivation of rice, sugar cane and vegetables while on the highlands crops like Irish potatoes and many varieties of fruits that thrive in cooler environments are cultivated. This is because the low lying valleys used for flood plain cultivation can be inundated reducing the usage of these marginal lands for agriculture. Similarly, erosion on slopes of the highland areas may be aggravated thus destroying farmlands or reducing productivity through fertility loss by erosion.

Many settlements are situated in the low lying valleys of rivers Niger and Benue. Response by increasing rainfall total will worsen the occurrences of flooding which is already prone in these settlements ( Ikusemoran et al., 2013 ). Also, other environmental disasters like erosion and landslides may be intensified especially in the highlands ( Aliba et al., 2015 ). Decreasing response of rains will lead to reduction in fishing activities and hydro-electric power generation which will adversely affect standard of living in the study area. Changing precipitation will worsen issues of migration and conflict in the region. Clashes between cattle herders and farmers have become pronounced due to competition for climate based resources and the situation will get worse if conditions become drier ( Chukwuma, 2020 ). Modeled projection of the implications of the global warming conditions on precipitation totals in the valley and highland areas will avail information on the anticipated future rainfall occurrence in the study area. This will help to plan ahead the expected vulnerability and climate risk, thus embarking on timely adaptation measures.

Topography can affect precipitation in at least three important ways. Firstly, it can intensify the solar heating over land by providing an elevated heat source. This magnifies the regional-scale land-sea temperature contrast and facilitates the onset and maintenance of monsoon regimes that produce convective rainfall and latent heating. Variations of this heating can affect weather and climate in other tropical areas, as well as in the extra tropics via atmospheric teleconnections. Secondly, topography can contribute to orographic rainfall and additional latent heating. That is, as moist air is forced up a slope, the air cools, moisture condenses and rainfall and latent heating occur with consequences similar to those associated with convective heating. Thirdly, topographic barriers in the tropics obstruct the large-scale air flow and force some air to go around rather than over topography. This mechanical effect disturbs the flow downstream and sets up large-scale circulation patterns that extend into the extra tropics via planetary long waves ( Meehl, 1992 ).

Topography also has specially marked effects on weather elements such as air humidity, temperature and rainfall. These effects result in concomitant changes in soil and vegetation distribution over hilly or mountainous areas ( Korner, 2004 : Viviroli & Weingartner, 2004 ). The mountain ecosystems help in stabilizing atmospheric circulation by creating barriers to free movement of winds.

The temperature trend in Nigeria since 1901 (Figure 1) shows increasing pattern, the mean air temperature in Nigeria between 1901 and 2005 was 26.6˚C while the temperature increase for the 105 years was 1.1˚C ( Odjugo, 2010 ). This is obviously higher than the global mean temperature increase of 0.74˚C recorded since 1860 when actual scientific temperature measurement started ( Spore, 2008 ; IPCC, 2007 ). Similarly, according to the Federal Ministry of Environment (2014) , temperature has been on the increase in Nigeria in the last five decades and has been very significant since 1980s. An increase in global precipitation is anticipated but this increase will be uneven across different regions, these calls for regional analysis of precipitation characteristics. Rainfall has however shown a general decreasing trend in Nigeria since 1901 (Figure 2) but with regional differences. This study therefore aims at modeling the response of precipitation to global warming conditions on different physiographic areas of lowland and highland in the Middle Belt Region of Nigeria. The specific objectives are to determine grand average of monthly rainfall and harmonics curves for the

Figure 1. Air temperature distribution in Nigeria between 1901 and 2005 ( Odjugo, 2010 ).

selected stations in lowland and the highland from 1961 to 2016 and model the implications of the global warming conditions on rainfall occurrences in the lowland and highland areas.

This study is limited to the valley area of Makurdi and the highland of the Jos Plateau which are located in the Middle Belt Region of the country within latitudes 6˚24'N to 11˚42'N and longitude 2˚42'E to 13˚6'E covering a total area of 320,000 km², about 35% of the total land area of Nigeria (Figure 3). The choice

Figure 2. Rainfall distribution in Nigeria between 1901 and 2005 ( Odjugo, 2010 ).

Figure 3. Nigeria showing mean annual rainfall spatial patterns ( Ishaku & Majid, 2010 ).

of Makurdi and Jos is because the two stations are the ones with the required recorded data with highest difference in elevation; Makurdi (92 m) and Jos (1286 m) and both stations experience rainfall abnormality in the country by recording rainfall amount that does not coincide with their latitudinal values. The period of study (1961-2016) 56 years is chosen to cover the recent five decades with reported cases of intense global warming and extreme rainfall events worldwide. The base year of 1961 is decided because of data availability in both stations of Makurdi and Jos.

2. Research Methodology

To model the implications of the global warming conditions on rainfall totals in the valley and highland areas, the Harmonic analysis technique was used. Harmonic analysis of a time series uses a Fourier series to analyze periodic fluctuations. It is a particularly useful tool in studying annual precipitation patterns as it reveals the spatial variation of various precipitation characteristics ( Isikwue et al., 2013 ). Harmonic Analysis, which is commonly applied to study periodic variations, decomposes a time series into its constituent parts if the time series represents a periodic phenomenon. It transforms a complex time series to a sum of many sinusoidal functions or harmonics ( Park, 2008 ). The Harmonic analysis is based on a mathematical principle that a curve, viewed as a function, may be represented by a series of trigonometric functions. This is as given by Isikwue et al. (2013) :

$X_{t} = \bar{X} + \sum_{t = 1}^{N / 2} [A_{i} \sin (\frac{360}{i^{2}}) i t + B_{i} \cos (\frac{360}{i^{2}}) i t]$ (1)

where;

$A_{i} = \frac{2}{N} \sum_{t = 1}^{N / 2} [\bar{X} \sin (\frac{360}{p} i t)]$ ; $B_{i} = \frac{2}{N} \sum_{t = 1}^{N / 2} [\bar{X} \cos (\frac{360}{p} i t)]$ (2)

$X_{t}$ is the observed value at time, t, $\bar{X}$ is the arithmetic mean, number of observations, i is the number of harmonics and P is the period of observation. In other words, the time series equals the mean plus the sum of all N/2 harmonics. The Equation (1) above can be rewritten as;

$X_{t} = \bar{X} + \sum_{t = 1}^{N / 2} C_{i} \cos [(\frac{360}{p}) i (t - t_{i})]$ (3)

The type of variation dominating the curve is revealed by a comparison of the sizes of the amplitudes C_i, where; $C_{i} = \sqrt{A_{i}^{2} + B_{i}^{2}}$ is the amplitude of the i^th harmonic and $t_{i} = P / 360$ , arc sin (A_i/C_i) is the time at which the i harmonic has a maximum. It can also be expressed in percentage. A harmonic with overwhelming contribution would definitely account for most of the periodic variation in the data, while the contributions of the other harmonics would be considered negligible. Large first harmonic amplitude suggests strong annual variation, while comparatively large second harmonic amplitude points to strong semiannual variation.

Autocorrelation plots of the data were made in order to determine whether significant relationship in the data. Paired sample T-test will be used to determine whether there is a significant relationship between the estimated rainfall values of the years 1961 and 2016 and their corresponding observed values. This serves as a test for the efficiency of the harmonic analysis model in estimating the rainfall amount for 20 and 50 years ahead in Makurdi and Jos representing two different altitudes.

Harmonic analysis on the average monthly rainfall observations was performed for the 56 years under study using the Turbo Pascal for windows programming language in order to implement the computation. This was carried out by fitting a periodic function of sinusoidal character to enhance the determination of the contribution of each harmonic (expressed as a percentage of total variation in the rainfall measurements it accounts for), the amplitude of each harmonic and the time at which each harmonic is maximum. The rainfall data was partitioned into monthly totals and each year was considered on the basis of the twelve months that make up the year. The 12 months coding is shown in Table 1.

3. Results and Discussion

The harmonic plots of both the valley and highland stations of Makurdi and Jos respectively show that the observed multiple peaks of the total rainfall in the time series plot are now reduced to bimodal patterns, by the amplitudes of the oscillations of the troughs and valleys of the harmonics. Hence, the harmonic analysis could have filtered or smoothened out some noise or spikes in the data. The harmonics plot of average monthly rainfall (mm) for the interval of 12 months for Makurdi and Jos is given in Figure 4 and Figure 5 respectively.

The result of harmonic plots of the grand or net average monthly rainfall (mm) for the interval of 12 months for the valley area of Makurdi and highland area of Jos show that there exists a similarity in the trend of variations of harmonic series plots of the data. Both plots exhibit single rainfall maxima or peak as shown in Figure 6 and Figure 7 respectively. That is, rainfall patterns are mono-modal in nature. This indicates that in a particular year, the rainfall peaks are observed in one single month of August for the valley of Makurdi and either July or August for the highland area of Jos. This implies that rainfall peak is attained earlier in the highland areas of Jos than the valley areas of Makurdi. This result partially agrees with the findings of Ogungbenro & Morakinyo (2014) in their work on rainfall distribution and change detection across climatic zones in Nigeria which revealed that rainfall peaks in July for areas within the Guinea Savanna Zone; but the result refutes their conclusion on the occurrence of August break and a double rainfall maximum within the belt. This difference could be attributed to the unique physiographic attributes of the valley and highland and their influence on rainfall behaviour as opposed to the other regions within the Savanna vegetation belt.

Results extract from the run of harmonic analysis on average monthly rainfall (mm) for the interval of 12 months for Makurdi and Jos are summarized in Table 2 and Table 3 respectively. Table 2 shows that the first harmonic dominates

Table 1. Code for the month axis along with the year

Source: Authors’ fieldwork, 2018.

Figure 4. Harmonic plots of average monthly rainfall for Makurdi.

Source: Authors’ fieldwork, 2018.

Figure 5. Harmonic plots for average monthly rainfall for Jos.

Source: Authors’ fieldwork, 2018.

Figure 6. Grand average of monthly rainfall and harmonics curves for Makurdi.

the periodic components in the monthly average rainfall of Makurdi as it has the highest percentage contribution of 92.27%, indicating that the monthly rainfall in the station actually fluctuates. The large amplitude of the first harmonic indicates strong annual variation of rainfall in the station as in the works of Wong et al. (2009) and Kirkyla & Hammed (1989) . Results from Table 3 shows that the

Source: Authors’ fieldwork, 2018.

Figure 7. Grand average of monthly rainfall and harmonics curves for Jos.

first harmonics also dominates the periodic components in the monthly average rainfall of Jos as it has the highest percentage contribution of 91.67, indicating fluctuation or periodicity of the monthly rainfall in the station. The periodic fluctuation is dominated by halve a cycle as is evident in the grand average monthly plots in Figure 6.

Using the grand average monthly rainfall obtained as 105.08 and 105.41 mm for Makurdi and Jos respectively as model estimates from the harmonic analysis, the period of 12 months, and the sine and cosine coefficients in Table 2 and Table 3, the periodic function X_t for the monthly average rainfall of Makurdi and Jos were obtained using extracts from equations

$X_{t} = 105.08 + \sum_{i - 1}^{α} [A_{t} \sin (30 i t) + B_{t} \cos (30 i t)]$ and

$X_{t} = 105.41 + \sum_{i - 1}^{α} [A_{t} \sin (30 i t) + B_{t} \cos (30 i t)]$ . Where A_i and B_i are coefficients

of sine and cosine respectively and i’s are integers ranging from 1 to 3 as given in Table 2 and Table 3. The equations were then implemented in the harmonic analysis program to make a short consecutive five year and long five years interval forecasts of monthly average rainfall measurements for Makurdi and Jos. The result of short consecutive five year and long five years interval forecasts of monthly average rainfall is presented in Table 4 and Table 5 for Makurdi and Table 6 and Table 7 for Jos respectively.

Modeled result of the short consecutive five years and long five years interval forecast of average monthly rainfall for the low land area of Makurdi is presented in Table 4 and Table 5 respectively. The result shows an increase in rainfall occurrences from the month of January to August. The forecast however, shows a decrease in rainfall from the month of September to December. The implication of the result is that there will be more rainfall earlier in the season in the lowland areas and lesser of the rainfall towards the end of the season. In other words, more rains should be expected immediately after onsets and lesser rains should be anticipated before cessations. The effect of this rainfall pattern on agriculture is that the second phase of crops that mature towards the end of

Table 2. Result extract from the run of harmonic analysis program on average monthly rainfall for Makurdi, Nigeria.