Rainfall is a determinant factor of many natural occurrences. Vegetation distributions
and types over land masses are as a result of rainfall (Ronen
and Avinoam, 1999; Tielborger and Kadmon, 2000;
Shukla et al., 1990). Animals breeding periods
synchronize with rainfall periods (Radford and Du Plessis,
2003). Rainfall events have been directly linked to sickness and diseases
particularly those of waterborne and vector-borne types (Hunter,
2003). Crops planting, yields and harvests are influenced by rainfall and
should be practiced in accordance with their respective enabling seasons to
ensured improved productivity (Laux et al., 2010;
Mudita et al., 2008; Omokhafe
and Emuedo, 2006). The gaseous content of soil composition from time to
time is much affected by rainfall (Lee et al., 2002).
Investments in agricultural produces and products are expected to be done in
accordance with knowledge of rainfall and other weather conditions (Morduch,
1995). And no matter how small the amount and duration of rainfall may be,
it is economically significant to some species of plants under certain climate
even so that it is hypothesized that the small events on the ecosystem dynamics
are more effective than larger events (Sala and Lauenroth,
1982). Naturally, rainfall variability is of spatial and temporal forms
and within these variations if by time series analysis no significant trend
is obtained then the rainfall is steady otherwise it has changed. The steady
state of rainfall over a reasonable length of time to some degree would ensure
stability in the aforementioned systems. Contrarily it could lead to disruption,
uncertainty and unpredictability of the systems.
With regards to rainfall, studies have pointed to the fact that the climate
is changing (Goswami et al., 2006; Adger
et al., 2003; Obot et al., 2010).
Specifically, the research of Ragab and Prudhomme (2002)
discusses the variability and uncertainty of rainfall across the whole globe
amidst global warming and among others it states that while North Africa witnesses
rainfall decrease, the regime of rainfall in some parts of South Africa is increasing.
On the other hand, no coherent trend has been reported in some regions, in the
face of different significant trends of other regions in Sri Lanka (Jayawardene
et al., 2005). However, Odjugo (2010) argues
that not any change in the climate should be considered as climate change since
climate fluctuates and varies in monthly, seasonal, annual, decades, periodic,
quasi-periodic or non-periodic time scales. And in his overview of climate change
in Nigeria, he established that rainfall has decreased by 81 mm within 105 years
period. Thus, not to mistake climate fluctuation for climate change, Ayoade
(2003) recommended that a secular variation not up to 100-150 years should
not be regarded as climate change if the condition will quickly reverse later.
The factors responsible for climate change are variations in solar intensity
and green house gases alongside aerosols (Hansen and Lacis,
1999). Anthropogenic activities leading to increased green house gases have
caused some natural processes to become chaotic and unpredictable. Such natural
processes that have been affected by man induced increased green house gases
particularly include global surface temperature and hydrological cycle (Trenberth,
1998). Although, no direct link between GHG and precipitation has been found
yet Karl and Trenberth (2003) in a modeled climate system
found that for extremely increasing temperature coupled with water holding capacity
of the atmosphere, there is corresponding extreme increase in precipitation.
This type of relationship whether of direct proportionality or inverse proportionality
of air temperature increase occasioned by GHG with rainfall in modeled climate
has also been established by other researchers. At times it has been inferred
from the study of other atmospheric parameters like Sea Surface Temperature
(SST) or by speculations in related researches (Cox et
al., 2008; Haarsma et al., 2005; Fauchereau
et al., 2003; Menon et al., 2002;
Gong and Wang, 2000). Therefore, it can be argued that
waiting for so long (100-150 years) as suggested by Ayoade
(2003) in the face of continuous excessive GHG released into the atmosphere
(USEPA, 2006) could be detrimental and too late to react
thereafter if the predictions from models turn out true.
The sun has an 11 years cycle and changes it polarity at the end of the cycle
and based on the reversibility of magnetic poles, one would say that the sun
has a 22 years periodicity (Moussas et al., 2005).
The solar cycle has being known to affect other processes in nature even the
night and day, seasons and years are fallouts of the relationship between the
sun and earth. So studies of atmospheric parameters that cover a period of 22
years would have witnessed at least one solar cycle influence and as such the
period should be deemed okay for the short term. However, the 11 years cycle
is not strictly an 11 years term but varies between the ranges of 10-12 years
and as such other different solar cycles differing in years of the range of
~87, ~210 and ~1,470 years periodicities are known to exist (Braun
et al., 2005). The solar cycle as it varies causes changes to other
physical parameters like the solar wind (Scherer and Fahr,
2003; Lean et al., 2002). The cycle is also
believed to be responsible for climate change. The 60,000 years long millennial
scale climate changes found in Greenland ice cores and North Atlantic ocean
cores has been attributed to variations in the solar cycles (Van
Geel et al., 1999). Also still in Greenland, Ram
et al. (1997) found the dust in ice-core dated to about 100,000 years
BP to have a solar forcing cycle of 11 years. Increase in surface temperature
has been found to coincide with increase in solar activity within a 400 years
term (Hoyt and Schatten, 1993) and Lean
et al. (1995) also attest to solar forcing on the surface temperature
with particular regards to the Northern hemisphere. The heat energy of ocean
is found to change along with an 11 years cycle (Wigley
and Raper, 1990). The essence of this research is to find out the trend
of rainfall in Abeokuta within a 22 years (1981-2002) period and the corresponding
effect the sun has on it.
MATERIALS AND METHODS
The location under focus is Abeokuta (7°15′N, 3°35′E) the
capital city of Ogun state, Nigeria. The data used for this research were obtained
from Nigerian Meteorological Services, NIMET office here in Abeokuta where the
data are reportedly taken. The 22 years (1981-2002) rainfall data were biased
into total amount of rainfall and total number of days of rainfall. To void
the effect of serial correlation on the outcome of the test for trend, the correlation
co-efficient R was examined and in cases whereby the correlation co-efficient
was ≥ 0.30 then the series was prewhitened using the method:
Examination of the possibility of existence of significance trend is by the Mann-Kendall rank correlation described below.
Mann-Kendall rank correlation; for a data set of n size whereby n is not <10, a mean of zero and a standard deviation of 1 also assuming that the time series is independent then the Mann-Kendall statistic S is described as:
Here, xi and xj are sequential data for the ith and jth terms.
For situation where ties occur then VAR (S) is extended to the form:
||The number of tied groups
||The number of data values in the pth group
The null hypothesis Ho for a two sided test is rejected when
at α level of significance. If Z is positive then the trend is increasing and if Z is negative then the trend is decreasing.
The effect of seasonality on the outcome of trend analysis can be eliminated be performing the statistical analysis on either monthly data or on data that are divided into different seasons. The monthly data are also evaluated so that the outcome will not be in doubt of seasonal effect on the yearly data.
In an attempt to verify if year to year variability of the rainfall accumulated amount received in the location is directly influenced by solar intensity within the period under review, the yearly values averaged from daily values of reconstructed Total Solar Intensity (TSI) data downloaded from Max Planck Institute website were used to estimated the daily solar radiation for the horizontal plane in the absence of the atmosphere.
The global solar radiation on the horizontal plane Ho (in MJ m-2)
received at a particular location can be calculated (Iqbal,
1983; Duffie and Beckman, 1980) as follows:
Whereby TSI is the total solar irradiation at the mid distance between the
sun and the earth otherwise known as the solar constant and the eccentric factor
E0 is given as:
The day angle Γ (in radiance) in the expression for the eccentric factor
above is given as:
Furthermore other parameters found in the expression for Ho such as the declination
angle δ and the hour angle ws can be given as:
Within the foregoing, dn is the day of the year and its a maximum of 366 for leap years otherwise it is 365 while Φ is the latitude of the location. The * value 366 instead of 365 was used for leap years.
Characterizing the rainfall from January to December, the pattern over the 22 years under review is such that starting from January when already the rainfall is low it increases gradually till it peaks in June. By July it descends quickly and goes to August break and then a swift rise to a second peak in September. The August break is a period when rainfall lessens considerably amidst the tick of the raining season and usually it occurs around the month of August every year in this part of the world. After the second peak is reached, there is another quick descend that goes to low level. The dry season stays from October and remain practically so through December, the last month of the year. This pattern is about the same for the total amount of rainfall and for its number of days (Fig. 1 and 2).
From the descriptive statistics (Table 1), the mean annual
rainfall for the 22 years period is 1181.3 mm while the highest yearly rainfall
amount is 1705.7 mm. It rained for 2428 days out of about 8008 days, implying
that the ratio of rain days to non-rain days is about 3:7.
||Cummulative monthly variation of total amount of rainfall
for 22 years of 1981-2002 in Abeokuta, Nigeria
|| Result of descriptive statistics of the total amount of rainfall
(mm) and total number of rain days for Abeokuta from 1981-2002
|| Non seasonal and seasonal results of the correlation coefficient
and the Mann-Kendall Z test for rainfall in Abeokuta from 1981-2002
|*Prewhitening was applied
||The correlation co-efficient R and the Mann-Kendall Z-test
for both total amount of rainfall (mm) and total number of days of rain
for the monthly periods of 1981-2002 in Abeokuta
|*Prewhitening was applied
Within the period, the average of rainy days is about 110 days, though the
number of rain days can be as low as 75 days and as high as 136 days.
The Zα/2 (critical Z) values which can be read off from statistical
table or evaluated as recommended in Obot et al.
(2010) at α equal to 0.10, 0.05 and 0.01 levels of significance or
90, 95 and 99% confidence levels are 1.64, 1.96 and 2.58, respectively. And
from the results of Table 2, the absolute Mann-Kendall Z values
for both the cumulative rainfall and rain days are 0.90 and 1.47, respectively
for non seasonal data. None of the absolute Z values is greater than any of
the critical values at the confidence level considered here hence the null hypothesis
that no significant trend occurred is accepted. To void the outcomes of any
seasonal effect, the data were segmented into the two seasonal periods of dry
season and raining season. The months that had their total rainfall amount lower
than the mean rainfall fell into the dry season. These dry months include January,
February, March, October, November and December. Whereas, the raining season
months are April, May, June, July, August and September (Fig.
3). The two seasons were analyzed to see if there is any significant trend,
again none existed (Table 2).
||Graph showing the cumulative monthly variation of rain days
for 22 years of 1981-2002 in abeokutta, Nigeria
||Block chart of the accumulated monthly deviation of rainfall
from the mean rainfall where upper blocks are raining seasons months and
lower blocks are dry seasons months of the year, respectively
Lastly the test was applied on monthly basis whereby also no significant trend
occurred (Table 3). Thus, there is no significant trend whatsoever
throughout the 22 years considered.
However, June showed characteristically no positive or negative trend for the
total amount of rainfall and rainy days. Both total amount and number of days
of rainfall in January and February have negative insignificant trends while
positive insignificant trends for both parameters exist in July, August, September,
October and December. Conflicting positive and negative trends between total
amount of rainfall and rainy days are found in 4 months namely March, April,
May and November (Table 3).
||Schematic diagram of the sun at different elliptical positions
across the earth
Year in year out rainfall occurrence relies on the sun-earth positions which
brings about the different seasons. Assuming that the earth is held fixed and
the sun is moving around the earth in its orbit then the sun is facing the earths
equator in March and September, respectively (Fig. 4). Apparently
from Fig. 3, the 2 months bring about the crossing over from
dry season to raining season and from raining season to dry season, respectively.
After March the raining season is in place and after September, the dry season
is in place. Notably, March is the lowest of the dry season while September
is the highest of the raining season. The disparity between the peculiarities
of the 2 months is that whereas no other month is as low in dryness as March,
June competes equally in high rainfall as September.
Starting from March (Autumnal equinox/spring) on a clockwise motion the sun
goes into the Northern hemisphere, moving upward from the equator, it attains
the highest position in the orbit in June Solstice (summer) before returning
to the equatorial plane in September (Vernal equinox/fall) that phase is the
raining season. Thereafter, the sun moves downward into the Southern path which
is not as long as the initial path from September, to the peak at December Solstice
(winter) and then moves up back to the equatorial plane in March.
During this second phase, the sun is much closer to the earth because the peak
of this trajectory is lower than that of the Northern path and thus much sunshine
is witnessed than the other time so the dry season is in place. It should be
taken into cognizance that the explanations of seasonal occurrences given here
hold mainly for regions in the equator where Nigeria is also situated.
The solar cycle (Fig. 5) starts from high phase in the beginning
of the data, makes sort of a y shaped kind of descends to a low phase around
||Yearly plot of estimated horizontal global solar radiation
at Abeokuta in the absence of the atmosphere
||Plot of yearly total rainfall amount of Aboekuta for the period
It then rises to a peak before repeating the format that was seen at the beginning
of the data. Within 10 years time around 1995, another such low stage of the
type of around 1985 is attained. In contrast, the rainfall fluctuations hit
four times low within this same period (Fig. 6).
With a cumulative monthly total amount of rainfall for 22 years getting as
high as about 4,500 mm (Fig. 1), the location is one that
experiences high amount of rain. Classifying the climate zones of Nigeria into
three sections namely Sahel, Savanna and Guinea (Omotosho
and Abiodun, 2007), Abeokuta the capital city of Ogun state is in the Southern
part of Nigeria and it falls into the Guinea climate zone. The location is not
too far away from the Atlantic ocean perhaps its closeness to the Atlantic ocean
is the reason for the abundance of rain and definitely it can support plants
and crops types that by nature survive in climates of high rainfall.
It seems that in recent times within Nigeria, most places witnessing significant
trend in rainfall time series are areas in the Northern part that particular
fall into the Sahel climate while those in the South and other Northern places
outside the Sahel are having steady regime of rainfall. In other words insignificant
changes in the trends of rainfall are wide spread in the South while the type
of significant trend at the North is that of increasing trend (Ati
et al., 2009; Obot et al., 2010).
Abeokuta witnessed no significant trends in the evaluations carried out like
other places in the same climatic zone as evidenced in the above cited works.
A major factor that could be considered in trends evaluation is the type of
method adapted by researches and another is the period that the studies portrayed.
These two factors can bring about contradicting results sometimes even over
the same location and caution must be taken when comparing works from different
In Stevens and North (1996) research work investigating
solar cycle forcing on the earths surface temperature, one of the selected
detected boxes is the region where Nigeria is situated; precisely the 10th out
of 36 locations where the 11 years solar cycle influenced the historical temperature
of both ocean and land. However, with regard to rainfall occurrence, the solar
cycle or intensity has no direct effect on it as seen from the graphs of the
yearly amount of rainfall (Fig. 6) and that of the solar radiation
(Fig. 5). Both show that the solar intensity has little or
no influence on the rainfall occurrence. The yearly rainfall availability and
variability can probably be attributed to the West African monsoon which is
yet to be fully understood. The monsoon which is a composite of some complex
natural mechanisms such as the ocean land temperature and wind interactions
and exchange, incidentally also has solar radiation as part of it (Abiodun
et al., 2008; Omotosho et al., 2000;
Le Barbe et al., 2002). Probably the Atlantic
ocean forcing is predominating whereby relegating that of solar to the background
(Lu and Delworth, 2005; Shanahan
et al., 2009). Again, the complex nature of rainfall is probably
the reason why the change in natural constituents of gasses (GHG) and climatic
parameter (temperature) has not been directly found to influence its occurrence.
It is important to note that with respect to solar forcing on rainfall, this
study may be regarded as inconclusive because for an ideal investigation the
rainfall data should be lengthy say much >100 years since the sun cycle is
an 11 years term. For the 22 years data of rainfall used in this research, it
corresponds to only two solar cycles which would result to two data points when
biased with the solar 11 years frame. Evidences of solar forcing on rainfall
arising from slight variations in solar intensity resulting in either drought
or flood have been found using long term data of about 3-9 thousand years ago
in this Holocene era (Agnihotri et al., 2002;
Hodell et al., 2001; Fleitmann
et al., 2003). But with the paucity of data in this region in general
and in this study in particular, the observed 2 cycles of about 10 years existing
in Fig. 5 could not be associated with any change in the rainfall
of Fig. 6. In the absence of long data, it is suggested that
palaeo-sciences, satellite observations and atmospheric modeling be used to
reconstruct it and further studies be carried out.
Since, all the period considered witnessed no significant trend coupled with
the uniqueness of the month of June, a month of very high rainfall that showed
no coherent trend what so ever, Abeokuta rainfall regime is stable and activities
like farming and agricultural investments can effectively be carried out in
accordance with the existing pattern of rainfall that is here characterized.
The raining season is from April to September while the dry season is from October
to March. However, continuous monitoring is advised because there can be a U-turn
in trend as time passes by (Obot et al., 2010).
Globally expect with multi decadal data of long past that were reconstructed,
solar forcing on rainfall is not known to exist and despite the fact that corresponding
solar forcing on temperature as well as hydrological cycle are known to occur
with data of recent times yet it does not extend to rainfall as against expectations
so more studies are needed to clearly account for the anomaly. Be that as it
may in the location studied for two solar minimums that occurred there were
four rainfall minimums.