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2016 SEASONAL RAINFALL PREDICTION (SRP)
Table of Contents
Foreword
Executive Summary
1.0 Evaluation of the 2015 Predictions
1.1 Temperatures
1.2 Rainfall
2.0 2016 Seasonal Rainfall Prediction
2.1 Day & Night Temperatures and Deviations from Normal for January to April
2.2 Predicted Rainfall Components:
2.2.1 Onset Dates of Growing Season and Deviations from Normal
2.2.2 Cessation Dates of Growing Season and Deviations from Normal
2.2.3 Length of Growing Season and Deviations from Normal
2.2.4 Annual Rainfall Amount and Deviations from Normal
2.2.5 The Little Dry Season and Dry Spell
2.2.6 Mosquito Bites & Malaria Severity Forecast
3.0 Socio-economic Implications
3.1 Agriculture & Food Security
3.2 Water Resources Management
3.3 Power Generation
3.4 Transportation (Air, Land and Sea)
3.5 Dam & River Flow Monitoring
3.6 Marine & Coastal Services
3.7 Health
3.8 Disaster Management
3.9 Telecommunication
3.10 Building & Construction
4.0 Rainfall & Temperature Prediction Tables
5.0 Glossary
6.0 NiMet Contacts Nationwide
Foreword
The influence of humans on the climate system has continued to be apparent
and in recent years climate changes and variability have continued to have
widespread impacts on humans and natural systems. Climate change will continue to
increase existing risks and create new risks for natural systems and humans if major steps
are not taken to stem the anthropogenic activities that set off the changes. The
associated risks arising from climate change are usually unevenly distributed and are
generally greater for disadvantaged people and communities at all levels of
development. Also climate change has continued to be a threat to sustainable
development goals and It is against this backdrop that every effort towards mitigating
the effects through early warning system should be the concern of every Government.
Climate outlooks are one of the veritable tools for planning and decision making in
climate sensitive sectors to reduce the associated risks.
.
Apart from oil and industries, agriculture remains the main stay of the Nigerian
economy (31% of the GDP). Incidentally it is also the main preoccupation of more than
70 percent of the population. The Agricultural practice is mainly rain fed and accurate
and timely prediction of rainfall and other related meteorological parameters such as
temperatures enable stakeholders plan their activities well and make informed
decisions that increase productivity in all the sectors of the economy.
The need to have quantitative means of predicting the expected rainfall is
essential and inevitable for the purposes of planning and policy formulation, provision of
information needed for longer-term decisions and early warnings of potential hazards.
This decision making process for increased productivity applies to every sector since
every facet of the economy requires weather and climate data and information as
critical input for informed decision making.
In recent times, public awareness of extreme weather and climate events have
been on the increase due to the associated disasters coupled with increased access to
media information on such events. NiMet has on yearly basis produced seasonal rainfall
predictions to enhance decision making process especially in rainfall sensitive sectors. It
has also been established that agricultural yields increase by at least 30 to 35 per cent
if agro-meteorological information is applied to farming systems.
The changes in sea surface temperature at the Pacific Ocean have been
observed to have a tele-connection effect to weather and climate patterns around
the world. It significantly affects the rainfall patterns in West Africa. Forecasting the
seasonal rainfall is a very complex process which depends on proper knowledge of the
atmosphere and ocean interactions. The El Niño–Southern Oscillation (ENSO) is a major
input to the Seasonal Rainfall Prediction (SRP) process. ENSO oscillation is the largest
contributor to inter-annual climate variability around the globe.
NiMet’s 2016 Seasonal Rainfall Prediction contains the evaluation 2015 forecast
and the prediction of the onset of rain, cessation of rain, length of growing season,
seasonal rainfall amount, temperature forecast, malaria Forecast, dry spell forecast,
domestic, industrial fire Incidence, little dry season and socio-economic implications.
This publication has become a tool that stakeholders look forward to its release every
year because of the value it adds to the productivity of the various sectors. Every effort
must be made to ensure that the information contained therein is disseminated to the
grassroots and in the language they will understand.
The SRP is recommended for all practitioners in the rainfall sensitive sectors for
informed decision making and effective and efficient planning for disaster risk
reduction. I therefore have the pleasure of presenting the 2016 SRP to all stakeholders in
all sectors of the economy especially those that are sensitive to the rainfall and the
general public.
Rt. Hon. Rotimi Amaechi
Hon. Minister of Transportation
January 2016
Executive Summary
The Nigerian Meteorological Agency (NiMet) has produced the 2016 edition of the
Seasonal Rainfall Prediction (SRP) in fulfillment its mandates of effectively monitoring the
weather and climate of Nigeria, provision of relevant meteorological information,
advisories and early warning services to the various weather-sensitive sectors of the
Nigerian economy. This prediction constitutes a decision support tool for Nigerians, as it
provides critical information to enhance informed decisions, especially for planners,
policy makers, and operators of the various rainfall-sensitive sectors of the economy.
Such sectors include agriculture, water resources management, environment
monitoring, health, disaster management and a host of other weather-sensitive sectors.
The input data for the production of the SRP include temperature, rainfall, ENSO
phase, phenological data, soil information and farming practices (among others), while
the outputs comprise the following critical information:
Day and night temperature forecast. These define expected comfort level
during the first four months of the year
Onset and cessation dates of the growing season
Length of the season
Annual amount of rainfall
The little dry season and the dry-spell in May – July
Malaria incidence forecast
Socio-economic implications
On the completion of the SRP early in the year, it is first presented to major
stakeholders for their inputs, specifically to the socio-economic implications section
before its presentation to the general public. The stakeholders cut across operators in
the agricultural sector, water resources, dam and river managers, health, energy,
disaster managers, researchers and the academia. It is thereafter released to the
public in order to provide sufficient lead-time for its incorporation into decision-making
processes of the various users such as policy makers, planners, farmers, water resources
experts and hydropower generators.
The prediction model, as in other years, is based the strong tele- connection
between the El- Nino Southern Oscillation (ENSO), Sea Surface Temperature (SST)
anomalies and the rain-bearing weather systems in Nigeria. The 2016 SRP is based on
the predicted persistence of the current strong El-Nino phase into the second quarter of
the year. The ENSO projections for 2016 point to a strong El-Nino threshold in the first
quarter of 2016 weakening to about 60 percent through April to June, and gradually
moving to a neutral phase after August. Based on this scenario, the 2016 rainfall regime
in Nigeria is likely to be predominantly under the influence of an El-Nino condition for
most parts of the year. NiMet will issue an update on this if a major change is observed.
The 2016 SRP includes the evaluation of the performance of the 2015 prediction to
ascertain the performance by comparing the predicted with observed values in
different parts of the country, rated in terms of skills (%) as good forecast or forecast out
where the forecast did not perform well. The result of the evaluation is used to modify
the model for the subsequent years. In 2015, temperature predictions performance for
the day and night ranged from 82-100 percent (table 1).
Table 1: Temperature forecast performance table.
Met Parameter Forecast Performance, %
January Day Temperature 100
January Night Temperature 96
February Day Temperature 95
February Night Temperature 82
March Day Temperature 95
March Night Temperature 95
April Day Temperature 92
April Night Temperature 84
The onset and cessation dates of rainfall also showed good performance of 93%
and 87% respectively. The length of the season achieved 87% skill while the annual
amount reached 84% performance. The forecasts were mostly out in the Sokoto area
for the rainfall components, and this is being corrected in the 2016 predictions.
The highlights of the 2016 predictions include:
Moderate – severe harmattan season during January and February
Warmer-than-normal conditions during February and April across the country
and a warmer South in March.
Late onset of the growing season in the Delta, the far northwest and northeast
and early onset over the central areas and inland of the South.
Early cessation of the rains in parts of the northwest and prolonged rainy season
over the inland of the southwest, Delta State and Akwa Ibom. Shorter length of
season is generally predicted for 2016
Rainfall is predicted to be above normal in parts of the northwest, Niger State,
inland of the southwest and the Delta region. Below-normal rainfall is projected
over Yobe, Gombe, Taraba, Kogi, and Benue States and down to the South of
the country.
Prospects of serious short-period heavy rainfall events during the peak of the
rainy season (July-September) in some parts of the South and central States,
despite the probabilistic rainfall projections, given the heavy rainfall
characteristics of the areas.
A moderate Little Dry Season in July and August is predicted, while dry-spells
(consecutive days of about 10days or more without rainfall) are predicted to
occur in the central States in May and northern States in June/July.
For the malaria forecast, while the mosquito bites index is high in most parts of
the country, the malaria severity index is predicted to be relatively moderate
during Mau – August (in the central States), becoming low in the other months.
Socio-economic Implications
The socio-economic implications of the 2016 SRP for the various key sectors, along with
some relevant advisories are summarized below:
Agriculture – The predicted late onset of the rains in and around Sokoto,
Zamfara, Kaduna, Borno and Adamawa will create water stress during the
beginning of the cropping season. The use of irrigation is advised. Warmer-than-
normal temperatures projected in February and April for several parts of the
country will negatively affect livestock, fish farming and water availability for
animals. Vaccination is advised to help the animals withstand the associated
health challenges.
Fig 1: Agriculture in Nigeria is still largely rain-fed
Transport – the predicted moderate harmattan is expected to affect air travel
with lots of delays and cancellations especially during January and February. The
inland water transport is likely to be challenged due to shallow water in the rivers
caused by below-normal rainfall predicted for Yobe, Gombe, Taraba, Kogi, and
Benue States. Daily weather forecasts by NiMet as well as short range weather
outlooks will help operators manage the situation.
Fig 2: Most transportation means are affected by weather
Dam and other river flow monitoring, operators are advised that the predicted
above-normal rainfall in some parts will enhance their activities. However,
caution should be exercised to reduce the negative impact of sudden release of
excess accumulated waters from the dams.
Fig 3: Proper information about rainfall enables better management of dams
Health sector, the predicted warmer conditions may translate to hotter days and
nights particularly in April when maximum day temperatures reach 40 – 44oC in
the North and central States. The minimum temperature may reach 37oC in Yola
and Kebbi States. The frequency of heat-related ailments may also attain very
high proportions. Aggressive enlightenment and vaccination programmes should
therefore be embarked upon on the release of this forecast.
Fig 4: Tropical diseases are better managed with good knowledge of the weather
conditions responsible for their occurrences.
Disaster risk preparedness: All the challenges listed above constitute issues for
disaster risk preparedness. The warmer-than-normal conditions predicted bring
drier-than-normal conditions and this creates required condition for the
incidence of bush, domestic and industrial fires across the country. Citizens are
advised to be careful handling highly inflammable materials and always switch
off their electrical appliances when there are power fluctuations and when they
are absent from home.
Fig 5: The frequency and intensity of rainfall and flood incidents are on the rise in recent
years.
Water Resources
There will be less prospects of water availability for domestic, industrial, agriculture
and power use in Yobe, Gombe, and Kebbi States, reducing in intensity southwards.
Generally this will affect stream-flow and groundwater recharge. Adequate support
through irrigation to improve agriculture in the states with below normal rainfall
prospects is advocated.
Hydropower generation will be positively impacted by the predicted above-
normal rainfall in affected areas such as the northwest, Niger State and inland of the
southwest. However, for dam and irrigation operations, there is need for continuous
monitoring of the weather forecasts as the season evolves, in order to reduce the
impact of flooding arising from uncontrolled release of excess rain-water in the dams.
Agencies charged with these tasks should watch out for likelihood of flooding in
regions that have prospects of above-normal rainfall. More importantly, planners should
note that irrespective of the expected rainfall forecasts, there is need to monitor trans-
boundary streams and river flows for effective dam operations, as well as flood control
and management.
During the peak rainy season, pockets of heavy 1-day rainfall events are
predicted to occur in and around Bauchi, Kano, Jigawa and several locations in the
South. River swells may inundate communities around the major rivers during the third
quarter of the year.
Fig 6: So much water in some areas and so little in the others.
1.0 Evaluation of the 2015 SRP
Results of the evaluation of the 2015 SRP are presented in this section, with the
portions in red indicating areas where the observed patterns differed significantly from
the predicted ones. NiMet places high priority in ensuring accuracy and reliability of its
predictions and as such, evaluation of the performance of the previous year’s forecasts
is always conducted prior to the production of present forecast.
1.1 Temperature
1.1.1 January Day and Night Temperatures
Figs 7a & 7b: Evaluation of January Day and Night Temperatures
1.1.2 February Day and Night Temperatures
Figs 8a & 8b: Evaluation of the February Day & Night Temperatures
1.1.3 March Day and Night Temperatures
Figs 9a & 9b: Evaluation of March Day and Night Temperatures
1.1.4 April Day and Night Temperatures
Figs 10a &10b: Evaluation of the April Day & Night Temperatures
The forecast performance for temperature is summarized on the table below:
Table 2: Temperature forecast performance in 2015 ranged 84 – 100 percent
Table 2: Temperature forecast performance.
Met Parameter Forecast Performance, %
January Day Temperature 100
January Night Temperature 96
February Day Temperature 95
February Night Temperature 82
March Day Temperature 95
March Night Temperature 95
April Day Temperature 92
April Night Temperature 84
1.2 Rainfall Prediction
1.2.1 Onset and Cessation Dates of the Growing Season
Figs 11a & 11b: Evaluation of the 2015 Onset and cessation dates of the growing season
1.2.2 Length of growing season and Annual Rainfall Amount
Figs 12a & 12b: Evaluation of the length of season and annual amount of rainfall
Table 3: Table showing cases where rainfall forecast was out and the reasons.
S/N SITE ACTUAL ANNUAL
RAINFALL
AMOUNT(MM)
PREDICTED
ANNUAL RAINFALL
AMOUNT (MM)
REMARKS
1. Asaba 2548 1682
Forecast under-predicted the
expected rainfall amount
2. Awka 2499 1773
3. Bauchi 2821 996
4. Benin 3544 2071
5. Ilorin 1701 1141
6. Warri 3180 2442
7. Iseyin 729 1161 Forecast over-predicted the
expected rainfall amount 8. Shaki 783 1276
9. Yola 618 925
The forecast performance for the rainfall components is summarized on the table
below:
Table 4: Table showing rainfall forecast performance
Met Parameter Forecast Performance, %
Onset Date of growing Season 93
Cessation Dates of Season 87
Length of Season 87
Annual Amount of Rainfall 84
2.0 2016 Seasonal Rainfall Predictions
The Nigerian Meteorological Agency (NiMet) has produced the 2016 Seasonal
Rainfall Prediction (SRP) in fulfillment of its mandate to provide critical weather and
climate information and advisories to enable informed decisions in the various sectors of
the economy. The information contained in the SRP find extensive applications in
agriculture and food security, water resources management, environment and disaster-
risk reduction, health, and hydropower generation and distribution (among others).
The 2016 edition of the SRP comprises:
* Onset and cessation dates of the growing season;
* Length of the growing season
* Seasonal amount of rainfall
* Day and night temperatures for comfort level assessments
* Little Dry Season and Dry spells
* Socio-economic implications and advisories
The predictions also show expected deviations in the predicted meteorological
parameters from to long-term averages. For example, a projected “warmer-than-
normal” condition in day temperature also provides departure values of the projected
changes from normal temperature conditions for the particular month. Similar details
are provided for the predicted rainfall components.
The input data for the production of the Seasonal Rainfall Prediction includes:
Daily maximum and minimum temperature
Daily rainfall
Daily solar radiation
El-Niño and Southern Oscillation (ENSO) calculations from the Seas Surface
Temperature (SST) observations and projections;
Phenological and soil information.
The temperature, rainfall and radiation data record used for the predictions spans
over 30 years for each of the 45 principal weather stations spread across the country
and underwent rigorous quality control.
In 2016, ENSO trends and projections indicate the dominance of the warm phase
and its lingering effect well into the season (up to October 2016) despite an expected
change to the neutral phase mid-season. The tele-connection between the projected
warm phase, the SST anomalies and rain-bearing weather systems over the country is
expected to drive the 2016 weather conditions across Nigeria. The 2016 SRP is therefore
based on the warm ENSO phase (i.e. El-Niño).
Fig 13: latest ENSO map showing the phase projections in 2016.
CPC/IRI Early-Month Consensus ENSO Forecast Probabilities
Table 5: Trend of ENSO in 2016
Season La Niña (%) Neutral (%) El Niño (%)
DJF 2016 ~0 ~0 100
JFM 2016 ~0 1 99
FMA 2016 ~0 4 96
MAM 2016 1 12 87
AMJ 2016 4 34 62
MJJ 2016 13 48 39
JJA 2016 22 52 26
JAS 2016 33 49 18
ASO 2016 40 46 14
2.1 Day & Night Temperatures and Deviations from Normal
Once the rains arrive and begin to set get established as from May, the
temperatures moderate with minimal changes, this is when the temperatures are most
critical. The result of the temperature predictions is presented in map format. This shows
areas in the country where departures from 30 year-temperature normal are expected
during the day and night, resulting in either colder, warmer or normal conditions in terms
of health comfort. Temperature forecast is provided for January-April period only
because.
2.1.1 January Day and Night Temperatures Prediction Deviations
Figs 14a & 14b: Predicted Day and Night Temperatures for January 2016
In January, most parts of the country are predicted to experience normal
temperature. However, Warmer-than-normal conditions are predicted for the
northwest, while Adamawa and parts of the central areas (blue colour) are predicted
to be slightly colder-than-normal. The night is a mix-bag: warmer conditions over the
northwest, parts of Gombe, Bauchi, Taraba, northern Cross River and a host other
places in red background (with the temperature change expected to reach +0.6oC)
and colder in the southwest, FCT, Imo and Akwa Ibom (with change expected to reach
-1.0 oC). The rest of the country is predicted to be normal. Extreme values of predicted
minimum and maximum temperatures are expected over Jos (12.0oC) and Lafia
(35.1oC) respectively.
2.1.2 February Day and Night Temperature Prediction Deviations
Figs 15a & 15b: Predicted Day and Night Temperatures for February 2016
The day and night in February are predicted to be warmer-than-normal, with
temperature change reaching 1.0oC from long-term average for the month. The
southwest is expected to be slightly cold over the Lagos coast during the day, and
normal at day and night in the inland areas. Lowest and highest temperatures for the
month are predicted to occur at Jos (14.9oC) and Yelwa (38.1oC) respectively.
2.1.3 March Day and Night Temperatures Prediction Deviations
Figs 16a & 16b: Predicted Day and Night Temperatures for March 2016
The southern and immediate inland areas are predicted to be warmer-than-normal in
March for both day and night (figxx). Peak temperature is predicted to reach a range
of 0.8-1.2oC in some locations. A colder-than-normal day is predicted for the North (with
departures reaching -1.4oC), while the night is expected to be mainly normal. Extreme
values of predicted maximum and minimum temperatures are expected over Yola
(38.5oC) and Jos (17.0oC) respectively.
2.1.4 April Day and Night Temperatures Prediction Deviations
Figs 17a & 17b: Predicted Day and Night Temperatures for April 2016
During April, warmer-than-normal conditions are projected for most parts of the country
during the day and night. The extreme North will be normal at both periods. Apri’sl
highest temperature is expected over Maiduguri (41.1oC), while the minimum is
predicted to occur in Jos (18.7oC).
In summary, the most discomfort will be felt in February and April, especially
during the day. The change in the day temperature is expected to increase by up to
1.4oC. The southern parts are expected to be very hot in March.
2.0 Rainfall Predictions
2.1 Onset Dates of Growing Season and Departure from 30 year average
Figs 18a & 18b: Predicted onset dates of growing season and departure from 30 year average
The graph above shows that the earliest onset date of growing season in 2016 is
February 29 in the coastal areas of the Niger Delta region, and gradually progresses
northwards in time. The latest is predicted to be last week in June in and around
northern Yobe State. On the deviation from normal map, late onset of the growing
season is predicted for Sokoto, Yobe, Borno, Gombe, Adamawa and Kaduna States. It is
also expected to be late in the northern areas of Niger Delta, especially northern Cross
River State
Early onset of the growing season is expected in all the areas in green colour, in the
inland of the South and Central States. Onset dates will be normal in Abuja (April 9),
Plateau, Bauchi, Kano, Katsina, Zamfara and all the other areas under the white
background.
2.2 Cessation Dates of Growing Season and Departure from 30 year average
Figs 19a & 19b: Predicted cessation dates of growing season and departure from 30 year
average
As was the case in 2015, an early cessation date of the growing season is
predicted for the extreme northern States of Sokoto, Zamfara, Katsina, Kano, Jigawa
and Yobe, around 27 September, 2016. This is the predicted earliest cessation date of
growing season in 2016. The cessation date is predicted to end around 16 December
2016 in the Niger Delta region. On the deviation map, an early cessation is also
projected for Kaduna, Gombe, Enugu, northern Cross River State and parts of Ogun
State. An extended rainfall season is predicted for the areas in green, mostly in the
southwest, Delta and Akwa Ibom States while the rest of the country is predicted to
have normal (30year normal) cessation dates. The predicted cessation dates will range
7 – 10days earlier in Anambra, Cross River, Plateau and Sokoto States.
2.3 Length of Growing Season and Departure from 30 year average
Figs 20a & 20b: Predicted length of growing season and departure from 30 year average
The length of the rainy season in 2016 is expected to range from 110 – 275 days,
increasing from the far North to the Niger Delta. A shorter length of the season is
predicted for a large parts of the country (fig 20b), ranging from 3 days to 20days. The
reduction in the length of the rainy season is expected to be significant around Kano,
southern Yobe, Plateau, southwest Taraba, Sokoto, Kogi, Delta (Asaba), Anambra and
northern Cross River States, ranging from 12 – 20days. There is low probability of longer
length of the rainy season (3 – 4days) in Akwa Ibom and Borno States in 2016.
2.4 Predicted Annual Rainfall and Departure from 30 year average
Figs 21a & 21b: Predicted annual rainfall and departure from 30 year average
The annual amount of rainfall is predicted to range from 300mm in the far north
to about 2500mm in the coastal areas of the Niger Delta. Rainfall amount is expected
to be reduced in all the areas in red (fig 21b), while it is predicted to be above normal in
and around Sokoto, Zamfara, Niger, Bauchi, Oyo, Ogun and Lagos States. The States in
white background are predicted to experience normal rainfall during the year.
2.5 2016 Little Dry Season and Dry spell Prediction
2.5.1 2016 Little Dry Season
The map below shows areas likely to experience the little dry season (short period
of little or no rain or dry spell) in July and/or August, 2016. The areas coloured in red
have very high prospects of experiencing the Little Dry Season (LDS) in 2016. Areas in
orange colour have medium probability while areas in peach colour have the lowest
probability of experiencing LDS in the country. The rest of the places in white are not
expected to be affected by the 2016 LDS. Also, in 2016, the month of August is
expected to be drier in the Bi–modal rainfall region of the south of the country. As El
Nino phase weakens in the second half of the year, these regions are likely to receive
more rain in August than the averages.
Fig 22: The Little Dry Season effect expected in 2016
2.5.2 Dry spell Prediction
Fig 23a & 23b: Predicted areas of occurrence of dry spell in May and June respectively
The central part of Nigeria is likely to experience dry-spell in the month of May.
This may last up 15 - 20days in and around the FCT, Niger, Nasarawa, Kwara, Kogi and
Benue States. Fig. 23 indicates that the extreme North (Sokoto to Borno states) has high
chances of experiencing dry-spells in the month of June, which may last between 10 –
21days.
2 4 6 8 10 12 14
2
4
6
8
10
12
14
ABE
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ABU
AKU
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BAU
BEN
BID
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JOS
KAD
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MIN
NGU
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OND
OSG
OWE
POR
POT
SHA
SOK
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WAR
YEL
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Legend (days)
LITTLE DRY SEASON FORECAST 2016
LONGITUDE (E)
LATI
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TM
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MO
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2.6 Mosquito Bites and Malaria Severity Indices
The predictions for the mosquito bites and malaria severity indices were first
introduced into the Seasonal Rainfall Prediction in 2015. Its introduction increased the
awareness of health risks attributable to weather and climate events. The 2016
predictions of the prospects of mosquito bites and malaria severity indices are given
below. It is expected that those in the health policy and management sector will take
advantage of the critical information contained therein to improve mitigation plans for
the year. The prediction is presented for each month of the year and shows the areas
where the bites and severity indices are expected to be strong or endemic.
2.6.1 Mosquito Bites and Malaria Severity Indices for January
Fig 24: Predicted mosquito bites index and malaria severity index in January
A moderate – extreme mosquito bites index is predicted for most parts of the
country in January, while it will be low in the far North. In the other hand, the malaria
severity index is expected to be moderate – high in parts of Ogun, Edo and Akwa Ibom
States. It is predicted to be low in other parts of the country.
2.6.2 Mosquito Bites and Malaria Severity Indices for February
Fig 25: Predicted mosquito bites index and malaria severity index in February
2.6.3 Mosquito Bites and Malaria Severity Indices for March
Fig 26: Predicted mosquito bites index and malaria severity index in March
In February and March, the projection is that mosquito bites index is expected to
increase in severity, reaching extreme proportion in several States in the central,
southwest, Delta and other areas. Malaria severity, however, is predicted to remain
moderate only in the coastal Niger Delta in February, but will affect more southern
areas in March.
2.6.4 Mosquito Bites and Malaria Severity Indices for April
Fig 27: Predicted mosquito bites index and malaria severity index in April
The first peak in the mosquito bites index for 2016 season is predicted to occur in
April (fig 27), though the malaria severity index is not expected to change much from
the March trend.
2.6.5 Mosquito Bites and Malaria Severity Indices for May
Fig 28: Predicted mosquito bites index and malaria severity index in May
2.6.6 Mosquito Bites and Malaria Severity Indices for June
Fig 29: Predicted mosquito bites index and malaria severity index in June
Between May and June, the mosquito bites index is expected to reduce slightly
in intensity, while the malaria severity index is predicted to be moderate – severe in the
South and central areas, reducing slightly in severity in June. Areas around Jos and its
environs are expected to record low mosquito bite index (fig 29); this could be
attributed to the relatively lower temperatures expected in the area. Most parts of the
North are expected to record low malaria severity index during the period, except for
areas around Maiduguri and Yelwa.
2.6.7 Mosquito Bites and Malaria Severity Indices for July
Fig 30: Predicted mosquito bites index and malaria severity index in July
2.6.8 Mosquito Bites and Malaria Severity Indices for August
Fig 31: Predicted mosquito bites index and malaria severity index in August
In July and August, an extreme case of mosquito bites index for most parts of the
country is predicted. The Jos area is the only one expected to be low. Malaria severity
index is also predicted to be moderately high in many States in the central and
northern States, slightly reducing in intensity in August.
2.6.9 Mosquito Bites and Malaria Severity Indices for September
Fig 32: Predicted mosquito bites index and malaria severity index in September
Though the mosquito bites index will remain high in most parts of the country in
September, the malaria severity index is predicted to continue to reduce, affecting
fewer areas than the previous months. It is however expected to remain extreme in the
FCT and Ondo States, becoming moderate in Borno, Bauchi, Plateau, Niger, Nasarawa,
Benue, Kogi, Delta, Enugu and parts of the southwest.
2.6.10 Mosquito Bites and Malaria Severity Indices for October
Fig 33: Predicted mosquito bites index and malaria severity index in October
The mosquito bites index will reduce in severity from the previous month, and the
malaria severity index is expected to be low in most areas except over Edo, FCT, Bauchi
and Niger States where it is predicted to be high.
2.6.11 Mosquito Bites and Malaria Severity Indices for November
Fig 34: Predicted mosquito bites index and malaria severity index in November
2.6.12 Mosquito Bites and Malaria Severity Indices for December
Fig 35: Predicted mosquito bites index and malaria severity index in December
The mosquito bites index is predicted to remain moderately high during
November-December. High malaria severity index is also expected over the FCT, while
the rest of the country will experience low influence.
3.0 Socio-economic Implications
3.1 Agriculture & Food Security
3.1.1 Crops
The predicted late onset and early cessation of rainfall in and around Sokoto,
Yobe, Zamfara, Kaduna, Borno and Adamawa States are likely to create water stress
leading to the reduction in production tonnage. Farmers and agriculturists need to be
aware of this important item in the 2016 SRP and should supplement with irrigation to
enhance crop development.
Early maturing and drought tolerant crop varieties especially maize, cowpea,
sorghum and millet should be provided by the relevant authorities at an affordable
price.
Climate Smart Agriculture (CSA) should be encouraged. For example. the use of
economic trees (Gum Arabic, Date palm, Shear, Jatropha etc.) for fencing, while Zero
tillage, mulching and other moisture conservation techniques is strongly advised.
3.1.2 Livestock
The warmer-than- normal conditions in February, March and April are expected
to negatively affect livestock production in the affected areas. Mortality rate is
expected to increase during these months due to temperature fluctuations; day-old
chicks may likely be most affected.
The drier-than-normal conditions are expected to create water stress in small
ponds making animals to go far in search of drinking water. In this regard, the use of
irrigation water bodies by the animals is recommended. More water should also be
harvested in various agricultural reservoirs and dams in the country. As a result of the
late onset, there will be high rate of nomadic migration. Therefore government should
encourage development of ranches and fodder production; in addition, grazing areas
should be properly and clearly marked out to reduce the recurrent clashes between
herdsmen and farmers
Necessary vaccines should be provided for animals due to likely spread of
diseases as a result of predicted warmer conditions in most parts of the country. Other
advisories for livestock operators include use of improved breeds of chicken (to be
provided by local and international agricultural research organizations) for better yields
in the year 2016 agricultural season.
31.3 Fish production is likely to be adversely affected as a result of warmer-
than-normal conditions especially in the coastal part of the country. Similarly, high run-
off predicted for some areas may not favour artisanal fish farming as the flood waters
may inundate and wash away the fishes. Aquaculture practitioners or operators should
take note of areas predicted to have high run-offs in order to avoid associated
impacts.
3.2 Water Resources Management
Above normal rainfall is predicted for the northwest (Sokoto, Zamfara and
Katsina states), Bauchi, parts of Niger, Oyo and Ogun States, whereas it will be below
normal rainfall in the southeast, Niger Delta, most parts of southwest, parts of northeast,
Kebbi and part of Kaduna State. Elsewhere, it is expected to be normal. Implications of
these for the water resources sector of the economy include:
Fig. 36: Agriculture in Nigeria is
still largely rain-fed
Less prospects of water availability for domestic, industrial, agriculture and power use in
the areas where below-normal rainfall is predicted. Generally this will affect stream-flow
and groundwater recharge. Adequate support through irrigation to improve agriculture
in the states with below normal rainfall is advocated.
Hydropower generation will be positively impacted by the predicted above normal
rainfall.
Need for continuous monitoring of areas with dams and irrigation facilities as the season
evolves in order to reduce incidences of flooding due to uncontrolled release of excess
rain-water that have accumulated in the dams.
In areas where the rainfall is predicted to be above normal, strategy should be put in
place for surface runoff harvesting in small surface ponds for irrigation and livestock
watering.
Responsible agencies should watch out for likelihood of flooding in regions with above
normal rainfall.
More importantly, planners should note that irrespective of whether the forecast is
above, normal or below, there is need to monitor trans-boundary streams and river
flows for effective dam operations, as well as flood control and management.
Fig. 37: So much water in some areas and so little in the others.
3.3 Power Generation
One of the major sources of electricity in Nigeria is through hydropower
generation. The prediction of above- normal rainfall amount in Niger State where three
hydro-electric power plants are situated(Jebba, Shiroro and Kainji dams), will impact
positively on hydropower generation, leading to increased power availability from
those facilities.
However, given the country’s high temperature and wind resources, other
sources of power generation like thermal which constitutes the use of renewable
energy like coal, gas and solar, as well as Wind turbines are highly recommended to
complement hydropower generation towards meeting current increasing electricity
demand of the country.
3.4 Transportation
3.4.1 Aviation
The harmattan season is predicted to continue well into the first quarter of 2016,
bringing with it, lots of dust in the prevailing strong winds at low levels. This is expected to
affect air travel with prospects of delays and cancellations, leading to loss of revenue.
Also, the expected warmer-than-normal temperature may cause airplanes to face
cargo restrictions. The onset of the rainy season is heralded by heavy storms, and these
have the capability to disrupt air travel as the runways become flooded and slippery
and often with impaired visibility.
Fig. 38: Most transportation means are affected by weather
3.4.2 Road & Rail
Warmer-than-normal temperatures expected over significant portions of the
country especially during February and April 2016 may cause road pavements to soften
and expand. This can create rutting and potholes, particularly in high-traffic areas and
can place stress on bridge joints. Uncontrolled bush burning during period of land
preparation for the start of the farming season can reduce visibility; road users should
be cautious during this period. The higher-than-normal temperature especially in March
and April can affect tyres and lead to road accidents.
Flooding of roads during rainfall makes the roads slippery, and users are
encouraged to exercise caution during these times.
In the same vein, high temperature may cause rail tracks to expand and buckle,
which may require track repairs or speed restrictions to avoid derailments. Motorist
should use fog lights during fog season and harmattan seasons to reduce road
accidents.
3.4.3 Marine
As a result of the predicted below-normal rainfall, inland water transport will be
negatively affected in 2016.
Thunderstorms and lightening that accompany the onset and cessation periods
can set oil installations ablaze leading to loss of revenue. Operators in this area
should take the necessary precautions in their operations.
Poor visibility due to advection of fog over the coast can adversely affect
coastal marine transportation and other marine activities
3.5 Dams & River Flow Monitoring
The predicted rainfall amount for 2016 is expected to be above normal in
Sokoto, Katsina, Bauchi and Zamfara, parts of Niger, Oyo and Ogun States. Many dams
located in the far northern areas are usually for irrigation and water-supply purposes
while those in the central and southern locations are mostly for water-supply and hydro-
power generation. The predicted condition therefore presents a surplus of water, which
must be well managed by way of planned discharge in order to avoid failure and
flooding of downstream communities and ecosystem. Drainage in these areas must be
cleared at all times to allow for free flow of excess water. Operators in these locations
need to plan for water conservation in order to increase availability of water during the
dry season.
3.6 Marine & Coastal Services
Though coastal marine transport will not be affected negatively, the inland
water transport will be challenged in 2016 except for parts of the northwest, Niger State
and parts of inland of the southwest where above-normal rainfall amount is expected.
Lesser loads should be carried by operators contend with heavy weight challenges, as
channels become too shallow for smooth sailing activities. Other marine activities like
fishing and recreation tend to be favoured by the predicted below-normal rainfall
condition. However, severe storms may lead to coastal inundations and disruptions in
marine travel, shipping, as well as oil exploration activities.
3.7 Health
Fig. 39: Proper information
about rainfall enables better
management of dams
The warmer-than-normal temperature conditions predicted in February and April
for most parts of the country may lead to hotter days and nights with heat stress and
dehydration, high incidence of Cerebra-Spinal Meningitis (CSM), skin rashes and heat
stroke. The relevant health authorities should increase national sensitization programmes
and routine immunization, especially amongst the most vulnerable group. Other health
advisories include:
This will likely aggravate the risk of heat- related illnesses and deaths, especially
for elderly, young children and people with related medical conditions.
Predicted moderate harmattan conditions are expected to promote high level
of dust suspension, especially during January and February. This will increase the
prospects of cold-weather related ailments such as pneumonia, asthma, catarrh
and cough, becoming severe in parts of Borno, Ekiti, Ondo, Delta, Anambra,
Cross Rivers, Akwa Ibom States and the FCT Abuja, where minimum temperature
is predicted to be colder than normal.
The above-normal-rainfall expected in parts of the northwest, Niger and inland of
the southwest may affect domestic water resources, leading to water
contamination, and bringing with it, health-related hazards such as cholera,
diarrhea and other water borne diseases.
For the mosquito bites and malaria severity forecasts, the authorities need to:
(i) Sensitize the people
(ii) Distribution of mosquito-treated nets and ensure they are used
(iii) Encourage individual and community hygiene
(iv) Enforce environmental sanitation.
3.8 Disaster Risk Management
Fig. 40: Tropical diseases are
better managed with good
knowledge of the weather
conditions responsible for their
occurrences.
Fig. 41: The frequency and intensity of rainfall and flood incidents are on the rise in recent years.
Challenges posed by the predictions of warmer-than-normal temperatures, late
onset of rains, early cessation and reduced rainfall amount in many parts of the country
in 2016 need to be addressed by the relevant authorities. These include:
Health challenges as disease vectors such as mosquitoes, insects and flies thrive
better under such warmer conditions.
Long Dry-spell of 15 – 20 days intensity in May over the FCT Abuja, Niger,
Nasarawa, Kwara, Kogi and Benue, extending to the extreme North in June.
Crop failure arising from false early starts of rains; farmers are advised to heed the
predictions and use the information contained in the SRP.
Strong gusty winds, which usually herald the arrival of the rains lead to
destruction of properties during the periods. Emergency managers should use
this information to sensitize communities in order to reduce such losses.
High frequency of fire incidents in many parts of the country due to the high
temperatures and dry, windy conditions. Citizens should be alerted by
Emergency managers to avoid dangerous practices (such as storing fuel at
home) that can trigger and escalate such disasters. Increased flood risk for Low-lying areas in Lagos, Port Harcourt, Sokoto, Niger,
Benue, Kogi and the coastal areas, which are perennial flood prone despite the
predicted drier-than-normal conditions in 2016. Likely flooding over areas in States such as Sokoto, Zamfara, Niger, Oyo, Ogun
and Lagos, which are expected to have above normal rainfall.
Likely reduction in crop yield and associated food insecurity in areas predicted
to have below normal rainfall. This could lead to displacement of people and
migration of herdsmen to a more suitable environment, which in turn can result in
communal conflict between herdsmen and farmers.
3.9 Telecommunication
Warmer-than-normal temperatures and the prospects of more intense rainstorms
accompanied by strong winds during the beginning of the rainy season and its
cessations will probably affect communication signal quality and infrastructure in 2016.
High temperatures in April and May across the country may heat-up communication
infrastructures such as cables and expand them, leading to low call-quality, drops and
/or breaks in communications. Intense thunderstorms during the peak rainy season also
cause damages in communication infrastructure. The period of the onset and cessation
of the rainy season, that is, March – May and October – November are critical. In 2016,
the onset and cessation periods are predicted to be very active particularly in the
northern parts of the country. The Nigerian Communication Commission (NCC) and
communication companies are expected to take necessary measures to minimize likely
hazard on the sector.
Fig. 43: Extreme weather such as high temperatures and thunderstorms damage critical
infrastructure in the sector
3.10 Building and Construction
Increasing trend is observed in the number of dry days during the dry season
(November-March) from year 2013 to – 2015 in the coastal areas as a consequence of
the effect of the persistent warm phase (El-Nino) of the ENSO during the years. The dry
season is a period when construction companies working in the Niger Delta undertake
most construction works because the dry condition (little or no rain) is most favourable
for construction works. The number of rain-days in the region is really high, (in the range
of 272-296 days), leaving shorter period without disruptions by rainfall for any meaningful
work. In 2016, it is projected that this dry period will increase from an average of 73days
to about 90days. Construction companies are encouraged to heed this advice
contained in this edition of the SRP.
4.0 Rainfall & Temperature Prediction Tables
4.1 Table 6: A Detailed Station by Station Predicted Day time Temperatures. Site Long Lat Jan Feb Mar Apr
ABE 3.33 7.20 34.8 36.8 36.1 35.1
ADE 5.20 7.60 34.5 36.9 37.0 36.4
ABU 7.20 9.00 33.0 34.8 34.4 33.6
AKU 5.30 7.20 33.0 35.1 34.3 33.5
ASA 6.23 6.82 34.0 35.8 35.8 34.9
AWK 7.07 6.20 34.0 35.7 35.5 34.7
BAU 9.82 10.28 30.7 34.2 36.5 38.1
BEN 5.60 6.33 33.1 35.5 35.0 34.7
BID 6.00 9.80 34.9 37.8 38.2 37.7
CAL 8.35 4.97 32.3 33.9 33.1 32.3
EKE 7.95 4.40 31.0 32.5 32.0 31.6
ENU 7.00 6.50 33.3 35.7 35.4 34.5
GOM 11.17 10.27 30.6 34.6 36.6 38.3
GUS 6.77 12.17 31.2 35.3 37.1 39.3
IBA 3.90 7.43 33.4 35.6 35.5 34.0
IBI 9.75 8.18 34.8 37.9 38.4 37.7
IJE 3.93 6.83 33.1 35.0 34.7 33.8
IKE 3.33 6.58 32.8 34.1 33.9 33.5
IKO 8.72 5.97 32.8 35.3 35.1 33.8
ILO 4.58 8.48 33.8 36.3 36.4 35.2
ISE 3.60 7.97 33.9 35.7 35.1 33.7
JOS 8.90 9.87 27.6 30.1 31.1 31.3
KAD 7.45 10.60 30.9 34.5 35.3 36.0
KAN 8.53 12.05 28.9 33.5 35.9 39.1
KAT 7.68 13.02 29.1 33.3 35.4 39.1
LAF 8.47 8.50 35.1 38.0 38.0 36.7
LAR 3.06 6.58 30.6 31.3 31.5 31.0
LOK 6.73 7.80 35.0 37.4 37.7 36.8
MAI 13.08 11.85 31.2 35.1 37.4 41.1
MAK 8.50 7.70 34.8 37.7 37.7 36.3
MIN 6.54 9.54 34.8 37.6 37.9 37.6
NGU 10.47 12.88 30.1 34.0 36.3 40.6
OGO 8.80 6.70 34.6 36.9 36.7 35.4
OND 4.83 7.10 33.0 34.8 34.5 33.0
OSG 4.50 7.82 33.7 35.6 35.2 33.7
OWE 7.03 5.48 33.4 35.3 34.8 33.9
POR 7.12 4.85 32.8 34.2 33.5 32.9
POT 11.03 11.70 30.7 34.6 36.2 39.3
SHA 3.47 8.35 33.6 35.7 35.3 33.7
SOK 5.20 12.92 32.7 36.3 38.0 40.9
UYO 7.92 5.05 32.9 34.7 34.2 33.1
WAR 5.73 5.52 32.8 34.2 34.0 33.6
YEL 4.50 11.00 35.0 38.1 39.2 39.2
YOL 12.47 9.23 34.1 37.9 39.5 40.1
ZAR 7.75 11.07 29.6 33.4 35.0 36.9
The highlighted stations have daytime temperatures above 39oC
Table 7: A Detailed Station by Station Predicted Night time Temperatures.
Site Long Lat Jan Feb Mar Apr
ABE 3.33 7.20 21.1 24.4 25.5 25.3
ABU 7.20 9.00 18.0 21.7 23.2 24.4
ADE 5.20 7.60 18.7 22.4 23.1 23.2
AKU 5.30 7.20 18.7 22.5 23.1 23.2
ASA 6.23 6.82 21.8 24.6 24.9 24.8
AWK 7.07 6.20 21.7 24.7 25.1 24.8
BAU 9.82 10.28 14.1 17.0 20.9 23.6
BEN 5.60 6.33 22.8 24.9 24.8 24.5
BID 6.00 9.80 21.2 24.2 25.9 26.2
CAL 8.35 4.97 22.9 24.5 24.3 24.1
EKE 7.95 4.40 22.4 24.1 24.4 24.1
ENU 7.00 6.50 21.4 24.0 24.9 24.9
GOM 11.17 10.27 15.3 18.4 21.8 24.4
GUS 6.77 12.17 15.4 18.3 21.7 24.5
IBA 3.90 7.43 22.3 24.3 24.6 24.2
IBI 9.75 8.18 19.1 22.3 24.9 26.5
IJE 3.93 6.83 22.0 24.4 25.1 24.8
IKE 3.33 6.58 23.1 25.0 25.5 25.3
IKO 8.72 5.97 20.6 23.0 23.8 24.0
ILO 4.58 8.48 19.8 22.8 23.8 24.0
ISE 3.60 7.97 20.7 22.9 23.7 23.5
JOS 8.90 9.87 12.0 14.9 17.0 18.7
KAD 7.45 10.60 15.1 18.4 21.2 22.8
KAN 8.53 12.05 13.5 16.7 20.5 24.2
KAT 7.68 13.02 13.4 16.5 20.0 24.1
LAF 8.47 8.50 18.8 23.0 25.3 26.0
LAR 3.06 6.58 24.1 26.3 26.6 25.9
LOK 6.73 7.80 20.0 24.3 26.0 26.3
MAI 13.08 11.85 12.9 16.3 19.9 24.4
MAK 8.50 7.70 18.8 23.1 25.3 25.8
MIN 6.54 9.54 20.9 23.5 25.5 25.6
NGU 10.47 12.88 13.9 16.7 20.4 24.0
OGO 8.80 6.70 20.6 22.7 23.4 24.0
OND 4.83 7.10 21.8 23.6 24.0 23.7
OSG 4.52 7.80 18.7 22.2 23.0 23.3
OWE 7.03 5.48 22.3 24.4 24.6 24.5
POR 7.12 4.85 21.3 23.3 23.8 23.8
POT 11.03 11.70 12.7 16.4 20.3 24.2
SHA 3.47 8.35 19.6 22.4 23.2 23.1
SOK 5.20 12.92 17.2 20.1 23.2 26.7
UYO 7.92 5.05 21.8 24.1 24.4 24.1
WAR 5.73 5.52 23.2 24.7 25.0 24.8
YEL 4.50 11.00 16.3 20.0 24.1 27.0
YOL 12.47 9.23 17.2 20.9 24.4 26.7
ZAR 7.75 11.07 14.2 17.4 20.6 23.1
5.1 Rainfall Prediction Tables for 2016
Table 8: Detailed station by station likely onset and cessation dates, length of rainy
season and seasonal amount of rainfall with their marginal errors. Station Onset
End Of Season
Length of Season
Seasonal Rainfall
Likely ME Days
Likely ME Days
Likely ME Days
Likely ME mm
ABE
2-Apr 2
2-Dec 5
244 6
1307 91
ADE
1-Apr 3
7-Dec 4
250 5
1371 51
ABU
23-Apr 4
20-Nov 2
211 5
1429 70
AKU
31-Mar 3
3-Dec 4
247 4
1377 50
ASA
15-Apr 6
6-Dec 4
235 8
1769 107
AWK
17-Apr 6
17-Nov 3
214 8
1846 102
BAU
29-May 2
23-Oct 4
147 6
1021 75
BEN
21-Mar 4
23-Dec 4
277 6
2097 140
BID
12-May 4
4-Nov 2
176 4
1079 76
CAL
10-Mar 5
28-Dec 2
293 5
2800 115
EKE
8-Mar 6
12-Dec 16
279 16
2892 384
ENU
13-Apr 3
20-Nov 5
221 5
1607 88
GOM
23-May 2
31-Oct 3
161 3
910 50
GUS
31-May 3
2-Oct 5
124 7
893 56
IBA
5-Apr 3
7-Dec 4
246 5
1194 70
IBI
11-May 5
18-Nov 2
191 6
929 43
IJE
2-Apr 4
16-Nov 5
228 6
1521 105
IKE
23-Mar 6
9-Dec 5
261 8
1382 104
IKO
29-Mar 3
22-Nov 6
238 7
2188 52
ILO
13-Apr 4
20-Nov 5
221 6
1192 81
ISE
8-Apr 4
29-Nov 4
235 4
1113 95
JOS
2-May 4
30-Oct 4
181 7
1270 27
KAD
22-May 3
3-Nov 5
165 5
1177 71
KAN
9-Jun 6
13-Oct 4
126 8
938 117
KAT
10-Jun 5
8-Oct 4
120 8
603 80
LAF
2-May 3
15-Nov 3
197 4
1188 84
LAR
1-Apr 7
5-Dec 4
248 11
1572 168
LOK
1-May 3
25-Nov 1
208 4
1072 63
MAI
13-Jun 3
16-Oct 2
125 4
569 67
MAK
1-May 2
20-Nov 4
203 5
1059 77
MIN
7-May 5
22-Nov 2
199 6
1136 54
NGU
21-Jun 4
14-Oct 4
115 7
396 33
OGO
3-May 4
12-Nov 2
193 3
1763 135
OND
24-Mar 5
14-Dec 4
265 6
1548 62
OSG
2-Apr 3
17-Nov 7
229 8
1313 65
OWE
18-Mar 4
15-Dec 4
272 6
2151 110
POR
7-Mar 4
18-Dec 3
286 4
2186 103
POT
12-Jun 5
17-Oct 4
127 5
611 53
SHA
11-Apr 2
18-Nov 4
221 5
1215 73
SOK
1-Jun 4
28-Sep 4
119 5
693 64
UYO
13-Mar 5
20-Dec 4
282 4
2226 105
WAR
9-Mar 4
26-Dec 2
292 4
2509 108
YEL
18-May 6
26-Oct 2
161 6
874 47
YOL
23-May 3
26-Oct 2
156 4
897 49
ZAR
19-May 3
1-Nov 4
166 4
1054 56
ME
Minimum 2
1
3
27
Range
Maximum 7
16
16
384
2-7 Days
1-16 Days
2-16 Days
26-384 mm
Table 9: Detailed city-by-city predicted onset and cessation dates of growing season,
length of season and seasonal rainfall amount.
State City
Long
Lat
Onset
Date
Season
End
Season
Length
Days
Annual
Rainfall
(mm)
Abia Aba 07.35 05.10 15-Mar 17-Dec 278 2335
Abiriba 07.73 05.70 22-Mar 11-Dec 265 2074
Akwete 07.35 04.88 12-Mar 19-Dec 283 2437
Arochukwu 07.92 05.38 18-Mar 14-Dec 272 2210
Bende 07.63 05.55 20-Mar 12-Dec 268 2137
Igbere 07.65 05.71 22-Mar 11-Dec 265 2070
Ikwanano 07.81 06.03 26-Mar 8-Dec 258 1940
Isiama 07.81 05.68 22-Mar 11-Dec 266 2082
Isiukwuato 07.46 05.76 23-Mar 11-Dec 264 2049
Lekwesi 07.45 05.97 25-Mar 9-Dec 260 1964
Mbosi 07.43 05.38 18-Mar 14-Dec 272 2210
Ntigha 07.48 05.22 16-Mar 15-Dec 275 2281
Osisioma
Ngwa
07.33
05.15 15-Mar 16-Dec 277 2312
Ukwa West 07.23 04.97 13-Mar 18-Dec 281 2395
Umuahia 07.48 05.52 20-Mar 13-Dec 269 2150
Umu-Obiakwa 07.47 05.15 15-Mar 16-Dec 277 2312
Umuopara 07.50 05.22 16-Mar 15-Dec 275 2281
Uzoakali 07.56 05.63 21-Mar 12-Dec 267 2103
Anambra Aguleri 06.88 06.33 29-Mar 5-Dec 252 1825
Agulu 07.06 06.11 27-Mar 7-Dec 257 1909
Alor 06.95 06.08 26-Mar 8-Dec 257 1921
Arondizuogu 07.10 05.85 24-Mar 10-Dec 262 2012
Awka 07.07 06.20 17-Apr 17-Nov 214 1846
Ihiala 06.86 05.85 24-Mar 10-Dec 262 2012
Mgbakwu 07.05 06.27 29-Mar 6-Dec 253 1848
Nnewi 06.92 06.02 26-Mar 8-Dec 259 1944
Nzam 06.72 06.45 31-Mar 4-Dec 250 1781
Ogidi 06.89 06.14 27-Mar 7-Dec 256 1897
Okija 06.84 05.91 24-Mar 9-Dec 261 1988
Omor 06.96 06.51 1-Apr 4-Dec 248 1759
Onitsha 06.78 06.15 27-Mar 7-Dec 256 1894
Otuocha 06.85 06.34 30-Mar 5-Dec 252 1821
Ozubulu 06.85 05.95 25-Mar 9-Dec 260 1972
Umuchu 07.06 06.20 28-Mar 7-Dec 255 1874
Umunze 07.23 05.96 25-Mar 9-Dec 260 1968
Ebonyi Abakaliki 08.08 06.33 29-Mar 5-Dec 252 1825
Ezzagu 08.13 06.34 30-Mar 5-Dec 252 1821
Odum Effium 08.03 06.74 3-Apr 2-Dec 243 1677
Ngbo 08.00 06.45 31-Mar 4-Dec 250 1781
Amagu 07.58 05.87 24-Mar 10-Dec 262 2004
Echialike 08.22 06.20 28-Mar 7-Dec 255 1874
Onueke 08.02 06.13 27-Mar 7-Dec 256 1901
Ohaozara 07.78 06.01 26-Mar 8-Dec 259 1948
Nguzu-Edda 07.82 05.77 23-Mar 10-Dec 264 2045
Afikpo 07.91 05.88 24-Mar 10-Dec 262 2000
Enugu Agbani 07.55 06.32 29-Mar 6-Dec 252 1829
Amagunze 07.65 06.33 29-Mar 5-Dec 252 1825
Awgu 07.47 06.07 26-Mar 8-Dec 258 1925
Eha-Amufu 07.77 06.65 2-Apr 3-Dec 245 1709
Emene 07.58 06.47 31-Mar 4-Dec 249 1773
Enugu 07.00 06.50 13-Apr 20-Nov 221 1607
Enugu-Ezike 07.46 06.98 6-Apr 30-Nov 238 1595
Ezeagu 07.73 06.27 29-Mar 6-Dec 253 1848
Igbo Eze 07.40 06.86 5-Apr 1-Dec 241 1636
Ikem 07.72 06.78 4-Apr 1-Dec 243 1663
Nsukka 06.85 07.38 11-Apr 26-Nov 230 1468
Ogbede 07.37 06.67 2-Apr 2-Dec 245 1702
Ohali 07.30 06.20 28-Mar 7-Dec 255 1874
Oji River 07.27 06.25 28-Mar 6-Dec 254 1855
Ozalla 07.47 06.30 29-Mar 6-Dec 253 1836
Udi 07.41 06.32 29-Mar 6-Dec 252 1829
Ukehe 07.41 06.55 1-Apr 3-Dec 247 1744
Uzo-Uwani 07.01 06.74 3-Apr 2-Dec 243 1677
Imo Aboh Mbaise 07.23 05.46 19-Mar 13-Dec 270 2176
Arondizuogu 07.10 05.85 24-Mar 10-Dec 262 2012
Ehime 07.31 05.67 22-Mar 11-Dec 266 2086
Etiti 07.35 05.62 21-Mar 12-Dec 267 2107
Mberichi 06.95 05.36 18-Mar 14-Dec 272 2219
Mbieri 07.05 05.58 21-Mar 12-Dec 268 2124
Ngor – Okpalla 07.16 05.32 17-Mar 15-Dec 273 2237
Nkwerre 07.10 05.75 23-Mar 11-Dec 264 2053
Obowo 07.32 05.60 21-Mar 12-Dec 267 2116
Ogboko 07.61 05.59 21-Mar 12-Dec 268 2120
Oguta 06.81 05.71 22-Mar 11-Dec 265 2070
Ohaji- Egbema 06.59 04.81 11-Mar 19-Dec 284 2470
Okigwe 07.35 05.83 23-Mar 10-Dec 263 2020
Orlu 07.04 05.80 23-Mar 10-Dec 263 2033
Orsu 06.96 05.86 24-Mar 10-Dec 262 2008
Owerri 07.03 05.48 18-Mar 15-Dec 272 2151
Umuduru 07.25 05.68 22-Mar 11-Dec 266 2082
Uruala 07.10 05.85 24-Mar 10-Dec 262 2012
Ekiti Ado Ekiti 05.20 07.60 1-Apr 7-Dec 250 1371
Efon 05.23 07.63 14-Apr 24-Nov 225 1393
Ekiti East 05.55 07.65 14-Apr 23-Nov 224 1388
Emure 05.46 07.44 12-Apr 25-Nov 229 1450
Ifelodun 05.04 07.50 12-Apr 25-Nov 227 1432
Ijero 05.07 07.81 16-Apr 22-Nov 221 1342
Ikere Ekiti 05.22 07.50 12-Apr 25-Nov 227 1432
Ikole 05.51 07.79 16-Apr 22-Nov 221 1348
Ilawe 05.11 07.60 14-Apr 24-Nov 225 1402
Ilawe Ekiti 05.05 07.37 11-Apr 26-Nov 230 1471
Irepodun 04.79 07.95 18-Apr 21-Nov 218 1304
Ise/orun 05.43 07.46 12-Apr 25-Nov 228 1444
Moriwo 05.10 07.38 11-Apr 26-Nov 230 1468
Omuo 05.41 07.88 17-Apr 21-Nov 219 1323
Oye 05.33 07.80 16-Apr 22-Nov 221 1345
Usi Ekiti 05.18 07.84 16-Apr 22-Nov 220 1334
Lagos Agbara 03.09 06.51 1-Apr 4-Dec 248 1759
Agege 03.33 06.62 2-Apr 3-Dec 246 1719
Ajah 03.57 06.47 31-Mar 4-Dec 249 1773
Apapa 03.37 06.45 31-Mar 4-Dec 250 1781
Badagry 02.88 06.37 30-Mar 5-Dec 251 1810
Egbeda 03.29 06.59 2-Apr 3-Dec 247 1730
Epe 03.98 06.56 1-Apr 3-Dec 247 1741
Ikeja 03.33 06.58 23-Mar 9-Dec 261 1382
Ikorodu 03.50 06.60 2-Apr 3-Dec 246 1726
Ikotun 03.30 06.51 1-Apr 4-Dec 248 1759
Iyana Ipaja 03.29 06.62 2-Apr 3-Dec 246 1719
Kosofe 03.40 06.59 2-Apr 3-Dec 247 1730
Lagos Island 03.06 06.58 1-Apr 5-Dec 248 1572
Marine 03.25 06.26 29-Mar 6-Dec 254 1851
Ojo 03.15 06.46 31-Mar 4-Dec 249 1777
Oshodi 03.50 06.30 29-Mar 6-Dec 253 1836
Somolu 03.38 06.54 1-Apr 4-Dec 248 1748
Surulere 03.35 06.50 31-Mar 4-Dec 249 1762
Yaba 03.38 06.51 1-Apr 4-Dec 248 1759
Ogun Abeokuta 03.33 07.20 2-Apr 2-Dec 244 1307
Abigi 04.33 06.54 1-Apr 4-Dec 248 1748
Ayetoro 03.03 07.23 9-Apr 27-Nov 233 1514
Eruwa 03.50 07.40 11-Apr 26-Nov 230 1462
Ewekoro 03.22 06.03 26-Mar 8-Dec 258 1940
ijebu-Igbo 04.00 06.95 6-Apr 30-Nov 239 1605
Ijebu-Ode 03.93 06.83 2-Apr 16-Nov 228 1521
Ikenne 03.71 06.86 5-Apr 1-Dec 241 1636
Ilaro 03.02 06.89 5-Apr 30-Nov 240 1626
Ipokia 02.84 06.52 1-Apr 4-Dec 248 1755
Obafemi
Owode 03.50 06.95 6-Apr 30-Nov 239 1605
Odogbolu 03.76 06.83 4-Apr 1-Dec 242 1646
Oja-Odan 02.84 06.89 5-Apr 30-Nov 240 1626
Otta 03.30 06.68 3-Apr 2-Dec 245 1698
Owu 04.03 06.81 4-Apr 1-Dec 242 1653
Sagamu 03.63 06.83 4-Apr 1-Dec 242 1646
Ondo Akure 05.30 07.20 31-Mar 3-Dec 247 1377
Araromi 04.50 06.60 2-Apr 3-Dec 246 1726
Idanre 05.14 07.09 7-Apr 29-Nov 236 1559
Ifon 05.78 06.92 5-Apr 30-Nov 240 1616
Ikare Akoko 05.80 07.50 12-Apr 25-Nov 227 1432
Ilaje 05.20 07.27 10-Apr 27-Nov 232 1502
Ilawe 05.06 07.40 11-Apr 26-Nov 230 1462
Ile-oluji 04.86 07.19 9-Apr 28-Nov 234 1527
Kajola Owena 05.00 07.20 9-Apr 28-Nov 234 1524
Odigbo 04.86 06.79 4-Apr 1-Dec 242 1660
Okeigbo 04.72 07.17 8-Apr 28-Nov 234 1534
Okitipupa 04.70 06.50 31-Mar 4-Dec 249 1762
Ondo 04.83 07.10 24-Mar 14-Dec 265 1548
Opuba 04.90 06.05 26-Mar 8-Dec 258 1933
Owo 05.58 07.18 9-Apr 28-Nov 234 1530
Osun Ede 04.43 07.73 15-Apr 23-Nov 223 1365
Ejigbo 04.32 07.90 17-Apr 21-Nov 219 1317
Gbongan 04.35 07.46 12-Apr 25-Nov 228 1444
Ijebu Jesa 04.82 07.68 14-Apr 23-Nov 224 1379
Ikirun 04.70 07.90 17-Apr 21-Nov 219 1317
Ikirun 04.70 07.90 17-Apr 21-Nov 219 1317
Ila 04.90 08.00 18-Apr 20-Nov 217 1291
Ila-Orogun 04.89 08.01 18-Apr 20-Nov 217 1288
Ile Ife 04.55 07.47 12-Apr 25-Nov 228 1441
Ilesa 04.73 07.62 14-Apr 24-Nov 225 1396
Ilobu 04.48 07.84 16-Apr 22-Nov 220 1334
Iperindo 04.82 07.49 12-Apr 25-Nov 228 1435
Iragbiji 04.70 07.89 17-Apr 21-Nov 219 1320
Iwo 04.18 07.63 14-Apr 24-Nov 225 1393
Okeigbo 04.70 07.16 8-Apr 28-Nov 235 1537
Oshogbo 04.50 07.82 2-Apr 17-Nov 229 1313
Oyo Ago Are 03.42 08.50 24-Apr 16-Nov 206 1166
Awe 03.94 07.82 16-Apr 22-Nov 221 1339
Ibadan 03.90 07.43 5-Apr 7-Dec 246 1194
Ibarapa East 03.49 07.61 14-Apr 24-Nov 225 1399
Ido 03.71 07.50 12-Apr 25-Nov 227 1432
Igbeti 04.13 08.75 27-Apr 13-Nov 201 1110
Igbo Ora 03.28 07.43 11-Apr 25-Nov 229 1453
Igboho 03.75 08.83 28-Apr 13-Nov 200 1093
Iresa 04.43 08.09 19-Apr 19-Nov 215 1267
Iseyin 03.60 07.97 8-Apr 29-Nov 235 1113
Iwere Ile 03.05 07.98 18-Apr 20-Nov 217 1296
Kishi 03.85 09.08 1-May 10-Nov 194 1042
Ogbomoso 04.25 08.14 20-Apr 19-Nov 214 1254
Oke- Ile 03.02 07.93 17-Apr 21-Nov 218 1309
Okeho/Oke Iho 03.35 08.03 19-Apr 20-Nov 216 1283
Oyo 03.93 07.84 16-Apr 22-Nov 220 1334
Shaki 03.47 08.35 11-Apr 18-Nov 221 1215
Akwa
Ibom Abak 07.47 04.59 9-Mar 21-Dec 289 2575
Eket 07.95 04.40 8-Mar 12-Dec 279 2892
Essien-Udim 07.45 05.05 14-Mar 17-Dec 279 2358
Etinan 07.86 04.85 12-Mar 19-Dec 283 2451
Ibeno 07.58 04.33 6-Mar 24-Dec 294 2704
Ikot Akpa Idem 07.60 04.89 12-Mar 18-Dec 282 2432
Ikot Ekpene 07.43 05.11 15-Mar 16-Dec 278 2330
Ikot-Abasi 07.34 04.34 6-Mar 23-Dec 294 2699
Mkpat-Enin 07.46 04.42 7-Mar 23-Dec 292 2659
Nsit-Ubium 07.40 05.08 15-Mar 17-Dec 278 2344
Onna 07.43 05.11 15-Mar 16-Dec 278 2330
Oron 08.14 04.50 8-Mar 22-Dec 291 2619
Uyo 07.92 05.05 13-Mar 20-Dec 282 2226
Bayelsa Amassama 06.11 04.97 13-Mar 18-Dec 281 2395
Brass 06.25 04.30 5-Mar 24-Dec 295 2719
Nembe 06.37 04.48 7-Mar 22-Dec 291 2629
Ogbia 06.50 04.40 6-Mar 23-Dec 293 2669
Ogboinbiri 05.97 04.82 11-Mar 19-Dec 284 2465
Oloibiri 06.30 04.66 10-Mar 21-Dec 287 2541
Oporoma 06.85 04.80 11-Mar 19-Dec 284 2474
Otuoke 06.31 04.79 11-Mar 19-Dec 284 2479
Sagbama 06.21 05.17 16-Mar 16-Dec 276 2303
Yenogoa 06.25 04.92 13-Mar 18-Dec 282 2418
Cross River Akampka 08.35 05.32 17-Mar 15-Dec 273 2237
Akpabuyo 08.41 04.92 13-Mar 18-Dec 282 2418
Akpet Central 08.10 05.55 20-Mar 12-Dec 268 2137
Calabar 08.35 04.97 10-Mar 28-Dec 293 2800
Ikom 08.72 05.97 29-Mar 22-Nov 238 2188
Obubra 08.33 06.10 27-Mar 8-Dec 257 1913
Obudu 09.17 06.65 2-Apr 3-Dec 245 1709
Odukpani 08.35 05.08 15-Mar 17-Dec 278 2344
Ogoja 08.80 06.70 3-May 12-Nov 193 1763
Okpoma 08.66 06.49 31-Mar 4-Dec 249 1766
Otu 08.11 05.29 17-Mar 15-Dec 274 2250
Sankwala 09.24 06.60 2-Apr 3-Dec 246 1726
Ugep 08.07 05.82 23-Mar 10-Dec 263 2025
Delta Abavo 06.18 06.12 27-Mar 7-Dec 256 1905
Abraka 06.10 05.79 23-Mar 10-Dec 263 2037
Agbor 06.15 06.25 28-Mar 6-Dec 254 1855
Aradhe 06.30 05.62 21-Mar 12-Dec 267 2107
Asaba 06.82 06.23 15-Apr 6-Dec 235 1769
Burutu 05.50 05.35 18-Mar 14-Dec 273 2223
Kwale 06.44 05.72 22-Mar 11-Dec 265 2066
Oduobori 06.06 05.15 15-Mar 16-Dec 277 2312
Oghara 06.08 05.48 19-Mar 13-Dec 270 2167
Ogwash-Ukwu 06.56 06.16 27-Mar 7-Dec 256 1890
Oki 06.13 06.23 28-Mar 6-Dec 254 1863
Owa-Alero 06.22 06.21 28-Mar 7-Dec 255 1871
Owa-Oyibu 06.20 06.18 28-Mar 7-Dec 255 1882
Oyoko 06.17 06.10 27-Mar 8-Dec 257 1913
Ozoro 06.22 05.53 20-Mar 13-Dec 269 2146
Sapele 05.67 05.89 24-Mar 9-Dec 261 1996
Ughelli 05.99 05.50 20-Mar 13-Dec 270 2158
Warri 05.73 05.52 9-Mar 26-Dec 292 2509
Edo Abudu 06.03 06.30 29-Mar 6-Dec 253 1836
Afuze 05.98 06.94 6-Apr 30-Nov 239 1609
Agenebode 06.69 07.11 8-Apr 28-Nov 236 1553
Auchi 06.27 07.07 7-Apr 29-Nov 237 1566
Benin 05.60 06.33 21-Mar 23-Dec 277 2097
Ekpoma 06.07 06.75 3-Apr 2-Dec 243 1674
Igueben 06.22 06.52 1-Apr 4-Dec 248 1755
Iyamoh 06.31 07.14 8-Apr 28-Nov 235 1543
Oredo 05.65 06.29 29-Mar 6-Dec 253 1840
Ozalla 06.02 06.80 4-Apr 1-Dec 242 1656
Siluko 05.16 06.53 1-Apr 4-Dec 248 1752
Ubiaja 06.38 06.66 2-Apr 2-Dec 245 1705
Uromi 06.33 06.71 3-Apr 2-Dec 244 1688
Rivers Abonnema 06.77 04.72 10-Mar 20-Dec 286 2512
Ahoade 06.65 05.09 15-Mar 17-Dec 278 2340
Bonny 07.15 04.42 7-Mar 23-Dec 292 2659
Bori 07.37 04.68 10-Mar 20-Dec 287 2532
Buguma 06.86 04.74 11-Mar 20-Dec 285 2503
Degema 06.77 04.77 11-Mar 20-Dec 285 2489
Elele 06.82 05.10 15-Mar 17-Dec 278 2335
Eleme 07.11 04.79 11-Mar 19-Dec 284 2479
Emohua 06.86 04.88 12-Mar 19-Dec 283 2437
Ogoni 07.15 04.78 11-Mar 19-Dec 285 2484
Okrika 07.08 04.74 11-Mar 20-Dec 285 2503
Omoko 06.65 05.34 18-Mar 14-Dec 273 2228
Opobo 07.55 04.62 9-Mar 21-Dec 288 2561
Oyigbo 07.14 04.87 12-Mar 19-Dec 283 2441
Phc 07.12 04.85 7-Mar 18-Dec 286 2186
Rumuodogo 06.79 04.92 13-Mar 18-Dec 282 2418
Adamawa Furfore 12.34 09.13 2-May 10-Nov 193 1032
Girei 12.33 09.22 3-May 9-Nov 191 1015
Gombi 12.43 10.09 13-May 1-Nov 173 878
Guyuk 11.93 09.91 11-May 3-Nov 177 902
Hong 12.55 10.14 14-May 1-Nov 172 871
Jada 12.10 08.72 27-Apr 14-Nov 202 1116
Lamurde 11.47 09.60 7-May 6-Nov 183 949
Madagali 13.63 10.88 23-May 25-Oct 156 796
Maiha 13.21 09.98 12-May 2-Nov 175 892
Mayo Belwa 12.03 09.03 1-May 11-Nov 195 1051
Michika 13.23 10.37 16-May 30-Oct 167 844
Mubi 13.25 10.27 15-May 31-Oct 169 855
Shelleng 12.00 09.89 11-May 3-Nov 177 905
Song 12.62 09.82 10-May 4-Nov 179 915
Toungo 12.05 08.12 20-Apr 19-Nov 214 1259
Yola 12.47 09.23 23-May 26-Oct 156 897
Bauchi Alkaleri 10.25 10.32 16-May 30-Oct 168 850
Azare 10.17 11.67 1-Jun 18-Oct 140 754
Bauchi 09.82 10.28 29-May 23-Oct 147 1021
Bulkachuwa 10.52 11.65 1-Jun 18-Oct 140 755
Dambam 10.71 11.68 1-Jun 18-Oct 140 754
Darazo 10.24 10.59 19-May 28-Oct 163 821
Duguri 09.76 09.90 11-May 3-Nov 177 903
Ganjuwa 10.17 10.86 22-May 25-Oct 157 797
Jama'are 09.56 11.39 29-May 20-Oct 146 764
Katagum 10.21 12.17 7-Jun 13-Oct 129 749
Misau 10.28 11.18 26-May 22-Oct 150 775
Ningi 09.34 11.04 24-May 24-Oct 153 784
Tafawa Balewa 09.55 09.74 9-May 4-Nov 180 927
Toro 09.04 10.03 12-May 2-Nov 174 885
Warji 09.45 11.11 25-May 23-Oct 152 779
Yakoba 09.84 10.31 16-May 30-Oct 168 851
Borno Askira/ Uba 12.91 10.65 20-May 27-Oct 161 815
Bama 13.68 11.51 30-May 19-Oct 143 759
Biu 12.18 10.61 19-May 28-Oct 162 819
Chibok 13.11 10.85 22-May 25-Oct 157 798
Damboa 12.75 11.15 26-May 23-Oct 151 777
Dikwa 13.91 12.04 5-Jun 15-Oct 132 749
Gumsuri 12.82 11.05 25-May 24-Oct 153 783
Gwoza 13.14 11.05 25-May 24-Oct 153 783
Jare 12.16 10.71 20-May 27-Oct 160 810
Konduga 13.41 11.64 1-Jun 18-Oct 140 755
Kukawa 13.57 12.92 16-Jun 7-Oct 114 772
Kwaya Kusar 11.50 10.30 16-May 30-Oct 169 852
Magumeri 12.83 12.11 6-Jun 14-Oct 131 749
Maiduguri 13.08 11.85 13-Jun 16-Oct 125 569
Nganzai 13.10 12.50 11-Jun 10-Oct 122 754
Monguno 13.36 12.40 10-Jun 11-Oct 124 752
Gombe Akko 10.57 10.17 14-May 1-Nov 171 867
Balanga 11.68 09.96 12-May 2-Nov 176 895
Billiri 11.09 09.50 6-May 7-Nov 185 965
Dukku 10.46 10.49 18-May 29-Oct 165 831
Funakaye 11.10 10.17 14-May 1-Nov 171 867
Gombe 11.17 10.28 23-May 31-Oct 161 910
Kaltungo 11.31 09.82 10-May 4-Nov 179 915
Kwami 11.15 10.30 16-May 30-Oct 169 852
Nafada 11.10 11.32 28-May 21-Oct 147 767
Shomgom 11.13 09.39 5-May 8-Nov 188 984
Yamaltu 11.30 10.14 14-May 1-Nov 172 871
Taraba Abako 09.89 07.63 14-Apr 24-Nov 225 1393
Abbare 11.61 09.25 3-May 9-Nov 191 1009
Bali 10.96 07.85 16-Apr 22-Nov 220 1331
Chediya 10.20 08.18 20-Apr 19-Nov 213 1244
Dampar 10.13 08.53 25-Apr 15-Nov 206 1159
Donga 10.05 07.72 15-Apr 23-Nov 223 1368
Dooshima 09.69 08.23 21-Apr 18-Nov 212 1231
Garin Bakari 10.98 08.56 25-Apr 15-Nov 205 1152
Gashaka 11.49 07.37 11-Apr 26-Nov 230 1471
Gassol 10.36 08.59 25-Apr 15-Nov 205 1145
Gembu 11.25 06.72 3-Apr 2-Dec 244 1684
Ibi 09.75 08.18 11-May 18-Nov 191 929
Karim Lamido 11.19 09.30 4-May 8-Nov 190 1000
Lau 11.27 09.21 3-May 9-Nov 192 1017
Moti 09.82 08.18 20-Apr 19-Nov 213 1244
Tsokundi 10.01 07.88 17-Apr 21-Nov 219 1323
Wukari 09.78 07.88 17-Apr 21-Nov 219 1323
Zing 11.75 09.00 30-Apr 11-Nov 196 1058
Yobe Buni -Yadi 11.99 11.27 27-May 22-Oct 148 770
Damaturu 11.96 11.74 2-Jun 17-Oct 138 752
Fika 11.18 11.28 27-May 21-Oct 148 770
Geidam 11.55 12.89 15-Jun 7-Oct 114 770
Gujba 11.56 11.30 27-May 21-Oct 148 768
Jakusko 10.14 12.38 9-Jun 11-Oct 125 752
Machina 09.59 13.06 17-Jun 5-Oct 111 780
Nguru 10.46 12.88 21-Jun 14-Oct 115 396
Potiskum 11.03 11.70 12-Jun 17-Oct 127 611
Yunusari 11.44 13.07 18-Jun 5-Oct 110 781
Yusufari 11.21 13.08 18-Jun 5-Oct 110 781
Kwara Afon 04.53 08.31 22-Apr 17-Nov 210 1211
Araromi Opin 05.82 08.14 20-Apr 19-Nov 214 1254
Bwen 02.89 08.84 28-Apr 13-Nov 199 1090
Esie 04.89 08.21 21-Apr 18-Nov 213 1236
Ijara Isin 05.02 08.25 21-Apr 18-Nov 212 1226
Ilofa 05.14 08.09 19-Apr 19-Nov 215 1267
Ilorin 04.54 08.89 13-Apr 20-Nov 221 1192
Jebba 04.82 09.11 1-May 10-Nov 194 1036
Kaiama 03.95 09.61 7-May 6-Nov 183 947
kosubosu 03.25 09.57 7-May 6-Nov 184 954
Lafiagi 05.41 08.85 28-Apr 13-Nov 199 1088
Offa 04.72 08.15 20-Apr 19-Nov 214 1251
Oke Oyi 04.72 08.58 25-Apr 15-Nov 205 1147
Omu Aran 05.09 08.14 20-Apr 19-Nov 214 1254
Osi 05.23 08.08 19-Apr 20-Nov 215 1270
Owu Isin 05.02 08.28 22-Apr 18-Nov 211 1219
Pategi 05.76 08.72 27-Apr 14-Nov 202 1116
Share 04.98 08.82 28-Apr 13-Nov 200 1095
Kogi Ajaokuta 06.65 07.56 13-Apr 24-Nov 226 1414
Amabo 06.72 06.63 2-Apr 3-Dec 246 1716
Ankpa 07.63 07.43 11-Apr 25-Nov 229 1453
Ayangba 07.17 07.49 12-Apr 25-Nov 228 1435
Bassa 07.05 07.90 17-Apr 21-Nov 219 1317
Ejiba 05.63 08.30 22-Apr 18-Nov 211 1214
Ero 06.69 07.58 13-Apr 24-Nov 226 1408
Idah 06.73 07.11 8-Apr 28-Nov 236 1553
Ife 05.76 07.92 17-Apr 21-Nov 219 1312
Imbaka 06.67 06.55 1-Apr 3-Dec 247 1744
Isanlu 05.67 08.15 20-Apr 19-Nov 214 1251
Itobe 07.56 07.72 15-Apr 23-Nov 223 1368
Iyara 05.97 07.84 16-Apr 22-Nov 220 1334
Kabba 06.07 07.84 16-Apr 22-Nov 220 1334
Lokoja 06.74 07.80 1-May 25-Nov 208 1072
Mopa 05.89 08.09 19-Apr 19-Nov 215 1267
Obajana 06.43 07.91 17-Apr 21-Nov 219 1315
Ogwo 06.65 06.75 3-Apr 2-Dec 243 1674
Okene 06.23 07.55 13-Apr 24-Nov 226 1417
Onyedega 06.67 06.88 5-Apr 30-Nov 241 1629
Plateau Bokkos 08.99 09.30 4-May 8-Nov 190 1000
Bukuru 08.86 09.77 9-May 4-Nov 180 922
Damshin 09.45 08.63 26-Apr 15-Nov 204 1136
Dengi 09.95 09.37 5-May 8-Nov 188 988
Ganjuwa 10.31 09.44 5-May 7-Nov 187 976
Jos 08.88 09.93 2-May 30-Oct 181 1270
Kwabzak 09.50 09.13 2-May 10-Nov 193 1032
Langtang 09.80 09.15 2-May 10-Nov 193 1028
Mabudi 09.86 08.58 25-Apr 15-Nov 205 1147
Mangu 09.14 09.49 6-May 7-Nov 186 967
Pankshin 09.43 09.33 4-May 8-Nov 189 995
Quan'pan 09.28 08.97 30-Apr 11-Nov 197 1064
Riyom 08.71 09.58 7-May 6-Nov 184 952
Wase 09.96 09.10 1-May 10-Nov 194 1038
Yelwa-
Shendam 09.66 08.81 28-Apr 13-Nov 200 1097
Nasarawa Akwanga 08.41 08.91 29-Apr 12-Nov 198 1076
Amaku 08.13 08.24 21-Apr 18-Nov 212 1229
Awe 09.14 08.11 20-Apr 19-Nov 215 1262
Bakara 07.49 08.36 23-Apr 17-Nov 209 1199
Doma 08.36 08.40 23-Apr 17-Nov 209 1190
Gidan Rai 08.36 08.06 19-Apr 20-Nov 216 1275
Giza 08.63 08.20 21-Apr 18-Nov 213 1239
Gwadi 08.34 08.92 29-Apr 12-Nov 198 1074
Kainyehu 07.14 08.09 19-Apr 19-Nov 215 1267
Keana 08.80 08.15 20-Apr 19-Nov 214 1251
Keffi 07.88 08.85 28-Apr 13-Nov 199 1088
Lafia 08.51 08.49 2-May 15-Nov 197 1188
Ninga 08.31 09.09 1-May 10-Nov 194 1040
Obi 08.76 08.36 23-Apr 17-Nov 209 1199
Toto 07.08 08.39 23-Apr 17-Nov 209 1192
Uke 07.69 08.91 29-Apr 12-Nov 198 1076
Wamba 08.60 08.94 29-Apr 12-Nov 197 1070
Benue Aliade 08.48 07.30 10-Apr 27-Nov 232 1493
Anyiin 08.58 07.71 15-Apr 23-Nov 223 1370
Egumale 07.96 06.80 4-Apr 1-Dec 242 1656
Gboko 09.00 07.32 10-Apr 26-Nov 231 1486
Idekpa 07.92 07.23 9-Apr 27-Nov 233 1514
Katsina Ala 09.28 07.16 8-Apr 28-Nov 235 1537
Kyado 09.72 07.65 14-Apr 23-Nov 224 1388
Makurdi 08.54 07.73 1-May 20-Nov 203 1059
Obagaji 07.91 07.88 17-Apr 21-Nov 219 1323
Obagaji 07.91 07.88 17-Apr 21-Nov 219 1323
Oju 07.91 07.38 11-Apr 26-Nov 230 1468
Okpoga 07.80 07.04 7-Apr 29-Nov 237 1576
Orokam 07.55 06.97 6-Apr 30-Nov 239 1599
Otukpo 08.14 07.20 9-Apr 28-Nov 234 1524
Ugbopko 07.88 07.66 14-Apr 23-Nov 224 1385
Wanunne 08.89 07.57 13-Apr 24-Nov 226 1411
Zaki Biam 09.61 07.51 12-Apr 25-Nov 227 1429
Niger Agwara 04.31 10.89 23-May 25-Oct 156 795
Baro 06.42 08.64 26-Apr 14-Nov 204 1134
Bida 06.01 09.07 12-May 4-Nov 176 1079
Duku 04.88 11.20 26-May 22-Oct 150 774
Gbako 05.97 09.00 30-Apr 11-Nov 196 1057
Jebba 04.83 09.11 1-May 10-Nov 194 1036
Kainji 04.61 09.86 10-May 3-Nov 178 909
Kontagora 05.47 10.40 17-May 29-Oct 167 841
Kutiwenji 05.68 09.52 6-May 6-Nov 185 962
Kwamba 07.17 09.20 3-May 9-Nov 192 1019
Lapai 06.57 09.05 1-May 11-Nov 195 1048
Minna 06.55 09.61 7-May 22-Nov 199 1136
Mokwa 05.05 09.29 4-May 9-Nov 190 1002
Paiko 06.63 09.43 5-May 7-Nov 187 977
Rijau 05.25 11.10 25-May 23-Oct 152 780
Shiroro 06.80 09.98 12-May 2-Nov 175 892
Warari 05.32 10.92 23-May 25-Oct 156 792
Wushishi 06.11 09.72 9-May 5-Nov 181 930
Abuja Abaji 06.94 08.47 24-Apr 16-Nov 207 1173
Abuja 07.48 09.07 23-Apr 20-Nov 211 1429
Asokoro 07.51 09.04 1-May 11-Nov 195 1050
Bassa 06.79 08.63 26-Apr 15-Nov 204 1136
Bwari 07.39 09.28 3-May 9-Nov 190 1004
Chukuku 07.15 08.84 28-Apr 13-Nov 199 1090
Gosa 07.29 08.94 29-Apr 12-Nov 197 1070
Gwagwalada 07.09 08.94 29-Apr 12-Nov 197 1070
Gwaska 07.28 09.02 30-Apr 11-Nov 196 1053
Karshi 07.55 08.82 28-Apr 13-Nov 200 1095
Kubwa 07.31 09.14 2-May 10-Nov 193 1030
Kuje 07.22 08.92 29-Apr 12-Nov 198 1074
Kwali 07.06 08.85 28-Apr 13-Nov 199 1088
Madalla 07.22 09.11 1-May 10-Nov 194 1036
Pegi 07.48 09.06 1-May 11-Nov 195 1046
Tando 06.85 09.20 3-May 9-Nov 192 1019
Zuba 07.39 09.06 1-May 11-Nov 195 1046
Kebbi Aliero 04.46 12.29 8-Jun 12-Oct 127 750
Argungu 04.52 12.72 13-Jun 8-Oct 118 762
Augie 04.59 12.89 15-Jun 7-Oct 114 770
Bagizza 04.42 12.97 16-Jun 6-Oct 113 775
Bagudo 04.22 11.40 29-May 20-Oct 146 764
Birnin Kebbi 04.20 12.43 10-Jun 11-Oct 124 753
Chinchinna 05.72 11.47 30-May 20-Oct 144 761
Gwandu 04.64 12.50 11-Jun 10-Oct 122 754
Illo 03.70 11.55 30-May 19-Oct 142 758
Jega 04.43 12.20 7-Jun 13-Oct 129 749
Mahuta 04.97 11.55 30-May 19-Oct 142 758
Maraba 04.73 10.32 16-May 30-Oct 168 850
Ngaski 04.71 10.40 17-May 29-Oct 167 841
Sakaba 05.60 11.07 25-May 23-Oct 152 782
Yelwa 04.50 11.00 18-May 26-Oct 161 874
Zuru 05.23 11.43 29-May 20-Oct 145 762
Sokoto Alikeru 05.99 12.93 16-Jun 6-Oct 113 772
Bodinga 05.22 13.04 17-Jun 5-Oct 111 779
Danboka 05.37 13.73 25-Jun 29-Sep 97 837
Domawa 04.70 12.35 9-Jun 12-Oct 126 751
Garinisa 04.58 11.63 31-May 18-Oct 141 755
Goronyo 05.67 13.43 22-Jun 2-Oct 103 808
Gwazange 04.26 13.42 22-Jun 2-Oct 103 807
Kurawa 06.36 13.52 23-Jun 1-Oct 101 816
Sakwabe 04.22 13.16 19-Jun 4-Oct 109 787
Shagari 04.99 12.62 12-Jun 9-Oct 120 758
Sokoto 05.20 12.92 1-Jun 28-Sep 119 693
Tambuwal 04.71 12.26 8-Jun 13-Oct 127 750
Tungan Mogaji 04.95 12.07 6-Jun 14-Oct 131 749
Wamako 05.09 13.03 17-Jun 6-Oct 111 778
Zamfara Anka 05.93 12.11 6-Jun 14-Oct 131 749
Bakura 05.87 12.60 12-Jun 9-Oct 120 758
Birnin Magaji 06.86 12.34 9-Jun 12-Oct 126 751
Bukkuyum 05.46 12.13 6-Jun 14-Oct 130 749
Doka Ayi 06.10 11.09 25-May 23-Oct 152 781
Donko 05.20 11.75 2-Jun 17-Oct 138 752
Galadi 06.43 13.06 17-Jun 5-Oct 111 780
Gummi 05.10 12.13 6-Jun 14-Oct 130 749
Gusau 06.77 12.17 31-May 2-Oct 124 893
Iraba 06.28 10.97 24-May 24-Oct 155 789
Kurua 05.64 12.47 10-Jun 11-Oct 123 754
Maru 06.33 11.68 1-Jun 18-Oct 140 754
Shinkafi 06.50 13.07 18-Jun 5-Oct 110 781
Talata Mafara 06.07 12.55 11-Jun 10-Oct 121 756
Zurmi 06.78 12.79 14-Jun 8-Oct 116 765
Kastina Bakori 07.42 11.56 31-May 19-Oct 142 757
Baure 08.75 12.83 15-Jun 7-Oct 115 767
Daura 08.30 13.00 17-Jun 6-Oct 112 776
Faskari 07.02 11.72 1-Jun 17-Oct 139 753
Funtua 07.30 11.52 30-May 19-Oct 143 759
Kaita 07.75 13.08 18-Jun 5-Oct 110 781
Katsina 07.68 13.02 10-Jun 8-Oct 120 603
Kuka 07.99 13.32 21-Jun 3-Oct 105 799
Kurfi 07.48 12.66 13-Jun 9-Oct 119 760
Kusada 07.98 12.47 10-Jun 11-Oct 123 754
Mani 07.87 12.86 15-Jun 7-Oct 115 769
Matazu 07.67 12.23 8-Jun 13-Oct 128 749
Musawa 07.67 12.13 6-Jun 14-Oct 130 749
Ruma 07.23 12.87 15-Jun 7-Oct 115 769
Runka 07.31 12.45 10-Jun 11-Oct 123 753
Safana 07.41 12.41 10-Jun 11-Oct 124 752
Kano Bagwai 08.14 12.15 7-Jun 14-Oct 130 749
Bichi 08.24 12.23 8-Jun 13-Oct 128 749
Dadin Kowa 08.63 10.70 20-May 27-Oct 160 811
Dambarta 08.52 12.43 10-Jun 11-Oct 124 753
Gabasawa 08.92 12.18 7-Jun 13-Oct 129 749
Gaya 09.00 11.83 3-Jun 16-Oct 136 751
Gezawa 08.72 12.03 5-Jun 15-Oct 132 749
Kachaku 09.26 11.54 30-May 19-Oct 143 758
Kano 08.53 12.05 9-Jun 13-Oct 126 938
Kunchi 08.27 12.50 11-Jun 10-Oct 122 754
Kura 08.43 11.77 2-Jun 17-Oct 138 752
Kwankwaso 08.40 11.58 31-May 19-Oct 142 757
Madobi 08.29 11.78 2-Jun 17-Oct 138 752
Rano 08.57 11.53 30-May 19-Oct 143 759
Rogo 07.83 11.57 31-May 19-Oct 142 757
Jigawa Amaryawa 08.35 12.56 11-Jun 10-Oct 121 756
Aujara 09.43 12.05 5-Jun 14-Oct 132 749
Babura 09.02 12.77 14-Jun 8-Oct 117 764
Basirka 10.24 11.15 26-May 23-Oct 151 777
Birnin Kudu 09.50 11.45 29-May 20-Oct 144 762
Dutse 09.33 11.80 2-Jun 17-Oct 137 751
Filla 08.57 12.67 13-Jun 9-Oct 119 760
Gumel 09.37 12.62 12-Jun 9-Oct 120 758
Gwaram 09.89 11.28 27-May 21-Oct 148 770
Gwiwa 08.33 12.78 14-Jun 8-Oct 117 765
Hadejia 10.03 12.40 10-Jun 11-Oct 124 752
Kafin Hausa 09.91 12.24 8-Jun 13-Oct 128 750
Kazaure 08.40 12.67 13-Jun 9-Oct 119 760
Kila 09.77 11.33 28-May 21-Oct 147 767
Maigatari 09.45 12.81 14-Jun 8-Oct 116 766
Malalaganta 08.28 12.77 14-Jun 8-Oct 117 764
Ringim 08.54 12.65 13-Jun 9-Oct 119 759
Kaduna Birnin Gwari 06.53 10.67 20-May 27-Oct 161 813
Giwa 07.41 11.28 27-May 21-Oct 148 770
Gwantu 08.46 09.23 3-May 9-Nov 191 1013
Ikara 08.23 11.18 26-May 22-Oct 150 775
Jaba 08.00 09.44 5-May 7-Nov 187 976
Jere 07.44 09.57 7-May 6-Nov 184 954
Kachia 07.95 09.87 10-May 3-Nov 178 908
Kaduna 07.45 10.60 22-May 3-Nov 165 1177
Kafanchan 08.28 09.57 7-May 6-Nov 184 954
Kaura 08.15 10.57 19-May 28-Oct 163 823
Kubau 08.38 10.97 24-May 24-Oct 155 789
Kudan 07.73 11.30 27-May 21-Oct 148 768
Makarfi 07.88 11.37 28-May 21-Oct 146 765
Saminaka 08.68 10.42 17-May 29-Oct 166 838
Zaria 07.75 11.07 25-May 23-Oct 152 782
Zonkwa 08.28 09.78 19-May 1-Nov 166 1054
5-Mar 28-Sep 97 396
25-Jun 28-Dec 295 2892
Table 10: Station’s Abbreviations and Corresponding full names.
STATION
STATION
ABBREVIATION NAME
ABE ABEOKUTA
ADE ADO-EKITI
ABU ABUJA
AKU AKURE
ASA ASABA
AWK AWKA
BAU BAUCHI
BEN BENIN
BID BIDA
CAL CALABAR
EKE EKET
ENU ENUGU
GOM GOMBE
GUS GUSAU
IBA IBADAN
IBI IBI
IJE IJEBU ODE
IKE IKEJA
IKO IKOM
ILO ILORIN
ISE ISEYIN
JOS JOS
KAD KADUNA
KAN KANO
KAT KATSINA
LAF LAFIA
LAR LAGOS
ROOF
LOK LOKOJA
MAI MAIDUGARI
MAK MAKURDI
MIN MINNA
NGU NGURU
OGO OGOJA
OND ONDO
OSG OSOGBO
OWE OWERRI
POR PORT
HARCOURT
POT POTISKUM
SHA SHAKI
SOK SOKOTO
UYO UYO
WAR WARRI
YEL YELWA
YOL YOLA
ZAR ZARIA
5.0 Glossary
1. Agro-meteorological information - Weather and climate information that, if
applied to guide agricultural activities, improves yields and enhances coping
strategies against adverse impact of climate-related hazards in the sector.
2. Annual rainfall amount – is the total amount of rainfall observed and recorded in
the year under reference.
3. Cessation-date of rainy season - Cessation date is determined when the
available water content at the root zone has dropped to 50%.
4. Bite Rate: The probability of mosquito biting frequency in an area at any given
time, based on its temperature and rainfall amount.
5. Climate change - Is a non-random change in climate that is measured over
several decades or longer, which may be due to natural or human-induced
causes.
6. Climate variability – refers to variations in the mean state and other statistics such
as standard deviations, the occurrence of extremes, climate on all spatial and
temporal scales beyond that of the individual events. Variability may be due to
natural internal processes within the climate system or anthropogenic external
forcing.
7. Coastal inundation – Flooding, which occurs when water is driven onto land from
an adjacent body of water such as the sea or ocean.
8. Comfort Index - An index of air temperature that provides daily satisfaction with
the thermal environment or an index, which combines air temperature and
relative humidity to determine satisfaction with the thermal environment.
9. Dry season farming- Farming practices sustained by irrigation during period of
little or no rainfall.
10. El- Nino – A warming of the Pacific Ocean water near the equator, off the coast
of Peru, that typically occurs every 3 – 7 years, and which dictates a shift in
normal weather patterns.
11. ENSO (El- Nino – Southern Oscillation) - a combination of El-Niño features and
strength of surface air pressure between the tropical eastern and western Pacific
ocean waters, which is usually computed from fluctuation in the surface air
pressures between Tahiti and Darwin in Australia.
12. ENSO – Neutral –normal temperature conditions in the ocean water of the
equator off the coast of Peru in South America.
13. Extreme weather – is an event that is rare at a particular place and time of the
year. Extreme weather event would normally be as rare as or rarer than the 10 or
90 percentile of the observed probability density function.
14. Global warming – An overall increase in the world temperatures, which is often
caused by additional heat being trapped by greenhouse gases mostly as a
result of human activities.
15. Green House Effect – The warming generated by the trapping of long-wave
radiation (heat) by Green House Gases in the atmosphere
16. IPCC – Inter-Governmental Panel on Climate Change.
17. La- Nina – An extensive cooling of the waters in the upper section of the tropical
eastern Pacific Ocean
18. Length of rainy season - is the number of days between the onset and cessation
dates of the rainy season.
19. MDG -Millennium Development Goals.
20. Onset-date of rainy season - is the date at which the available water content of
the root zone at the beginning of the cropping season reaches 50%.
21. Perishable goods – Agricultural goods that lose considerable value if delayed in
conveyance from the produce point to the desired place of sale. They are
goods that go bad rapidly if a weather-controlled preservation technique is not
employed.
22. Phenological information - Is information on periodic plant and animal life cycle
of growth such as flowering, breeding, and migration; and how these are
influenced by seasonal and inter-annual variations in climate, as well as habitat
factor.
23. Sea Surface Temperature (SST) anomalies – refers to the deviations from long-
term averages in the mean temperature of the ocean in the upper few metres.
24. Seasonal Rainfall Prediction (SRP) – Forecast of weather or climate condition for
a period or season ranging from about three months to one year.
25. Tele-connection – describes statistical correlations between weather events that
occur at different parts of the world.
26. Vision 20:20:20: Nigeria's Vision to become one of the top twenty (20) advanced
Nations' economies by the year 2020.
6.0 NiMet Contacts Nationwide
S/N NAMES STATES PHONE NUMBER
1. Mr. J. Iyanam Abia 08059740971 [email protected]
2. Mr.Y.E.Folorunsho Abuja 08183221691 [email protected],
3. Mr. I.O. Ajao Adamawa 07011769213 [email protected]
4. Mr. C.E. Ngoka AkwaIbom 08038771060 [email protected]
5. Mr. O.A. Audu Anambra 08038654850 [email protected]
6. Mr. J. Ayawari Bauchi 08065522719
08073765340
7. Mr. W.N. Uriah Bayelsa 08028693332
08038822237
8. Mr. G.K. Danye Benue 08035512477 [email protected]
9. Mr. B. Sule Borno 08057275915,
08036621988
10 Ayi, A.B(MRS) Cross
Rivers
08090331909,
08057821353
11 Mbon, E.E. Delta 08028536476
08137640843
12 Mr. T.A. Nwaogu Ebonyi 08130469187 [email protected]
13 Mr. Nwainokpor, E. Edo 09052445108 emmanuelnwainokpor@yahoo.
com
14 Mr. J.K. Eboh Enugu 08034959593 [email protected]
15 Mr. Lawal, Ekiti 08068380251 [email protected]
16 Mr. P.I. Uba Gombe 08089713529 [email protected]
17 Abbey, M.C.(Mrs.) Imo 08037904236 [email protected]
18 Mr. A. Dauda Jigawa 080544274186 [email protected]
19 Mr. Kazachiang, T.V. Kaduna 08124088883 [email protected]
20 Mr. Z. Bello Kano 08033648831 [email protected]
21 Mr. E.R. Idiong Katsina 08062560501 [email protected]
22 Mohammed, k.A.
Kebbi 08067990231
08023921369
23 Mr. O.A. Osunlalu Kogi 08036820685
08024564382
24 Mrs. I. Adewole Kwara 08120001105 [email protected]
25 Mr. Oyebade, S.A. Lagos 08036565169 [email protected]
26 Mr. S.M. Okesola Niger 08038836624 [email protected]
27 Mr. Habila I .S Nasarawa 07061893315 [email protected]
28 Mr. J.A. Alabi Ogun 08060154682 [email protected]
29 Mr. J. O. Bolum Ondo 08035690364
30 Mr. Onyeoziri, J.I. Osun 08038936185
08068955296
31 Mr. M.A. Olayiwola Oyo 08034825509 [email protected]
32 Miss R.O. Umar Plateau 08057334354 [email protected]
33 Mr. I.S. Frank Rivers 08037650208 [email protected]
34 Mr. A.M. Buba Sokoto 08058368711
08068867209
35. Mr. S. Bala Taraba 08029883300
08031540444
36 Mr. I.M. Abbas Yobe 08082933672 [email protected]
37 Mr. M.R. Garba Zamfara 08061263508
08071405193
38 Mr. Ogbuani, C.R. Ikeja 08080808660
09084444884
