Analysis of rainfall trends and variabilities for three decades in Sub – Sahara Africa

Abstract

Rainfall trend is an important climatic factor that influences agricultural products, groundwater production, drainage planning, commercial and industrial activities. The research aims to determine the trends and variability of monthly, seasonal, and annual rainfall for 30 years (from 1980 to 2010) in Sokoto (13.0059° N, 5.2476° E) and Maiduguri (11. 8333° N, 13.1500° E) using archives data obtained from the Nigeria Meteorological Agency (NiMet), Oshodi Lagos Nigeria. Statistical models were used to analyze the data. The results reveal that the maximum rainfall recorded was 371.60 mm at Maiduguri station and 374.90 mm at Sokoto station which shows a higher rainfall peak in Sokoto than Maiduguri. The coefficient of variation in the Sokoto station (126.39%) was higher than that of Maiduguri station (61.78%) which indicates that there was more rainfall variability in Sokoto than in Maiduguri. Seasonally, the average rainfall recorded in both stations was 61.78% and 126.39% respectively. No rainfall was recorded in January, February, and November for Maiduguri station, more so, no rainfall was recorded in January, November, and December for Sokoto station. According to Man-Kendal trend analysis, significant trends (p<0.5) were observed in Maiduguri and Sokoto. Therefore, the modelled statistical approach on rainfall trends and variability revealed that the peak month of annual rainfall is between June and September for the two stations. It can be recommended that the government should make favourable policies to utilize the rainfall received during this period to store more water in reservoirs and construction of water channels across the country.

Modeling and Forecasting Selected Meteorological Parameters for the Environmental Awareness in Sub-Sahel West Africa Stations

“…Furthermore, ARIMA models have been shown to be one of the most widely utilized models for a variety of applications, including science, technology, economy, market, commerce, and industry [4,6,7]. ARIMA models, in particular, have been found to be effective in forecasting various weather conditions [26]. [20] revealed linear ARIMA model and quadratic model as the overall best performing model for the prediction of the monthly and annual temperature in Libya.…”

Relationship between Air Temperature and Rainfall Variability of Selected Stations in Sub-Sahara Africa

“…Numerous studies carried out on rainfall time series across the world revealed that the effect is positive and negative on the trends of rainfall [6]. Xu et al [11], Wang et al [12], Anghileri et al [13] and Aweda et al [14] expressed different analyses on the trend of rainfall and its fluctuations through diverse places across the entire world. Nevertheless, period sequence study of rain shown either reducing or accumulating rainfall, depending on the place [15].…”

Seasonal Autoregressive Integrated Moving Average Modelling and Forecasting of Monthly Rainfall in Selected African Stations

“…On May 1 st 2023, HelioClim-1 data used for the study years was accessed for all the stations considered, that is, Abuja, Cairo, Nairobi, Pretoria, and Yaoundé . Furthermore, the data used ranges from 1980 to 2022 were collected as a monthly average for January through December of each year in comma-separated value (CSV) format, according to Aweda et al [2,29].…”