Meteorological parameters study and temperature forecasting in selected stations in Sub-Sahara Africa using MERRA-2 Data

Abstract

The study and forecast of climatic phenomena have progressed over time, but the huge knowledge with information gathered has aided in comprehending and anticipating weather changes. The goal of this research was to look at some specific meteorological characteristics and forecast air temperature over a number of stations in Osun State, Nigeria. Monthly rainfall, relative humidity, air temperature, air pressure, wind speed and direction for four stations were gathered from the HelioClim website archives and used in this study. For each variable, descriptive statistics were calculated. The normality of the data was determined using the Shapiro-Wilks test. The data was tested for stationarity using the Augmented Dickey Fuller (ADF) test, and different types of Autoregressive Integrated Moving Average (ARIMA) models were fitted. According to the statistics, the highest average temperature was observed in March (𝑇=23.90𝐶). The months of June, July, August, and September had the highest mean relative humidity (𝑅𝐻=88.4%), pressure (𝑃=987ℎ𝑃𝑎), wind speed (𝑊𝑆=1.8𝑚/𝑠), wind direction (𝑊𝐷=225.10), and rainfall (𝑅𝐹=413𝑚𝑚). In January, the coefficient of variation (COV) for temperature was larger than in other months. In June, January, and December, relative humidity (RH), air pressure, rainfall, and wind speed and direction were all higher. The air temperature stationarity was tested using the Augmented Dickey Fuller (ADF) test, which revealed (p>0.05) but became stationary after the first difference (p<0.05). The temperature effect follows the same trend in ARIMA (1, 1, 1) forecasts for 2021 and 2022. As a result, air temperature modeling and forecasting are difficult tasks for any monthly time series. It is advised that all-time series models for any investigated location be considered, as well as meteorological conditions, in order to select the most appropriate model.