Modeling Seasonal Rainfall Variability and Climate Change Impacts in Calabar Metropolis: An ARIMA Approach
Abstract
This study develops a mathematical model to analyse seasonal rainfall patterns and climate change impacts in Calabar Metropolis, Nigeria, using 31 years (1990–2021) meteorological data. The Autoregressive Integrated Moving Average (ARIMA) model was applied to forecast the rainfall, temperature, and relative humidity. The results revealed a slight upward trend in annual rainfall (0.0832 mm/year) and identified July–September as peak rainfall months. The ARIMA model for the rainfall showed a Mean Absolute Percentage Error (MAPE) of 26,690.0, indicating high variability. Increasing rainfall intensity (β = 0.437) contributed significantly to building losses and flooding, exacerbated by inadequate drainage systems. The study underscores the urgency of integrating climate-resilient urban planning and water management strategies to mitigate flood risks in Calabar Metropolis.