Comparative Analysis of Trigonometric and Polynomial Models in Meteorological Parameter Prediction for Sub-Saharan West African Stations
Journal Title: Acadlore Transactions on Geosciences - Year 2024, Vol 3, Issue 1
Abstract
Meteorological parameter modeling is imperative for predicting future atmospheric conditions. This study focuses on the Sub-Saharan region of West Africa, a region characterized by its climatic diversity and unique weather patterns, making it an ideal subject for meteorological research. The objective was to model meteorological parameters using trigonometric and polynomial functions, assessing their predictive accuracy in selected West African stations. The parameters considered include air temperature, air pressure, wind speed, rainfall, and relative humidity, with data sourced from the HelioClim satellite archive, spanning 1980 to 2022. The data, recorded in comma-separated value (CSV) format, were analyzed using descriptive statistics, specifically mean and standard deviation. Each meteorological parameter underwent modeling through both polynomial and trigonometric functions. The comparative effectiveness of these models was evaluated using the adjusted coefficient of determination and Root Mean Square Error (RMSE). The preference for the adjusted coefficient of determination over the standard coefficient of determination (R2) was due to its ability to account for biases arising from variances in the number of parameters in both model types. The results indicated that both trigonometric and polynomial models are robust in their predictive capabilities, demonstrating their utility in accurate parameter estimation and future weather prediction. These findings suggest that such models are valuable tools in climate studies, enhancing understanding and awareness of weather conditions in the Sub-Saharan West African region.
Authors and Affiliations
Francis Olatunbosun Aweda,Timothy Kayode Samson
Keywords
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- EP ID EP749379
- DOI 10.56578/atg030101
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