A hybrid Fourier–PSO model for hourly wind speed forecasting over a 4-year horizon: A tropical coastal case study

Modelling wind speed at hourly resolution over multi-year horizons remains challenging, particularly in tropical regions influenced by strong climatic variability. This study presents a hybrid Fourier–PSO framework for four-year ahead wind speed forecasting using ERA5 reanalysis data for Barranquilla, Colombia. The methodology combines spectral decomposition through the Fourier Transform with a signal-to-noise ratio criterion to identify dominant harmonic components. A reduced subset of harmonics is subsequently adjusted using Particle Swarm Optimization, while keeping the original frequencies fixed to preserve physical consistency. The model is trained using 38 years of historical data and evaluated over an independent four-year test period. The hybrid model achieved Root Mean Square Error values close to 2.0 m/s, Mean Absolute Error values between 1.6 and 1.7 m/s, and correlation coefficients ranging from 0.65 to 0.70 over the independent test horizon. The results support a stable and interpretable approach for long-term wind resource characterization in tropical environments.