Understanding the inherent features of wind speed (variability on different time scales) has become critical for assured wind power availability, grid stability, and effective power management. The study utilizes the wavelet, autocorrelation, and FFT (fast Fourier transform) techniques to analyze and assimilate the fluctuating nature of wind speed data collected over a period of 29–42 years at different locations in the Kingdom of Saudi Arabia. The analyses extracted the intrinsic features of wind speed, including the long-term mean wind speed and fluctuations at different time scales (periods), which is critical for meteorological purposes including wind power resource assessment and weather forecasting. The longterm mean wind speed varied between 1.45 m/s at Mecca station and 3.73 m/s at Taif. The annual variation is the largest (±0.97 m/s) at Taif and the smallest (±0.25 m/s) at Mecca. Similarly, the wind speed fluctuation with different periods was also discussed in detail. The spectral characteristics obtained using FFT reveal that Al-Baha, Najran, Taif and Wadi-Al-Dawasser having a sharp peak at a frequency f = 0.00269 (1/day) retain a more regular annual repetition of wind speed than Bisha, Khamis-Mushait, Madinah, Mecca, and Sharourah. Based on the autocorrelation analysis and FFT results, the stations are divided into three groups: (i) having strong annual modulations (Al-Baha, Najran, Taif and Wadi-Al-Dawasser), (ii) having comparable annual and half-yearly modulations (Bisha, Khamis-Mushait, and Mecca) and (iii) having annual modulation moderately prominent (Madinah and Sharourah).