Conventional cup anemometers are widely used but limited by coarse sampling in representing turbulence. To address this, we introduce a cumulative spectral density (CSD) approach that quantifies turbulence contributions from 1-min wind speed records while explicitly accounting for aliasing. In this framework, aliasing is interpreted as a diagnostic signal of unresolved high-frequency fluctuations rather than spurious noise. Synthetic experiments using idealized spectra show that aliasing redistributes unresolved variance into lower frequencies and show that normalized CSD ratios are sensitive to this redistribution. Application to 1 year of daily, quality-controlled wind speed records (≥1 ms−1) from the Bukgangneung station, a World Meteorological Organization (WMO) surface site in South Korea, indicates that daily turbulence intensity (TI), defined as the ratio of the standard deviation to the mean wind speed of 24-hr, 1-min series, ranges from 0.3 to 0.8. For four representative 24-hr series selected by daily TI and mean wind speed, the normalized CSD, computed with a cutoff frequency of 1/30 (or 1/60) min−1 and evaluated at 1/10 min−1, effectively quantifies sub-hourly turbulence characteristics in cup anemometer records. Extending the analysis to a 5-year data set (2020–2024) from Gangneung and Bukgangneung, two WMO sites separated by ∼6 km, reveals systematic differences: Gangneung records are shifted toward higher normalized CSD ratios, with central values of 0.67 compared to 0.51 at Bukgangneung. These findings demonstrate that the CSD approach provides a practical and robust tool for extracting turbulence information from low-frequency wind data and offers improved diagnostics for both research and operational applications.