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In this paper, a systematic analysis of hourly wind-speed data obtained from three potential wind-generation sites (in North Dakota) is analyzed. The power spectra of the data exhibited a power-law decay characteristic of 1/fα processes with possible long-range correlations. Conventional analysis using Hurst exponent estimators proved to be inconclusive. Subsequent analysis using detrended fluctuation analysis revealed a crossover in the scaling exponent (α). At short time scales, a scaling exponent of α∼1.4 indicated that the data resembled Brownian noise, whereas for larger time scales the data exhibited long-range correlations (α∼0.7). The scaling exponents obtained were similar across the three locations. Our findings suggest the possibility of multiple scaling exponents characteristic of multifractal signals.