What is already known:
What this study adds:
While sonic anemometers have been in use for nearly 50 years, there is no literature which investigates the optimal sampling rate for sonic anemometers based on the Shannon-Nyquist Sampling Theorem. In this experiment, wind is treated as a wavelet, so that sonic anemometer data with multiple sampling rates can be analyzed using spectral analysis techniques. From the power spectrum, it is then possible to determine the minimum frequency at which a sonic anemometer must sample in order to maximize the amount of information gathered from the wavelet, while minimizing the amount of data stored. Using data from the Oklahoma Mesonet and data collected on-site, no obvious peak is present in any resulting power spectra that can be definitively be considered viable. This result suggests a nearly random power distribution among frequencies, which is better-suited for averaging and integrating data collection processes.