Improving the Correlation of SODAR to Anemometry using New Post-Processing Filtering Techniques

The use of SODAR (Sonic Detection and Ranging) for wind resource assessment is becoming increasingly popular due to the need for wind data at higher heights. Its accuracy and reliability, however, have been questioned in recent experimental studies. This paper summarizes the development and use of a new post-processing filtering algorithm which improves the correlation between SODAR and anemometry. Five filters were developed by comparing SODAR and tower data and also by analyzing anemometer data from five tall towers. The filters include 1) Maximum Vertical Turbulence Intensity 2) Maximum Horizontal Turbulence Intensity 3) Minimum and Maximum (Normalized) Vertical Wind Speed 4) Noise Filter and 5) Shear Filter. Of the filters, the most significant is the shear filter which compares the wind speed at 70 m to wind speeds at every other height and then filters based on a calculated shear exponent. Tall tower data from five different sites was used to determine the ranges of acceptable shear exponents. The algorithm was tested on two SODAR data sets and the effect of each filter was analyzed by comparing the SODAR data to near-by tower data. A significant improvement in the correlation between SODAR and anemometer data was observed in both SODAR data sets