Annualizing wind statistics from ground-based remote sensing

Short-term (one to several months) ground-based remote sensing campaigns are often used in wind resource assessment in conjunction with conventional anemometry to establish characteristics of the wind profile above the typical 50- or 60-m tower height. Both sodar and lidar profiling instrumentation are being used for this purpose.

The most robust description of the wind profile is obtained when the remote sensing data are filtered using the signal characteristics of the instrument as well as anemometry data. The resulting filtered data set may reflect reduced availability with respect to certain ambient conditions. In order for remote sensing to be an effective component of the wind resource assessment process it is important to understand whether the availability affects the longer-term statistics of the wind, and how to compensate for it.

The interpretation of results from short-term campaigns may require annualizing the statistics describing the wind speed, the shear and the turbulence intensity. A technique for accomplishing this scaling is being developed which utilizes a simple surface energy balance model and surrogate measures of the stability. The characterization of extreme or unusual events such as extreme directional shear in the presence of low-level jet-like conditions is also under examination.

This paper aims to establish procedures for annualizing wind statistics from remote sensing profilers taking into account the differential availability of such devices relative to anemometry. Autoregressive and spectral time series techniques will be explored as a means of statistically characterizing the wind resource from sodar and lidar. Recommended practices guidelines for the use of remote sensing in wind resource assessment will also be discussed.