New DOE Lidar Buoys: Evaluation of meteorological and oceanographic sensor data obtained during initial offshore performance tests

The U.S. DOE is procuring two WindSentinel buoys from AXYS Technologies, Inc. These buoys will provide long-term offshore wind profile data to support research needed to accelerate the utilization of offshore wind energy in the U.S. The buoys will be operated for the U.S. DOE by Pacific Northwest National Laboratory (PNNL.) Upon commissioning of the buoys, they will be deployed for an evaluation period in the Strait of Juan de Fuca near PNNL's Marine Sciences Laboratory. In addition to the wind-profiling lidars, the WindSentinel buoys are equipped with a suite of oceanographic and meteorological instruments for measurement of air temperature, barometric pressure, relative humidity, wave height, wave period, water conductivity, water temperature, and water depth. The data from these instruments will be useful for improved understanding of air-sea interactions, and the statistical relationships between surface and subsurface conditions with hub height winds. This presentation describes the results of an analysis of the instrument data collected along with the lidar wind profile measurements during the deployment in the Strait of Juan de Fuca. For the deployment, the two buoys were moored in approximately 80 meters of water. The mooring design allowed the buoys to remain between 500 meters and 1180 meters of each other. For the first part of the analysis, the measurements from the two buoys were compared with each other and with data from a National Buoy Data Center (NBDC) station approximately 16 kilometers away. The data from the two buoys are expected to be related on a meso-scale, and the buoy data and the NBDC station data are expected to agree on a macro-scale. For the second part of the analysis, the statistical relationships between the environmental sensor data and the lidar wind profile data are explored. Specifically, linear and non-linear models relating the wave spectral data, surface wind, solar radiation and current profile data to the wind profile and turbulence were generated, and compared to models reported in the literature. The results of the first part of the evaluation, the comparative analysis, establishes confidence in the sensor measurements. The results of the second part, the statistical modeling, contributes to improved predictions of the wind profile from readily available surface and sub-surface measurements.