Quantifying observational relevance and uncertainty along the US East Coast using a suite of floating LiDAR buoys

The expansion of offshore wind development along the US East Coast has boosted the need for accurate assessment of the wind resource in the region. Currently, floating LiDAR buoy observations are considered the most accurate measurements available to determine offshore wind conditions at hub height. However, deploying and maintaining these instruments in such challenging offshore conditions is extremely expensive and thus, few observational data sets exist. To address the need for more observations, TGS has deployed five floating LiDAR buoys along the US East Coast as part of their multi-client business model. Combining these observations with open-source datasets has led to unparalleled spatial coverage, enabling investigations of atmospheric conditions and model biases throughout the region.

Here, we present our work to quantify the spatial representativeness of floating LiDAR buoys. We invoke the LiDAR buoy observations as well as Weather Research and Forecast (WRF) simulations and the ERA5 reanalysis data to understand correlation length scales as well as the coherence of different observation locations at various timescales. To further quantify the spatial influence of each observation, we bias correct WRF simulations in the region using one LiDAR observation at a time. This allows us to quantify the impact of each observation as a function of distance and understand where model biases are most pronounced. We find that buoys have varying degrees of influence in the region, indicating there may be more optimal locations to deploy future campaigns to reduce the overall uncertainty of the wind resource in the region.