Results from the Position of Offshore Wind Energy Resources (POWER) Study

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Thursday, 8 January 2015: 8:30 AM
224B (Phoenix Convention Center - West and North Buildings)
Melinda Marquis, NOAA, Boulder, CO; and J. Olson, R. M. Banta, Y. L. Pichugina, S. Benjamin, E. P. James, J. M. Wilczak, I. V. Djalalova, L. Bianco, J. Carley, and J. W. Cline

In response to a request by the Department of Energy (DOE), the National Oceanic and Atmospheric Administration (NOAA) conducted a study to provide information about the type and spatial density of observations needed to characterize the wind resource in the offshore environment. The goal is to lower risk to investors by reducing uncertainty in the offshore wind resource when sites are considered for development of offshore wind farms. The study focused on the Northeast Atlantic coastal region. NOAA leveraged the 2004 New England Air Quality Study (NEAQS) in the POWER project. Key findings from POWER inform critical future research efforts and include the following: 1.) Composite maps of 80-m wind speed predictions from the HRRR model, averaged over the 2 years, for the U.S. and coastal waters, reveal many interesting aspects of spatial variations in the offshore wind fields, such as the variability of the cross-shore gradient of wind-speed. 2.) Measurements from the High Resolution Dopper Lidar (HRDL) and a wind profiling radar aboard the Ron Brown Ship (RHB) during the NEAQS study illustrate significant spatial and temporal variability of the wind field aloft over the ocean. 3.) The HRRR and its parent, the RAP, in general showed model winds to be biased slow by 0.5 to 2 m s-1, and model agreement with the measurements was within 2 m s-1 (RMSE) above 100 m ASL for the initial conditions. Similar results were also found with a new, hourly-updated version of the NAM forecast system which featured data assimilation cycles for both its 12 km parent and 4 km CONUSnest domains. 4.) Data denial experiments indicated that, in general, assimilating additional profiler data improved all model forecasts for several hours over the ocean at the Ron Brown Ship location by up to 0.2 m s-1 (8%). 5.) The critical horizontal scales of wind variability offshore are unknown, so they must be determined by measurement, which could then be used to verify whether the NWP models are also capable of reproducing the spatial flow variability observed. Long-term arrays of wind-profiling offshore buoys are recommended as an important component of a measurement strategy to understand offshore flow variability. A useful offshore wind-energy measurement network would consist of an appropriate mixture of cross-shore transects of buoy-mounted wind-profiling sensors and along-shore lines of these sensors, and several options are presented, depending on the problem to be addressed. Mobile-sensing platforms, such as the RHB and/or aircraft, will be required along with the long-term arrays to characterize along-shore variability and discover recurrent areas of stronger and weaker flows. Intensive Observational Periods (IOP's) are recommended to focus resources and understand meteorological processes driving the flow variability in the along- and cross-shore directions. 6.) An augmentation of boundary-layer profilers inland is recommended for better characterization of the regional meteorology and improved NWP assimilation results.