Lidar Buoy Data Analysis: Basic Assessment of Observed Conditions and Instrument Performance Off Virginia and New Jersey
Abstract
One of the challenges for developing offshore wind energy in the United States has been a lack of long-term observations to characterize the wind resource and design load conditions and to provide validation for the numerical weather prediction models. To address this challenge, the U.S. Department of Energy supported the procurement in 2014 and subsequent deployment of two buoys equipped with motion-compensated lidars and a comprehensive set of supporting meteorological and oceanographic (“metocean”) measurement systems. Each of the systems was deployed off the U.S. East Coast in excess of one year—one each near the coasts of Virginia and New Jersey. One notable observation from both buoys is the dramatic dependence of the wind shear on atmospheric stability as indicated by the air-sea temperature difference. This observation suggests that the commonly used neutral log law will not be a fully suitable representation of wind shear off the U.S. East Coast. This report provides a basic summary of observations at each location from key systems on each of the buoys as well as an assessment of instrument performance. These data are beginning to fill a long-standing observational gap for the wind energy community in the United States.
- Publication Date:
- Research Org.:
- Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 1481260
- Report Number(s):
- PNNL-28058
- DOE Contract Number:
- AC05-76RL01830
- Resource Type:
- Technical Report
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 17 WIND ENERGY; lidar; buoy; lidar buoy; offshore wind energy; offshore resource characterization; offshore; marine atmospheric boundary layer
Citation Formats
Shaw, William J., Pekour, Mikhail S., and Newsom, Rob K. Lidar Buoy Data Analysis: Basic Assessment of Observed Conditions and Instrument Performance Off Virginia and New Jersey. United States: N. p., 2018.
Web. doi:10.2172/1481260.
Shaw, William J., Pekour, Mikhail S., & Newsom, Rob K. Lidar Buoy Data Analysis: Basic Assessment of Observed Conditions and Instrument Performance Off Virginia and New Jersey. United States. doi:10.2172/1481260.
Shaw, William J., Pekour, Mikhail S., and Newsom, Rob K. Fri .
"Lidar Buoy Data Analysis: Basic Assessment of Observed Conditions and Instrument Performance Off Virginia and New Jersey". United States. doi:10.2172/1481260. https://www.osti.gov/servlets/purl/1481260.
@article{osti_1481260,
title = {Lidar Buoy Data Analysis: Basic Assessment of Observed Conditions and Instrument Performance Off Virginia and New Jersey},
author = {Shaw, William J. and Pekour, Mikhail S. and Newsom, Rob K.},
abstractNote = {One of the challenges for developing offshore wind energy in the United States has been a lack of long-term observations to characterize the wind resource and design load conditions and to provide validation for the numerical weather prediction models. To address this challenge, the U.S. Department of Energy supported the procurement in 2014 and subsequent deployment of two buoys equipped with motion-compensated lidars and a comprehensive set of supporting meteorological and oceanographic (“metocean”) measurement systems. Each of the systems was deployed off the U.S. East Coast in excess of one year—one each near the coasts of Virginia and New Jersey. One notable observation from both buoys is the dramatic dependence of the wind shear on atmospheric stability as indicated by the air-sea temperature difference. This observation suggests that the commonly used neutral log law will not be a fully suitable representation of wind shear off the U.S. East Coast. This report provides a basic summary of observations at each location from key systems on each of the buoys as well as an assessment of instrument performance. These data are beginning to fill a long-standing observational gap for the wind energy community in the United States.},
doi = {10.2172/1481260},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2018},
month = {10}
}