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Title: Lidar - ND Halo Scanning Doppler, Boardman - Derived Data

The University of Notre Dame (ND) scanning LiDAR dataset used for the WFIP2 Campaign is provided. The LiDAR is a Halo Photonics Stream Line Scanning Doppler LiDAR. **It is highly recommended to discuss any planned use of these data with University of Notre Dame scientists**. For more information refer to the attached "WFIP2 Project (lidar.z07)" Readme file.
Authors:
Publication Date:
DOE Contract Number:
67025F
Product Type:
Dataset
Research Org(s):
Atmosphere to Electrons (A2e) Data Archive and Portal, Pacific Northwest National Laboratory; PNNL
Sponsoring Org:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Wind and Water Technologies Office (EE-4W)
Subject:
17 Wind Energy
OSTI Identifier:
1402002

Leo, Laura. Lidar - ND Halo Scanning Doppler, Boardman - Derived Data. United States: N. p., Web. doi:10.21947/1402002.
Leo, Laura. Lidar - ND Halo Scanning Doppler, Boardman - Derived Data. United States. doi:10.21947/1402002.
Leo, Laura. 2018. "Lidar - ND Halo Scanning Doppler, Boardman - Derived Data". United States. doi:10.21947/1402002. https://www.osti.gov/servlets/purl/1402002.
@misc{osti_1402002,
title = {Lidar - ND Halo Scanning Doppler, Boardman - Derived Data},
author = {Leo, Laura},
abstractNote = {The University of Notre Dame (ND) scanning LiDAR dataset used for the WFIP2 Campaign is provided. The LiDAR is a Halo Photonics Stream Line Scanning Doppler LiDAR. **It is highly recommended to discuss any planned use of these data with University of Notre Dame scientists**. For more information refer to the attached "WFIP2 Project (lidar.z07)" Readme file.},
doi = {10.21947/1402002},
year = {2018},
month = {1} }
  1. A2e is a multi-year, multi-stakeholder DOE research and development initiative tasked with improving wind plant performance and mitigating risk and uncertainty to achieve substantial reduction in the cost of wind energy production. The A2e strategic vision will enable a new generation of wind plant technology, in which smart wind plants are designed to achieve optimized performance stemming from more complete knowledge of the inflow wind resource and complex flow through the wind plant. Focus areas include high fidelity modeling, verification, and validation; aeroacoustics; integrated wind plant control; integrated systems and analysis; reliability; and data archiving.
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