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

Abstract

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 Section 4.c) in the updated version of the "WFIP2 Project (lidar.z07)" Readme file, where the lidar.z07.b0 dataset is fully explained.

Authors:
Publication Date:
Research Org.:
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)
OSTI Identifier:
1402036
DOE Contract Number:
67025F
Resource Type:
Data
Data Type:
Specialized Mix
Country of Publication:
United States
Language:
English
Subject:
17 Wind Energy

Citation Formats

Otarola, Sebastian. Lidar - ND Halo Scanning Doppler, Boardman - Reviewed Data. United States: N. p., 2017. Web. doi:10.21947/1402036.
Otarola, Sebastian. Lidar - ND Halo Scanning Doppler, Boardman - Reviewed Data. United States. doi:10.21947/1402036.
Otarola, Sebastian. Mon . "Lidar - ND Halo Scanning Doppler, Boardman - Reviewed Data". United States. doi:10.21947/1402036. https://www.osti.gov/servlets/purl/1402036.
@article{osti_1402036,
title = {Lidar - ND Halo Scanning Doppler, Boardman - Reviewed Data},
author = {Otarola, Sebastian},
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 Section 4.c) in the updated version of the "WFIP2 Project (lidar.z07)" Readme file, where the lidar.z07.b0 dataset is fully explained.},
doi = {10.21947/1402036},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Mon Oct 23 00:00:00 EDT 2017},
month = {Mon Oct 23 00:00:00 EDT 2017}
}

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