Technical University of Denmark

File(s) not publicly available

Reason: We are currently converting dataset to the FAIR lidar data format. We expect that the dataset will be uploaded by Q1 of 2018. Anyone who needs this dataset earlier then the indicated deadline are welcome to get in touch with the dataset authors.

Perdigão-2015: multi-lidar flow mapping over the complex terrain site including the wind turbine inflow and wake measurements

online resource
posted on 2018-11-07, 11:59 authored by Nikola Vasiljevic, Nikolas Angelou, Guillaume Lea

This dataset has been recorded by three long-range WindScanners and three short-range WindScanners during the Perdigão 2015 campaign. For the campaign which took place in central Portugal near the village of Perdigão three scanners were located on two mountain ridges that run in parallel for about 2 km. The scanners carried out six synchronized scanning scenarios: a transect scan perpendicular to the ridges; a virtual mast within the valley; a scan following a transect 80 m above the southwest ridge; and three scans to capture the wake and the inflow of the 2 MW wind turbine that operates on the southwest ridge.

This is an original dataset. It represents Level 2.3 data product in the FAIR lidar data schematics, that is geo-located radial velocities stored in NetCDF files with dimensions of time, range and line-of-sight number.

Consult a list of references for more details about :

(1) WindScanner (

(2) FAIR lidar data standard (

(3) Holds information on the paper that presents the Perdigão-2015 dataset.

For more details on the measurement campaign refer to the (3) .


EUDP - 64013-0405, IFD - 1305-00024A, ERANET+ - ENER/FP7/618122/NEWA, FP7-INFRASTRUCTURES - 312372



Vale Cobrão, Portugal


from 2015-05-01 to 2015-07-01


  • Wind power plant;>Wind farm;>Wakes
  • Siting;>Resource assessment


  • Not applicable


  • Measurements;>Field experiment

External conditions

  • Terrain type;>Complex;>Ridge
  • Terrain type;>Complex;>Hilly
  • Topography;>Rural
  • Location;>Onshore;>Inland

Data category

  • Meteorological data


Jakob Mann, Michael Courtney, Per Hansen, Claus Brian Munk Pedersen, Robert Menke, Jose Carlos Matos, Jose Laginha Palma