Tall wind profile validation of ERA5, NORA3, and NEWA datasets using lidar observations

<p>The development of large wind turbines and airborne wind energy (AWE) systems requires reliable wind speed datasets at heights above the atmospheric surface layer. Traditional measurement approaches relying on met masts (meteorological masts) fall short of addressing these needs. In this st...

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Main Authors: E. Cheynet, J. M. Diezel, H. Haakenstad, Ø. Breivik, A. Peña, J. Reuder
Format: Article
Language:English
Published: Copernicus Publications 2025-04-01
Series:Wind Energy Science
Online Access:https://wes.copernicus.org/articles/10/733/2025/wes-10-733-2025.pdf
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author E. Cheynet
E. Cheynet
J. M. Diezel
J. M. Diezel
H. Haakenstad
Ø. Breivik
Ø. Breivik
A. Peña
J. Reuder
J. Reuder
J. Reuder
author_facet E. Cheynet
E. Cheynet
J. M. Diezel
J. M. Diezel
H. Haakenstad
Ø. Breivik
Ø. Breivik
A. Peña
J. Reuder
J. Reuder
J. Reuder
author_sort E. Cheynet
collection DOAJ
description <p>The development of large wind turbines and airborne wind energy (AWE) systems requires reliable wind speed datasets at heights above the atmospheric surface layer. Traditional measurement approaches relying on met masts (meteorological masts) fall short of addressing these needs. In this study, we validate three different model-based datasets, namely the 3 km Norwegian Hindcast archive (NORA3), the New European Wind Atlas (NEWA), and ECMWF Reanalysis v5 (ERA5), using Doppler wind lidar data from several locations in Norway and the North Sea. The validation focuses on altitudes from 100 to 500 m above ground, covering the operational range of large wind turbines and AWE systems. Our findings indicate that ERA5 and NORA3 perform similarly well in offshore locations in terms of bias, correlation coefficient, root-mean-square error, and Earth mover's distance. The choice of an appropriate wind speed database depends on the topography, altitude and error metrics of interest. However, NORA3 outperforms the other two models in two coastal sites and one complex-terrain site. In most cases, the agreement between the models and lidar measurements increases with height.</p>
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publishDate 2025-04-01
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spelling doaj-art-d9f4079eaa6040959d7f516ee6ac6b9e2025-08-20T02:24:30ZengCopernicus PublicationsWind Energy Science2366-74432366-74512025-04-011073375410.5194/wes-10-733-2025Tall wind profile validation of ERA5, NORA3, and NEWA datasets using lidar observationsE. Cheynet0E. Cheynet1J. M. Diezel2J. M. Diezel3H. Haakenstad4Ø. Breivik5Ø. Breivik6A. Peña7J. Reuder8J. Reuder9J. Reuder10Geophysical Institute, University of Bergen, Bergen, NorwayBergen Offshore Wind Centre, University of Bergen, Bergen, NorwayGeophysical Institute, University of Bergen, Bergen, NorwayBergen Offshore Wind Centre, University of Bergen, Bergen, NorwayNorwegian Meteorological Institute, Bergen, Norway.Geophysical Institute, University of Bergen, Bergen, NorwayNorwegian Meteorological Institute, Bergen, Norway.DTU Wind and Energy Systems, Technical University of Denmark, Roskilde, DenmarkGeophysical Institute, University of Bergen, Bergen, NorwayBergen Offshore Wind Centre, University of Bergen, Bergen, NorwayBjerknes Centre for Climate Research, Bergen, Norway<p>The development of large wind turbines and airborne wind energy (AWE) systems requires reliable wind speed datasets at heights above the atmospheric surface layer. Traditional measurement approaches relying on met masts (meteorological masts) fall short of addressing these needs. In this study, we validate three different model-based datasets, namely the 3 km Norwegian Hindcast archive (NORA3), the New European Wind Atlas (NEWA), and ECMWF Reanalysis v5 (ERA5), using Doppler wind lidar data from several locations in Norway and the North Sea. The validation focuses on altitudes from 100 to 500 m above ground, covering the operational range of large wind turbines and AWE systems. Our findings indicate that ERA5 and NORA3 perform similarly well in offshore locations in terms of bias, correlation coefficient, root-mean-square error, and Earth mover's distance. The choice of an appropriate wind speed database depends on the topography, altitude and error metrics of interest. However, NORA3 outperforms the other two models in two coastal sites and one complex-terrain site. In most cases, the agreement between the models and lidar measurements increases with height.</p>https://wes.copernicus.org/articles/10/733/2025/wes-10-733-2025.pdf
spellingShingle E. Cheynet
E. Cheynet
J. M. Diezel
J. M. Diezel
H. Haakenstad
Ø. Breivik
Ø. Breivik
A. Peña
J. Reuder
J. Reuder
J. Reuder
Tall wind profile validation of ERA5, NORA3, and NEWA datasets using lidar observations
Wind Energy Science
title Tall wind profile validation of ERA5, NORA3, and NEWA datasets using lidar observations
title_full Tall wind profile validation of ERA5, NORA3, and NEWA datasets using lidar observations
title_fullStr Tall wind profile validation of ERA5, NORA3, and NEWA datasets using lidar observations
title_full_unstemmed Tall wind profile validation of ERA5, NORA3, and NEWA datasets using lidar observations
title_short Tall wind profile validation of ERA5, NORA3, and NEWA datasets using lidar observations
title_sort tall wind profile validation of era5 nora3 and newa datasets using lidar observations
url https://wes.copernicus.org/articles/10/733/2025/wes-10-733-2025.pdf
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