Articles | Volume 2, issue 1
https://doi.org/10.5194/wes-2-211-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/wes-2-211-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
04 May 2017
Research article |
| 04 May 2017
An intercomparison of mesoscale models at simple sites for wind energy applications
DTU Wind Energy, Frederiksborgvej 399, 4000 Roskilde, Denmark
Andrea N. Hahmann
DTU Wind Energy, Frederiksborgvej 399, 4000 Roskilde, Denmark
Anna Maria Sempreviva
DTU Wind Energy, Frederiksborgvej 399, 4000 Roskilde, Denmark
Jake Badger
DTU Wind Energy, Frederiksborgvej 399, 4000 Roskilde, Denmark
Hans E. Jørgensen
DTU Wind Energy, Frederiksborgvej 399, 4000 Roskilde, Denmark
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- Using 3DVAR data assimilation to measure offshore wind energy potential at different turbine heights in the West Mediterranean A. Ulazia et al. 10.1016/j.apenergy.2017.09.030
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- The Alaiz experiment: untangling multi-scale stratified flows over complex terrain P. Santos et al. 10.5194/wes-5-1793-2020
- Evaluating Mesoscale Simulations of the Coastal Flow Using Lidar Measurements R. Floors et al. 10.1002/2017JD027504
- Sodar Observation of the ABL Structure and Waves over the Black Sea Offshore Site V. Lyulyukin et al. 10.3390/atmos10120811
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- Long-term uncertainty quantification in WRF-modeled offshore wind resource off the US Atlantic coast N. Bodini et al. 10.5194/wes-8-607-2023
- A sensitivity study of the WRF model in offshore wind modeling over the Baltic Sea H. Li et al. 10.1016/j.gsf.2021.101229
- Sensitivity of simulated wind power under diverse spatial scales and multiple terrains using the weather research and forecasting model Y. He et al. 10.1016/j.energy.2023.129430
- Measurements and Modelling of Offshore Wind Profiles in a Semi-Enclosed Sea N. Svensson et al. 10.3390/atmos10040194
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- Quantifying sensitivity in numerical weather prediction‐modeled offshore wind speeds through an ensemble modeling approach M. Optis et al. 10.1002/we.2611
- Advanced methodology for wind resource assessment near hydroelectric dams in complex mountainous areas L. Yang et al. 10.1016/j.energy.2019.116487
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- The NEWA Ferry Lidar Experiment: Measuring Mesoscale Winds in the Southern Baltic Sea J. Gottschall et al. 10.3390/rs10101620
- Relationships between Terrain Features and Forecasting Errors of Surface Wind Speeds in a Mesoscale Numerical Weather Prediction Model W. Xue et al. 10.1007/s00376-023-3087-5
20 citations as recorded by crossref.
- Using 3DVAR data assimilation to measure offshore wind energy potential at different turbine heights in the West Mediterranean A. Ulazia et al. 10.1016/j.apenergy.2017.09.030
- Developing a 20-year high-resolution wind data set for Puerto Rico J. Yang et al. 10.1016/j.energy.2023.129439
- The Alaiz experiment: untangling multi-scale stratified flows over complex terrain P. Santos et al. 10.5194/wes-5-1793-2020
- Evaluating Mesoscale Simulations of the Coastal Flow Using Lidar Measurements R. Floors et al. 10.1002/2017JD027504
- Sodar Observation of the ABL Structure and Waves over the Black Sea Offshore Site V. Lyulyukin et al. 10.3390/atmos10120811
- Characterizing model uncertainties in simulated coast-to-offshore wind over the northeast U.S. using multi-platform measurements from the TCAP field campaign S. Tai et al. 10.1016/j.renene.2024.122022
- Long-term uncertainty quantification in WRF-modeled offshore wind resource off the US Atlantic coast N. Bodini et al. 10.5194/wes-8-607-2023
- A sensitivity study of the WRF model in offshore wind modeling over the Baltic Sea H. Li et al. 10.1016/j.gsf.2021.101229
- Sensitivity of simulated wind power under diverse spatial scales and multiple terrains using the weather research and forecasting model Y. He et al. 10.1016/j.energy.2023.129430
- Measurements and Modelling of Offshore Wind Profiles in a Semi-Enclosed Sea N. Svensson et al. 10.3390/atmos10040194
- The making of the New European Wind Atlas – Part 1: Model sensitivity A. Hahmann et al. 10.5194/gmd-13-5053-2020
- Gap-Filling Sentinel-1 Offshore Wind Speed Image Time Series Using Multiple-Point Geostatistical Simulation and Reanalysis Data S. Hadjipetrou et al. 10.3390/rs15020409
- Quantifying sensitivity in numerical weather prediction‐modeled offshore wind speeds through an ensemble modeling approach M. Optis et al. 10.1002/we.2611
- Advanced methodology for wind resource assessment near hydroelectric dams in complex mountainous areas L. Yang et al. 10.1016/j.energy.2019.116487
- An assessment of the mesoscale to microscale influences on wind turbine energy performance at a peri-urban coastal location from the Irish wind atlas and onsite LiDAR measurements R. Byrne et al. 10.1016/j.seta.2019.100537
- Assessing boundary condition and parametric uncertainty in numerical-weather-prediction-modeled, long-term offshore wind speed through machine learning and analog ensemble N. Bodini et al. 10.5194/wes-6-1363-2021
- The sensitivity of the Fitch wind farm parameterization to a three-dimensional planetary boundary layer scheme A. Rybchuk et al. 10.5194/wes-7-2085-2022
- Evaluation of wind farm parameterizations in the WRF model under different atmospheric stability conditions with high-resolution wake simulations O. García-Santiago et al. 10.5194/wes-9-963-2024
- The NEWA Ferry Lidar Experiment: Measuring Mesoscale Winds in the Southern Baltic Sea J. Gottschall et al. 10.3390/rs10101620
- Relationships between Terrain Features and Forecasting Errors of Surface Wind Speeds in a Mesoscale Numerical Weather Prediction Model W. Xue et al. 10.1007/s00376-023-3087-5
Latest update: 23 Mar 2025
Short summary
Understanding uncertainties in wind resource assessment associated with the use of the output from numerical weather prediction (NWP) models is important for wind energy applications. A better understanding of the sources of error reduces risk and lowers costs. Here, an intercomparison of the output from 25 NWP models is presented. The study shows that model errors are larger and agreement between models smaller at inland sites and near the surface.
Understanding uncertainties in wind resource assessment associated with the use of the output...
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