Articles | Volume 14, issue 3
https://doi.org/10.5194/amt-14-2219-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/amt-14-2219-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
A 2-year intercomparison of continuous-wave focusing wind lidar and tall mast wind measurements at Cabauw
Royal Netherlands Meteorological Institute (KNMI), Utrechtseweg 297, 3731 GA, De Bilt, the Netherlands
Fred C. Bosveld
Royal Netherlands Meteorological Institute (KNMI), Utrechtseweg 297, 3731 GA, De Bilt, the Netherlands
Marijn J. de Haij
Royal Netherlands Meteorological Institute (KNMI), Utrechtseweg 297, 3731 GA, De Bilt, the Netherlands
Arnoud Apituley
Royal Netherlands Meteorological Institute (KNMI), Utrechtseweg 297, 3731 GA, De Bilt, the Netherlands
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Cited
16 citations as recorded by crossref.
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- Tall wind profile validation of ERA5, NORA3, and NEWA datasets using lidar observations E. Cheynet et al. 10.5194/wes-10-733-2025
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- Profiling the Planetary Boundary Layer Wind with a StreamLine XR Doppler LiDAR: Comparison to In-Situ Observations and WRF Model Simulations T. Tzadok et al. 10.3390/rs14174264
- A Unified Formulation for the Computation of the Six-Degrees-of-Freedom-Motion-Induced Errors in Floating Doppler Wind LiDARs A. Salcedo-Bosch et al. 10.3390/rs15061478
- Research on Wind Field Characteristics Measured by Lidar in a U-Shaped Valley at a Bridge Site J. Wang et al. 10.3390/app11209645
- Advancing Data Quality Assurance with Machine Learning: A Case Study on Wind Vane Stalling Detection V. de Feiter et al. 10.3390/atmos16020129
- Atmospheric Boundary Layer Wind Profile Estimation Using Neural Networks, Mesoscale Models, and LiDAR Measurements A. García-Gutiérrez et al. 10.3390/s23073715
- Wind resource assessment uncertainty for a TLP-based met mast D. Foussekis & F. Mouzakis 10.1088/1742-6596/2018/1/012018
- Quantification of greenhouse gas emissions from a municipal solid waste incinerator using an uncrewed aerial vehicle K. Kim et al. 10.1016/j.envint.2025.109396
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15 citations as recorded by crossref.
- Wind observations from hot‐air balloons and the application in an NWP model E. de Bruijn et al. 10.1002/met.2128
- Atmospheric visibility inferred from continuous-wave Doppler wind lidar M. Queißer et al. 10.5194/amt-15-5527-2022
- Tall wind profile validation of ERA5, NORA3, and NEWA datasets using lidar observations E. Cheynet et al. 10.5194/wes-10-733-2025
- Measurement report: Evaluation of the TOF-ACSM-CV for PM1.0 and PM2.5 measurements during the RITA-2021 field campaign X. Liu et al. 10.5194/acp-24-3405-2024
- Analysis of the measurement uncertainty for a 3D wind lidar W. Knöller et al. 10.5194/amt-17-6913-2024
- Underestimation of strong wind speeds offshore in ERA5: evidence, discussion and correction R. Gandoin & J. Garza 10.5194/wes-9-1727-2024
- Ten-Year Analysis of Mediterranean Coastal Wind Profiles Using Remote Sensing and In Situ Measurements C. Calidonna et al. 10.3390/wind5020009
- Mesoscale modelling of North Sea wind resources with COSMO-CLM: model evaluation and impact assessment of future wind farm characteristics on cluster-scale wake losses R. Borgers et al. 10.5194/wes-9-697-2024
- Profiling the Planetary Boundary Layer Wind with a StreamLine XR Doppler LiDAR: Comparison to In-Situ Observations and WRF Model Simulations T. Tzadok et al. 10.3390/rs14174264
- A Unified Formulation for the Computation of the Six-Degrees-of-Freedom-Motion-Induced Errors in Floating Doppler Wind LiDARs A. Salcedo-Bosch et al. 10.3390/rs15061478
- Research on Wind Field Characteristics Measured by Lidar in a U-Shaped Valley at a Bridge Site J. Wang et al. 10.3390/app11209645
- Advancing Data Quality Assurance with Machine Learning: A Case Study on Wind Vane Stalling Detection V. de Feiter et al. 10.3390/atmos16020129
- Atmospheric Boundary Layer Wind Profile Estimation Using Neural Networks, Mesoscale Models, and LiDAR Measurements A. García-Gutiérrez et al. 10.3390/s23073715
- Wind resource assessment uncertainty for a TLP-based met mast D. Foussekis & F. Mouzakis 10.1088/1742-6596/2018/1/012018
- Quantification of greenhouse gas emissions from a municipal solid waste incinerator using an uncrewed aerial vehicle K. Kim et al. 10.1016/j.envint.2025.109396
1 citations as recorded by crossref.
Latest update: 08 May 2025
Short summary
Doppler wind lidars are laser-based remote sensing instruments that measure the wind up to a few hundred metres or even a few kilometres. Their data can improve weather models and help forecasters. To investigate their accuracy and required meteorological conditions, we have carried out a 2-year measurement campaign of a wind lidar at our Cabauw test site and made a comparison with cup anemometers and wind vanes at several levels in a 213 m tall meteorological mast.
Doppler wind lidars are laser-based remote sensing instruments that measure the wind up to a few...