Articles | Volume 10, issue 7
https://doi.org/10.5194/amt-10-2595-2017
© 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/amt-10-2595-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
20 Jul 2017
Research article |
| 20 Jul 2017
Improved observations of turbulence dissipation rates from wind profiling radars
Katherine McCaffrey
CORRESPONDING AUTHOR
University of Colorado, Cooperative Institute for Research in Environmental
Sciences at the NOAA Earth System Research Laboratory, Physical Sciences Division, 325 Broadway, Boulder, CO 80305-3337, USA
NOAA Earth System Research Laboratory, Physical Sciences Division, 325 Broadway, Boulder, CO 80305-3337, USA
Laura Bianco
University of Colorado, Cooperative Institute for Research in Environmental
Sciences at the NOAA Earth System Research Laboratory, Physical Sciences Division, 325 Broadway, Boulder, CO 80305-3337, USA
NOAA Earth System Research Laboratory, Physical Sciences Division, 325 Broadway, Boulder, CO 80305-3337, USA
James M. Wilczak
NOAA Earth System Research Laboratory, Physical Sciences Division, 325 Broadway, Boulder, CO 80305-3337, USA
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Cited
25 citations as recorded by crossref.
- Turbulence kinetic energy dissipation rate: assessment of radar models from comparisons between 1.3 GHz wind profiler radar (WPR) and DataHawk UAV measurements H. Luce et al. https://doi.org/10.5194/amt-16-3561-2023
- A Two-Cool-Season Wind Profiler–Based Analysis of Westward-Directed Gap Flow through the Columbia River Gorge P. Neiman et al. https://doi.org/10.1175/MWR-D-19-0026.1
- Elucidating the atmospheric boundary layer turbulence by combining UHF radar wind profiler and radiosonde measurements over urban area of Beijing R. Solanki et al. https://doi.org/10.1016/j.uclim.2022.101151
- Experimental Evaluation of Theoretical Formulations for the Correction of Spectral Widths of MST Radar Spectra S. Kumar et al. https://doi.org/10.1109/TGRS.2020.3026059
- Eddy dissipation rates in the dryline boundary layer R. Solanki et al. https://doi.org/10.1007/s10652-023-09954-w
- An Operational Early-Warning Model for Low-Level Turbulence Based on Radar Wind Profiler Observations J. Guo et al. https://doi.org/10.1007/s13351-026-6041-5
- Spatial and temporal variability of turbulence dissipation rate in complex terrain N. Bodini et al. https://doi.org/10.5194/acp-19-4367-2019
- Comparison of Observations and Predictions of Daytime Planetary-Boundary-Layer Heights and Surface Meteorological Variables in the Columbia River Gorge and Basin During the Second Wind Forecast Improvement Project L. Bianco et al. https://doi.org/10.1007/s10546-021-00645-x
- Physics-Constrained Probabilistic Tomography of 0–2 km Eddy Dissipation Rate Fields from Heterogeneous Ground-Based Atmospheric Observations Z. Wang et al. https://doi.org/10.3390/atmos17070693
- Elucidating the boundary layer turbulence dissipation rate using high-resolution measurements from a radar wind profiler network over the Tibetan Plateau D. Meng et al. https://doi.org/10.5194/acp-24-8703-2024
- Stability Dependence of the Turbulent Dissipation Rate in the Convective Atmospheric Boundary Layer Y. Lv et al. https://doi.org/10.1029/2023GL103326
- Turbulence kinetic energy dissipation rates estimated from concurrent UAV and MU radar measurements H. Luce et al. https://doi.org/10.1186/s40623-018-0979-1
- The effect of onshore winds on the atmospheric boundary layer height under clear sky conditions in the coastal region of Southeast China B. Liu et al. https://doi.org/10.1016/j.atmosres.2025.108328
- Characteristics of Eddy Dissipation Rates in Atmosphere Boundary Layer Using Doppler Lidar Y. Chu et al. https://doi.org/10.3390/rs17091652
- Turbulence Dissipation Rate in the Atmospheric Boundary Layer: Observations and WRF Mesoscale Modeling during the XPIA Field Campaign D. Muñoz-Esparza et al. https://doi.org/10.1175/MWR-D-17-0186.1
- Differences in wind farm energy production based on the atmospheric stability dissipation rate: Case study of a 30 MW onshore wind farm D. Kim & B. Kim https://doi.org/10.1016/j.energy.2021.122380
- Intelligent Detection of Turbulence Dissipation Rates From Radar Wind Profiler by Machine Learning Algorithms B. Liu et al. https://doi.org/10.1109/TGRS.2025.3638351
- Estimation of turbulence dissipation rate and its variability from sonic anemometer and wind Doppler lidar during the XPIA field campaign N. Bodini et al. https://doi.org/10.5194/amt-11-4291-2018
- Quantifying the local and remote impacts of sub‐grid physical processes on the Southeast Pacific sea surface fluxes in the Community Atmosphere Model version 5 by a limited‐area parameter perturbation approach S. Liu et al. https://doi.org/10.1002/joc.7308
- The Second Wind Forecast Improvement Project (WFIP2): Observational Field Campaign J. Wilczak et al. https://doi.org/10.1175/BAMS-D-18-0035.1
- Postdeployment Calibration of a Tropical UHF Profiling Radar via Surface- and Satellite-Based Methods L. Hartten et al. https://doi.org/10.1175/JTECH-D-18-0020.1
- Estimation of Eddy Dissipation Rate in a Common Volume of X-Band Dual-Polarization DWR and MST Radar in Different Types of Precipitation R. Enugonda & T. Rao https://doi.org/10.1109/TGRS.2026.3722253
- U.S. East Coast Lidar Measurements Show Offshore Wind Turbines Will Encounter Very Low Atmospheric Turbulence N. Bodini et al. https://doi.org/10.1029/2019GL082636
- Physically Constrained Machine Learning Retrieval of Turbulence Dissipation Rate From Radar Wind Profiler X. Ma et al. https://doi.org/10.1109/TGRS.2026.3735122
- Cloud vertical structure across China from a national Ka-band cloud radar network: thermodynamic, dynamical, and land-surface controls H. Xu et al. https://doi.org/10.5194/acp-26-14303-2026
25 citations as recorded by crossref.
- Turbulence kinetic energy dissipation rate: assessment of radar models from comparisons between 1.3 GHz wind profiler radar (WPR) and DataHawk UAV measurements H. Luce et al. https://doi.org/10.5194/amt-16-3561-2023
- A Two-Cool-Season Wind Profiler–Based Analysis of Westward-Directed Gap Flow through the Columbia River Gorge P. Neiman et al. https://doi.org/10.1175/MWR-D-19-0026.1
- Elucidating the atmospheric boundary layer turbulence by combining UHF radar wind profiler and radiosonde measurements over urban area of Beijing R. Solanki et al. https://doi.org/10.1016/j.uclim.2022.101151
- Experimental Evaluation of Theoretical Formulations for the Correction of Spectral Widths of MST Radar Spectra S. Kumar et al. https://doi.org/10.1109/TGRS.2020.3026059
- Eddy dissipation rates in the dryline boundary layer R. Solanki et al. https://doi.org/10.1007/s10652-023-09954-w
- An Operational Early-Warning Model for Low-Level Turbulence Based on Radar Wind Profiler Observations J. Guo et al. https://doi.org/10.1007/s13351-026-6041-5
- Spatial and temporal variability of turbulence dissipation rate in complex terrain N. Bodini et al. https://doi.org/10.5194/acp-19-4367-2019
- Comparison of Observations and Predictions of Daytime Planetary-Boundary-Layer Heights and Surface Meteorological Variables in the Columbia River Gorge and Basin During the Second Wind Forecast Improvement Project L. Bianco et al. https://doi.org/10.1007/s10546-021-00645-x
- Physics-Constrained Probabilistic Tomography of 0–2 km Eddy Dissipation Rate Fields from Heterogeneous Ground-Based Atmospheric Observations Z. Wang et al. https://doi.org/10.3390/atmos17070693
- Elucidating the boundary layer turbulence dissipation rate using high-resolution measurements from a radar wind profiler network over the Tibetan Plateau D. Meng et al. https://doi.org/10.5194/acp-24-8703-2024
- Stability Dependence of the Turbulent Dissipation Rate in the Convective Atmospheric Boundary Layer Y. Lv et al. https://doi.org/10.1029/2023GL103326
- Turbulence kinetic energy dissipation rates estimated from concurrent UAV and MU radar measurements H. Luce et al. https://doi.org/10.1186/s40623-018-0979-1
- The effect of onshore winds on the atmospheric boundary layer height under clear sky conditions in the coastal region of Southeast China B. Liu et al. https://doi.org/10.1016/j.atmosres.2025.108328
- Characteristics of Eddy Dissipation Rates in Atmosphere Boundary Layer Using Doppler Lidar Y. Chu et al. https://doi.org/10.3390/rs17091652
- Turbulence Dissipation Rate in the Atmospheric Boundary Layer: Observations and WRF Mesoscale Modeling during the XPIA Field Campaign D. Muñoz-Esparza et al. https://doi.org/10.1175/MWR-D-17-0186.1
- Differences in wind farm energy production based on the atmospheric stability dissipation rate: Case study of a 30 MW onshore wind farm D. Kim & B. Kim https://doi.org/10.1016/j.energy.2021.122380
- Intelligent Detection of Turbulence Dissipation Rates From Radar Wind Profiler by Machine Learning Algorithms B. Liu et al. https://doi.org/10.1109/TGRS.2025.3638351
- Estimation of turbulence dissipation rate and its variability from sonic anemometer and wind Doppler lidar during the XPIA field campaign N. Bodini et al. https://doi.org/10.5194/amt-11-4291-2018
- Quantifying the local and remote impacts of sub‐grid physical processes on the Southeast Pacific sea surface fluxes in the Community Atmosphere Model version 5 by a limited‐area parameter perturbation approach S. Liu et al. https://doi.org/10.1002/joc.7308
- The Second Wind Forecast Improvement Project (WFIP2): Observational Field Campaign J. Wilczak et al. https://doi.org/10.1175/BAMS-D-18-0035.1
- Postdeployment Calibration of a Tropical UHF Profiling Radar via Surface- and Satellite-Based Methods L. Hartten et al. https://doi.org/10.1175/JTECH-D-18-0020.1
- Estimation of Eddy Dissipation Rate in a Common Volume of X-Band Dual-Polarization DWR and MST Radar in Different Types of Precipitation R. Enugonda & T. Rao https://doi.org/10.1109/TGRS.2026.3722253
- U.S. East Coast Lidar Measurements Show Offshore Wind Turbines Will Encounter Very Low Atmospheric Turbulence N. Bodini et al. https://doi.org/10.1029/2019GL082636
- Physically Constrained Machine Learning Retrieval of Turbulence Dissipation Rate From Radar Wind Profiler X. Ma et al. https://doi.org/10.1109/TGRS.2026.3735122
- Cloud vertical structure across China from a national Ka-band cloud radar network: thermodynamic, dynamical, and land-surface controls H. Xu et al. https://doi.org/10.5194/acp-26-14303-2026
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In this paper, we use two wind profiling radars, operating along side a highly instrumented 300 m meteorological tower, to observe turbulence dissipation rates in the planetary boundary layer from an optimized performance setup. Analysis of post-processing techniques, including spectral averaging and moments' calculation methods, shows the optimal parameters which result in good agreement, especially after bias corrections, with sonic anemometers on the tall tower.
In this paper, we use two wind profiling radars, operating along side a highly instrumented...
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