The Wind Profile in the Coastal Boundary Layer: Wind Lidar Measurements and Numerical Modelling

Floors, Rogier; Vincent, Claire Louise; Gryning, Sven‐Erik; Peña, Alfredo; Batchvarova, Ekaterina

doi:10.1007/s10546-012-9791-9

Cited by 64 publications

(65 citation statements)

References 39 publications

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“…Different PBL schemes were examined to determine which parametrization performs best for windenergy forecasting. The results showed that the performance of the simulations was highly dependent on stability; simulations tended to show vertical wind shear less than that observed in agreement with Floors et al (2013). Similar evaluations using Høvsøre measurements were performed in Hahmann et al (2012).…”

Section: Numerical Weather Predictionmentioning

confidence: 64%

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Ten Years of Boundary-Layer and Wind-Power Meteorology at Høvsøre, Denmark

Peña

Floors

Sathe

et al. 2015

Boundary-Layer Meteorol

100

103

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Operational since 2004, the National Centre for Wind Turbines at Høvsøre, Denmark has become a reference research site for wind-power meteorology. In this study, we review the site, its instrumentation, observations, and main research programs. The programs comprise activities on, inter alia, remote sensing, where measurements from lidars have been compared extensively with those from traditional instrumentation on masts. In addition, with regard to wind-power meteorology, wind-resource methodologies for wind climate extrapolation have been evaluated and improved. Further, special attention has been given to research on boundary-layer flow, where parametrizations of the length scale and wind profile have been developed and evaluated. Atmospheric turbulence studies are continuously conducted at Høvsøre, where spectral tensor models have been evaluated and extended to account for atmospheric stability, and experiments using microscale and mesoscale numerical modelling.

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Section: Numerical Weather Predictionmentioning

confidence: 64%

“…The climatology of LLJs at Høvsøre was studied using combined lidar/mast wind profiles, applying the same criteria as Baas et al (2009) and Floors et al (2013). LLJs occur frequently for southeasterly and northerly flows.…”

Section: Low-level Jet (Llj)mentioning

confidence: 99%

Ten Years of Boundary-Layer and Wind-Power Meteorology at Høvsøre, Denmark

Peña

Floors

Sathe

et al. 2015

Boundary-Layer Meteorol

100

103

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“…There are a multitude of applied models for the growth of the internal boundary layer (Melas and Kambezidis 1992;Gryning and Batchvarova 1990). For applied use, we here suggest the model of Troen and Petersen (1989) because it is easy to apply but, as pointed out by Floors et al (2013), overestimates the height of the momentum internal boundary layer. Floors et al (2011) found the height of the velocity internal boundary layer to be about one-third of the height of the internal boundary layer when estimated from the model in Troen and Petersen (1989), and half of the height for other models.…”

Section: Reversal-height Analysismentioning

confidence: 95%

“…Frehlich (1996) argued that if the CNR falls below a prescribed threshold (he recommended CNR > -22 dB), the uncertainty in the wind speed is too large for the measurements to be useful. Floors (2013) and Peña et al (2013) found good agreement between wind lidar and cup-anemometer measurements at 100 m for wind-lidar data filtered with CNR > -22 dB and deteriorated agreement for decreasing CNR thresholds.…”

Section: Introductionmentioning

confidence: 92%

“…The Doppler wind-lidar technique is under rapid development, with measurements currently reaching several km in altitude under favourable conditions (O'Connor et al 2010;Floors et al 2013;Peña et al 2013). However, the quality and height range of the wind observations depend on the strength of the backscattered signal compared to the noise signal, the so-called carrier-to-noise ratio (CNR).…”

Section: Introductionmentioning

confidence: 99%

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Weibull Wind-Speed Distribution Parameters Derived from a Combination of Wind-Lidar and Tall-Mast Measurements Over Land, Coastal and Marine Sites

Gryning

Floors

Peña

et al. 2015

Boundary-Layer Meteorol

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Wind-speed observations from tall towers are used in combination with observations up to 600 m in altitude from a Doppler wind lidar to study the long-term conditions over suburban (Hamburg), rural coastal (Høvsøre) and marine (FINO3) sites. The variability in the wind field among the sites is expressed in terms of mean wind speed and Weibull distribution shape-parameter profiles. The consequences of the carrier-to-noise-ratio (CNR) threshold-value choice on the wind-lidar observations are revealed as follows. When the wind-lidar CNR is lower than a prescribed threshold value, the observations are often filtered out as the uncertainty in the wind-speed measurements increases. For a pulsed heterodyne Doppler lidar, use of the traditional -22 dB CNR threshold value at all measuring levels up to 600 m results in a ≈7 % overestimation in the long-term mean wind speed over land, and a ≈12 % overestimation in coastal and marine environments. In addition, the height of the profile maximum of the shape parameter of the Weibull distribution (so-called reversal height) is found to depend on the applied CNR threshold; it is found to be lower at small CNR threshold values. The reversal height is greater in the suburban (high roughness) than in the rural (low roughness) area. In coastal areas the reversal height is lower than that over land and relates to the internal boundary layer that develops downwind from the coastline. Over the sea the shape parameter increases towards the sea surface. A parametrization of the vertical profile of the shape parameter fits well with observations over land, coastal regions and over the sea. An applied model for the dependence of the reversal height on the surface roughness is in good agreement with the observations over land.

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Evaluating Mesoscale Simulations of the Coastal Flow Using Lidar Measurements

2018

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The atmospheric flow in the coastal zone is investigated using lidar and mast measurements and model simulations. Novel dual‐Doppler scanning lidars were used to investigate the flow over a 7 km transect across the coast, and vertically profiling lidars were used to study the vertical wind profile at offshore and onshore positions. The Weather, Research and Forecasting model is set up in 12 different configurations using 2 planetary boundary layer schemes, 3 horizontal grid spacings and varied sources of land use, and initial and lower boundary conditions. All model simulations describe the observed mean wind profile well at different onshore and offshore locations from the surface up to 500 m. The simulated mean horizontal wind speed gradient across the shoreline is close to that observed, although all simulations show wind speeds that are slightly higher than those observed. Inland at the lowest observed height, the model has the largest deviations compared to the observations. Taylor diagrams show that using ERA‐Interim data as boundary conditions improves the model skill scores. Simulations with 0.5 and 1 km horizontal grid spacing show poorer model performance compared to those with a 2 km spacing, partially because smaller resolved wave lengths degrade standard error metrics. Modeled and observed velocity spectra were compared and showed that simulations with the finest horizontal grid spacing resolved more high‐frequency atmospheric motion.

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The Wind Profile in the Coastal Boundary Layer: Wind Lidar Measurements and Numerical Modelling

Cited by 64 publications

References 39 publications

Ten Years of Boundary-Layer and Wind-Power Meteorology at Høvsøre, Denmark

Ten Years of Boundary-Layer and Wind-Power Meteorology at Høvsøre, Denmark

Weibull Wind-Speed Distribution Parameters Derived from a Combination of Wind-Lidar and Tall-Mast Measurements Over Land, Coastal and Marine Sites

Evaluating Mesoscale Simulations of the Coastal Flow Using Lidar Measurements

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