Bias and Uncertainty of a Lidar Measurement in a Complex Terrain: CanWEA 2011
1
[1] : Yamada, T, (1983), Simulations of nocturnal drainage flows by a q2l turbulence closure model, Journal of Atmospheric Sciences, vol. 40, Issue 1, pp.91-106 [2] :A.N. Ross, S.B. Vosper ; Neutral Turbulent flow over forested hills [3]: Boquet M. et al.: Innovative Solutions for Pulsed Wind LiDAR Accuracy in Complex Terrain, ISARS 2010. Remote sensing systems are more and more used during campaign of measurements for wind resource assessments. Pulsed lidars have a proven accuracy on flat terrains and offshore conditions, while in complex terrain the loss of flow homogeneity can create a sensor bias during the transformation of measured radial wind speed to horizontal wind speed (in some cases up to 10%). In previous studies, it has been shown that Computation Fluid Dynamics (CFD) enables to compute the topographical effects on the wind flow over complex terrain and bring a corrective parameter to the lidar data. The post-correction methodology raises however some questions as the influence of the model calibration on the correction performances. We propose to study the sensitivity of the correction factor to several model parameters, by varying the topographical data like roughness, forest density and atmospheric stability. Indeed, it is studied the correction of bias in lidar data introduced by terrain complexity and the uncertainty added through the application of post-correction methodologies. Abstract Abstract Description of the Case study Description of the Case study Conclusions Conclusions CANWEA 2011, Vancouver By varying the site parameterizations 11 scenarii have been created in order to test the sensitivity of the Lidar module: roughness and canopy height vary from 1.5 to 3 meters, forest density from high to low density, and atmospheric stability from stable to neutral stability. Results are interpreted according to: • Speed-up factor above the lidar (close to cup position) • Inflow angle above the lidar • Difference of inflow angles at the lidar measurement points (4 points distant from a few tens of meters): this value is used for the correction. A low variation of it means a low variation of the corrected data • Mean deviation between corrected data and cup Orographical data – 3D view Horizontal and vertical mesh for 90° wind direction • Acciona, as a collaborative partner and owner of the CFD software and of the lidar, has provided data from a met mast and the lidar measured on a complex terrain site. • Meteodyn has run CFD computations over the site under various calibrations and provided the corrected lidar data to LEOSPHERE. • LEOSPHERE has analyzed the results. The corrected wind speeds are compared to the anemometer’s measurements at the three heights and mean deviations resulting linear orthogonal regressions performed at every height are compared to each other to study their variation against the model calibration. Methodology Methodology Anemometer heights 33.5m 63.9m 66m Lidar heights 40m 60m 70m Bias South-East ~9.5% -8.5% -4.6% Scenarii 1 2 3 4 5 6 7 8 9 10 11 Roughness 0.2 0.2 0.2 0.3 0.3 0.3 0.3 0.3 0.4 0.4 0.4 Forest density H L N N N H L L H L N Atmospheric stability 2 2 2 0 2 2 0 2 2 2 2 Point at the vertical of the Lidar Average Std 70m Speed-up factor (-) 0.97 1.36 1.36 0.97 1.16 1.14 0.99 1.19 1.06 1.16 1.12 1.13 0.137 70m inflow (°) 0.10 0.00 0.20 0.10 0.30 0.40 -0.10 0.10 0.20 0.00 0.30 0.146 0.151 Differences between East & West points of the beams Average std 70m inflow (°) 0.1 0.3 0.2 0.1 0.2 0.1 0.2 0.3 0.1 0.2 0.1 0.17 0.079 Resulting Mean Deviation Average std 70m deviation (%) 0.4 0.8 0.6 0.9 0 -0.4 0.7 0.7 0.3 -0.4 -0.3 0.3 0.496 The information resulting from the CFD calculation and required for the correction is much less sensitive to roughness and atmospheric stability than the speed-up factors and inflow angles. The bias in the measured data can therefore be reduced keeping the uncertainty of the results as low as required for using the resulting data in the assessment of the wind resource. Further studies on various site topographies will be conducted to confirm this result. A 66m met mast equipped with calibrated cup and sonic anemometers according to IEC standards is located on a complex terrain near the sea and a pulsed lidar is installed at about 5 meters from the mast. Elevation difference between the two instruments is less than 1m. 4 months of data from October 2010 to February 2011 are used in the study. The main wind direction South-East is studied. Correlation of 10min horizontal wind speed (blue scatter plot) and calculated lidar to cup mean deviation in percentage (red scatter plot) Bias and Uncertainty of a Lidar Measurement in Complex Terrain Matthieu BOQUET 1 , Céline BEZAULT 2 1 LEOSPHERE ([email protected]), 2 METEODYN ([email protected]) South-East wind direction - height 70m Correlation of bin- averaged horizontal wind speed (blue scatter plot) and calculated lidar to cup mean deviation in percentage (red scatter plot). Results Results Corrected lidar data for scenario 5 South-East wind direction - height 70m References References Bias is here reduced at 70m height from -4.6% to 0.3% in average, with a standard deviation around this mean value of 0.49%, and a resulting deviation ranging from -0.4% to 0.9%. Accuracy of the corrected data is therefore within the cup and mounting uncertainties expected for a traditional wind measurement campaign on a complex site.
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Poster presentation at CanWEA 2011.
Transcript of Bias and Uncertainty of a Lidar Measurement in a Complex Terrain: CanWEA 2011
[1] : Yamada, T, (1983), Simulations of nocturnal drainage flows by a q2l
turbulence closure model, Journal of Atmospheric Sciences, vol. 40,
Issue 1, pp.91-106
[2] :A.N. Ross, S.B. Vosper ; Neutral Turbulent flow over forested hills
[3]: Boquet M. et al.: Innovative Solutions for Pulsed Wind LiDAR Accuracy
in Complex Terrain, ISARS 2010.
Remote sensing systems are more and more used during campaign of measurements for wind resource assessments. Pulsed lidars have a proven accuracy on flat terrains
and offshore conditions, while in complex terrain the loss of flow homogeneity can create a sensor bias during the transformation of measured radial wind speed to horizontal
wind speed (in some cases up to 10%). In previous studies, it has been shown that Computation Fluid Dynamics (CFD) enables to compute the topographical effects on the
wind flow over complex terrain and bring a corrective parameter to the lidar data.
The post-correction methodology raises however some questions as the influence of the model calibration on the correction performances. We propose to study the
sensitivity of the correction factor to several model parameters, by varying the topographical data like roughness, forest density and atmospheric stability.
Indeed, it is studied the correction of bias in lidar data introduced by terrain complexity and the uncertainty added through the application of post-correction
methodologies.
AbstractAbstract
Description of the Case studyDescription of the Case study
ConclusionsConclusions
CANWEA 2011, Vancouver
By varying the site parameterizations 11 scenarii have been created in order to test the sensitivity of the Lidar module: roughness and canopy height vary from 1.5 to 3
meters, forest density from high to low density, and atmospheric stability from stable to neutral stability. Results are interpreted according to:
• Speed-up factor above the lidar (close to cup position)
• Inflow angle above the lidar
• Difference of inflow angles at the lidar measurement points (4 points distant from a few tens of meters): this value is used for the correction. A low variation of it means a low
variation of the corrected data
• Mean deviation between corrected data and cup
Orographical data – 3D view Horizontal and vertical mesh for 90° wind direction
• Acciona, as a collaborative partner and owner of the CFD software and of the lidar, has provided data from a met mast and the lidar measured on a complex terrain site.
• Meteodyn has run CFD computations over the site under various calibrations and provided the corrected lidar data to LEOSPHERE.
• LEOSPHERE has analyzed the results. The corrected wind speeds are compared to the anemometer’s measurements at the three heights and mean deviations resulting
linear orthogonal regressions performed at every height are compared to each other to study their variation against the model calibration.
MethodologyMethodology
Anemometer heights 33.5m 63.9m 66m
Lidar heights 40m 60m 70m
Bias South-East ~9.5% -8.5% -4.6%
Scenarii 1 2 3 4 5 6 7 8 9 10 11
Roughness 0.2 0.2 0.2 0.3 0.3 0.3 0.3 0.3 0.4 0.4 0.4
Forest density H L N N N H L L H L N
Atmospheric stability 2 2 2 0 2 2 0 2 2 2 2
Point at the vertical of the Lidar Average Std
70m Speed-up factor (-) 0.97 1.36 1.36 0.97 1.16 1.14 0.99 1.19 1.06 1.16 1.12 1.13 0.137
70m inflow (°) 0.10 0.00 0.20 0.10 0.30 0.40 -0.10 0.10 0.20 0.00 0.30 0.146 0.151
Differences between East & West points of the beams Average std
70m inflow (°) 0.1 0.3 0.2 0.1 0.2 0.1 0.2 0.3 0.1 0.2 0.1 0.17 0.079
Resulting Mean Deviation Average std
70m deviation (%) 0.4 0.8 0.6 0.9 0 -0.4 0.7 0.7 0.3 -0.4 -0.3 0.3 0.496
The information resulting from the CFD calculation and required for the correction is much less sensitive to
roughness and atmospheric stability than the speed-up factors and inflow angles. The bias in the measured
data can therefore be reduced keeping the uncertainty of the results as low as required for using the resulting
data in the assessment of the wind resource. Further studies on various site topographies will be conducted
to confirm this result.
A 66m met mast equipped with calibrated cup and sonic anemometers according to IEC standards is located on a complex terrain near the sea and a pulsed lidar is installed
at about 5 meters from the mast. Elevation difference between the two instruments is less than 1m. 4 months of data from October 2010 to February 2011 are used in the
study. The main wind direction South-East is studied.
Correlation of 10min
horizontal wind speed
(blue scatter plot) and
calculated lidar to cup
mean deviation in
percentage (red scatter
plot)
Bias and Uncertainty of a Lidar Measurement in
Complex TerrainMatthieu BOQUET1, Céline BEZAULT2
1LEOSPHERE ([email protected]), 2METEODYN ([email protected])
South-East wind direction - height 70m
Correlation of bin-
averaged horizontal
wind speed (blue
scatter plot) and
calculated lidar to cup
mean deviation in
percentage (red scatter
plot).
ResultsResults
Corrected lidar data for
scenario 5South-East wind direction - height 70m
ReferencesReferences
Bias is here reduced at 70m height from -4.6% to 0.3% in average, with a standard deviation around this mean value of 0.49%, and a resulting deviation ranging from -0.4%
to 0.9%. Accuracy of the corrected data is therefore within the cup and mounting uncertainties expected for a traditional wind measurement campaign on a complex site.
