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Bringing satellite winds to hub-height
Badger, Merete; Pena Diaz, Alfredo; Bredesen, Rolv Erlend; Berge, Erik; Hahmann, Andrea N.; Badger,
Jake; Karagali, Ioanna; Hasager, Charlotte Bay; Mikkelsen, Torben Krogh
Published in:
Proceedings of EWEA 2012 - European Wind Energy Conference & Exhibition
Publication date:
2012
Document Version
Publisher final version (usually the publisher pdf)
Link to publication
Citation (APA):
Badger, M., Pena Diaz, A., Bredesen, R. E., Berge, E., Hahmann, A. N., Badger, J., ... Mikkelsen, T. (2012).
Bringing satellite winds to hub-height. In Proceedings of EWEA 2012 - European Wind Energy Conference &
Exhibition. European Wind Energy Association (EWEA).
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Bringing satellite winds to hub-height
Merete Badger, DTU Wind Energy, Denmark
Rolv Erlend Bredesen, Erik Berge
Kjeller Vindteknikk, Norway
Alfredo Peña, Andrea Hahmann, Jake Badger,
Ioanna Karagali, Charlotte Hasager, Torben Mikkelsen
DTU Wind Energy, Denmark
Ocean wind fields from satellites
Scatterometer
Synthetic Aperture
Radar (SAR)
Wind speed and direction
Wind speed
Spatial resolution
0.25°lat/lon
500 m
Spatial coverage
Global
Selected areas
Up to 70 km from coastline
None
Temporal resolution
Twice daily
Variable
– less than one per day
Temporal coverage
Systematically since 1991
ScanSAR since 1995
Current sensors
ASCAT, OSCAT,
HY2A, MetOp-B
Envisat ASAR,
Radarsat-1/2
Rain sensitivity
High – rain flags provided
Low
Retrieved parameters
Coastal mask
2
DTU Wind Energy, Technical University of Denmark
5/9/2012
Level of detail for scatterometer and SAR winds
3
QuikScat mean wind speed
DTU Wind Energy, Technical University of Denmark
Envisat ASAR mean wind5/9/2012
speed
From radar backscatter to wind
A geophysical model function is applied
to retrieve 10-meter ocean winds from
radar backscatter.
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DTU Wind Energy, Technical University of Denmark
5/9/2012
Application 1:
Wind resource mapping from SAR wind fields
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DTU Wind Energy, Technical University of Denmark
5/9/2012
Application 2:
Wind farm wake analyses and wake model validation
Wind speed from ERS-2 SAR,
February 25, 2003
From: Christiansen, M. B. & Hasager, C. B. 2005, Wake effects of large offshore wind farms identified
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DTU Wind Energy, Technical University of Denmark
5/9/2012
from
satellite
SAR. Remote Sensing of Environment, 98, 251-268
Application 3:
Characterizing mesoscale wind phenomena
- and validation of mesoscale models
Strait of Gibraltar
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DTU Wind Energy, Technical University of Denmark
The Azores
5/9/2012
Challenges for the application of SAR wind fields in
offshore wind energy
Challenge 1:
Dealing with a limited number of samples
See: Badger et al. 2010, Wind class sampling of satellite SAR
imagery for offshore wind resource mapping. J. Appl. Meteor.
Climat., 49, 2474-2491.
Challenge 2:
Bringing satellite winds from the 10-m vertical level
to the hub-height of modern wind turbines
- the topic of this presentation
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DTU Wind Energy, Technical University of Denmark
5/9/2012
Recent advances
- which make the lifting of SAR wind fields possible
• A validated description of vertical wind profiles at high levels is available
(Peña, A. et al. 2008, Measurements and Modelling of the Wind Speed Profile in the Marine
Atmospheric Boundary Layer, Bound.-Layer Meteor., 129, pp. 479-495)
• Wind retrieval algorithms can produce Equivalent Neutral Winds (ENW)
(Hersbach, H. 2010, Comparison of C-band Scatterometer CMOD5.N Equivalent
Neutral Winds with ECMWF, J. Atmos. Oceanic Technol., 27, pp. 721-736)
• Satellite SAR imagery is available in larger quantities
(500-1,000 overlapping scenes over sites in the European Seas)
• Mesoscale modeling has been performed for significant areas and time periods
• Offshore measurements are available for validation (masts and LiDAR)
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DTU Wind Energy, Technical University of Denmark
5/9/2012
Bringing satellite winds to hub-height (100 m)
• Friction velocity, u* from the satellite ENW:
u 10 SAR
u
 10 
= ∗ SAR ln 
κ  z0 
,
u∗2SAR
z0 = α c
g
• Obukhov length, L
- using WRF parameters T2 and HFX:
LWRF / SAR
10
− u∗3SAR T2WRF
=
g κ HFX WRF
DTU Wind Energy, Technical University of Denmark
LWRF/SAR > 0: stable
LWRF/SAR ≤ 0: unstable
5/9/2012
Bringing satellite winds to hub-height (100 m)
• Stability function, ψ(z/L):
LWRF/SAR > 0 :
ψ
(
z
LWRF / SAR
LWRF/SAR ≤ 0 : ψ 
z

L
 WRF / SAR



)
= − 4.7
z
LWRF / SAR
1/ 3
3  1+ x + x2 
 2x +1  π


z
 − 3 arctan
= ln
+

, x = 1 − 12
2 
3
3
3
L



WRF / SAR 

• Wind speed at 100 m, u100
- using WRF parameters T2, HFX, PBLH:
LWRF/SAR > 0 :
u 100 SAR
u∗ SAR  100
100 


ln
=
−ψ  100  1 −



κ  z0
2 PBLH 
L
 
 WRF / SAR 




LWRF/SAR ≤ 0 : u 100 SAR = u∗ SAR ln 100 −ψ

 100 

 
κ  z0
 LWRF / SAR  

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DTU Wind Energy, Technical University of Denmark
5/9/2012
100-m winds at Fino-1
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DTU Wind Energy, Technical University of Denmark
5/9/2012
100-m Weibull fit at Fino-1
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DTU Wind Energy, Technical University of Denmark
5/9/2012
Spatial wind variability over the North Sea
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DTU Wind Energy, Technical University of Denmark
5/9/2012
Sampling effects over the North Sea
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DTU Wind Energy, Technical University of Denmark
5/9/2012
Special situation: Low boundary-layer height
• The applied wind profile equations
are valid within the atmospheric
boundary-layer
• Data are discarded when the
boundary-layer height is <50 m
• Up to 4% of the WRF samples are
discarded over the North Sea over
a year
• None of the 80 SAR scenes, and
concurrent WRF samples, are
discarded
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DTU Wind Energy, Technical University of Denmark
5/9/2012
Conclusions
• Satellite SAR data lifted to 100 m under-estimate the wind speed at Fino-1
• Concurrent WRF simulations also under-estimate the 100-m wind speed at
Fino-1
• SAR-WRF agreement is generally good over the North Sea with the largest
differences near the coast of Germany
• The number of SAR samples (80) is insufficient to describe the mean wind
climate accurately
• Work is in progress to improve the accuracy of lifted satellite wind fields
• Satellite observations represent a valuable source of information for
offshore wind energy applications (e.g. wind resource mapping, wind farm
wake analyses)
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DTU Wind Energy, Technical University of Denmark
5/9/2012
Acknowledgements
Satellite data:
The European Space Agency (ESA)
Remote Sensing Systems (RSS)
SAR wind field retrieval:
Collecte Localisation Satellites (CLS)
The Johns Hopkins University, Applied Physics Laboratory (JHU/APL)
Fino-1 and Fino-2 mast data:
Bundesministerium für Umwelt (BMU), Projektträger Juelich (PTJ), Deutsches
Windenergie Institut (DEWI)
Funding:
EU-NORSEWInD (TREN-FP7EN-21908)
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DTU Wind Energy, Technical University of Denmark
5/9/2012