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SAR-Based Wind Resource Statistics in the Baltic Sea
- Source :
- Remote Sensing, Vol 3, Iss 1, Pp 117-144 (2011), Remote Sensing; Volume 3; Issue 1; Pages: 117-144, Hasager, C B, Badger, M, Pena Diaz, A, Larsén, X G & Bingöl, F 2011, ' SAR-based Wind Resource Statistics in the Baltic Sea ', Remote Sensing, vol. 3, no. 1, pp. 117-144 . https://doi.org/10.3390/rs3010117
- Publication Year :
- 2011
- Publisher :
- MDPI AG, 2011.
-
Abstract
- Ocean winds in the Baltic Sea are expected to power many wind farms in the coming years. This study examines satellite Synthetic Aperture Radar (SAR) images from Envisat ASAR for mapping wind resources with high spatial resolution. Around 900 collocated pairs of wind speed from SAR wind maps and from 10 meteorological masts, established specifically for wind energy in the study area, are compared. The statistical results comparing in situ wind speed and SAR-based wind speed show a root mean square error of 1.17 m s−1, bias of −0.25 m s−1, standard deviation of 1.88 m s−1 and correlation coefficient of R2 0.783. Wind directions from a global atmospheric model, interpolated in time and space, are used as input to the geophysical model function CMOD-5 for SAR wind retrieval. Wind directions compared to mast observations show a root mean square error of 6.29° with a bias of 7.75°, standard deviation of 20.11° and R2 of 0.950. The scale and shape parameters, A and k, respectively, from the Weibull probability density function are compared at only one available mast and the results deviate ~2% for A but ~16% for k. Maps of A and k, and wind power density based on more than 1000 satellite images show wind power density values to range from 300 to 800 W m−2 for the 14 existing and 42 planned wind farms.
- Subjects :
- Wind power
Meteorology
business.industry
Science
Maximum sustained wind
Vindenergi
Wind direction
Wind speed
Wind wave model
wind resource
Offshore wind power
Wind profile power law
satellite SAR
Wind shear
offshore wind
wind energy
General Earth and Planetary Sciences
Environmental science
Wind Energy
Wind power meteorology
business
Remote sensing
Vindkraftmeteorologi
Subjects
Details
- Language :
- English
- ISSN :
- 20724292
- Volume :
- 3
- Issue :
- 1
- Database :
- OpenAIRE
- Journal :
- Remote Sensing
- Accession number :
- edsair.doi.dedup.....2209ca756015a022f58c9f71b1323618
- Full Text :
- https://doi.org/10.3390/rs3010117