Abstract
Satellite remote sensing of ocean surface winds are presented with focus on wind energy applications. The history on operational and research-based satellite ocean wind map** is briefly described for passive microwave, scatterometer and synthetic aperture radar (SAR). Currently 6 GW installed capacity is found in the European Seas. The European Wind Energy Association, EWEA, expects the cumulative offshore capacity in Europe will reach 150 GW in year 2030. The offshore environment is far less well-known than over land and this increases the challenge of planning, operation and maintenance offshore. Satellite-based ocean surface wind data can fill a gap in our understanding of marine winds, their temporal and spatial variations. The statistics from satellite-based ocean surface wind maps include wind resources, long-term trend analysis and daily variations in winds. Some examples using data from passive microwave radiometer, scatterometer and SAR are presented from the North Sea and Baltic Sea. These seas are home to the majority of offshore wind farms today and many new offshore wind farm projects are in progress here.
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Abbreviations
- ALOS:
-
Advanced Land Observing Satellite
- AMSR:
-
Advanced Microwave Scanning Radiometer
- ASAR:
-
Advanced Synthetic Aperture Radar
- ASCAT:
-
Advanced scatterometer
- ASI:
-
Italian Space Agency
- CFOSat:
-
Chinese French Ocean Satellite
- CLS:
-
Collecte Localisation Satellites
- CNES:
-
Centre National d’Etudes des Spatiales
- CNSA:
-
China National Space Administration
- COSMO-SkyMed:
-
COnstellation of small Satellites for the Mediterranean basin Observation
- CSA:
-
Canadian Space Agency
- DLR:
-
German Aerospace Centre
- DMSP:
-
Defense Meteorological Satellite Program
- DTOC:
-
Design Tools for Offshore wind farm Clusters
- EERA:
-
European Energy Research Alliance
- EOLI-SA:
-
Earth Observation Link-Stand Alone
- ERS:
-
European Remote Sensing satellite
- ESA:
-
European Space Agency
- EUMETSAT:
-
European Organisation for the Exploitation of Meteorological Satellites
- EWEA:
-
European Wind Energy Association
- FINO:
-
Forschungsplattformen in Nord- und Ostsee
- GCOM-W2:
-
Global Change Observation Mission, W: Water cycle
- GMF:
-
Geophysical Model Function
- HH:
-
Horizontal receive, horizontal transmit
- HJ:
-
Huan **g (Environmental Protection and Disaster Monitoring Constellation)
- HY:
-
Chinese Ocean Color Satellite
- ISRO:
-
Indian Space Research Organisation
- JAXA:
-
Japan Aerospace Exploration Agency
- JERS:
-
Japanese Earth Remote Sensing Satellite
- JHU APL:
-
Johns Hopkins University, Applied Physics Laboratory
- JPL:
-
Jet Propulsion Laboratory
- LTAN:
-
Local Time Ascending Node
- MDA:
-
MacDonald Dettwiler and Associates
- NAO:
-
North Atlantic Oscillation
- NASA:
-
National Aeronautics and Space Administration
- NASDA:
-
National Space Agency of Japan
- NESDIS:
-
National Environmental Satellite, Data and Information Service
- NOGAPS:
-
Navy Operational Global Atmospheric Prediction System
- NOAA:
-
National Oceanic and Atmospheric Administration
- NORSEWInD:
-
Northern Seas Wind Index Database
- NSCAT:
-
NASA scatterometer
- NSIDC:
-
National Snow and Ice Data Center
- NSOAS:
-
National Satellite Ocean Application Service (in China)
- PALSAR:
-
Phased Array L-band Synthetic Aperture Radar
- PO.DAAC:
-
Physical Oceanography Distributed Active Archive
- RSS:
-
Remote Sensing Systems
- SAR:
-
Synthetic Aperture Radar
- ScatSat:
-
Scatterometer Satellite
- SMMR:
-
Scanning Multichannel Microwave Radiometer
- SSM/I:
-
Special Sensor Microwave Imager
- SSMIS:
-
Special Sensor Microwave Imager Sounder
- TanDEM:
-
TerraSAR-X add-on for Digital Elevation Measurement
- TerraSAR:
-
Terra Synthetic Aperture Radar
- TMI:
-
TRMM Microwave Imager
- TRMM:
-
Tropical Rainfall Measuring Mission
- TSX-NG:
-
TerraSAR-X Next Generation
- VV:
-
Vertical receive, vertical transmit
- WRF:
-
Weather Research and Forecasting
References
Wentz FJ (1997) A well-calibrated ocean algorithm for SSM/I. J Geophys Res 102(C4):8703–8718
Wentz FJ, Spencer RW (1998) SSM/I rain retrievals within a unified all-weather ocean algorithm. J Atmos Sci 55:1613–1627
NSIDC. http://nsidc.org/data/docs/daac/ssmi_instrument.gd.html
Hasager C, Mouche A, Badger M, Astrup P, Nielsen M (2009) Satellite wind in EU-Norsewind scientific proceedings of European wind energy conference and exhibition, pp 144–147, Marseille (FR) 16–19 Mar 2009
FINO (2002). http://www.bsh.de/en/Marine_data/Observations/Projects/FINO/index.jsp
Charnock H (1955) Wind stress over a water surface. Q J R Meteorol Soc 81:639–640
Troen I, Petersen EL (1989) European wind atlas, Risø National Laboratory ISBN 87-550-1482-8
NASA Quick Scatterometer (2006) QuikSCAT science data product, user’s manual, overview and geophysical data products. Version 3.0, Jet Propulsion Laboratory, California Institute of Technology, D-18053-Rev A, Sep 2006
Liu WT, Tang W (1996) Equivalent neutral wind. National Aeronautics and Space Administration, Jet Propulsion Laboratory (US, and United States), National Aeronautics and Space Administration, Jet Propulsion Laboratory, California Institute of Technology; National Aeronautics and Space Administration; National Technical Information Service, distributor
Ebuchi N, Graber HC, Caruso MJ (2002) Evaluation of wind vectors observed by QuikSCAT/SeaWinds using ocean buoy data. J Atmos Oceanic Technol 19:2049–2062
Bourassa MA, Legler DM, O’Brien JJ, Smith SR (2003) SeaWinds validation with research vessels. J Geophys Res 108(C2):3019. doi:10.1029/2001JC001028
Tang W, Liu WT, Stiles BW (2004) Evaluation of high-resolution ocean surface vector winds measured by QuikSCAT scatterometer in coastal regions. IEEE Transactions on Geoscience and Remote Sensing, f42, pp 1762–1769
Boutin J, Quilfen Y, Merlivat L, Piolle JF (2009) Global average of air-sea CO2 transfer velocity from QuikSCAT scatterometer wind speeds. J Geophys Res-Oceans 114:C04007
Pickett MH, Tang W, Rosenfeld LK, Wash CH (2003) QuikSCAT satellite comparisons with near-shore buoy wind data off the U.S. West Coast. J Atmos Oceanic Technol 20:1869–1879
Gille ST, Llewellyn Smith SG, Statom NM (2005) Global observations of the land breeze. Geophys Res Lett 32:1–4
Liu WT (2002) Progress in scatterometer application. J Oceanography 58(1)
Chelton DB, Freilich MH, Sienkiewicz JM, Von Ahn JM (2006) On the use of QuikSCAT scatterometer measurements of surface winds for marine weather prediction. Mon Wea Rev 134:2055–2071
Chelton DB, Freilich MH (2005) Scatterometer-based assessment of 10-m wind analyses from the operational ECMWF and NCEP numerical weather prediction models. Mon Wea Rev 133:409–429
Hoffman RN, Leidner SM (2005) An introduction to the near-real-time QuikSCAT data. Weather Forecast 20:476–493
Karagali I, Badger M, Hahmann A, Peña A, Hasager C, Sempreviva AM (2013) Spatical and temporal variability in winds in the Northern European Seas. Renew Energy 57: 200–210
Valenzuela GR (1978) Theories for the interaction of electromagnetic and ocean waves—A review. Bound-Layer Meteorol 13:61–85
Isoguchi O, Shimada M (2009) An L-band ocean geophysical model function derived from PALSAR. IEEE Trans Geosci Remote Sens 47:1925–1936. doi:10.1109/TGRS.2008.2010864
Thompson DR, Monaldo FM, Horstmann J, Christiansen MB (2008) Geophysical model functions for the retrieval of ocean surface winds. 2nd International Workshop on Advance in SAR Oceanography from ENVISAT and ERS Missions, The European Space Agency, Rome, Italy 21–25 Jan 2008
Stoffelen A, Anderson DLT (1993) Wind retrieval and ERS-1 scatterometer radar backscatter measurements. Adv Space Res 13:53–60
Gerling TW (1986) Structure of the surface wind field from the SEASAT SAR. J Geophys Res 91:2308–2320
Fichaux N, Ranchin T (2002) Combined extraction of high spatial resolution wind speed and direction from SAR images: a new approach using wavelet transform. Can J Remote Sens 28:510–516
Du Y, Vachon PW, Wolfe J (2002) Wind direction estimation from SAR images of the ocean using wavelet analysis. Can J Remote Sens 28:498–509
Koch W (2004) Directional analysis of SAR images aiming at wind direction. IEEE Trans Geosci Remote Sens 42:702–710
Horstmann J, Koch W, Lehner S (2004) Ocean wind fields retrieved from the advanced synthetic aperture radar aboard ENVISAT. Ocean Dyn 54:570–576
Quilfen Y, Chapron B, Elfouhaily T, Katsaros K, Tournadre J (1998) Observation of tropical cyclones by high-resolution scatterometry. J Geophys Res 103:7767–7786
Stoffelen A, Anderson DLT (1997) Scatterometer data interpretation: estimation and validation of the transfer function CMOD4. J Geophys Res 102:5767–5780
Hersbach H, Stoffelen A, de Haan S (2007) An improved C-band scatterometer ocean geophysical model function: CMOD5. J Geophys Res-Oceans, 112
Elfouhaily TM (1996) Modéle couple vent/vagues et son application à la télédétection par micro-onde de la surface de la mer. University of Paris 7
Thompson D, Elfouhaily T, Chapron B (1998) Polarization ratio for microwave backscattering from the ocean surface at low to moderate incidence angles, pp 1671–1676
Vachon PW, Dobson EW (2000) Wind retrieval from RADARSAT SAR images: selection of a suitable C-band HH polarization wind retrieval model. Can J Remote Sens 26:306–313
Mouche AA, Hauser D, Daloze JF, Guerin C (2005) Dual-polarization measurements at C-band over the ocean: Results from airborne radar observations and comparison with ENVISAT ASAR data. IEEE Trans Geosci Remote Sens 43:753–769
Hasager CB, Dellwik E, Nielsen M, Furevik B (2004) Validation of ERS-2 SAR offshore wind-speed maps in the North Sea. Int J Remote Sens 25:3817–3841
Christiansen MB, Koch W, Horstmann J, Hasager CB, Nielsen M (2006) Wind resource assessment from C-band SAR. Remote Sens Environ 105:68–81
Hasager CB, Badger M, Peña A, Larsén XG (2010) SAR-based wind resource statistics in the Baltic Sea. Remote Sens 3(1): 117–144. doi:10.3390/rs3010117
Monaldo FM, Thompson DR, Beal RC, Pichel WG, Clemente-Colón P (2001) Comparison of SAR-derived wind speed with model predictions and ocean buoy measurements. IEEE Trans Geosci Remote Sens 39:2587–2600
Fetterer F, Gineris D, Wackerman CC (1998) Validating a scatterometer wind algorithm for ERS-1 SAR. IEEE Trans Geosci Remote Sens 36:479–492
Monaldo FM, Thompson DR, Pichel WG, Clemente-Colon P (2004) A systematic comparison of QuikSCAT and SAR ocean surface wind speeds. IEEE Trans Geosci Remote Sens 42:283–291
Horstmann J, Schiller H, Schulz-Stellenfleth J, Lehner S (2003) Global wind speed retrieval from SAR. IEEE Trans Geosci Remote Sens 41:2277–2286
Furevik B, Johannessen O, Sandvik AD (2002) SAR-retrieved wind in polar regions—comparison with in situ data and atmospheric model output. IEEE Trans Geosci Remote Sens 40:1720–1732
Young G, Winstead N (2005) Meteorological phenomena in high resolution SAR wind imagery. High resolution wind monitoring with wide swath SAR: A user’s guide. In: Beal B, Young G, Monaldo F, Thompson D, Winstead N, Scott C (eds) U.S. Department of Commerce, National Oceanic and Atmospheric Administration, pp 13–34
Alpers W, Ivanov A, Horstmann J (2009) Observations of Bora events over the Adriatic Sea and Black Sea by Spaceborne Synthetic Aperture Radar. Mon Weather Rev 137:1150–1161. doi:10.1175/2008MWR2563.1
Barthelmie RJ, Badger J, Pryor SC, Hasager CB, Christiansen MB, Jorgensen BH (2007) Offshore coastal wind speed gradients: issues for the design and development of large offshore windfarms. Wind Eng 31:369–382
Larsén XG, Larsen S, Badger M (2010) A case study of mesoscale spectra of wind and temperature, observed and simulated. Q J R Meteorol Soc 137(654): 264−274
Christiansen MB, Hasager CB (2005) Wake effects of large offshore wind farms identified from satellite SAR. Remote Sens Environ 98:251–268
Christiansen MB, Hasager CB (2006) Using airborne and satellite SAR for wake map** offshore. Wind Energy 9:437–455
Barthelmie RJ, Pryor SC (2003) Can satellite sampling of offshore wind speeds realistically represent wind speed distributions. J Appl Meteorol 42:83–94
Badger M, Badger J, Nielsen M, Hasager CB, Peña A (2010) Wind class sampling of satellite SAR imagery for offshore wind resource map**. J Appl Meteorol Climatology. doi:10.1175/2010JAMC2523.1
Hasager C, Peña A, Christiansen M, Astrup P, Nielsen M, Monaldo F, Thompson D, Nielsen P (2008) Remote sensing observation used in offshore wind energy. IEEE J Sel Topics Appl Earth Observations Remote Sens 1(1):67–79
Beal B, Young G, Monaldo F, Thompson D, Winstead N, Scott C (eds) (2005) High resolution wind monitoring with wide swath SAR: A user’s guide. U.S. Department of Commerce, National Oceanic and Atmospheric Administration
Peña A, Hasager C, Gryning S-E (2008) Measurements and modelling the wind speed profile in the marine atmospheric boundary layer. Bound-Layer Meteorol 129:479–495
Acknowledgments
We acknowledge the satellite remote sensing data available for analysis. This includes QuikSCAT and SSM/I. QuikSCAT data are produced by Remote Sensing Systems and sponsored by the NASA Ocean Vector Winds Science Team. Data are available at www.remss.com. SSM/I are produced by Remote Sensing Systems and sponsored by the NASA Earth Science MEaSUREs DISCOVER Project. Data are available at www.remss.com. We acknowledge satellite data provided by the European Space Agency, the EO-3644 ERS and Envisat and EO-6773 ERS, Envisat, ALOS PALSAR and RADARSAT grants. The Johns Hopkins University, Applied Physics Laboratory is thanked for use and support of the APL/NOAA SAR Wind Retrieval System. We acknowledge the meteorological data from FINO-1 the Forschungsprojekt FINO [Forschungsplattformen in Nord- und Ostsee (North and Baltic Sea)]. We acknowledge support from the EU-NORSEWInD project www.norsewind.eu TREN-FP7EN-219048, in years 2008–2012 and EERA-DTOC www.eera-dtoc.eu FP7-ENERGY-2011-1/n°282797 in years 2012–2015.
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Hasager, C.B., Badger, M., Astrup, P., Karagali, I. (2013). Satellite Remote Sensing in Offshore Wind Energy. In: Pardalos, P., Rebennack, S., Pereira, M., Iliadis, N., Pappu, V. (eds) Handbook of Wind Power Systems. Energy Systems. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41080-2_21
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