Badger, Jake

Badger, Merete

Hasager, Charlotte Bay

Nielsen, Morten

Synthetic aperture radar (SAR) measurements from satellites can be used to estimate the spatial wind speed variation offshore in great detail. The radar senses cm-scale roughness at the sea surface which can be translated to wind speed at the height 10 m using an empirical geophysical model function. A system has been setup at Risoe DTU for offshore wind retrievals from ENVISAT radar data. The resulting wind maps have a spatial resolution of ~500 m. If 70 or more overlapping satellite SAR scenes are available for a given area of interest it is possible to estimate the wind resource. A major advantage of satellite-based offshore wind resource assessment is the spatial information gained at high resolution from the satellite imagery. Limitations include the low sampling rate and the fixed acquisition times of satellite data. A new satellite scene is typically available every 3-4 days over a given site of interest and the acquisition takes place in the morning and evening only. At Risoe DTU we have utilized our ever-growing collection of wind maps from ENVISAT to compute wind statistics for the North Sea and the Baltic Sea. The reliability and the spatial coverage of the satellite-based wind climatology have improved gradually as more data were collected. The satellite scenes have been treated as random samples and weighted equally in our previous analyses. Here we introduce a novel sampling strategy based on the wind class methodology that is normally applied in numerical modeling of wind resources. The method is applied within a wind and solar resource assessment study for the United Arab Emirates funded by MASDAR and coordinated by UNEP. Thirty years of NCEP/NCAR reanalysis data are used to define approximately 100 geostrophic wind classes. These wind classes show climatologically representative large-scale meteorological conditions for the region of interest. The wind classes are used to make the most representative selection of satellite images from the ENVISAT image catalogue. A minimum of one satellite image is chosen per wind class. The frequency of occurrence of each wind class is used to weight the satellite-derived winds for the calculation of wind climatology. The applied selection and analysis of images should improve the reliability of wind climate estimates compared to random selection of images each given equal weighting

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Downloaded from orbit.dtu.dk on: Dec 17, 2017A Novel Sampling Method for Satellite-Based Offshore Wind Resource EstimationBadger, Merete; Badger, Jake; Hasager, Charlotte Bay; Nielsen, MortenPublication date:2009Document VersionPublisher's PDF, also known as Version of recordLink back to DTU OrbitCitation (APA):Badger, M., Badger, J., Hasager, C. B., & Nielsen, M. (2009). A Novel Sampling Method for Satellite-BasedOffshore Wind Resource Estimation. Poster session presented at European Offshore Wind 2009, Stockholm,Sweden.A NOVEL SAMPLING METHOD FOR SATELLITE BASED     -  OFFSHORE WIND RESOURCE ESTIMATIONPO 130    .Merete Badger Jake Badger Charlotte Hasager Morten Nielsen ,  ,  ,  Wi d E Di i i Ri DTU D kn  nergy v s on, sø , enmarAbstract Sampling method Synthetic aperture radar (SAR) measurements from satellites can be used to Sampling of satellite observations is based on 100 wind classes defined usingestimate the spatial wind speed variation offshore in great detail. The radar senses NCEP/NCAR re-analysis data. Satellite images are weighted according to thecm scale roughness at the sea surface which can be translated to wind speed at freq enc of occ rrence for each ind class- u y u w .the height 10 m using an empirical geophysical model function A system has been.t t Ri DTU th N ti l L b t f S t i bl E i D k fse up a sø , e a ona a ora ory or us a na e nergy n enmar , oroffshore wind retrievals from Envisat radar data.If 70 or more overlapping satellite SAR scenes are available for a given area ofinterest it is possible to estimate the wind resource from the satellite samples A.j d t f t llit b d ff h i d t i thma or a van age o sa e e- ase o s ore w n resource assessmen s espatial information gained at high resolution from the satellite imagery Limitations.include the low sampling rate and the fixed acquisition times of satellite data. A newsatellite scene is typically available every 3 4 days over a given site of interest and-the acquisition takes place in the morning and evening only.At Risø DTU we have utilized our ever growing collection of wind maps from S t llit f i d l S t llit f ll 100 i d l- a e e coverage or one w n  c ass a e e coverage or a   w n  c asses, Envisat to compute wind statistics for the North Sea and the Baltic Sea. The representing a single wind situation amounting to 234 images in totalreliability and the spatial coverage of the satellite based wind climatology have    .      . -improved gradually as more data were collected The satellite scenes have been Wind resources.t t d d l d i ht d ll i i l H rea e as ran om samp es an we g e equa y n our prev ous ana yses. erewe introduce a novel sampling strategy based on the wind class methodology that Wind fields retrieved from satellite imagery are combined for a statistical analysis.is normally applied in numerical modeling of wind resources. The method is appliedwithin a wind and solar resource assessment study for the United Arab Emiratesfunded by Masdar and coordinated by the United Nations Environment Programme(UNEP).Thirty years of NCEP/NCAR re-analysis data are used to define approximately 100geostrophic wind classes These wind classes show climatologically representative.large-scale meteorological conditions for the region of interest The wind classes.d t k th t t ti l ti f t llit i f thare use o ma e e mos represen a ve se ec on o sa e e mages rom eEnvisat image catalogue The frequency of occurrence of each wind class is used.to weight the satellite-derived winds for the calculation of wind climatology. Theapplied selection and analysis method improves the reliability of wind climateestimates compared to random selection of images each given equal weighting.Satellite wind fields  M f th i d d t 10 UAE b d t llit b tiap o e mean w n spee a m over ase on sa e e o serva ons.The spatial resolution is 1 km The contour plot below uses the same color scale. .Eastern UAE and Oman: Ocean winds are strongly affected by the mountainous            terrain Sheltering effects are frequently observed; especially at westerly winds.         . Map of the mean wind speed at 10 m over UAE based on KAMM modeling of thesame wind classes A good agreement is found between satellite and model wind.speeds offshore.ConclusionsDetailed wind resource maps can be produced from satellite SAR observations atan accuracy comparable with mesoscale modeling The use of intelligent sampling. ,th th d li f t llit i l d t i d tra er an ran om samp ng, o sa e e magery ea s o an mprove accuracy aa lower cost as fewer satellite images are needed, .A k l d tc now e gemen sW t f ll k l d M d ’ t f thi k S t llit d t fe gra e u y ac now e ge as ar s suppor or s wor . a e e a a are romthe European Space Agency (ESA) Re-analysis data are provided by the National.C t f E i t l P di ti d th N ti l C t f At h ien res or nv ronmen a re c on an e a ona en er or mosp er cWestern UAE and Qatar: Ocean winds are generally weak due to sheltering fromResearch (NCEP/NCAR)             .the Qatar Peninsula. Prevailing winds are from the north-west.        E Off h Wi d 2009 C f & E hibiti 14 16 S t b St kh l S duropean s ore n on erence x on, – ep em er, oc o m, we en           

A Novel Sampling Method for Satellite-Based Offshore Wind Resource Estimation

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A Novel Sampling Method for Satellite-Based Offshore Wind Resource Estimation

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