Badger, Jake

Badger, Merete

Bingöl, Ferhat

Foussekis, Dimitri

Hasager, Charlotte Bay

Karagali, Ioanna

Nielsen, Morten

Topouzelis, Konstantinos

Online Research Database In Technology

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Downloaded from orbit.dtu.dk on: Dec 20, 2017Off-shore Wind Atlas of the Central Aegean Sea: A simple comparison of NCEP/NCARRE-analysis data, QuickSCAT and ENVISAT Synthetic Aperture Radar (SAR) by use ofWind Atlas MethodBingöl, Ferhat; Hasager, Charlotte Bay; Karagali, Ioanna; Badger, Jake; Badger, Merete; Foussekis,Dimitri ; Nielsen, Morten; Topouzelis, KonstantinosPublication date:2012Document VersionPublisher's PDF, also known as Version of recordLink back to DTU OrbitCitation (APA):Bingöl, F., Hasager, C. B., Karagali, I., Badger, J., Badger, M., Foussekis, D., ... Topouzelis, K. (2012). Off-shoreWind Atlas of the Central Aegean Sea: A simple comparison of NCEP/NCAR RE-analysis data, QuickSCAT andENVISAT Synthetic Aperture Radar (SAR) by use of Wind Atlas Method. Poster session presented at EWEA2012 - European Wind Energy Conference & Exhibition, Copenhagen, Denmark.[1] Wind class sampling of satellite SAR imagery for offshore wind resource mapping Badger, M.; Badger, J.; Nielsen, M.; Hasager, C.B.; Peña, A.. J. Appl. Meteorol. Climatol. 2010, Vol. 49, p. 2474-2491 [2] SAR-Based Wind Resource Statistics in the Baltic Sea, Hasager, C. B., Badger, M.,  Peña, A., Larsén, X.G.,  Bingöl, F. Remote Sens. 2011, 3, 117-144; doi:10.3390/rs3010117 [3] Ioanna Karagali. Offshore Wind Energy: Wind and Sea Surface Temperature from Satellite Observations. PhD thesis, DTU Wind Energy, 2012. [4] I. Troen and E.L. Petersen. European wind atlas. Technical report, Risø A National Laboratory, Roskilde, 1989. Offshore wind energy is progressing rapidly in many parts of the world. Among them, the Aegean Sea is a unique area. Until now, several offshore locations (e.g. North Sea [1], Baltic Sea [2]) have been investigated by means of a new technique based on ENVISAT Synthetic Aperture Radar (SAR) data.  In the current study we try to investigate the positive and the negative sides of SAR results at the Central Aegean Sea and compare with two other parallel developing techniques; NCEP/NCAR re-analysis based Ocean wind Atlas  scatterometer winds QuickSCAT [3].  WAsP software and/or method is used in all steps of the study. Abstract Off shore Wind Atlas of Aegean Sea  A simple comparison of RE-analysis data, QuickSCAT and SAR   Ferhat Bingöl(1) F Charlotte Hasager(1) P Ioanna Karagali(1) Jake Badger(1) Merete Badger(1)  Dimitris Foussekis (2) Morten Nielsen (1) Konstantinos Topouzelis(3)   (1) DTU Wind Energy, Roskilde,  DENMARK (2) CRES, Athens, GREECE (3) University of the Aegean, Mitilene, GREECE PO. ID 144 Method Data Sources Results References                EWEA 2012, Copenhagen, Denmark: Europe’s Premier Wind Energy Event   Our final goal with our data sources was to create wind atlases to generate resource grids for certain areas. The subject in a 'wind atlas' is a systematic and comprehensive collection of regional wind climates (RWC) derived by the wind atlas methodology [4].  Standard wind resource grid calculations are made by using the three different data sets and these datasets are described in the Data Sources section. All applied steps to reach the resource grid are available in the conference proceedings.  NCEP/NCAR : Re-analysis data for the period of 1971 to 2001 is used. The data has approximately 2o resolution and it consists of 6-hourly model results. Therefore each wind atlas is a product of nearly 60000 samples. Wind Atlases at 4 locations in Central Aegean sea are chosen for the selected area.  QuickSCAT: With a daily global coverage of more than 90% of the world's oceans, QuickSCAT provides a valuable dataset with more than 10 years, between 1999 and 2009, of two daily observations at 10m a.s.l. Data are available at a 0.25o grid. After the source data is filtered for rain, the grid points of the selected area include almost 5000 valid wind speed and wind direction measurements during the 10 years of measurement [3].  ENVISAT SAR: The mission is running since 2001, where high resolution wind fields can be measured at 10m height a.s.l. DTU Wind Energy processes several SAR images a day. The Central Aegean dataset currently includes 500 ENVISAT ASAR WMS scenes from March 2010 and March 2012.SAR data has been used in several other places where in-situ measurement comparisons were available. [1,2]. 450k,4100k 750k,4400k NCEP/NCAR QuickSCAT Selected Area NCEP/NCAR derived ocean wind atlas captures only large-scale flow features. Flow features due to meso-scale phenomena are missing. This area provides a test bench for evaluating other wind atlas products derived from alternative reanalysis data set. This will an important element to the evaluation of the global wind atlas project.  QuickSCAT has a higher than NCEP/NCAR and lower than ENVISAT SAR spatial detail. The averaging inherent in the wind retrieval process of QuickSCAT and NCEP/NCAR eliminates the small scale features seen by SAR. Acknowledgements • NCEP/NCAR reanalysis data are provided by the National (USA) Center for Environmental Prediction (NCEP) and the National (USA) Center for Atmospheric Research (NCAR). • QuickScat data are produced by Remote Sensing Systems and sponsored by the NASA Ocean Vector Winds Science Team. Data are available at www.remss.com. One can rapidly calculate the wind resource map of an offshore location including statistical parameters by using the WAsP based tools we have created for different  type of data sources. A shortcoming of this study is the lack of validation with in-situ measurements which would greatly improve the usage of the datasets. It is intended that several on-shore and off-shore calculations are used in further steps of this study. Nevertheless, obtained knowledge can be used to locate possible offshore masts for future campaigns, especially when the SAR results are used. Conclusion NCEP/NCAR QuickSCAT ENVISAT SAR +10% -10% A +15% -15% k +25% -25% E GRS87 Lesvos Chios Evoia 

Off-shore Wind Atlas of the Central Aegean Sea: A simple comparison of NCEP/NCAR RE-analysis data, QuickSCAT and ENVISAT Synthetic Aperture Radar (SAR) by use of Wind Atlas Method

Offshore wind energy is progressing rapidly in many parts of the world including Europe. While our understanding of offshore wind is growing parallel to that, most of the offshore wind development is located in shallow or transitional waters. Deep, open sea was never preferred by developers due to high costs, but with the new developments in floating turbine design, it seems that offshore wind parks in deep waters will also be a possibility in the future. Whether on-shore or offshore, the first step of a site assessment is to estimate the wind resources. Usually well-known conventional methods are used to produce estimates of wind resources by means of at least one year data from a single or multiple points on the terrain. This criterion is dicult to satisfy in offshore locations where measurements are costly and sparse. Therefore other methods are required (e.g satellite imagery or reanalysis model results). Unfortunately all of these methods are still under development and do not provide data acceptable for bankable wind assessment reports. On the other hand, they give good indications of the geographical distribution of the wind resources and that is very useful for decision making and planning of feasibility studies and of actual project preparation. Until now, several offshore wind resources (e.g. North Sea [1], Baltic Sea [2]) have been investigated by means of ENVISAT Synthetic Aperture Radar (SAR) data. In the current study we investigate the positive and the negative aspects of using SAR data at the Central Aegean Sea and compare with two other parallel developing techniques; NCEP/NCAR re-analysis based Ocean wind Atlas and scatterometer winds QuickSCAT 1. WAsP software and/or method is used in all steps of the study

                       General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.  • Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal   If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim.     Downloaded from orbit.dtu.dk on: Dec 20, 2017Off-shore Wind Atlas of the Central Aegean Sea: A simple comparison of NCEP/NCARRE-analysis data, QuickSCAT and ENVISAT Synthetic Aperture Radar (SAR) by use ofWind Atlas MethodBingöl, Ferhat; Hasager, Charlotte Bay; Karagali, Ioanna; Badger, Jake; Badger, Merete; Foussekis,Dimitri ; Nielsen, Morten; Topouzelis, KonstantinosPublished in:Proceedings of EWEA 2012 - European Wind Energy Conference &amp; ExhibitionPublication date:2012Document VersionPublisher's PDF, also known as Version of recordLink back to DTU OrbitCitation (APA):Bingöl, F., Hasager, C. B., Karagali, I., Badger, J., Badger, M., Foussekis, D., ... Topouzelis, K. (2012). Off-shoreWind Atlas of the Central Aegean Sea: A simple comparison of NCEP/NCAR RE-analysis data, QuickSCAT andENVISAT Synthetic Aperture Radar (SAR) by use of Wind Atlas Method. In Proceedings of EWEA 2012 -European Wind Energy Conference & Exhibition (Vol. 3, pp. 1579-1585). European Wind Energy Association(EWEA).Off-shore Wind Atlas of the Central Aegean Sea:A simple comparison of NCEP/NCAR RE-analysisdata, QuickSCAT and ENVISAT Synthetic ApertureRadar (SAR) by use of Wind Atlas MethodFerhat Bingo¨l1†, Charlotte Hassager1, Ioanna Karagali1, Jake Badger1 ,Merete Badger1,Dimitri Foussekis2, Morten Nielsen 1,Konstantinos Topouzelis3,1Denmark Technical University, Wind Energy, Frederiksborgvej 399 4000 Roskilde, Denmark,2CRES - The Centre for Ren. Eng. Sources and Saving, Marathonos Ave, Pikermi Attiki, Greece3University of the Aegean, Department of Marine Sciences, University Hill, 81100 Mitilene, Greece† To whom correspondence should be addressed; E-mail: febi@dtu.dk.April 13, 20121 IntroductionOffshore wind energy is progressing rapidly in many parts of the world including Europe.While our understanding of offshore wind is growing parallel to that, most of the offshorewind development is located in shallow or transitional waters. Deep, open sea was neverpreferred by developers due to high costs, but with the new developments in floatingturbine design, it seems that offshore wind parks in deep waters will also be a possibilityin the future.Whether on-shore or offshore, the first step of a site assessment is to estimate thewind resources. Usually well-known conventional methods are used to produce estimatesof wind resources by means of at least one year data from a single or multiple points onthe terrain. This criterion is difficult to satisfy in offshore locations where measurementsare costly and sparse. Therefore other methods are required (e.g satellite imagery or re-analysis model results). Unfortunately all of these methods are still under developmentand do not provide data acceptable for bankable wind assessment reports. On the otherhand, they give good indications of the geographical distribution of the wind resources1and that is very useful for decision making and planning of feasibility studies and of actualproject preparation.Until now, several offshore wind resources (e.g. North Sea [1], Baltic Sea [2]) havebeen investigated by means of ENVISAT Synthetic Aperture Radar (SAR) data. In thecurrent study we investigate the positive and the negative aspects of using SAR dataat the Central Aegean Sea and compare with two other parallel developing techniques;NCEP/NCAR re-analysis based Ocean wind Atlas and scatterometer winds QuickSCAT1. WAsP software and/or method is used in all steps of the study.2 Available DatasetsThree data sources are used in this study;• NCEP/NCAR: Re-analysis data [3] for the 50-year period 1954 to 2003 are used.The data have approximately 2o resolution, consist of 6-hourly output from theassimilation system. Therefore each wind atlas is a product of nearly 60000 samples.Wind Atlases at 4 locations in the Central Aegean sea were chosen for the selectedarea.• QuikSCAT: With a daily global coverage of more than 90% of the world’s oceans,QuickSCAT provides a valuable dataset with more than 10 years, from 1999 to 2009,of two daily observations at 10m a.s.l. Data are available at a 0.25o grid. After thesource data are filtered for rain, the grid points of the selected area include almost5000 valid wind speed and wind direction measurements during the 10 years or themission lifetime [4].• ENVISAT Synthetic Aperture Radar - SAR: The mission is running since2002, where high resolution wind fields can be retrieved at 10 m height a.s.l. DTUWind Energy processes several SAR images a day. The Central Aegean datasetcurrently includes 500 ENVISAT ASAR WMS scenes from March 2010 to March2012.SAR data has been used in several other places where in-situ measurementcomparisons were available [1, 2].3 Calculation domainWe have chosen to investigate a section of the Central Aegean Sea, based on the followingcriteria:• the least available spatial data: To be able to make a full-comparison we hadto limit the calculation zone according to the least available data set, which isQuickSCAT (Figure 1 - calculation boundary). This calculation domain is also usedfor the other two data sets.• the coast line: Available data in coastal areas depends on the data source, thereforean island free zone in the Central Aegean is chosen and, furthermore, a 5km bufferzone is applied to any land in the selected domain.1QuikScat data are produced by Remote Sensing Systems and sponsored by the NASA Ocean VectorWinds Science Team. Data are available at www.remss.com.2Land5km coastline bufferQuikSCAT data locationsNCEP/NCAR data locationsCalculation boundaryFigure 1: Available data points and calculation boundaries. The map has the borders ofmin(450000,4100000) and max(750000,4400000) (GRS87).3• the seasonal coverage: Data sets are neither from the same period nor havethe same sampling frequency. This is the nature of data sets, but each data setis chopped for evenly distributed seasons and only full-year data sets are used.Therefore, seasonal variations are equally represented.4 MethodOur final goal with our data sources was to create wind atlases to generate resourcegrids for certain areas. The subject in a ’wind atlas’ is a systematic and comprehensivecollection of regional wind climates (RWC) derived by the wind atlas methodology.The wind atlas methodology in general was first developed and described in detail forthe European Wind Atlas at DTU Wind Energy in 1989 [5]. The methodology is the coreof the industry standard software WAsP 2.The following steps are used to apply the Wind Atlas Method on each dataset.1. A hi-definition elevation and roughness map of the the Central Aegean was createdand used in all the steps below. The calculation domain is a sub-region of thecalculation map which is at least 50 km away from each borders.2. Each data set point is converted into a standard WAsP statistical ”Observed WindClimate“ file. Such a file includes frequency and Weibull parameters of each windsector. In our case we used 12 sectors.3. Statistical files are converted into wind atlases. Each wind atlas includes an h x rsize of matrix where h is the number of heights and r is the number of roughnessvalues.4. Each Wind Atlas is applied only to the area where its source data was collected. Forexample, a single NCEP/NCAR derived Wind Atlas (interpolation of four availabledata points) is used for the whole area while for QuickSCAT data, each grid pointis only applied to the data area of has 0.25o x 0.25o. In the case of SAR the pointcalculation was made for each 1km to 1km areas.5. If there are more than one areas available for any of the data set, the final resultsare combined in a single resource grid file (with the grid size 1km x 1km) for eachdataset.6. Due to the fact that the difference in data periods and the uncertainty of windmeasurements are very high, it is not possible to compare spatial sensitivity withthe calculated values. Therefore, each resource grid is normalized with its meanvalue.2Further information about the methodology and the software can be found at www.wasp.dk, includinga long list of references4NCEP/NCAR QuickSCAT ENVISAT SARA [m/s]k [-]E[W/m2]Figure 2: 1km x 1km gridded results calculated withWind Atlas Method. A is the Weibull scale parameter,k is the Weibull shape parameter. E is the power densitycalculated using A and k for standard air density.+10% +15% +25%A¯ k¯ E¯-10% -15% -25%55 ResultsNCEP/NCAR and QuickSCAT data have been analysed over the selected area by meansof the WASP software while SAR data is analysed by means of a WAsP derived DTUWind Energy in-house tool called s-WAsP 3. Run results are combined in Figure 2.The NCEP/NCAR derived ocean wind atlas captures only large-scale flow features.Flow features due to meso-scale phenomena are missing. This area provides a test benchfor evaluating other wind atlas products derived from alternative reanalysis data set. Thiswill an important element to the evaluation of the Global Wind Atlas project 4.QuickSCAT has a higher than NCEP/NCAR and lower than ENVISAT SAR spatialdetail. The averaging inherent in the NCEP/NCAR and in the wind retrieval process ofQuikSCAT eliminates the small scale features seen by SAR.6 ConclusionOne can rapidly calculate the wind resource map of an offshore location including sta-tistical parameters by using the WAsP based tools we have created for different types ofdata sources.A shortcoming of this study is the lack of validation with in-situ measurements whichwould greatly improve the usage of the datasets. It is intended that several on-shore andoff-shore calculations are used in further studies.Nevertheless, the results from this analysis can be used to identify possible locationsfor the installation of offshore masts for future campaigns, especially when the SAR resultsare used.3s-WAsP is a special version of wind atlas methodology for the satellite wind speed measurements.The software is an in-house study and is not commercially available. For more information, contact;Charlotte Hassager [cbha@dtu.dk]4The Global Wind Atlas [EUDP 11-II, Globalt Vind Atlas, 64011-0347] is a Danish contribution tothe Clean Energy Ministerial Multilateral Working Group on Solar and Wind Technologies, Global Solarand Wind Atlas project.6AcknowledgementsNCEP/NCAR reanalysis data are provided by the National (USA) Center for Environ-mental Prediction (NCEP) and the National (USA) Center for Atmospheric Research(NCAR).QuikScat data are produced by Remote Sensing Systems and sponsored by the NASAOcean Vector Winds Science Team. Data are available at www.remss.com.ENVISAT SAR data are provided by the European Space Agency.References[1] M. Badger, J. Badger, M. Nielsen, C.B. Hasager, and A. Pena. Wind class sampling ofsatellite SAR imagery for offshore wind resource mapping. Appl. Meteorol. Climatol.,49:2474–2491, 2010.[2] Charlotte Bay Hasager, Merete Badger, Alfredo Pena Diaz, Xiaoli Guo Larsen, andFerhat Bingol. SAR-based wind resource statistics in the baltic sea. Remote Sensing,3(1):117–144, 2011.[3] Kalnay et al. The ncep/ncar 40-year reanalysis project. Bull. Amer. Meteor. Soc.,77:437–470, 1996.[4] Ioanna Karagali. Offshore Wind Energy: Wind and Sea Surface Temperature fromSatellite Observations. PhD thesis, DTU Wind Energy, 2012.[5] I. Troen and E.L. Petersen. European wind atlas. Technical report, Risø NationalLaboratory, Roskilde, 1989.7

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Off-shore Wind Atlas of the Central Aegean Sea: A simple comparison of NCEP/NCAR RE-analysis data, QuickSCAT and ENVISAT Synthetic Aperture Radar (SAR) by use of Wind Atlas Method

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