FN Archimer Export Format
PT J
TI Offshore wind climatology based on synergetic use of Envisat ASAR, ASCAT and QuikSCAT
BT 
AF HASAGER, Charlotte B.
   MOUCHE, Alexis
   BADGER, Merete
   BINGOL, Ferhat
   KARAGALI, Ioanna
   DRIESENAAR, Tilly
   STOFFELEN, Ad
   PENA, Alfredo
   LONGEPE, Nicolas
AS 1:1;2:2;3:1;4:1;5:1;6:3;7:3;8:1;9:4;
FF 1:;2:PDG-ODE-LOS;3:;4:;5:;6:;7:;8:;9:;
C1 Tech Univ Denmark, DTU Wind Energy, DK-4000 Roskilde, Denmark.
   IFREMER, F-29280 Plouzane, France.
   KNMI, NL-3730 AE De Bilt, Netherlands.
   CLS, F-29280 Plouzane, France.
C2 UNIV TECH DENMARK (DTU ENERGY), DENMARK
   IFREMER, FRANCE
   ROYAL NETHERLANDS METEOROL INST, NETHERLANDS
   CLS, FRANCE
SI BREST
SE PDG-ODE-LOS
UM LOPS
IN WOS Ifremer jusqu'en 2018
   copubli-france
   copubli-europe
IF 5.881
TC 73
UR https://archimer.ifremer.fr/doc/00239/35007/33542.pdf
LA English
DT Article
DE ;Offshore wind;SAR;QuikSCAT;ASCAT;Wind energy;Resource;Northern Europe
AB The offshore wind climatology in the Northern European seas is analysed from ten years of Envisat synthetic aperture radar (SAR) images using a total of 9256 scenes, ten years of QuikSCAT and two years of ASCAT gridded ocean surface vector wind products and high-quality wind observations from four meteorological masts in the North Sea. The traditional method for assessment of the wind resource for wind energy application is through analysis of wind speed and wind direction observed during one or more years at a meteorological mast equipped with well-calibrated anemometers at several levels. The cost of such measurements is very high and therefore they are only sparsely available. An alternative method is the application of satellite remote sensing. Comparison of wind resource statistics from satellite products is presented and discussed including the uncertainty on the wind resource. The diurnal wind variability is found to be negligible at some location but up to 0.5 m s− 1 at two sites. Synergetic use of observations from multiple satellites in different orbits provides wind observations at six times in the diurnal cycle and increases the number of observations. At Horns Rev M2, FINO1 and Greater Gabbard satellite and in situ collocated samples show differences in mean wind speed of − 2%, − 1% and 3%, respectively. At Egmond aan Zee the difference is 10%. It is most likely due to scatterometer data sampled further offshore than at the meteorological mast. Comparing energy density with all samples at Horns Rev M2 shows overestimation 7–19% and at FINO1 underestimation 2–5% but no clear conclusion can be drawn as the comparison data are not collocated. At eight new offshore wind farm areas in Denmark, the variability in mean energy density observed by SAR ranges from 347 W m− 2 in Sejerøbugten to 514 W m− 2 at Horns Rev 3. The spatial variability in the near-shore areas is much higher than at areas located further offshore.
PY 2015
PD JAN
SO Remote Sensing Of Environment
SN 0034-4257
PU Elsevier Science Inc
VL 156
UT 000347579900021
BP 247
EP 263
DI 10.1016/j.rse.2014.09.030
ID 35007
ER

EF