Open AccessWind characteristics in the North and Baltic Seas from the QuikSCAT satellite
Author(s) -
Karagali Ioanna,
Peña Alfredo,
Badger Merete,
Hasager Charlotte Bay
Publication year - 2014
Publication title -
wind energy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.743
H-Index - 92
eISSN - 1099-1824
pISSN - 1095-4244
DOI - 10.1002/we.1565
Subject(s) - environmental science , meteorology , offshore wind power , wind speed , satellite , wind power , flagging , weibull distribution , atmospheric instability , climatology , wind direction , numerical weather prediction , geography , geology , statistics , engineering , mathematics , cartography , aerospace engineering , electrical engineering
The QuikSCAT mission provided valuable daily information on global ocean wind speed and direction from July 1999 until November 2009 for various applications including numerical weather prediction, ocean and atmospheric modelling. One new and important application for wind vector satellite data is offshore wind energy, where accurate and frequent measurements are required for siting and operating modern wind farms. The greatest advantage of satellite observations rests in their extended spatial coverage. This paper presents analyses of the 10 year data set from QuikSCAT, for the overview of the wind characteristics observed in the North and Baltic Seas, where most of Europe's offshore wind farms operate and more will be constructed. Significant issues in data availability are identified, directly related to the flagging schemes. In situ observations from three locations in the North Sea are used for comparisons. Mean biases (in situ minus satellite) are close to zero for wind speed and ‐2.7° for wind direction with a standard deviation of 1.2 m s − 1 and 15°, respectively. The impact of using QuikSCAT and in situ measurements extrapolated to 10 m for wind power density estimations is assessed, accounting for possible influences of rain‐contaminated retrievals, the sample size, the atmospheric stability effects and either fitting the Weibull distribution or obtaining the estimates from the time series of wind speed observations.Copyright © 2012 John Wiley & Sons, Ltd.