Synthetic aperture radar satellite data for offshore wind assessment: A strategic sampling approach

Beaucage, Philippe; Lafrance, Gaétan; Lafrance, J; Choisnard, Julien; Bernier, Monique

doi:10.1016/j.jweia.2010.10.005

Cited by 16 publications

(10 citation statements)

References 25 publications

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“…Offshore wind energy resources are mainly estimated from in situ wind measurements [8], satellite data, numerical simulation results [9], and reanalysis data [10][11][12]. With progress in microwave remote sensing, a great deal of satellite-derived data have been obtained and applied in the study of wind energy resources, including sea surface wind distribution data derived from Synthetic Aperture Radars (SAR) and scatterometers, such as the Earth Resources Satellite ERS-2 SAR (1995-2011) [13,14], Environment Satellite (ENVISAT) Advanced Synthetic Aperture Radar (ASAR) (2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012) [14][15][16][17][18][19], RADARSAT-1 SAR (1995 [20], SeaWinds onboard QuikSCAT (1999QuikSCAT ( -2009 [17,[19][20][21][22][23][24][25][26][27], ASCAT onboard METOP-A (2007-present) [17,18,27,28] and OceanSat-2 scatterometer (OSCAT, 2009-present) [28,29]. Wind fields retrieved from SAR imagery have a high spatial resolution (<100 m).…”

Section: Introductionmentioning

confidence: 99%

“…As diurnal ocean wind variations are apparent, statistics derived from a single satellite are limited both synoptically and spatially and therefore using multiple sources of satellite data are imperative to gain a more comprehensive recording and analysis of ocean wind energy in space and time [14,17]. A growing number of studies are now focusing on wind resources assessment based on multiple satellite data [17][18][19][20]27,28], albeit with the reduction of uncertainties largely ignored.…”

Section: Introductionmentioning

confidence: 99%

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Assessing Global Ocean Wind Energy Resources Using Multiple Satellite Data

Guo

Zhang

et al. 2018

Remote Sensing

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Wind energy, as a vital renewable energy source, also plays a significant role in reducing carbon emissions and mitigating climate change. It is therefore of utmost necessity to evaluate ocean wind energy resources for electricity generation and environmental management. Ocean wind distribution around the globe can be obtained from satellite observations to compensate for limited in situ measurements. However, previous studies have largely ignored uncertainties in ocean wind energy resources assessment with multiple satellite data. It is against this background that the current study compares mean wind speeds (MWS) and wind power densities (WPD) retrieved from scatterometers (QuikSCAT, ASCAT) and radiometers (WindSAT) and their different combinations with National Data Buoy Center (NDBC) buoy measurements at heights of 10 m and 100 m (wind turbine hub height) above sea level. Our results show an improvement in the accuracy of wind resources estimation with the use of multiple satellite observations. This has implications for the acquisition of reliable data on ocean wind energy in support of management policies.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Assessing Global Ocean Wind Energy Resources Using Multiple Satellite Data

Guo

Zhang

et al. 2018

Remote Sensing

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“…Among the available space-borne radar systems (e.g. scatterometers, passive microwave radiometers), SAR satellite imagery provides relatively higher resolution wind atlases [17]. A study focused on Baltic Sea found out SAR data to have higher accuracy with observed WPD of 300-800 W/m 2 [18].…”

Section: Satellite Datamentioning

confidence: 99%

Offshore Wind Energy: Resource Assessment

Nagababu

Harish

2020

The Handbook of Environmental Chemistry

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“…In situ wind measurements used for offshore wind energy resources assessment [4][5][6][7][8][9][10][11][12] are usually limited and sparse, involving coastal stations, buoys, ships, masts, and oil platforms. Due to the development of microwave remote sensing, previous studies revealed that sea surface wind data derived from satellite data have been applied to offshore and ocean wind resources assessment, including sea surface wind data derived from synthetic aperture radars (SAR) [13][14][15][16][17][18][19][20][21][22][23][24], scatterometers [3,19,[23][24][25][26][27][28][29][30][31][32][33][34][35][36][37][38][39][40], and radiometers [39][40][41][42]. The low temporal resolution (3−7 images each month) of SAR leads to less overlapping of samples [24].…”

Section: Introductionmentioning

confidence: 99%

Assessment of China’s Offshore Wind Resources Based on the Integration of Multiple Satellite Data and Meteorological Data

Guo

Huang

Liu³

et al. 2019

Remote Sensing

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Wind resources assessment plays a significant role in site selection for the construction of offshore wind farms. Mean wind speeds (MWS), wind power densities (WPD), and Weibull parameters are the most important variables for wind resources assessment. These variables were estimated with the synergetic use of multiple satellite data (QuikSCAT + WindSAT + ASCAT) and meteorological data from coastal stations using spatial interpolation methods, including inverse distance weighting (IDW), ordinary kriging (OK), and ordinary co-kriging (OCK). The spatial variability of offshore wind energy resources over the China Sea is assessed at heights of 10 m and 100 m (hub height of wind turbine). Then, 8 buoy measurements were used to evaluate the accuracy of the offshore wind resources assessment. Our results show that combining multiple satellite data and coastal meteorological data improves the accuracy of wind resources assessment in the offshore areas and the OCK method show the best performance for accuracy in most cases. The statistical results comparing buoy-derived MWS and interpolated MWS show a root mean square error (RMSE) of 0.17 m/s and correlation coefficient (Corr.) of 0.987 at a height of 10 m. Statistics of the comparison between buoy-derived WPD and interpolated WPD by OCK show a RMSE of 23.38 W/m2 at a height of 10 m. The results show that the highest wind resources are mainly found in the Taiwan Strait and offshore regions in Fujian province.

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Synthetic aperture radar satellite data for offshore wind assessment: A strategic sampling approach

Cited by 16 publications

References 25 publications

Assessing Global Ocean Wind Energy Resources Using Multiple Satellite Data

Assessing Global Ocean Wind Energy Resources Using Multiple Satellite Data

Offshore Wind Energy: Resource Assessment

Assessment of China’s Offshore Wind Resources Based on the Integration of Multiple Satellite Data and Meteorological Data

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