TY - JOUR
T1 - Validation of Sentinel-1 offshore winds and average wind power estimation around Ireland
AU - De Montera, Louis
AU - Remmers, Tiny
AU - O'Connell, Ross
AU - Desmond, Cian
N1 - Publisher Copyright:
© 2020 EDP Sciences. All rights reserved.
PY - 2020/8/17
Y1 - 2020/8/17
N2 - In this paper, surface wind speed and average wind power derived from Sentinel-1 Synthetic Aperture Radar Level 2 Ocean (OCN) product were validated against four weather buoys and three coastal weather stations around Ireland. A total of 1544 match-up points was obtained over a 2-year period running from May 2017 to May 2019. The match-up comparison showed that the satellite data underestimated the wind speed compared to in situ devices, with an average bias of 0.4ms-1, which decreased linearly as a function of average wind speed. Long-term statistics using all the available data, while assuming a Weibull law for the wind speed, were also produced and resulted in a significant reduction of the bias. Additionally, the average wind power was found to be consistent with in situ data, resulting in an error of 10% and 5% for weather buoys and coastal stations, respectively. These results show that the Sentinel-1 Level 2 OCN product can be used to estimate the wind resource distribution, even in coastal areas. Maps of the average and seasonal wind speed and wind power illustrated that the error was spatially dependent, which should be taken into consideration when working with Sentinel-1 Synthetic Aperture Radar data.
AB - In this paper, surface wind speed and average wind power derived from Sentinel-1 Synthetic Aperture Radar Level 2 Ocean (OCN) product were validated against four weather buoys and three coastal weather stations around Ireland. A total of 1544 match-up points was obtained over a 2-year period running from May 2017 to May 2019. The match-up comparison showed that the satellite data underestimated the wind speed compared to in situ devices, with an average bias of 0.4ms-1, which decreased linearly as a function of average wind speed. Long-term statistics using all the available data, while assuming a Weibull law for the wind speed, were also produced and resulted in a significant reduction of the bias. Additionally, the average wind power was found to be consistent with in situ data, resulting in an error of 10% and 5% for weather buoys and coastal stations, respectively. These results show that the Sentinel-1 Level 2 OCN product can be used to estimate the wind resource distribution, even in coastal areas. Maps of the average and seasonal wind speed and wind power illustrated that the error was spatially dependent, which should be taken into consideration when working with Sentinel-1 Synthetic Aperture Radar data.
UR - https://www.scopus.com/pages/publications/85090434692
U2 - 10.5194/wes-5-1023-2020
DO - 10.5194/wes-5-1023-2020
M3 - Article
AN - SCOPUS:85090434692
SN - 2366-7443
VL - 5
SP - 1023
EP - 1036
JO - Wind Energy Science
JF - Wind Energy Science
IS - 3
ER -