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Remote Sens. 2018, 10(1), 100; doi:10.3390/rs10010100

Assessing Global Ocean Wind Energy Resources Using Multiple Satellite Data

1
Institute of Applied Remote Sensing and Information Technology, Zhejiang University, Hangzhou 310058, China
2
Key Laboratory of Agricultural Remote Sensing and Information Systems, Hangzhou 310058, China
3
State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, State Oceanic Administration, Hangzhou 310012, China
4
Jiangsu Climate Centre, Jiangsu Meteorological Bureau, Nanjing 210009, China
5
Zhejiang Climate Centre, Zhejiang Meteorological Bureau, Hangzhou 310007, China
6
Department of Land Management, Zhejiang University, Hangzhou 310058, China
7
Department of Agro-meteorology and Geo-informatics, Magbosi Land, Water and Environment Research Centre (MLWERC), Sierra Leone Agricultural Research Institute (SLARI), Freetown PMB 1313, Sierra Leone
8
Institute of Remote Sensing and Earth Sciences, Hangzhou Normal University, Hangzhou 311121, China
*
Author to whom correspondence should be addressed.
Received: 29 October 2017 / Revised: 29 December 2017 / Accepted: 9 January 2018 / Published: 12 January 2018
(This article belongs to the Special Issue Remote Sensing of Atmospheric Conditions for Wind Energy Applications)
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Abstract

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. View Full-Text
Keywords: wind energy resources; QuikSCAT; WindSAT; ASCAT; global ocean wind energy resources; QuikSCAT; WindSAT; ASCAT; global ocean
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Guo, Q.; Xu, X.; Zhang, K.; Li, Z.; Huang, W.; Mansaray, L.R.; Liu, W.; Wang, X.; Gao, J.; Huang, J. Assessing Global Ocean Wind Energy Resources Using Multiple Satellite Data. Remote Sens. 2018, 10, 100.

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