Estimation of Global Wind Energy Input to the Surface Waves Based on the Scatterometer
Mechanical energy input into the ocean from the atmosphere is primarily produced via the ocean surface waves. First, the total wind generation surface wave energy is estimated as nearly 80 TW (1 TM = 10(12) W), based on an empirical formulation and the wave age (beta) retrieved from the Earth Remote...
Published in: | IEEE Geoscience and Remote Sensing Letters |
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Language: | English |
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2012
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Online Access: | http://ir.qdio.ac.cn/handle/337002/12145 https://doi.org/10.1109/LGRS.2012.2189194 |
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ftchinacasciocas:oai:ir.qdio.ac.cn:337002/12145 2023-05-15T18:25:27+02:00 Estimation of Global Wind Energy Input to the Surface Waves Based on the Scatterometer Liu, Guoqiang He, Yijun Zhang, Yuanzhi Shen, Hui Liu, GQ (reprint author), Oceans Canada, Bedford Inst Oceanog, Dartmouth, NS B2Y 4A2, Canada. 2012-11-01 http://ir.qdio.ac.cn/handle/337002/12145 https://doi.org/10.1109/LGRS.2012.2189194 英语 eng IEEE GEOSCIENCE AND REMOTE SENSING LETTERS Liu, Guoqiang; He, Yijun; Zhang, Yuanzhi; Shen, Hui.Estimation of Global Wind Energy Input to the Surface Waves Based on the Scatterometer,IEEE GEOSCIENCE AND REMOTE SENSING LETTERS,2012,9(6):1017-1020 http://ir.qdio.ac.cn/handle/337002/12145 doi:10.1109/LGRS.2012.2189194 Scatterometer Sea State Remote Sensing Surface Wave Energy Geochemistry & Geophysics Engineering Electrical & Electronic Remote Sensing Article 期刊论文 2012 ftchinacasciocas https://doi.org/10.1109/LGRS.2012.2189194 2022-06-27T05:34:20Z Mechanical energy input into the ocean from the atmosphere is primarily produced via the ocean surface waves. First, the total wind generation surface wave energy is estimated as nearly 80 TW (1 TM = 10(12) W), based on an empirical formulation and the wave age (beta) retrieved from the Earth Remote Sensing-1/2 satellite scatterometer observations. Second, the distribution of the wind-generated surface wave energy density shows that the main input occurs in the westerlies in the Southern Hemisphere and could reach up to 3.58 W/m(2) with an average value of 0.24 W/m(2) in the global ocean during a seven-day period. Third, we find that the downward energy flux rate from wind to surface waves can reach around 24% in the Southern Ocean and storm tracks in the northwest Pacific and Atlantic Oceans where the wind waves dominate, but a low downward rate of around 7% in tropical oceans with an average of 11% over the global oceans is observed. Article in Journal/Newspaper Southern Ocean Institute of Oceanology, Chinese Academy of Sciences: IOCAS-IR Pacific Southern Ocean IEEE Geoscience and Remote Sensing Letters 9 6 1017 1020 |
institution |
Open Polar |
collection |
Institute of Oceanology, Chinese Academy of Sciences: IOCAS-IR |
op_collection_id |
ftchinacasciocas |
language |
English |
topic |
Scatterometer Sea State Remote Sensing Surface Wave Energy Geochemistry & Geophysics Engineering Electrical & Electronic Remote Sensing |
spellingShingle |
Scatterometer Sea State Remote Sensing Surface Wave Energy Geochemistry & Geophysics Engineering Electrical & Electronic Remote Sensing Liu, Guoqiang He, Yijun Zhang, Yuanzhi Shen, Hui Liu, GQ (reprint author), Oceans Canada, Bedford Inst Oceanog, Dartmouth, NS B2Y 4A2, Canada. Estimation of Global Wind Energy Input to the Surface Waves Based on the Scatterometer |
topic_facet |
Scatterometer Sea State Remote Sensing Surface Wave Energy Geochemistry & Geophysics Engineering Electrical & Electronic Remote Sensing |
description |
Mechanical energy input into the ocean from the atmosphere is primarily produced via the ocean surface waves. First, the total wind generation surface wave energy is estimated as nearly 80 TW (1 TM = 10(12) W), based on an empirical formulation and the wave age (beta) retrieved from the Earth Remote Sensing-1/2 satellite scatterometer observations. Second, the distribution of the wind-generated surface wave energy density shows that the main input occurs in the westerlies in the Southern Hemisphere and could reach up to 3.58 W/m(2) with an average value of 0.24 W/m(2) in the global ocean during a seven-day period. Third, we find that the downward energy flux rate from wind to surface waves can reach around 24% in the Southern Ocean and storm tracks in the northwest Pacific and Atlantic Oceans where the wind waves dominate, but a low downward rate of around 7% in tropical oceans with an average of 11% over the global oceans is observed. |
format |
Article in Journal/Newspaper |
author |
Liu, Guoqiang He, Yijun Zhang, Yuanzhi Shen, Hui Liu, GQ (reprint author), Oceans Canada, Bedford Inst Oceanog, Dartmouth, NS B2Y 4A2, Canada. |
author_facet |
Liu, Guoqiang He, Yijun Zhang, Yuanzhi Shen, Hui Liu, GQ (reprint author), Oceans Canada, Bedford Inst Oceanog, Dartmouth, NS B2Y 4A2, Canada. |
author_sort |
Liu, Guoqiang |
title |
Estimation of Global Wind Energy Input to the Surface Waves Based on the Scatterometer |
title_short |
Estimation of Global Wind Energy Input to the Surface Waves Based on the Scatterometer |
title_full |
Estimation of Global Wind Energy Input to the Surface Waves Based on the Scatterometer |
title_fullStr |
Estimation of Global Wind Energy Input to the Surface Waves Based on the Scatterometer |
title_full_unstemmed |
Estimation of Global Wind Energy Input to the Surface Waves Based on the Scatterometer |
title_sort |
estimation of global wind energy input to the surface waves based on the scatterometer |
publishDate |
2012 |
url |
http://ir.qdio.ac.cn/handle/337002/12145 https://doi.org/10.1109/LGRS.2012.2189194 |
geographic |
Pacific Southern Ocean |
geographic_facet |
Pacific Southern Ocean |
genre |
Southern Ocean |
genre_facet |
Southern Ocean |
op_relation |
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS Liu, Guoqiang; He, Yijun; Zhang, Yuanzhi; Shen, Hui.Estimation of Global Wind Energy Input to the Surface Waves Based on the Scatterometer,IEEE GEOSCIENCE AND REMOTE SENSING LETTERS,2012,9(6):1017-1020 http://ir.qdio.ac.cn/handle/337002/12145 doi:10.1109/LGRS.2012.2189194 |
op_doi |
https://doi.org/10.1109/LGRS.2012.2189194 |
container_title |
IEEE Geoscience and Remote Sensing Letters |
container_volume |
9 |
container_issue |
6 |
container_start_page |
1017 |
op_container_end_page |
1020 |
_version_ |
1766206908168929280 |