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...

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Published in:IEEE Geoscience and Remote Sensing Letters
Main Authors: Liu, Guoqiang, He, Yijun, Zhang, Yuanzhi, Shen, Hui, Liu, GQ (reprint author), Oceans Canada, Bedford Inst Oceanog, Dartmouth, NS B2Y 4A2, Canada.
Format: Article in Journal/Newspaper
Language:English
Published: 2012
Subjects:
Online Access:http://ir.qdio.ac.cn/handle/337002/12145
https://doi.org/10.1109/LGRS.2012.2189194
id ftchinacasciocas:oai:ir.qdio.ac.cn:337002/12145
record_format openpolar
spelling 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
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