Global Drag-Coefficient Estimates From Scatterometer Wind and Wave Steepness
A neural-network model was developed to retrieve the wave steepness (delta), which was used to represent the sea state (particularly wave state), from the European Remote Sensing (ERS) scatterometer onboard ERS-1/2. Using the retrieved delta and scatterometer wind speed, we calculated and examined t...
Published in: | IEEE Transactions on Geoscience and Remote Sensing |
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Online Access: | http://ir.qdio.ac.cn/handle/337002/11578 https://doi.org/10.1109/TGRS.2010.2082554 |
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ftchinacasciocas:oai:ir.qdio.ac.cn:337002/11577 2023-05-15T18:25:02+02:00 Global Drag-Coefficient Estimates From Scatterometer Wind and Wave Steepness Liu, Guoqiang He, Yijun Shen, Hui Guo, Jie 2011-05-01 http://ir.qdio.ac.cn/handle/337002/11578 https://doi.org/10.1109/TGRS.2010.2082554 英语 eng IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING Liu, Guoqiang; He, Yijun; Shen, Hui; Guo, Jie.Global Drag-Coefficient Estimates From Scatterometer Wind and Wave Steepness,IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,2011,49(5):1499-1503 http://ir.qdio.ac.cn/handle/337002/11578 doi:10.1109/TGRS.2010.2082554 Air-sea Interaction Neural Networks (Nns) Remote Sensing Geochemistry & Geophysics Engineering Article 期刊论文 2011 ftchinacasciocas https://doi.org/10.1109/TGRS.2010.2082554 2022-06-27T05:34:10Z A neural-network model was developed to retrieve the wave steepness (delta), which was used to represent the sea state (particularly wave state), from the European Remote Sensing (ERS) scatterometer onboard ERS-1/2. Using the retrieved delta and scatterometer wind speed, we calculated and examined the drag coefficient (C-D) over the global ocean. The results show that C-D changes significantly when wave steepness is included in the calculation. Combining wave steepness and wind speed increases C-D by nearly 14% on average. That change is spatially variable, ranging from -18.76% for the tropical Eastern Pacific Ocean to 104% for the Southern Ocean. A neural-network model was developed to retrieve the wave steepness (delta), which was used to represent the sea state (particularly wave state), from the European Remote Sensing (ERS) scatterometer onboard ERS-1/2. Using the retrieved delta and scatterometer wind speed, we calculated and examined the drag coefficient (C(D)) over the global ocean. The results show that C(D) changes significantly when wave steepness is included in the calculation. Combining wave steepness and wind speed increases C(D) by nearly 14% on average. That change is spatially variable, ranging from -18.76% for the tropical Eastern Pacific Ocean to 104% for the Southern Ocean. Article in Journal/Newspaper Southern Ocean Institute of Oceanology, Chinese Academy of Sciences: IOCAS-IR Pacific Southern Ocean IEEE Transactions on Geoscience and Remote Sensing 49 5 1499 1503 |
institution |
Open Polar |
collection |
Institute of Oceanology, Chinese Academy of Sciences: IOCAS-IR |
op_collection_id |
ftchinacasciocas |
language |
English |
topic |
Air-sea Interaction Neural Networks (Nns) Remote Sensing Geochemistry & Geophysics Engineering |
spellingShingle |
Air-sea Interaction Neural Networks (Nns) Remote Sensing Geochemistry & Geophysics Engineering Liu, Guoqiang He, Yijun Shen, Hui Guo, Jie Global Drag-Coefficient Estimates From Scatterometer Wind and Wave Steepness |
topic_facet |
Air-sea Interaction Neural Networks (Nns) Remote Sensing Geochemistry & Geophysics Engineering |
description |
A neural-network model was developed to retrieve the wave steepness (delta), which was used to represent the sea state (particularly wave state), from the European Remote Sensing (ERS) scatterometer onboard ERS-1/2. Using the retrieved delta and scatterometer wind speed, we calculated and examined the drag coefficient (C-D) over the global ocean. The results show that C-D changes significantly when wave steepness is included in the calculation. Combining wave steepness and wind speed increases C-D by nearly 14% on average. That change is spatially variable, ranging from -18.76% for the tropical Eastern Pacific Ocean to 104% for the Southern Ocean. A neural-network model was developed to retrieve the wave steepness (delta), which was used to represent the sea state (particularly wave state), from the European Remote Sensing (ERS) scatterometer onboard ERS-1/2. Using the retrieved delta and scatterometer wind speed, we calculated and examined the drag coefficient (C(D)) over the global ocean. The results show that C(D) changes significantly when wave steepness is included in the calculation. Combining wave steepness and wind speed increases C(D) by nearly 14% on average. That change is spatially variable, ranging from -18.76% for the tropical Eastern Pacific Ocean to 104% for the Southern Ocean. |
format |
Article in Journal/Newspaper |
author |
Liu, Guoqiang He, Yijun Shen, Hui Guo, Jie |
author_facet |
Liu, Guoqiang He, Yijun Shen, Hui Guo, Jie |
author_sort |
Liu, Guoqiang |
title |
Global Drag-Coefficient Estimates From Scatterometer Wind and Wave Steepness |
title_short |
Global Drag-Coefficient Estimates From Scatterometer Wind and Wave Steepness |
title_full |
Global Drag-Coefficient Estimates From Scatterometer Wind and Wave Steepness |
title_fullStr |
Global Drag-Coefficient Estimates From Scatterometer Wind and Wave Steepness |
title_full_unstemmed |
Global Drag-Coefficient Estimates From Scatterometer Wind and Wave Steepness |
title_sort |
global drag-coefficient estimates from scatterometer wind and wave steepness |
publishDate |
2011 |
url |
http://ir.qdio.ac.cn/handle/337002/11578 https://doi.org/10.1109/TGRS.2010.2082554 |
geographic |
Pacific Southern Ocean |
geographic_facet |
Pacific Southern Ocean |
genre |
Southern Ocean |
genre_facet |
Southern Ocean |
op_relation |
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING Liu, Guoqiang; He, Yijun; Shen, Hui; Guo, Jie.Global Drag-Coefficient Estimates From Scatterometer Wind and Wave Steepness,IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,2011,49(5):1499-1503 http://ir.qdio.ac.cn/handle/337002/11578 doi:10.1109/TGRS.2010.2082554 |
op_doi |
https://doi.org/10.1109/TGRS.2010.2082554 |
container_title |
IEEE Transactions on Geoscience and Remote Sensing |
container_volume |
49 |
container_issue |
5 |
container_start_page |
1499 |
op_container_end_page |
1503 |
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1766206165682749440 |