Acquisition of the Wide Swath Significant Wave Height from HY-2C through Deep Learning

Significant wave height (SWH) is of great importance in industries such as ocean engineering, marine resource development, shipping and transportation. Haiyang-2C (HY-2C), the second operational satellite in China’s ocean dynamics exploration series, can provide all-weather, all-day, global observat...

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Autores principales:	Jichao Wang, Ting Yu, Fangyu Deng, Zongli Ruan, Yongjun Jia
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	HY-2C deep learning the wide swath significant wave height Science Q
Acceso en línea:	https://doaj.org/article/87d05642b51845b99bd97fb28881018f
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spelling	oai:doaj.org-article:87d05642b51845b99bd97fb28881018f2021-11-11T18:56:10ZAcquisition of the Wide Swath Significant Wave Height from HY-2C through Deep Learning10.3390/rs132144252072-4292https://doaj.org/article/87d05642b51845b99bd97fb28881018f2021-11-01T00:00:00Zhttps://www.mdpi.com/2072-4292/13/21/4425https://doaj.org/toc/2072-4292Significant wave height (SWH) is of great importance in industries such as ocean engineering, marine resource development, shipping and transportation. Haiyang-2C (HY-2C), the second operational satellite in China’s ocean dynamics exploration series, can provide all-weather, all-day, global observations of wave height, wind, and temperature. An altimeter can only measure the nadir wave height and other information, and a scatterometer can obtain the wind field with a wide swath. In this paper, a deep learning approach is applied to produce wide swath SWH data through the wind field using a scatterometer and the nadir wave height taken from an altimeter. Two test sets, 1-month data at 6 min intervals and 1-day data with an interval of 10 s, are fed into the trained model. Experiments indicate that the extending nadir SWH yields using a real-time wide swath grid product along a track, which can support oceanographic study, is superior for taking the swell characteristics of ERA5 into account as the input of the wide swath SWH model. In conclusion, the results demonstrate the effectiveness and feasibility of the wide swath SWH model.Jichao WangTing YuFangyu DengZongli RuanYongjun JiaMDPI AGarticleHY-2Cdeep learningthe wide swath significant wave heightScienceQENRemote Sensing, Vol 13, Iss 4425, p 4425 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	HY-2C deep learning the wide swath significant wave height Science Q
spellingShingle	HY-2C deep learning the wide swath significant wave height Science Q Jichao Wang Ting Yu Fangyu Deng Zongli Ruan Yongjun Jia Acquisition of the Wide Swath Significant Wave Height from HY-2C through Deep Learning
description	Significant wave height (SWH) is of great importance in industries such as ocean engineering, marine resource development, shipping and transportation. Haiyang-2C (HY-2C), the second operational satellite in China’s ocean dynamics exploration series, can provide all-weather, all-day, global observations of wave height, wind, and temperature. An altimeter can only measure the nadir wave height and other information, and a scatterometer can obtain the wind field with a wide swath. In this paper, a deep learning approach is applied to produce wide swath SWH data through the wind field using a scatterometer and the nadir wave height taken from an altimeter. Two test sets, 1-month data at 6 min intervals and 1-day data with an interval of 10 s, are fed into the trained model. Experiments indicate that the extending nadir SWH yields using a real-time wide swath grid product along a track, which can support oceanographic study, is superior for taking the swell characteristics of ERA5 into account as the input of the wide swath SWH model. In conclusion, the results demonstrate the effectiveness and feasibility of the wide swath SWH model.
format	article
author	Jichao Wang Ting Yu Fangyu Deng Zongli Ruan Yongjun Jia
author_facet	Jichao Wang Ting Yu Fangyu Deng Zongli Ruan Yongjun Jia
author_sort	Jichao Wang
title	Acquisition of the Wide Swath Significant Wave Height from HY-2C through Deep Learning
title_short	Acquisition of the Wide Swath Significant Wave Height from HY-2C through Deep Learning
title_full	Acquisition of the Wide Swath Significant Wave Height from HY-2C through Deep Learning
title_fullStr	Acquisition of the Wide Swath Significant Wave Height from HY-2C through Deep Learning
title_full_unstemmed	Acquisition of the Wide Swath Significant Wave Height from HY-2C through Deep Learning
title_sort	acquisition of the wide swath significant wave height from hy-2c through deep learning
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/87d05642b51845b99bd97fb28881018f
work_keys_str_mv	AT jichaowang acquisitionofthewideswathsignificantwaveheightfromhy2cthroughdeeplearning AT tingyu acquisitionofthewideswathsignificantwaveheightfromhy2cthroughdeeplearning AT fangyudeng acquisitionofthewideswathsignificantwaveheightfromhy2cthroughdeeplearning AT zongliruan acquisitionofthewideswathsignificantwaveheightfromhy2cthroughdeeplearning AT yongjunjia acquisitionofthewideswathsignificantwaveheightfromhy2cthroughdeeplearning
_version_	1718431657302687744

Acquisition of the Wide Swath Significant Wave Height from HY-2C through Deep Learning

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