Purely satellite data-driven deep learning forecast of complicated tropical instability waves

doi:10.1126/sciadv.aba1482

CORC > 海洋研究所 > 中国科学院海洋研究所 > 海洋环流与波动重点实验室

	Purely satellite data-driven deep learning forecast of complicated tropical instability waves
	Zheng, Gang 4; Li, Xiaofeng 2,3; Zhang, Rong-Hua 2,3; Liu, Bin 1
刊名	SCIENCE ADVANCES
	2020-07-01
卷号	6 期号:29 页码:9
ISSN号	2375-2548
DOI	10.1126/sciadv.aba1482
通讯作者	Li, Xiaofeng(lixf@qdio.ac.cn)
英文摘要	Forecasting fields of oceanic phenomena has long been dependent on physical equation-based numerical models. The challenge is that many natural processes need to be considered for understanding complicated phenomena. In contrast, rules of the processes are already embedded in the time-series observation itself. Thus, inspired by largely available satellite remote sensing data and the advance of deep learning technology, we developed a purely satellite data-driven deep learning model for forecasting the sea surface temperature evolution associated with a typical phenomenon: a tropical instability wave. During the testing period of 9 years (2010-2019), our model accurately and efficiently forecasts the sea surface temperature field. This study demonstrates the strong potential of the satellite data-driven deep learning model as an alternative to traditional numerical models for forecasting oceanic phenomena.
资助项目	Strategic Priority Research Program of the Chinese Academy of Sciences[XDB42000000] ; Strategic Priority Research Program of the Chinese Academy of Sciences[XDA19090103] ; Key R&D Project of Shandong Province[2019JZZY010102] ; National Natural Science Foundation of China[41676167] ; National Natural Science Foundation of China[41776183] ; Key Deployment Project of Center for Ocean Mega-Science, CAS[COMS2019R02] ; CAS Program[Y9KY04101L] ; Project of State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography[SOEDZZ2003]
WOS研究方向	Science & Technology - Other Topics
语种	英语
出版者	AMER ASSOC ADVANCEMENT SCIENCE
WOS记录号	WOS:000552227800010
内容类型	期刊论文
源URL	[http://ir.qdio.ac.cn/handle/337002/167996]
专题	海洋研究所_海洋环流与波动重点实验室
通讯作者	Li, Xiaofeng
作者单位	1.Shanghai Ocean Univ, Coll Marine Sci, Shanghai 201306, Peoples R China 2.Chinese Acad Sci, Big Data Ctr, Inst Oceanol, CAS Key Lab Ocean Circulat & Waves, Qingdao 266071, Peoples R China 3.Chinese Acad Sci, Ctr Ocean Megasci, Qingdao 266071, Peoples R China 4.Minist Nat Resources, State Key Lab Satellite Ocean Environm Dynam, Inst Oceanog 2, Hangzhou 310012, Peoples R China
推荐引用方式 GB/T 7714	Zheng, Gang,Li, Xiaofeng,Zhang, Rong-Hua,et al. Purely satellite data-driven deep learning forecast of complicated tropical instability waves[J]. SCIENCE ADVANCES,2020,6(29):9.
APA	Zheng, Gang,Li, Xiaofeng,Zhang, Rong-Hua,&Liu, Bin.(2020).Purely satellite data-driven deep learning forecast of complicated tropical instability waves.SCIENCE ADVANCES,6(29),9.
MLA	Zheng, Gang,et al."Purely satellite data-driven deep learning forecast of complicated tropical instability waves".SCIENCE ADVANCES 6.29(2020):9.