Purely satellite data–driven deep learning forecast of complicated tropical instability waves-Reference-Cited by-同舟云学术

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

Published:2020-07-17 Issue:29 Volume:6 Page:
ISSN:2375-2548
Container-title:Science Advances
language:en
Short-container-title:Sci. Adv.

Author:

Zheng Gang¹^ORCID,Li Xiaofeng²³^ORCID,Zhang Rong-Hua²³,Liu Bin⁴^ORCID

Affiliation:

1. State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, Ministry of Natural Resources, Hangzhou 310012, China.

2. CAS Key Laboratory of Ocean Circulation and Waves, Big Data Center, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China.

3. Center for Ocean Mega-Science, Chinese Academy of Sciences, Qingdao 266071, China.

4. College of Marine Sciences, Shanghai Ocean University, Shanghai 201306, China.

Abstract

We developed a deep learning model to forecast the sea surface temperature evolution associated with tropical instability waves.

Funder

the National Natural Science Foundation of China

the Strategic Priority Research Program of the Chinese Academy of Sciences

the Key R & D Project of Shandong Province

the Key Deployment Project of Center for Ocean Mega-Science, CAS

the CAS Program

the Project of State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography

Publisher

American Association for the Advancement of Science (AAAS)

Subject

Multidisciplinary

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