Applying machine learning in devising a parsimonious ocean mixing parameterization scheme-Reference-Cited by-同舟云学术

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Applying machine learning in devising a parsimonious ocean mixing parameterization scheme

Published:2022-09 Issue: Volume:203 Page:105163
ISSN:0967-0645
Container-title:Deep Sea Research Part II: Topical Studies in Oceanography
language:en
Short-container-title:Deep Sea Research Part II: Topical Studies in Oceanography

Author:

Han Guoqing,Cen Haobin,Jiang Jiahan,Gao Xiaoqian,Jiang Xingliang,Zhou Shuyi,Xie Wenhong,Ji Jinlin,Bethel Brandon J.,Dong Changming

Funder

Southern Marine Science and Engineering Guangdong Laboratory

Publisher

Elsevier BV

Subject

Oceanography

Reference44 articles.

1. Forecasting hurricane-forced significant wave heights using a long short-term memory network in the Caribbean Sea;Bethel;Ocean Sci.,2022

2. Applications of deep learning to ocean data inference and subgrid parameterization;Bolton;J. Adv. Model. Earth Syst.,2019

3. A hybrid vertical mixing scheme and its application to tropical ocean models;Chen;J. Phys. Oceanogr.,1994

4. Two-way nesting in split-explicit ocean models: algorithms, implementation and validation;Debreu;Ocean Model.,2012

5. Oceanic mesoscale eddy detection method based on deep learning;Duo;Rem. Sens.,2019

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1. A Physical‐Informed Neural Network for Improving Air‐Sea Turbulent Heat Flux Parameterization;Journal of Geophysical Research: Atmospheres;2024-09-02

2. Application of data-driven mixing parameterization scheme in a regional ocean model;Ocean Modelling;2024-04

3. Application of deep learning in estimating the convective mixing induced by brine rejection;Ocean Modelling;2024-04

4. Instant deep sea debris detection for maneuverable underwater machines to build sustainable ocean using deep neural network;Science of The Total Environment;2023-06

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