Application of deep learning in estimating the convective mixing induced by brine rejection-Reference-Cited by-同舟云学术

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Application of deep learning in estimating the convective mixing induced by brine rejection

Published:2024-04 Issue: Volume:188 Page:102314
ISSN:1463-5003
Container-title:Ocean Modelling
language:en
Short-container-title:Ocean Modelling

Author:

Gao Xiaoqian,Han Guoqing,Sun Wenjin,Zhou Shuyi,Xie Wenhong,Cen Haobin,Ji Jinlin,Wang Haili,Dong Changming

Funder

Southern Marine Science and Engineering Guangdong Laboratory

Natural Science Foundation of Shandong Province

Guangzhou Municipal Science and Technology Project

Publisher

Elsevier BV

Reference34 articles.

1. Large-eddy simulations of deep-ocean convection: analysis of the vorticity dynamics;Barbosa;J. Turbul.,2000

2. Modeling the interplay between sea ice formation and the oceanic mixed layer: limitations of simple brine rejection parameterizations;Barthélemy;Ocean Model.,2015

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

4. Applications of Deep Learning to Ocean Data Inference and Subgrid Parameterization;Bolton;J. Adv. Model. Earth Syst.,2019

5. Identification of modeled ocean plumes in Greenland Gyre ERS-1 SAR data;Carsey;Geophys. Res. Lett.,1993

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