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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Parameterizing Vertical Mixing Coefficients in the Ocean Surface Boundary Layer Using Neural Networks
Aakash Sane, Brandon G. Reichl, Alistair Adcroft, et al.
Journal of Advances in Modeling Earth Systems (2023) Vol. 15, Iss. 10
Open Access | Times Cited: 13

Showing 13 citing articles:

Implementation and Evaluation of a Machine Learned Mesoscale Eddy Parameterization Into a Numerical Ocean Circulation Model
Cheng Zhang, Pavel Perezhogin, Cem Gültekin, et al.
Journal of Advances in Modeling Earth Systems (2023) Vol. 15, Iss. 10
Open Access | Times Cited: 24
Opinion: Optimizing climate models with process knowledge, resolution, and artificial intelligence
Tapio Schneider, L. Ruby Leung, Robert C. J. Wills
Atmospheric chemistry and physics (2024) Vol. 24, Iss. 12, pp. 7041-7062
Open Access | Times Cited: 13
Turbulence Closure With Small, Local Neural Networks: Forced Two‐Dimensional and β‐Plane Flows
Kaushik Srinivasan, Mickaël D. Chekroun, James C. McWilliams
Journal of Advances in Modeling Earth Systems (2024) Vol. 16, Iss. 4
Open Access | Times Cited: 7
Generative Data‐Driven Approaches for Stochastic Subgrid Parameterizations in an Idealized Ocean Model
Pavel Perezhogin, Laure Zanna, Carlos Fernandez‐Granda
Journal of Advances in Modeling Earth Systems (2023) Vol. 15, Iss. 10
Open Access | Times Cited: 15
Cross‐Attractor Transforms: Improving Forecasts by Learning Optimal Maps Between Dynamical Systems and Imperfect Models
Niraj Agarwal, Daniel E. Amrhein, Ian Grooms
Geophysical Research Letters (2025) Vol. 52, Iss. 4
Open Access
Machine Learning for Online Sea Ice Bias Correction Within Global Ice‐Ocean Simulations
William K. Gregory, Mitchell Bushuk, Yongfei Zhang, et al.
Geophysical Research Letters (2024) Vol. 51, Iss. 3
Open Access | Times Cited: 2
The K‐Profile Parameterization Augmented by Deep Neural Networks (KPP_DNN) in the General Ocean Turbulence Model (GOTM)
Jianguo Yuan, Jun‐Hong Liang, Eric P. Chassignet, et al.
Journal of Advances in Modeling Earth Systems (2024) Vol. 16, Iss. 9
Open Access | Times Cited: 2
A Machine Learning Approach for Deriving Atmospheric Temperatures and Typhoon Warm Cores From FY‐3E MWTS‐3 Observations
Zeyi Niu, Xiaolei Zou
Journal of Geophysical Research Machine Learning and Computation (2024) Vol. 1, Iss. 3
Open Access | Times Cited: 1
The K-profile Parameterization augmented by Deep Neural Networks (KPP_DNN) in the General Ocean Turbulence Model (GOTM)
Jianguo Yuan, Jun‐Hong Liang, Eric P. Chassignet, et al.
Authorea (Authorea) (2024)
Open Access
Cross-attractor transforms: Improving forecasts by learning optimal maps between dynamical systems and imperfect models
Niraj Agarwal, Daniel E. Amrhein, Ian Grooms
Authorea (Authorea) (2024)
Open Access
A Stable Implementation of a Data‐Driven Scale‐Aware Mesoscale Parameterization
Pavel Perezhogin, Cheng Zhang, Alistair Adcroft, et al.
Journal of Advances in Modeling Earth Systems (2024) Vol. 16, Iss. 10
Open Access
Parameterization of Langmuir circulation under geostrophic effects using the data-driven approach
Yu Gao, Jinbao Song, Shuang Li, et al.
Progress In Oceanography (2024), pp. 103403-103403
Closed Access
Machine learning for online sea ice bias correction within global ice-ocean simulations
William K. Gregory, Mitchell Bushuk, Yongfei Zhang, et al.
arXiv (Cornell University) (2023)
Open Access
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