Estimation of Daily Arctic Winter Sea Ice Thickness from Thermodynamic Parameters Using a Self-Attention Convolutional Neural Network

Estimation of Daily Arctic Winter Sea Ice Thickness from Thermodynamic Parameters Using a Self-Attention Convolutional Neural Network

Thermodynamic parameters play a crucial role in determining polar sea ice thickness (SIT); however, modeling their relationship is difficult due to the complexity of the influencing mechanisms. In this study, we propose a self-attention convolutional neural network (SAC-Net), which aims to model the...

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Bibliographic Details
Main Authors: Zeyu Liang, Qing Ji, Xiaoping Pang, Pei Fan, Xuedong Yao, Yizhuo Chen, Ying Chen, Zhongnan Yan
Format: Article
Language:English
Published: MDPI AG 2023-03-01
Series:Remote Sensing
Subjects:
sea ice thickness
thermodynamic parameters
neural network
Arctic
Online Access:https://www.mdpi.com/2072-4292/15/7/1887

Internet

https://www.mdpi.com/2072-4292/15/7/1887

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