Bias correction of Arctic sea ice thickness products based on factor selection and machine learning methods-Reference-Cited by-同舟云学术

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Bias correction of Arctic sea ice thickness products based on factor selection and machine learning methods

Published:2024-08 Issue: Volume:149 Page:104069
ISSN:0141-1187
Container-title:Applied Ocean Research
language:en
Short-container-title:Applied Ocean Research

Author:

Wu Hongqian^ORCID,Wang Yangjun^ORCID,Zhang Ren,Yan Hengqian,Hong Mei

Funder

Hunan Provincial Natural Science Foundation

National Natural Science Foundation of China

Publisher

Elsevier BV

Reference70 articles.

1. Uncertainty in modeled Arctic sea ice volume;Schweiger;J. Geophys. Res.,2011

2. Assimilation of SMOS sea ice thickness in the regional ice prediction system;Gupta;Int. J. Remote Sens.,2021

3. Differences between ICESat and CryoSat-2 sea ice thicknesses over the arctic: consequences for analyzing the ice volume trend;Kim;J. Geophys. Res.: Atmospheres,2020

4. Arctic sea ice thickness variations from CryoSat-2 satellite altimetry data;Xiao;Sci. China Earth. Sci.,2021

5. Variation of sea ice and perspectives of the Northwest Passage in the Arctic Ocean;Chen;Adv. Climate Change Research,2021

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