Estimation of daytime all-sky sea surface temperature from Himawari-8 based on multilayer stacking machine learning-Reference-Cited by-同舟云学术

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Estimation of daytime all-sky sea surface temperature from Himawari-8 based on multilayer stacking machine learning

Published:2024-08 Issue: Volume:132 Page:104055
ISSN:1569-8432
Container-title:International Journal of Applied Earth Observation and Geoinformation
language:en
Short-container-title:International Journal of Applied Earth Observation and Geoinformation

Author:

He Hongchang,Fan Donglin^ORCID,Wang Ruisheng,Lyu Xiaoyue^ORCID,Fu Bolin,Huang Yuan,Sheng Jingran

Funder

Bagui Scholars Program of Guangxi Zhuang Autonomous Region

Guangxi Natural Science Foundation

Publisher

Elsevier BV

Reference48 articles.

1. Data Interpolating Empirical Orthogonal Functions (DINEOF): a tool for geophysical data analyses;Alvera-Azcárate;Mediterr. Mar. Sci.,2011

2. On the scattering and absorption properties of cirrus cloud;Baran;J. Quant. Spectrosc. Radiat. Transf. VII Electromagn. Light Scatter. Non-Spherical Part.: Theory Meas. Appl.,2004

3. DINCAE 1.0: a convolutional neural network with error estimates to reconstruct sea surface temperature satellite observations;Barth;Geosci. Model Dev.,2020

4. DINCAE 2.0: multivariate convolutional neural network with error estimates to reconstruct sea surface temperature satellite and altimetry observations;Barth;Geosci. Model Dev.,2022

5. An introduction to Himawari-8/9 — Japan’s new-generation geostationary meteorological satellites;Bessho;J. Meteorol. Soc. Jpn.,2016

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