Machine-Learned Cloud Classes From Satellite Data for Process-Oriented Climate Model Evaluation-Reference-Cited by-同舟云学术

Machine-Learned Cloud Classes From Satellite Data for Process-Oriented Climate Model Evaluation

Published:2023 Issue: Volume:61 Page:1-15
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Kaps Arndt¹^ORCID,Lauer Axel¹^ORCID,Camps-Valls Gustau²^ORCID,Gentine Pierre³^ORCID,Gomez-Chova Luis²^ORCID,Eyring Veronika¹^ORCID

Affiliation:

1. Institut für Physik der Atmosphäre, Deutsches Zentrum für Luft- und Raumfahrt (DLR), Oberpfaffenhofen, Germany

2. Image Processing Laboratory (IPL), University of Valencia, Valencia, Spain

3. Department of Earth and Environmental Engineering and the Center for Learning the Earth with Artificial intelligence and Physics (LEAP), Columbia University, New York, NY, USA

Funder

European Research Council (ERC) Synergy Grant “Understanding and Modeling the Earth System with Machine Learning (USMILE)” under the Horizon 2020 Research and Innovation Programme

ESA Climate Change Initiative Climate Model User Group

Deutsches Klimarechenzentrum (DKRZ) granted by its Scientific Steering Committee

Leibniz-Rechenzentrum

Spanish Ministry of Science and Innovation

National Science Foundation Science and Technology Center for Learning the Earth with Artificial intelligence and Physics

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Link

https://ieeexplore.ieee.org/ielam/36/10006360/10025016-aam.pdf

Reference39 articles.

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