Improvement of MiRS Sea Surface Temperature Retrievals Using a Machine Learning Approach-Reference-Cited by-同舟云学术

Improvement of MiRS Sea Surface Temperature Retrievals Using a Machine Learning Approach

Published:2022 Issue: Volume:15 Page:1857-1868
ISSN:1939-1404
Container-title:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
language:
Short-container-title:IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

Author:

Liu Shuyan¹^ORCID,Grassotti Christopher²^ORCID,Liu Quanhua³^ORCID,Zhou Yan²,Lee Yong-Keun²^ORCID

Affiliation:

1. Cooperative Institute for Research in the Atmosphere, Colorado State University, Fort Collins, CO, USA

2. Cooperative Institute for Satellite Earth System Studies, Earth System Science Interdisciplinary Center, College Park, MD, USA

3. National Oceanic and Atmospheric Administration, National Environmental Satellite Data Information Service, Center for Satellite Applications and Research, College Park, MD, USA

Funder

National Oceanic and Atmospheric Administration

Cooperative Institute for Satellite and Earth System Studies at the University of Maryland/Earth System Science Interdisciplinary Center

Joint Polar Satellite System

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Atmospheric Science,Computers in Earth Sciences

Link

http://xplorestaging.ieee.org/ielx7/4609443/9656571/09712418.pdf?arnumber=9712418

Reference29 articles.

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2. Kalman Filter–Based CMORPH

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5. A review of satellite-based microwave observations of sea surface temperatures

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