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Review

Satellite Oceanography in NOAA: Research, Development, Applications, and Services Enabling Societal Benefits from Operational and Experimental Missions

by
Eric Bayler
1,*,
Paul S. Chang
1,
Jacqueline L. De La Cour
1,2,
Sean R. Helfrich
1,
Alexander Ignatov
1,
Jeff Key
1,
Veronica Lance
1,
Eric W. Leuliette
1,
Deirdre A. Byrne
1,
Yinghui Liu
1,
Xiaoming Liu
1,3,
Menghua Wang
1,
Jianwei Wei
1,4 and
Paul M. DiGiacomo
1
1
National Oceanic and Atmospheric Administration (NOAA), National Environmental Satellite, Data, and Information Service (NESDIS), Center for Satellite Applications and Research (STAR), College Park, MD 20740, USA
2
Cooperative Institute for Satellite Earth System Studies, Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD 20740, USA
3
Cooperative Institute for Research in the Atmosphere (CIRA), Colorado State University, Fort Collins, CO 80521, USA
4
Global Science and Technology, Inc., Greenbelt, MD 20770, USA
*
Author to whom correspondence should be addressed.
Remote Sens. 2024, 16(14), 2656; https://doi.org/10.3390/rs16142656 (registering DOI)
Submission received: 27 February 2024 / Revised: 17 April 2024 / Accepted: 27 June 2024 / Published: 20 July 2024
(This article belongs to the Special Issue Oceans from Space V)

Abstract

The National Oceanic and Atmospheric Administration’s (NOAA) Center for Satellite Applications and Research (STAR) facilitates and enables societal benefits from satellite oceanography, supporting operational and experimental satellite missions, developing new and improved ocean observing capabilities, engaging users by developing and distributing fit-for-purpose data, applications, tools, and services, and curating, translating, and integrating diverse data products into information that supports informed decision making. STAR research, development, and application efforts span from passive visible, infrared, and microwave observations to active altimetry, scatterometry, and synthetic aperture radar (SAR) observations. These efforts directly support NOAA’s operational geostationary (GEO) and low Earth orbit (LEO) missions with calibration/validation and retrieval algorithm development, implementation, maintenance, and anomaly resolution, as well as leverage the broader international constellation of environmental satellites for NOAA’s benefit. STAR’s satellite data products and services enable research, assessments, applications, and, ultimately, decision making for understanding, predicting, managing, and protecting ocean and coastal resources, as well as assessing impacts of change on the environment, ecosystems, and climate. STAR leads the NOAA Coral Reef Watch and CoastWatch/OceanWatch/PolarWatch Programs, helping people access and utilize global and regional satellite data for ocean, coastal, and ecosystem applications.
Keywords: satellite; oceanography; research; development; operational satellite; oceanography; research; development; operational

Share and Cite

MDPI and ACS Style

Bayler, E.; Chang, P.S.; De La Cour, J.L.; Helfrich, S.R.; Ignatov, A.; Key, J.; Lance, V.; Leuliette, E.W.; Byrne, D.A.; Liu, Y.; et al. Satellite Oceanography in NOAA: Research, Development, Applications, and Services Enabling Societal Benefits from Operational and Experimental Missions. Remote Sens. 2024, 16, 2656. https://doi.org/10.3390/rs16142656

AMA Style

Bayler E, Chang PS, De La Cour JL, Helfrich SR, Ignatov A, Key J, Lance V, Leuliette EW, Byrne DA, Liu Y, et al. Satellite Oceanography in NOAA: Research, Development, Applications, and Services Enabling Societal Benefits from Operational and Experimental Missions. Remote Sensing. 2024; 16(14):2656. https://doi.org/10.3390/rs16142656

Chicago/Turabian Style

Bayler, Eric, Paul S. Chang, Jacqueline L. De La Cour, Sean R. Helfrich, Alexander Ignatov, Jeff Key, Veronica Lance, Eric W. Leuliette, Deirdre A. Byrne, Yinghui Liu, and et al. 2024. "Satellite Oceanography in NOAA: Research, Development, Applications, and Services Enabling Societal Benefits from Operational and Experimental Missions" Remote Sensing 16, no. 14: 2656. https://doi.org/10.3390/rs16142656

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