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Technical Note

A Completeness and Complementarity Analysis of the Data Sources in the NOAA In Situ Sea Surface Temperature Quality Monitor (iQuam) System

1
NOAA Center for Satellite Applications and Research, College Park, MD 20740, USA
2
Cooperative Institute for Research in the Atmosphere, Colorado State University, Fort Collins, CO 80523, USA
*
Author to whom correspondence should be addressed.
Academic Editors: Jorge Vazquez and Alexander Kokhanovsky
Remote Sens. 2021, 13(18), 3741; https://doi.org/10.3390/rs13183741
Received: 4 August 2021 / Revised: 13 September 2021 / Accepted: 15 September 2021 / Published: 18 September 2021
(This article belongs to the Special Issue Remote Sensing Data Sets)
In situ sea surface temperatures (SST) are the key component of the calibration and validation (Cal/Val) of satellite SST retrievals and data assimilation (DA). The NOAA in situ SST Quality Monitor (iQuam) aims to collect, from various sources, all available in situ SST data, and integrate them into a maximally complete, uniform, and accurate dataset to support these applications. For each in situ data type, iQuam strives to ingest data from several independent sources, to ensure most complete coverage, at the cost of some redundancy in data feeds. The relative completeness of various inputs and their consistency and mutual complementarity are often unknown and are the focus of this study. For four platform types customarily employed in satellite Cal/Val and DA (drifting buoys, tropical moorings, ships, and Argo floats), five widely known data sets are analyzed: (1) International Comprehensive Ocean-Atmosphere Data Set (ICOADS), (2) Fleet Numerical Meteorology and Oceanography Center (FNMOC), (3) Atlantic Oceanographic and Meteorological Laboratory (AOML), (4) Copernicus Marine Environment Monitoring Service (CMEMS), and (5) Argo Global Data Assembly Centers (GDACs). Each data set reports SSTs from one or more platform types. It is found that drifting buoys are more fully represented in FNMOC and CMEMS. Ships are reported in FNMOC and ICOADS, which are best used in conjunction with each other, but not in CMEMS. Tropical moorings are well represented in ICOADS, FNMOC, and CMEMS. Some CMEMS mooring reports are sampled every 10 min (compared to the standard 1 h sampling in all other datasets). The CMEMS Argo profiling data set is, as expected, nearly identical with those from the two Argo GDACs. View Full-Text
Keywords: iQuam; in situ SST; ICOADS; FNMOC; CMEMS; AOML; drifters; tropical moorings; ships; Argo floats; data completeness iQuam; in situ SST; ICOADS; FNMOC; CMEMS; AOML; drifters; tropical moorings; ships; Argo floats; data completeness
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MDPI and ACS Style

Zhang, H.; Ignatov, A. A Completeness and Complementarity Analysis of the Data Sources in the NOAA In Situ Sea Surface Temperature Quality Monitor (iQuam) System. Remote Sens. 2021, 13, 3741. https://doi.org/10.3390/rs13183741

AMA Style

Zhang H, Ignatov A. A Completeness and Complementarity Analysis of the Data Sources in the NOAA In Situ Sea Surface Temperature Quality Monitor (iQuam) System. Remote Sensing. 2021; 13(18):3741. https://doi.org/10.3390/rs13183741

Chicago/Turabian Style

Zhang, Haifeng, and Alexander Ignatov. 2021. "A Completeness and Complementarity Analysis of the Data Sources in the NOAA In Situ Sea Surface Temperature Quality Monitor (iQuam) System" Remote Sensing 13, no. 18: 3741. https://doi.org/10.3390/rs13183741

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