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Open AccessLetter

Error Estimation of Pathfinder Version 5.3 Level-3C SST Using Extended Triple Collocation Analysis

1
Cooperative Institute for Satellite Earth System Studies (CISESS)-Maryland, University of Maryland, College Park, MD 20740, USA
2
National Centers for Environmental Information (NCEI), NOAA/NESDIS, Silver Spring, MD 20910, USA
3
Cooperative Institute for Research in Atmosphere (CIRA), Colorado State University, Fort Collins, CO 80523, USA
4
Center for Satellite Applications and Research (STAR), NOAA/NESDIS, College Park, MD 20740, USA
5
National Centers for Environmental Information (NCEI), NOAA/NESDIS, Asheville, NC 28801, USA
*
Author to whom correspondence should be addressed.
Remote Sens. 2020, 12(4), 590; https://doi.org/10.3390/rs12040590
Received: 27 January 2020 / Revised: 6 February 2020 / Accepted: 8 February 2020 / Published: 11 February 2020
Sea Surface Temperature (SST) is an essential climate variable (ECV) for monitoring the state and detecting changes in the climate. The concept of ECVs, developed by the Global Climate Observing System (GCOS) program of the World Meteorological Organization (WMO), has been broadly adopted in worldwide science and policy circles Besides being a climate change indicator, the global SST field is an essential input for atmospheric models, air-sea exchange studies, understanding marine ecosystems, operational weather, and ocean forecasting, military and defense operations, tourism, and fisheries research. It is, therefore, critical to understand the errors associated with SST measurements from both in situ measurements and satellite observations. The customary way of validating a satellite SST is to compare it with in situ measured SSTs. This method, however, will have inaccuracies due to uncertainties involving both types of measurements. A triple collocation (TC) error analysis can be implemented on three mutually independent error-prone measurements to estimate the root-mean-square error (RMSE) of each measurement. In this study, the error characterization for the Pathfinder SST version 5.3 (PF53) dataset is performed using an extended TC (ETC) method and reported to be in the range of 0.31 to 0.37 K. These values are reasonable, as is evident from corresponding very high (~0.98) unbiased signal-to-noise ratio (SNR) values. View Full-Text
Keywords: sea surface temperature; Pathfinder SST; triple collocation; error characterization; root-mean-square error sea surface temperature; Pathfinder SST; triple collocation; error characterization; root-mean-square error
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MDPI and ACS Style

Saha, K.; Dash, P.; Zhao, X.; Zhang, H.-M. Error Estimation of Pathfinder Version 5.3 Level-3C SST Using Extended Triple Collocation Analysis. Remote Sens. 2020, 12, 590.

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