DOI: 10.3390/rs12040590
论文题名: Error estimation of pathfinder version 5.3 level-3C SST using extended triple collocation analysis
作者: Saha K. ; Dash P. ; Zhao X. ; Zhang H.M.
刊名: Remote Sensing
ISSN: 20724292
出版年: 2020
卷: 12, 期: 4 语种: 英语
英文关键词: Error characterization
; Pathfinder SST
; Root-mean-square error
; Sea surface temperature
; Triple collocation
Scopus关键词: Atmospheric temperature
; Climate change
; Climate models
; Ecosystems
; Errors
; Mean square error
; Signal to noise ratio
; Submarine geophysics
; Surface properties
; Surface waters
; Uncertainty analysis
; Error characterizations
; Pathfinder SST
; Root mean square errors
; Sea surface temperature (SST)
; Triple collocation
; Oceanography
英文摘要: 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. © 2020 by the authors. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/159667
Appears in Collections: 气候变化与战略
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作者单位: Cooperative Institute for Satellite Earth System Studies (CISESS)-Maryland, University of Maryland, College Park, MD 20740, United States; National Centers for Environmental Information (NCEI), NOAA/NESDIS, Silver Spring, MD 20910, United States; Cooperative Institute for Research in Atmosphere (CIRA), Colorado State University, Fort Collins, CO 80523, United States; Center for Satellite Applications and Research (STAR), NOAA/NESDIS, College Park, MD 20740, United States; National Centers for Environmental Information (NCEI), NOAA/NESDIS, Asheville, NC 28801, United States
Recommended Citation:
Saha K.,Dash P.,Zhao X.,et al. Error estimation of pathfinder version 5.3 level-3C SST using extended triple collocation analysis[J]. Remote Sensing,2020-01-01,12(4)