Importance of Reference Dataset Improvements for Argo Delayed-Mode Quality Control |
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Authors: | Email author" target="_blank">Taiyo?KobayashiEmail author Shinya?Minato |
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Institution: | (1) Institute of Observational Research for Global Change, Japan Agency for Marine-Earth Science and Technology, Yokosuka, Kanagawa 237-0061, Japan |
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Abstract: | For the Argo Project, monitoring the global upper ocean by a large number of profiling floats, maintaining the quality of
salinity data is critical; the goal for measurement accuracy is ±0.01. Experiments using the method of Wong et al. (2003), the standard delayed-mode quality control (dQC) for the Project, show that its performance depends critically on
the reference datasets used. This study concludes that the method is useful for Argo and has sufficient potential to achieve
the goal for salinity measurement in the North Pacific, when suitable reference datasets are prepared. Considering the Wong
et al. (2003) algorithms, we suggest that reference datasets with the following characteristics will be most suitable for Argo
dQC: They should be basically derived from the most extensive datasets, such as the latest World Ocean Database; in regions
with denser observations, datasets with carefully quality controls should be used; in the regions with subsurface temperature
inversions, such as the subarctic North Pacific, the profiles used for the reference must extend below the deepest temperature
maximum to prepare proper salinities for the deep layer reference. |
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Keywords: | Argo project quality control salinity climatological dataset |
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