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    Improved statistical method for quality control of hydrographic observations

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    Article (3.700Mb)
    Date
    2020-05-04
    Author
    Gourrion, Jérôme  Concept link
    Szekely, Tanguy  Concept link
    Killick, Rachel E.  Concept link
    Owens, W. Brechner  Concept link
    Reverdin, Gilles  Concept link
    Charpon, Bertrand  Concept link
    Metadata
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    Citable URI
    https://hdl.handle.net/1912/25918
    As published
    https://doi.org/10.1175/JTECH-D-18-0244.1
    DOI
    10.1175/JTECH-D-18-0244.1
    Keyword
     Ocean; Climatology; Salinity; Temperature; Data quality control; Oceanic variability 
    Abstract
    Realistic ocean state prediction and its validation rely on the availability of high quality in situ observations. To detect data errors, adequate quality check procedures must be designed. This paper presents procedures that take advantage of the ever-growing observation databases that provide climatological knowledge of the ocean variability in the neighborhood of an observation location. Local validity intervals are used to estimate binarily whether the observed values are considered as good or erroneous. Whereas a classical approach estimates validity bounds from first- and second-order moments of the climatological parameter distribution, that is, mean and variance, this work proposes to infer them directly from minimum and maximum observed values. Such an approach avoids any assumption of the parameter distribution such as unimodality, symmetry around the mean, peakedness, or homogeneous distribution tail height relative to distribution peak. To reach adequate statistical robustness, an extensive manual quality control of the reference dataset is critical. Once the data have been quality checked, the local minima and maxima reference fields are derived and the method is compared with the classical mean/variance-based approach. Performance is assessed in terms of statistics of good and bad detections. It is shown that the present size of the reference datasets allows the parameter estimates to reach a satisfactory robustness level to always make the method more efficient than the classical one. As expected, insufficient robustness persists in areas with an especially low number of samples and high variability.
    Description
    Author Posting. © American Meteorological Society, 2020. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of the Atmospheric and Oceanic Technology 37(5), (2020): 789-806, doi:10.1175/JTECH-D-18-0244.1.
    Collections
    • Physical Oceanography (PO)
    Suggested Citation
    Gourrion, J., Szekely, T., Killick, R., Owens, B., Reverdin, G., & Chapron, B. (2020). Improved statistical method for quality control of hydrographic observations. Journal of Atmospheric and Oceanic Technology, 37(5), 789-806.
     

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