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Uncertainty evaluation of CTD measurements: a metrological approach to water-column coastal parameters in the Gulf of La Spezia area

TitleUncertainty evaluation of CTD measurements: a metrological approach to water-column coastal parameters in the Gulf of La Spezia area
Publication TypeArticolo su Rivista peer-reviewed
Year of Publication2018
AuthorsRaiteri, G., Bordone A., Ciuffardi Tiziana, and Pennecchi F.
JournalMeasurement: Journal of the International Measurement Confederation
Volume126
Pagination156-163
ISSN02632241
KeywordsChemical analysis, Chemical and biologicals, Coastal monitoring, Conductivity-temperature depth profilers, Guide to the expression of uncertainty in measurements, Monte Carlo methods, Parameter estimation, Probability density function, Probability distributions, Propagation of distributions, Standard frameworks, Uncertainty analysis, Uncertainty evaluation, Water columns
Abstract

The ENEA Marine Environment Research Centre of S. Teresa has been involved since the ‘70s in monitoring, analysis and comprehension of physical, chemical and biological processes in marine environment. The purpose of this work is to describe the recently-implemented metrological approach aimed at evaluating the uncertainty associated with measurements performed by a Conductivity-Temperature-Depth profiler (CTD) during routine coastal campaigns in the Eastern Ligurian Sea, close to the Gulf of La Spezia. Main effort of this work is focused on applying, to each involved parameter, the standard framework for uncertainty evaluation as prescribed by the Guide to the expression of uncertainty in measurement. To this aim, an appropriate uncertainty evaluation is performed by combining type A and B contributions, evaluated from experimental data obtained in reproducibility conditions and from calibration certificates periodically supplied by manufacturer, respectively. Concerning in situ measured practical salinity, probability density functions modelling water pressure, temperature and conductivity, from which salinity depends, are propagated by application of the Monte Carlo method for propagation of distributions, hence obtaining the salinity uncertainty. © 2018 Elsevier Ltd

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URLhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85048804898&doi=10.1016%2fj.measurement.2018.05.058&partnerID=40&md5=6a96174e67f45f70dd44ddbc6df40066
DOI10.1016/j.measurement.2018.05.058
Citation KeyRaiteri2018156