Title | Uncertainty evaluation of CTD measurements: a metrological approach to water-column coastal parameters in the Gulf of La Spezia area |
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Publication Type | Articolo su Rivista peer-reviewed |
Year of Publication | 2018 |
Authors | Raiteri, G., Bordone A., Ciuffardi Tiziana, and Pennecchi F. |
Journal | Measurement: Journal of the International Measurement Confederation |
Volume | 126 |
Pagination | 156-163 |
ISSN | 02632241 |
Keywords | Chemical 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 |
Notes | cited By 0 |
URL | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85048804898&doi=10.1016%2fj.measurement.2018.05.058&partnerID=40&md5=6a96174e67f45f70dd44ddbc6df40066 |
DOI | 10.1016/j.measurement.2018.05.058 |
Citation Key | Raiteri2018156 |