Dissolved oxygen (DO) is one of the most important drivers of ocean biogeochemical cycles and marine life, and in many areas its concentration has declined due to climate change. In recent decades, a growing number of autonomous oceanographic platforms has been equipped with sensors for direct in situ measurements of oxygen levels. However, to ensure high quality and comparable data, these observations need to be validated or, if necessary, corrected. In this paper, we compiled all the available DO data collected by Argo floats and gliders in the South Adriatic Pit (Mediterranean Sea) between 2014 and 2020. This dataset includes data for which it was not possible to apply conventional quality-control methods. Therefore, we had to apply tailored procedures based on well-established best practices for correction. The aim is to showcase how these tailored procedures allowed us to achieve the best possible quality of data and generate consistent datasets. The drift of the glider DO sensors related to storage was also estimated. The described procedure could be useful in similar cases where the conventional methods are not viable, thus making available potentially useful data.
Correction and harmonization of dissolved oxygen data from autonomous platforms in the South Adriatic Pit (Mediterranean Sea)
Gerin R.;Martellucci R.;Savonitto G.
;Notarstefano G.;Comici C.;Cardin V.;Bussani A.;Pacciaroni M.;Mauri E.
2024-01-01
Abstract
Dissolved oxygen (DO) is one of the most important drivers of ocean biogeochemical cycles and marine life, and in many areas its concentration has declined due to climate change. In recent decades, a growing number of autonomous oceanographic platforms has been equipped with sensors for direct in situ measurements of oxygen levels. However, to ensure high quality and comparable data, these observations need to be validated or, if necessary, corrected. In this paper, we compiled all the available DO data collected by Argo floats and gliders in the South Adriatic Pit (Mediterranean Sea) between 2014 and 2020. This dataset includes data for which it was not possible to apply conventional quality-control methods. Therefore, we had to apply tailored procedures based on well-established best practices for correction. The aim is to showcase how these tailored procedures allowed us to achieve the best possible quality of data and generate consistent datasets. The drift of the glider DO sensors related to storage was also estimated. The described procedure could be useful in similar cases where the conventional methods are not viable, thus making available potentially useful data.File | Dimensione | Formato | |
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