Preprints
https://doi.org/10.5194/os-2021-22
https://doi.org/10.5194/os-2021-22

  06 Apr 2021

06 Apr 2021

Review status: this preprint is currently under review for the journal OS.

Filtering method based on cluster analysis to avoid salinity drifts and recover Argo data in less time

Emmanuel Romero1, Leonardo Tenorio-Fernandez2, Iliana Castro1, and Marco Castro1 Emmanuel Romero et al.
  • 1Tecnológico Nacional de México/Instituto Tecnológico de La Paz
  • 2CONACyT-Instituto Politécnico Nacional–Centro Interdisciplinario de Ciencias Marinas

Abstract. Currently there is a huge amount of freely available hydrographic data and it is increasingly important to have access to it efficiently and easily provided with as much information as possible. Argo is a global collection of around 4000 active autonomous hydrographic profilers. Argo data goes through two quality processes, real time and delayed mode. This work shows a methodology to filter profiles within a given polygon using the odd-even algorithm, this allows analysis of a study area, regardless of size, shape or location. Also, gives two filtering methods to discard only the real time quality control data that present salinity drifts, thus taking advantage of the largest possible amount of valid data within a given polygon. In the study area selected as an example, it was possible to recover around 80 % in the case of the first filter and 30 % in the case of the second of the total real time quality control data that are usually discarded due to problems such as salinity drifts, this allows researchers to use any of the filters or a combination of both to have a greater amount of data within the study area of their interest in a matter of minutes, unlike waiting for the delayed mode quality control that takes up to 12 months to be completed.

Emmanuel Romero et al.

Status: open (until 01 Jun 2021)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse

Emmanuel Romero et al.

Model code and software

romeroqe/cluster_qc: Filtering Methods based on cluster analysis for Argo Data Emmanuel Romero; Leonardo Tenorio-Fernandez; Iliana Castro; Marco Castro https://doi.org/10.5281/zenodo.4595802

Emmanuel Romero et al.

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Short summary
Due to the need to obtain a greater amount of data in less time in areas with little in situ hydrographic data, an algorithm based on cluster analysis is proposed. This algorithm allows to admit Argo data in real time quality control which has patterns similar to data in delayed mode. To test this, a study area with high scientific interest but with little concentration of in situ data was chosen. In this area 80 % of the data normally discarded because of salinity drifts was recovered.