Articles | Volume 17, issue 5
Research article
17 Sep 2021
Research article |  | 17 Sep 2021

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

Emmanuel Romero, Leonardo Tenorio-Fernandez, Iliana Castro, and Marco Castro

Related authors

Improving the thermocline calculation over the global ocean
Emmanuel Romero, Leonardo Tenorio-Fernandez, Esther Portela, Jorge Montes-Aréchiga, and Laura Sánchez-Velasco
Ocean Sci., 19, 887–901,,, 2023
Short summary

Cited articles

Argo: Argo [data set], available at:, last access: January 2020a. a, b
Argo: Argo float data and metadata from Global Data Assembly Centre (Argo GDAC) – Snapshot of Argo GDAC of December 10st 2020, [data set],, 2020b. a, b, c
Argo Data Management Team: Argo user's manual V3.3, Report,, 2019. a, b
Argo Data Management: Argo Data Management, available at:, last access: 2020. a, b
Coriolis: Coriolis: In situ data for operational oceanography, available at:, last access: 2020. a
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 real-time quality control of Argo data which has patterns similar to data in delayed mode. To test this, a study area of 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.