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

Abstract

Abstract. Currently there is a huge amount of freely available hydrographic data, and it is increasingly important to have easy access to it and to be provided with as much information as possible. Argo is a global collection of around 4000 active autonomous hydrographic profilers. Argo data go 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. The aim is to offer two filtering methods and to discard only the real-time quality control data that present salinity drifts. This takes 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 that uses cluster analysis and 30 % in the case of the second, which discards profilers with salinity drifts, of the total real-time quality control data that are usually discarded by the users due to problems such as salinity drifts. This allows users 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, rather than waiting for the delayed-mode quality control that takes up to 12 months to be completed. This methodology has been tested for its replicability in five selected areas around the world and has obtained good results.

Improving the thermocline calculation over the global ocean

“…Using RTQC data would increase the amount of data available for our computations. However, Argo recommends using only DMQC for scientific research, since the RTQC tests are automated and may contain bad data, as explained in the manuals (Argo Data Management Team, 2022) and even using the best quality control flag, as shown in Romero et al (2021), therefore, using this data could cause the erroneous computation of the MLD and MTD.…”