Recommendations for in-situ data Near Real Time Quality Control

With the construction of operational oceanography systems, the need for real-time has become more and more important. A lot of work had been done in the past, within National Data Centres (NODC) and International Oceanographic Data and Information Exchange (IODE) to standardise delayed mode quality control procedures. Concerning such quality control procedures applicable in real-time (within hours to a maximum of a week from acquisition), which means automatically, some recommendations were set up for physical parameters but mainly within projects without consolidation with other initiatives. During the past ten years the EuroGOOS community has been working on such procedures within international programs such as Argo, OceanSites or GOSUD, or within EC projects such as Mersea, MFSTEP, FerryBox, ECOOP, and MyOcean. In collaboration with the FP7 SeaDataNet project that is standardizing the delayed mode quality control procedures in NODCs, and MyOcean GMES FP7 project that is standardizing near real time quality control procedures for operational oceanography purposes, the DATA-MEQ working group decided to put together this document to summarize the recommendations for near real-time QC procedures that they judged mature enough to be advertised and recommended to EuroGOOS.

SCOR WG 142: Quality Control Procedures for Oxygen and Other Biogeochemical Sensors on Floats and Gliders. Recommendation for oxygen measurements from Argo floats, implementation of in-air-measurement routine to assure highest long-term accuracy

Recommendation for Oxygen Measurements from Argo Floats: Implementation of In-Air-Measurement Routine to Assure Highest Long-term Accuracy As Argo has entered its second decade and chemical/biological sensor technology is improving constantly, the marine biogeochemistry community is starting to embrace the successful Argo float program. An augmentation of the global float observatory, however, has to follow rather stringent constraints regarding sensor characteristics as well as data processing and quality control routines. Owing to the fairly advanced state of oxygen sensor technology and the high scientific value of oceanic oxygen measurements (Gruber et al., 2010), an expansion of the Argo core mission to routine oxygen measurements is perhaps the most mature and promising candidate (Freeland et al., 2010). In this context, SCOR Working Group 142 “Quality Control Procedures for Oxygen and Other Biogeochemical Sensors on Floats and Gliders” (www.scor-int.org/SCOR_WGs_WG142.htm) set out in 2014 to assess the current status of biogeochemical sensor technology with particular emphasis on float-readiness, develop pre- and post-deployment quality control metrics and procedures for oxygen sensors, and to disseminate procedures widely to ensure rapid adoption in the community.

Argo quality control manual for dissolved oxygen concentration

This document is the Argo quality control manual for Dissolved oxygen concentration. It describes two levels of quality control: • The first level is the real-time system that performs a set of agreed automatic checks. • Adjustment in real-time can also be performed and the real-time system can evaluate quality flags for adjusted fields • The second level is the delayed-mode quality control system.

Copernicus In Situ TAC, Real Time Quality Control for WAVES

In April 2017, CMEMS plans to launch the WAVES NRT products. This document is focused in the automatic RTQC of the collected wave data. The validation procedure includes the delayed mode quality control of the data and will be specified in another guideline. To perform any kind of quality control to wave data, first it’s necessary to know the nature of the measurements and the analysis performed to those measurements to obtain the wave parameters. For that reason next chapter is dedicated to show the usual wave analysis and the different parameters and estimators obtained.

A compilation of global bio-optical in situ data for ocean-colour satellite applications

A compiled set of in situ data is important to evaluate the quality of ocean-colour satellite-data records. Here we describe the data compiled for the validation of the ocean-colour products from the ESA Ocean Colour Climate Change Initiative (OC-CCI). The data were acquired from several sources (MOBY, BOUSSOLE, AERONET-OC, SeaBASS, NOMAD, MERMAID, AMT, ICES, HOT, GeP&CO), span between 1997 and 2012, and have a global distribution. Observations of the following variables were compiled: spectral remote-sensing reflectances, concentrations of chlorophyll a, spectral inherent optical properties and spectral diffuse attenuation coefficients. The data were from multi-project archives acquired via the open internet services or from individual projects, acquired directly from data providers. Methodologies were implemented for homogenisation, quality control and merging of all data. No changes were made to the original data, other than averaging of observations that were close in time and space, elimination of some points after quality control and conversion to a standard format. The final result is a merged table designed for validation of satellite-derived ocean-colour products and available in text format. Metadata of each in situ measurement (original source, cruise or experiment, principal investigator) were preserved throughout the work and made available in the final table. Using all the data in a validation exercise increases the number of matchups and enhances the representativeness of different marine regimes. By making available the metadata, it is also possible to analyse each set of data separately. The compiled data are available at doi: 10.1594/PANGAEA.854832 (Valente et al., 2015).

Description of the Argo GDAC File Checks: Data Format and Consistency Checks

Every Argo data file submitted by a DAC for distribution on the GDAC has its format and data consistency checked by the Argo FileChecker. Two types of checks are applied: 1. Format checks. Ensures the file formats match the Argo standards precisely. 2. Data consistency checks. Additional data consistency checks are performed on a file after it passes the format checks. These checks do not duplicate any of the quality control checks performed elsewhere. These checks can be thought of as “sanity checks” to ensure that the data are consistent with each other. The data consistency checks enforce data standards and ensure that certain data values are reasonable and/or consistent with other information in the files. Examples of the “data standard” checks are the “mandatory parameters” defined for meta-data files and the technical parameter names in technical data files. Files with format or consistency errors are rejected by the GDAC and are not distributed. Less serious problems will generate warnings and the file will still be distributed on the GDAC. Reference Tables and Data Standards: Many of the consistency checks involve comparing the data to the published reference tables and data standards. These tables are documented in the User’s Manual. (The FileChecker implements “text versions” of these tables.)