Christine Coatanoan

Quality Control of Large Argo Datasets

Abstract Argo floats have significantly improved the observation of the global ocean interior, but as the size of the database increases, so does the need for efficient tools to perform reliable quality control. It is shown here how the classical method of optimal analysis can be used to validate very large datasets before operational or scientific use. The analysis system employed is the one implemented at the Coriolis data center to produce the weekly fields of temperature and salinity, and the key data are the analysis residuals. The impacts of the various sensor errors are evaluated and twin experiments are performed to measure the system capacity in identifying these errors. It appears that for a typical data distribution, the analysis residuals extract 2/3 of the sensor error after a single analysis. The method has been applied on the full Argo Atlantic real-time dataset for the 2000–04 period (482 floats) and 15% of the floats were detected as having salinity drifts or offset. A second test was per...

On the Use of Satellite Altimeter Data in Argo Quality Control

Abstract Satellite altimeter measurements are used to check the quality of the Argo profiling floats time series. The method compares collocated sea level anomalies from altimeter measurements and dynamic height anomalies calculated from Argo temperature and salinity profiles for each Argo float time series. Different kinds of anomalies (sensor drift, bias, spikes, etc.) have been identified on some real-time but also delayed-mode Argo floats. About 4% of the floats should probably not be used until they are carefully checked and reprocessed by the principal investigators (PIs). The method appears to be very complementary to the existing quality control checks performed in real time or delayed mode. It could also be used to quantify the impact of the adjustments made in delayed mode on the pressure, temperature, and salinity fields.