iQuam was developed at NOAA Center for Satellite Application and Research (STAR). It performs three major functions, in near-real time:

  • Quality control (QC) of in situ SSTs
  • Monitoring of QCed in situ SSTs online
  • Serving of reformatted in situ SST data with quality level and flags appended

The real time processing is performed as follows

from Sep 1981 - Mar 2010, ICOADS data was used instead of GTS.

Ship and buoy (drifters and moorings) data come from ICOADS, NCEP or FNMOC. Real time data are refreshed every 24hrs and ingested into iQuam with a latency of 4 hours on average. FNMOC, IMOS, HR-Drifter, ICOADS and ARGO data come with their own quality flags (QFs), which are preserved in the iQuam output files. In general, QFs from data sources are not used in the iQuam QC. Also, a blacklist QF based on the Copernicus Maritime Service (CMS) blacklist compiled by Meteo France is reported in iQuam output files but not used in iQuam QC. ARGO QFs are used to select the best quality near-surface data from above 10m depth, which are further subjected to the standard iQuam QC. ARGO data includes a greylist, which is is also reported in QFs but not used in QC. A blacklist for drifters, compiled by AOML, is also used. Again, this information is stored in QFs but not used in the QC.

iQuam QC is then performed and corresponding QFs are appended (but not applied) to in situ data. All in situ data are preserved in iQuam files, and no data excluded based on iQuam or external QFs. QCed in situ data, stored in self-described NetCDF format, are available via HTTP or FTP.

Currently, all processing of the previous month's data is completed by the 15th day of the following month.

The QC algorithm implemented in iQuam consists of different steps of processing which can be categorized into five groups:

  • Prescreening - Processing which precedes QC checks and is aimed at resolving known data-specific historical problems (e.g., removing of duplicates and wrongly formatted data).
  • Plausibility check - Analyzes individual fields in the data records and relationships between them to verify their plausibility (e.g., geolocation check).
  • Internal consistency check - Checks different measurements from the same platform for internal consistency (e.g., tracking and SST spike checks).
  • Mutual consistency check - Checks nearby measurements from different platforms for consistency (also known as 'cross-platform' or 'buddy check').
  • External consistency check - Checks in situ SST for consistency with reference (first-guess) field (also called 'reference check' or 'background check')

Inherited QC information - QC information from external sources, e.g. ICOADS QC, Argo QC and buoy blacklists - is reported in iQuam files but not used in setting up the iQuam QC.

In addition to some basic processing steps, the 5 major steps are duplicate removal (DR), platform track check (TC), SST spike check (SC), reference check (RC) and cross-platform check (XC). Algorithms for the reference check and the cross-platform check are employed from the currently existing Bayesian QC method [Lorenc and Hammon, 1988; Ingleby and Huddleston, 2007] with minor modifications. Details can be found in the following publications:

  • Xu, F. and A. Ignatov, 2013: in situ SST quality monitor (iQuam), JTECH, submitted. download
  • Ingleby, B. and M. Huddleston, 2007: Quality control of ocean temperature and salinity profiles - historical and real-time data, J Marine Systems, 65, 158-175.
  • Lorenc, A.C. and O. Hammon, 1988: Objective quality control of observations using Bayesian methods. Theory, and a practical implementation. Q. J. R. Meteorol. Soc. 114, 515-543.

Flowchart of QC algorithm is as follows.

Monitoring of statistics of both QC and SST anomalies are also provided in iQuam. It includes monthly global maps, monthly QC/SST statistics, long-term time-series and individual platform statistics (track map, SST time series and performance history). In most cases, daily maps and statistics are available as well.

Interfaces are shown below.

The interface for platform monitoring:

Time series of monthly statistics (SD of Pathfinder minus in situ SST) before (left) and after (right) QC: