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Satellite Sea Surface Salinity Monitor

Level 2 Level 3 Level 4
Aquarius/ADPS (NASA)
Aquarius/CAP (JPL)

NCEI Level 2
SSS Quality Monitor
Under Development:
Aquarius/ADPS (NASA)
Aquarius/CAP (JPL)
Aquarius (NOAA)
Under Development:

Recent Highlights

Upcoming Meetings:

  • SMOS-MODE: Working Groups + Management Committee (12-13 Jun 2014, Naples, Italy)
  • Aquarius/SAC-D Ocean Salinity Science Team Meeting (11-14 Nov 2014, Seattle, WA)
  • ESA Ocean Salinity Science and Salinity Remote Sensing Workshop (26-28 Nov 2014, Exeter, UK)
  • AGU Fall Meeting: Special session on scientific accomplishments from the Aquarius 3-year prime mission

4SQM Objectives

  • Serve as a community tool for near real-time analytical and statistical comparison of major global SSS products

What 4SQM does?

  • Analytical and statistical comparison between satellite SSS products & in situ data
  • Analytical and statistical intercomparison of satellite SSS products


  • Global quality control and statistical checks for self- and cross-consistency using maps, histograms, time series, and dependencies of SSS differences

Contact Us

This site is being incrementally developed

Functionality and data served by this site are continually updated and extended; please check back soon for new content.


Data Providers

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Data and images displayed on STAR's websites are for experimental use only and are not official operational NOAA products.  Read more >


Global Quality Control

Even a small fraction of extreme values (outliers) can affect the Gaussian parameters, especially the higher order moments. Therefore, along with the conventional central moments (mean, standard deviation), their robust counterparts (median, robust standard deviation) are also calculated and used for outlier removal. Here, RSD is defined as: (3rd quartile - 1st quartile)/1.38 (cf., Tietjen, 1986). The outliers may be due to contaminant points in TS (satellite SST) or TR (reference SST), or both. Or, they may be caused by space-time mismatch in the areas of high SST gradients, e.g., at warm or cold oceanic fronts.

Identification and removal of outliers is important for QC. A common approach is removing data points beyond the "mean ± 4×StdDev" range or by using a fixed cut-off. However, conventional central moments themselves may be contaminated by outliers and a "fixed cut-off" is not an objective approach. In L2-SQUAM and L3-SQUAM, the screening is done using the "median ± 4×RSD" criterion (c.f., Merchant & Harris, 1999). Gaussian statistics are calculated 2 ways: before and after removing outliers. The effects can be seeing using the toggle button in the L2 and L3 histogram & time series.