in situ SSTs are critical in satellite SST Cal/Val. In SST community, calibration means to derive coefficients for regression algorithm, and validation means to monitor and evaluate quality of satellite product. However, the quality of in situ SST are highly non-uniform due to several reasons. First, in situ data are measured by a large variety of sensors on different platforms, e.g. ships, drifting and mooring buoys. Second, extra errors are induced during transmission and processing. For buoys, they are often operated in hostile environment and some may be left unattended for long time. For Ships, the measurments may be impacted by human operations. Therefore, quality control (QC) is absolutely necessary before in situ data can be further used in Cal/Val.
A few erroneous measurements could corrupt the whole data set and thus significantly affect Cal/Val results. A demonstration is given below: the Standard Deviation (SD) of in situ SST minus Pathfinder SST (from satellite), before QC (top) and after QC (bottom). It clearly shows that removing only 2~4% report will significantly improve the quality of the data. Without QC, the data cannot be used in Cal/Val.
Time series of monthly statistics (SD of in situ minus Pathfinder) BEFORE QC:
Time series of monthly statistics (SD of in situ minus Pathfinder) AFTER QC:
Currently in remote sensing community, QC is usually overly simplistic and non-objective, e.g. ±2K wrt. climatology. On the other hand, QC can be much more sophisticated as usually done in meteorological Community. Such advanced QC is necessary because different types of errors should be handled in different ways and QC should be more robust to inaccurucies in the reference SST. QC algorithm employed by iQuam is described in algorithm tab.
