Abstract
Satellite observations of sea surface salinity (SSS) have been validated in a number of instances using different forms of in situ data, including Argo floats, moorings and gridded in situ products. Since one of the most energetic time scales of variability of SSS is seasonal, it is important to know if satellites and gridded in situ products are observing the seasonal variability correctly. In this study we validate the seasonal SSS from satellite and gridded in situ products using observations from moorings in the global tropical moored buoy array. We utilize six different satellite products, and two different gridded in situ products. For each product we have computed seasonal harmonics, including amplitude, phase and fraction of variance (R2). These quantities are mapped for each product and for the moorings. We also do comparisons of amplitude, phase and R2 between moorings and all the satellite and gridded in situ products. Taking the mooring observations as ground truth, we find general good agreement between them and the satellite and gridded in situ products, with near zero bias in phase and amplitude and small root mean square differences. Tables are presented with these quantities for each product quantifying the degree of agreement.
Highlights
Sea surface salinity (SSS) has been observed by satellite for over 10 years since the launch of the Soil Moisture and Ocean Salinity (SMOS; [1]) instrument in 2009
As illustration of Maps the method, we show the mooring data, harmonic fit, Scripps Institution of Oceanography (SIO) data
With the first harmonic amplitudes, we find that most satellite and gridded in situ products compare well with the moorings (Figure 9 and Table 2)
Summary
Sea surface salinity (SSS) has been observed by satellite for over 10 years since the launch of the Soil Moisture and Ocean Salinity (SMOS; [1]) instrument in 2009. Individual satellite measurements are compared with nearby in situ measurements such as individual Argo floats [4], or more commonly with gridded Argo products such as that of Roemmich et al [14] or the global Hybrid Coordinate Ocean Model (HYCOM) [3]. Problems exist with this type of comparison, . Gridded Argo products have their own uncertainty related to the sparse sampling and the gridding process [16]
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