Toward SMOS L4 SSS Products: Improving L3 SSS With Auxiliary SSS Data

The Soil Moisture and Ocean Salinity (SMOS) mission will provide for the first time satellite observations of sea-surface salinity (SSS). At level 3 (L3) of the SMOS processing chain, a large amount of SSS data obtained by the satellite will be summarized in gridded products with the aim of synthesizing the information and reducing the error of individual SSS observations. A further improvement of SSS maps could come from the combination of L3 products with auxiliary SSS data from Argo buoys, ships of opportunity, or moored oceanographic stations. In this paper, we investigate the benefits of combining SMOS data with different auxiliary data sets. We show that the greatest error reductions come from the increase in the spatial-data coverage, even if the temporal coverage is scarce. Conversely, redundant information (i.e., many observations close to each other) or very localized measurements, even if they have a high temporal resolution, do not provide a significant improvement of the SSS products. We show that the most useful auxiliary data in terms of improving the analysis accuracy are those obtained in areas where SMOS data are noisier or, as a second choice, where the SSS field has a large variance. We also show that for areas with the same error in the L3 product (whatever the source of those errors is), it is more advisable to place the auxiliary observations in areas with longer correlation length scales.