Preliminary validation of SMOS salinity products

I Encuentro de la Oceanografía Física Española (EOF), 13-15 de octubre 2010, BarcelonaThe Soil Moisture and Ocean Salinity mission (SMOS) from the European Space Agency, launched in November 2009, has initiated the era of satellite‐based salinity observations. However, because of the numerous geophysical contamination sources and the retrieval complexity, salinity products have a low signal‐to‐noise ratio at Level 2 (satellite swath‐based observations). Averaging data in space and time is expected to allow a reduction of the observational error down to mission requirements (0.1 psu) at Level 3 (global maps with regular distribution). However, robust, geophysical consistency is expected to be reached at Level 4, when the SMOS salinity data is combined with data from other sources as, for example, satellite sea surface temperature, surface winds, estimates of evaporation and precipitation, and even remotely‐sensed ocean color. At Level 3, salinity outputs are scrutinized on the basis of their temporal and spatial variability. A first objective is the detection of residual potential error patterns not detected at lower data processing levels (due to residual instrument calibration, external contributions from sun or galactic glint, and land contamination). Specific selection of environmental conditions is used to help distinguish the role of each factor. The second objective concerns the validation against average meridional distribution and global distribution maps. The results will help discerning other potential sources of bias coming from the salinity inversion algorithm and the imperfect forward empirical models and auxiliary information. The spatial patterns of departure from climatology are compared to spatial patterns of other geophysical parameters and anomalies. Other ongoing tasks include checking the consistency between the along‐track salinities at level 2 and the spatio‐temporal averages at level 3 provided by the operational Level 3/4 centre (CP34), and evaluating the expected variance reduction with increasing averaging windows. On the other hand, two strategies are foreseen at the SMOS‐Barcelona Expert Centre (SMOSBEC) to provide Level 4 salinity products: Data Fusion (combination of data from different sources to improve inferences for each product) and Data Assimilation (combination of data from different sources with a numerical model representing the dynamical evolution of the system). Preliminary results at Level 3 will be presented at the conference as well as the methodology planned for SSS Level 4 product development and validationPeer Reviewe