Effect of Sea Water Dielectric Constant Model and Sea Surface Temperature Ancillary Data on Remote Sensing of Sea Surface Salinity
[13-Nov-2014] Dinnat, E., Boutin, J., Xiaobin, Y., and Le Vine, D.
Presented at the 2014 Aquarius/SAC-D Science Team Meeting
ESA's Soil Moisture and Ocean Salinity (SMOS) and NASA's Aquarius use L-band (1.4 GHz) radiometers to measure emission from the sea surface and retrieve SSS. Significant differences in SSS retrieved by both sensors are observed, with SMOS SSS being generally lower than Aquarius SSS, except for very cold waters where SMOS SSS is the highest overall. Differences are mostly between -1 psu and +1 psu (psu, practical salinity unit), with a significant regional and latitudinal dependence. We investigate the impact of the vicarious calibration and retrieval algorithm used by both mission on these differences.
One notable difference between the two missions is the sea water dielectric constant model. SMOS uses the model by Klein and Swift (1977)  and Aquarius uses the model by Meissner and Wentz (2012) . The dielectric constant model is used: 1/ to calibrate the instruments by comparing radiometric measurements to forward model simulations, and 2/ to invert SSS from surface brightness temperature (Tb). In order to assess the impact of the dielectric constant model on the SSS difference, we reprocess the Aquarius data using the model used for SMOS. Specifically, we use the Klein and Swift model for the reference ocean used in the calibration of Aquarius; then we used it again, keeping all other factors the same, to perform the inversion to obtain SSS.
Another important difference between both missions algorithms is the ancillary product used for sea surface temperature (SST). Aquarius uses the daily optimally interpolated (OI) SST from NOAA, that relies on in situ (ship and buoys) measurements and satellite data from the Advanced Very High Resolution Radiometer (AVHRR) infrared (IR) sensor . We compare this SST product to the Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) produced by the Met Office  that uses microwave sensors in addition to IR sensor. Similarly to what was done for the dielectric constant study, we reprocess the Aquarius data, including the calibration and retrieval steps, using the OSTIA SST instead of the NOAA OI SST.
We will present the impact of the dielectric constant model and the SST product on the differences between SMOS and Aquarius and show comparisons with in situ data from the Argo global network of free-drifting floats.
 L. A. Klein and C. T. Swift, An improved model for the dielectric constant of sea water at microwave frequencies, IEEE Transactions on Antennas and Propagation, vol. AP-25, no. 1, pp. 104-111, 1977.
 T. Meissner and F. J. Wentz 2012, The Emissivity of the Ocean Surface Between 6 and 90 GHz Over a Large Range of Wind Speeds and Earth Incidence Angles, IEEE Trans. Geosci. Remote Sens., vol. 50, no. 8, pp. 3004-3026, Aug. 2012.
 R. Reynolds et al., Daily High-Resolution-Blended Analyses for Sea Surface Temperature, J. Climate, vol. 20, pp. 5473-5496, 2007.
 C. J. Donlon et al., The Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) system, Remote Sensing of Environment, vol. 116, pp. 140-158, Jan. 2012.