Deriving Sea Surface Salinity and Density Variations From Satellite and Aircraft Microwave Radiometer Measurements: Application to Coastal Plumes Using STARRS

摘要

Using brightness temperature $Tb$ measurements from L-band airborne microwave radiometers, with independent sea surface temperature (SST) observations, sea surface salinity (SSS) can be remotely determined with errors of about 1 psu in temperate regions. Nonlinearities in the relationship between $Tb$, SSS, and SST produce variations in the sensitivity of salinity $S$ to variations in $Tb$ and SST. Despite significant efforts devoted to SSS remote sensing retrieval algorithms, little consideration has been given to deriving density $D$ from remotely sensed SSS and SST. Density is related to $S$ and $T$ through the equation of state. It affects the ocean''s static stability and its dynamical response to forcings. By chaining together two empirical relationships (flat-sea emissivity and equation of state) to form an inversion algorithm for sea surface density (SSD) in terms of $Tb$ and SST, we develop a simple L-band SSD retrieval algorithm. We use this to investigate the sensitivity of SSD retrievals to observed $Tb$ and SST and infer errors in $D$ for typical sampling configurations of the airborne Salinity, Temperature, And Roughness Remote Scanner (STARRS) and satellite-borne Soil Moisture and Ocean Salinity (SMOS) and Aquarius radiometers. We then derive $D$ from observations of river plumes obtained using STARRS and demonstrate several oceanographic applications: the observations are used to study varia-tions in $T$ and $S$ effects on $D$ in the Mississippi plume, and the across-shelf density gradient is used to infer surface geostrophic shear and subsurface geostrophic current in the Plata plume. Future basin-scale applications of SSD retrievals from satellite-borne microwave radiometers such as SMOS and Aquarius are anticipated.