Presented at the 2015 Aquarius/SAC-D Science Team MeetingAquarius/SACD was the first L-band remote sensing mission combining the active and passive instruments for global mapping of ocean surfaces. The radiometer data are sensitive to the change of sea surface salinity, but also subject to the influence of ocean surface roughness. The Aquarius radar observations, essentially insensitive to the ocean salinity, would provide the characterization of surface roughness, which could be impacted by ocean surface wind, wave, and boundary layer stability. We will describe the geophysical model functions (GMF) for radiometer and radar data derived from close to four years of Aquarius data and their applications to combined active and passive retrieval of sea surface salinity and wind. The NASA's Soil Moisture Active Passive (SMAP) mission, launched in January 2015, includes a polarimetric radiometer and a multi-polarization synthetic aperture radar, which share a single 6-m rotating mesh antenna, producing a fixed incidence angle conical scan at 40â°[;] across a 1000-km swath and a 2-3 day global revisit. We found that the Aquarius GMFs provide strikingly accurate representation of the SMAP data for ocean observations, even at extreme high winds ([>]30 m/s wind speed), although their spatial resolutions differ by about a factor of two to three. We have applied the Aquarius GMFs for retrieval of SSS and ocean surface wind from the SMAP data. The retrieval algorithm leverages the QuikSCAT/Rapidscat algorithms to account for SMAP's two-look geometry (fore and aft looks from the conical scan) and dual-polarization observations of SMAP. The retrieved wind speed from SMAP for hurricanes has a remarkable agreement with the maximum wind speeds for hurricanes or typhoons, demonstrating the applicability of Aquarius GMFs for a wide range of wind speed for remote sensing of sea surfaces. This paper will provide the latest salinity and wind retrieval results from the Aquarius and SMAP missions. The Aquarius data demonstrate the feasibility of ocean surface salinity remote sensing, but also provide the basis of using L-band microwave data for severe weather monitoring.