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Highlights Sea surface salinity retrieved from SMAP radiometer is validated with in situ data  SMAP achieved 0.2 PSU accuracy on a monthly basis in tropics comparing with Argo OI  SMAP can track large salinity changes occurred within a month consistent with buoy  SMAP SSS retrieved in Mediterranean sea and BOB assessed with ship TSG and Argo STS Highlights (for review) Abstract 11 12 Sea surface salinity (SSS) retrieved from SMAP radiometer measurements is validated 13 with in situ salinity measurements collected from Argo floats, tropical moored buoys and 14 ship-based thermosalinograph (TSG) data. SMAP SSS achieved accuracy of 0.2 PSU on a 15 monthly basis in comparison with Argo gridded data in the tropics and mid--16 latitudes. In tropical oceans, time series comparison of salinity measured at 1 m by 17 moored buoys indicates that SMAP can track large salinity changes occurred within a 18 month. Synergetic analysis of SMAP, SMOS and Argo data allows us to identify and 19 exclude erroneous jumps or drift in some real--time buoy data from assessment of 20 satellite retrieval. The resulting SMAP--buoy matchup analysis leads to an average 21 standard deviation of 0.22 PSU and correlation coefficient of 0.73 on weekly scale; the 22 average standard deviation reduced to 0.17 PSU and the correlation improved to 0.8 on 23 monthly scale. SMAP L3 daily maps reveals salty water intrusion from the Arabian Sea 24 into the Bay of Bengal during the Indian summer monsoon, consistent with the daily 25 *Manuscript Click here to download Manuscript: SMAP_SSS_validation_RSE.pdf 29

Satellite microwave sensors, both active scatterometers and passive radiometers, have been systematically measuring near-surface ocean winds for nearly 40 years, establishing an important legacy in studying and monitoring weather and climate variability. As an aid to such activities, the various wind datasets are being intercalibrated and merged into consistent climate data records (CDRs). The ocean wind CDRs (OW-CDRs) are evaluated by comparisons with ocean buoys and intercomparisons among the different satellite sensors and among the different data providers. Extending the OW-CDR into the future requires exploiting all available datasets, such as OSCAT-2 scheduled to launch in July 2016. Three planned methods of calibrating the OSCAT-2 measurements include 1) direct Ku-band intercalibration to QuikSCAT and RapidScat; 2) multisensor wind speed intercalibration; and 3) calibration to stable rainforest targets. Unfortunately, RapidScat failed in August 2016 and cannot be used to directly calibrate OSCAT-2. A particular future continuity concern is the absence of scheduled new or continuation radiometer missions capable of measuring wind speed. Specialized model assimilations provide 30-year long high temporal/spatial resolution wind vector grids that composite the satellite wind information from OW-CDRs of multiple satellites viewing the Earth at different local times.

Strengths and weakness of remotely sensed winds are discussed, along with the current capabilities for remotely sensing winds and stress. Future missions are briefly mentioned. The observational needs for a wide range of wind and stress applications are provided. These needs strongly support a short list of desired capabilities of future missions and constellations.

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