A new high‐resolution sea surface salinity (SSS) analysis has been produced using Aquarius satellite observations from September 2011 to June 2015. The motivation for the new product is twofold: to produce Level‐4 SSS analysis that is consistent with existing in situ observations such as from Argo profile data, and to reduce the large‐scale satellite biases that have existed in all versions of the standard Level‐3 Aquarius products. The new product is a weekly SSS analysis on a nearly global 0.5° grid. The analysis method is optimum interpolation (OI) that takes into account analyzed errors of the observations, specific to the Aquarius instrument. The method also includes a large‐scale correction for satellite biases, filtering of along‐track SSS data prior to OI, and the use of realistic correlation scales of SSS anomalies. All these features of the analysis are shown to result in more accurate SSS maps. In particular, the method reduces the effects of relative biases between the Aquarius beams and eliminates most of the large‐scale, space‐varying, and time‐varying satellite biases relative to in situ data, including spurious annual signals. Statistical comparison between the weekly OI SSS maps and concurrent buoy data demonstrates that the global root‐mean‐square error of the analysis is smaller than 0.2 pss for nearly all weeks over the ∼4 year period of comparison. The utility of the OI SSS analysis is also exemplified by the derived patterns of regional SSS variability.

Aquarius was the first NASA satellite to observe the sea surface salinity (SSS) over the global ocean. The mission successfully collected data from 25 August 2011 to 7 June 2015. The Aquarius project released its final version (Version-5) of the SSS data product in December 2017. The purpose of this paper is to summarize the validation results from the Aquarius Validation Data System (AVDS) and other statistical methods, and to provide a general view of the Aquarius SSS quality to the users. The results demonstrate that Aquarius has met the mission target measurement accuracy requirement of 0.2 psu on monthly averages on 150 km scale. From the triple point analysis using Aquarius, in situ field and Hybrid Coordinate Ocean Model (HYCOM) products, the root mean square errors of Aquarius Level-2 and Level-3 data are estimated to be 0.17 psu and 0.13 psu, respectively. It is important that caution should be exercised when using Aquarius salinity data in areas with high radio frequency interference (RFI) and heavy rainfall, close to the coast lines where leakage of land signals may significantly affect the quality of the SSS data, and at high-latitude oceans where the L-band radiometer has poor sensitivity to SSS.

Using newly available satellite observations of Sea Surface Salinity (SSS), we provide, for the first time, a detailed and synoptic view of the spatiotemporal variability of SSS in the South China Sea (SCS). The results depict the SCS as a very dynamic region exhibiting variability over a broad range of time scales, from intra‐seasonal to inter‐annual, with the seasonal cycle dominating (∼47% of the total SSS variance). The seasonal distribution of SSS has considerable latitudinal variations: the strongest variance across the southern SCS (∼5‐12^oN), weaker in the northern part of the sea (north of ∼18^oN), with the weakest seasonal SSS variability in between. The factors controlling patterns of seasonal SSS distribution are closely related to both the external freshwater forcing and ocean processes over the entire SCS monsoon system. The most active inter‐annual SSS variability is found in the northeastern and eastern parts of the SCS, as well as the adjacent western Pacific. A significant basin‐wide salinification began in summer of 2015, peaked in spring of 2016 with the averaged amplitude of up to 0.5 PSU, and maintained until the fall of 2016. Such persistent salinification during 2015‐2016 following a strong El Nino event can be largely modulated by El Nino‐related atmospheric and oceanic dynamics. The intra‐seasonal variability was found to be surprisingly weak throughout the SCS (the standard deviation < 0.2 PSU), except for a few regions near the coast where it is likely related to the intra‐seasonal variability in the monsoon rainfall and subsequent variations in river runoff.

Argo profiling floats and L‐band passive microwave remote sensing have significantly improved the global sampling of sea surface salinity (SSS) in the past 15 years, allowing the study of the range of SSS seasonal variability using concurrent satellite and in situ platforms. Here, harmonic analysis was applied to four 0.25° satellite products and two 1° in situ products between 2016 and 2018 to determine seasonal harmonic patterns. The 0.25° World Ocean Atlas (WOA) version 2018 was referenced to help assess the harmonic patterns from a long‐term perspective based on the 3‐year period. The results show that annual harmonic is the most characteristic signal of the seasonal cycle, and semiannual harmonic is important in regions influenced by monsoon and major rivers. The percentage of the observed variance that can be explained by harmonic modes varies with products, with values ranging between 50% and 72% for annual harmonic and between 15% and 19% for semiannual harmonic. The large spread in the explained variance by the annual harmonic reflects the large disparity in nonseasonal variance (or noise) in the different products. Satellite products are capable of capturing sharp SSS features on meso‐ and frontal scales and the patterns agree well with the WOA 2018. These products are, however, subject to the impacts of radiometric noises and are algorithm dependent. The coarser‐resolution in situ products may underrepresent the full range of high‐frequency small scale SSS variability when data record is short, which may have enlarged the explained SSS variance by the annual harmonic.