To address the need for a consistent, continuous, long-term, high-resolution sea surface salinity (SSS) dataset for ocean research and applications, a trial SSS analysis is produced in the eastern tropical Pacific from multi-satellite observations. The new SSS data record is a merging of observations from two NASA satellite missions and covers the period from September 2011 to August 2018. The beginning segment, covering the period from September 2011 to June 2015, utilizes Aquarius SSS data and is based on the optimum interpolation analysis (OI SSS) developed at the University of Hawaii (Melnichenko et al., 2016). The analysis is produced on a 0.25-degree grid and uses a dedicated bias-correction algorithm to correct the satellite retrievals for large-scale biases with respect to in-situ data. The time series is continued with the Soil Moisture Active Passive (SMAP) satellite-based SSS data provided by Remote Sensing Systems (RSS). To ensure consistency and continuity in the data record, SMAP SSS fields are adjusted using a set of optimally designed spatial filters and in-situ (primarily Argo) data to remove large-scale biases, and, at the same time, reduce small-scale noise. The consistency and accuracy of the new SSS data set is evaluated against in-situ salinity from Argo and TAO buoy array.A more detailed description of the Aquarius/SMAP SSS dataset and the evaluation statistics can be found in Melnichenko et al., 2018.

The Aquarius/SMAP SSS analysis in the eastern tropical Pacific (170-70°W, 25°S-25°N) is produced on a uniform grid with 0.25° resolution and temporal resolution of 4 days for the period September 2011 - August 2018.

Digital data of the analysis (netCDF files) are available here.

File Naming Convention:

- SSS_Aquarius_SMAP_Combined_EEP_v50_v30_weekly_YYYY_MM_DD,

where

- [YYYY] is the year,

- [MM] is the month, and

- [DD] is the day of the weekly SSS map in the file.