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  • 1
    Publication Date: 2022-10-26
    Description: © The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Yu, L. Variability and uncertainty of satellite sea surface salinity in the subpolar North Atlantic (2010-2019). Remote Sensing, 12(13), (2020): 2092, doi:10.3390/rs12132092.
    Description: Satellite remote sensing of sea surface salinity (SSS) in the recent decade (2010–2019) has proven the capability of L-band (1.4 GHz) measurements to resolve SSS spatiotemporal variability in the tropical and subtropical oceans. However, the fidelity of SSS retrievals in cold waters at mid-high latitudes has yet to be established. Here, four SSS products derived from two satellite missions were evaluated in the subpolar North Atlantic Ocean in reference to two in situ gridded products. Harmonic analysis of annual and semiannual cycles in in situ products revealed that seasonal variations of SSS are dominated by an annual cycle, with a maximum in March and a minimum in September. The annual amplitudes are larger (〉0.3 practical salinity scale (pss)) in the western basin where surface waters are colder and fresher, and weaker (~0.06 pss) in the eastern basin where surface waters are warmer and saltier. Satellite SSS products have difficulty producing the right annual cycle, particularly in the Labrador/Irminger seas where the SSS seasonality is dictated by the influx of Arctic low-salinity waters along the boundary currents. The study also found that there are basin-scale, time-varying drifts in the decade-long SMOS data records, which need to be corrected before the datasets can be used for studying climate variability of SSS
    Description: This research was funded by NASA Ocean Salinity Science Team (OSST) activities through Grant 80NSSC18K1335.
    Keywords: Sea surface salinity ; Subpolar North Atlantic ; SMAP ; SMOS ; Argo ; Harmonic analysis ; Seasonal and interannual variations
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 2
    Publication Date: 2022-10-26
    Description: © The Author(s), 2021. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Bingham, F. M., Brodnitz, S., & Yu, L. Sea surface salinity seasonal variability in the tropics from satellites, gridded in situ products and mooring observations. Remote Sensing, 13(1), (2021): 110, doi:10.3390/rs13010110.
    Description: Satellite observations of sea surface salinity (SSS) have been validated in a number of instances using different forms of in situ data, including Argo floats, moorings and gridded in situ products. Since one of the most energetic time scales of variability of SSS is seasonal, it is important to know if satellites and gridded in situ products are observing the seasonal variability correctly. In this study we validate the seasonal SSS from satellite and gridded in situ products using observations from moorings in the global tropical moored buoy array. We utilize six different satellite products, and two different gridded in situ products. For each product we have computed seasonal harmonics, including amplitude, phase and fraction of variance (R2). These quantities are mapped for each product and for the moorings. We also do comparisons of amplitude, phase and R2 between moorings and all the satellite and gridded in situ products. Taking the mooring observations as ground truth, we find general good agreement between them and the satellite and gridded in situ products, with near zero bias in phase and amplitude and small root mean square differences. Tables are presented with these quantities for each product quantifying the degree of agreement.
    Description: This research was funded by the National Aeronautics and Space Administration under grant number 80NSSC18K1322.
    Keywords: Sea surface salinity ; Seasonal variability ; Satellite validation ; Harmonic analysis ; Mooring observations
    Repository Name: Woods Hole Open Access Server
    Type: Article
    Location Call Number Limitation Availability
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