2022
DOI: 10.5194/essd-14-307-2022
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Improved BEC SMOS Arctic Sea Surface Salinity product v3.1

Abstract: Abstract. Measuring salinity from space is challenging since the sensitivity of the brightness temperature (TB) to sea surface salinity (SSS) is low (about 0.5 K psu−1), while the SSS range in the open ocean is narrow (about 5 psu, if river discharge areas are not considered). This translates into a high accuracy requirement of the radiometer (about 2–3 K). Moreover, the sensitivity of the TB to SSS at cold waters is even lower (0.3 K psu−1), making the retrieval of the SSS in the cold waters even more challen… Show more

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Cited by 19 publications
(25 citation statements)
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“…Salinity observations from remote sensing strongly rely on in situ data for calibration and quality control, and although great improvement was attained since the implementation of SSS observation networks, such as the Voluntary Observing Ships from the French SSS Observation Service (Alory et al., 2015), global coverage is far from being achieved. Therefore the community urges for better salinity observations, especially in high latitudes (Martínez et al., 2021; Vinogradova et al., 2019).…”
Section: Discussionmentioning
confidence: 99%
“…Salinity observations from remote sensing strongly rely on in situ data for calibration and quality control, and although great improvement was attained since the implementation of SSS observation networks, such as the Voluntary Observing Ships from the French SSS Observation Service (Alory et al., 2015), global coverage is far from being achieved. Therefore the community urges for better salinity observations, especially in high latitudes (Martínez et al., 2021; Vinogradova et al., 2019).…”
Section: Discussionmentioning
confidence: 99%
“…Exp0 assimilated all available altimeter data, SST, sea ice concentration, sea ice drift, T/S profiles, sea ice thickness, except any SMOS SSS products. ExpV2 and ExpV3 additionally assimilated V2.0 and V3.1 of SSS products from BEC, which were tested and retrieved by a series of algorithms considering the low temperature and sea ice cover in the Arctic (Olmedo et al, 2017;Martínez et al, 2022).…”
Section: Summary and Discussionmentioning
confidence: 99%
“…Using the quantitative SSS misfits (Table 2), the impact indexes at each subregion (S1 to S6) further indicates whether the misfits are significantly decreased or not. Outside of the central Arctic, the v2.0 SSS product loses the impacts in this system, but the V3.1 SSS brings more wider significant impacts around the Arctic, which clearly benefits from the related retrieval algorithms for the refined effective resolution (Martínez et al, 2022). However, in the region S6, the SSS in ExpV3 has no significant constraint on the misfits and only brings a reduction in the bias.…”
Section: Summary and Discussionmentioning
confidence: 99%
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