@article{fdi:010073204,
  title = {{N}ew {SMOS} {S}ea {S}urface {S}alinity with reduced systematic errors and improved variability},
  author = {{B}outin, {J}. and {V}ergely, {J}. {L}. and {M}archand, {S}. and {D}'{A}mico, {F}. and {H}asson, {A}. and {K}olodziejczyk, {N}. and {R}eul, {N}. and {R}everdin, {G}. and {V}ialard, {J}{\'e}r{\^o}me},
  editor = {},
  language = {{ENG}},
  abstract = {{S}alinity observing satellites have the potential to monitor river fresh-water plumes mesoscale spatio-temporal variations better than any other observing system. {I}n the case of the {S}oil {M}oisture and {O}cean {S}alinity ({SMOS}) satellite mission, this capacity was hampered due to the contamination of {SMOS} data processing by strong land sea emissivity contrasts. {K}olodziejczyk et al. (2016) (hereafter {K}2016) developed a methodology to mitigate {SMOS} systematic errors in the vicinity of continents, that greatly improved the quality of the {SMOS} {S}ea {S}urface {S}alinity ({SSS}). {H}ere, we find that {SSS} variability, however, often remained underestimated, such as near major river mouths. {W}e revise the {K}2016 methodology with: a) a less stringent filtering of measurements in regions with high {SSS} natural variability (inferred from {SMOS} measurements) and b) a correction for seasonally-varying latitudinal systematic errors. {W}ith this new mitigation, {SMOS} {SSS} becomes more consistent with the independent {SMAP} {SSS} close to land, for instance capturing consistent spatio-temporal variations of low salinity waters in the {B}ay of {B}engal and {G}ulf of {M}exico. {T}he standard deviation of the differences between {SMOS} and {SMAP} weekly {SSS} is < 0.3 pss in most of the open ocean. {T}he standard deviation of the differences between 18 day {SMOS} {SSS} and 100-km averaged ship {SSS} is 0.20 pss (0.24 pss before correction) in the open ocean. {E}ven if this standard deviation of the differences increases closer to land, the larger {SSS} variability yields a more favorable signal-to-noise ratio, with r(2) between {SMOS} and {SMAP} {SSS} larger than 0.8. {T}he correction also reduces systematic biases associated with man-made {R}adio {F}requency {I}nterferences ({RFI}), although {SMOS} {SSS} remains more impacted by {RFI} than {SMAP} {SSS}. {T}his newly-processed dataset will allow the analysis of {SSS} variability over a larger than 8 years period in regions previously heavily influenced by land-sea contamination, such as the {B}ay of {B}engal or the {G}ulf of {M}exico.},
  keywords = {{SMOS} ; {S}ea {S}urface {S}alinity ; {SMAP} ; {ATLANTIQUE} ; {PACIFIQUE} ; {OCEAN} {INDIEN} ; {GANGE} ; {BRAHMAPOUTRE} ; {BENGALE} {GOLFE} ; {MISSISSIPPI} ; {MEXIQUE} {GOLFE} ; {CONGO} {FLEUVE} ; {NIGER} {FLEUVE} ; {AMAZONE}},
  booktitle = {},
  journal = {{R}emote {S}ensing of {E}nvironment},
  volume = {214},
  numero = {},
  pages = {115--134},
  ISSN = {0034-4257},
  year = {2018},
  DOI = {10.1016/j.rse.2018.05.022},
  URL = {https://www.documentation.ird.fr/hor/fdi:010073204},
}