4.7 Article

Validating Salinity from SMAP and HYCOM Data with Saildrone Data during EUREC4A-OA/ATOMIC

Journal

REMOTE SENSING
Volume 14, Issue 14, Pages -

Publisher

MDPI
DOI: 10.3390/rs14143375

Keywords

saildrone; salinity; Soil Moisture Active Passive (SMAP); Hybrid Coordinate Ocean Model (HYCOM); EUREC(4)A; ATOMIC; physical oceanography; remote sensing; air-sea interactions

Funding

  1. NASA Physical Oceanography grant [80NSSC20K1003]
  2. European Research Council (ERC)
  3. Max Planck Society (MPG)
  4. German Research Foundation (DFG)
  5. National Ocean Partnership Program
  6. Office of Naval Research
  7. German Meteorological Weather Service (DWD)
  8. German Aerospace Center (DLR)
  9. U.S. Navy

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This study utilized saildrone uncrewed surface vehicles to validate satellite and model salinity data in the Western Tropical Atlantic and found fine-scale salinity variability that was not captured by the satellite and model products. These findings will aid in the improvement of numerical weather prediction and climate models.
The 2020 'Elucidating the role of clouds-circulation coupling in climate-Ocean-Atmosphere' (EUREC(4)A-OA) and the 'Atlantic Tradewind Ocean-Atmosphere Mesoscale Interaction Campaign' (ATOMIC) campaigns focused on improving our understanding of the interaction between clouds, convection and circulation and their function in our changing climate. The campaign utilized many data collection technologies, some of which are relatively new. In this study, we used saildrone uncrewed surface vehicles, one of the newer cutting edge technologies available for marine data collection, to validate Level 2 and Level 3 Soil Moisture Active Passive (SMAP) satellite and Hybrid Coordinate Ocean Model (HYCOM) sea surface salinity (SSS) products in the Western Tropical Atlantic. The saildrones observed fine-scale salinity variability not present in the lower-spatial resolution satellite and model products. In regions that lacked significant small-scale salinity variability, the satellite and model salinities performed well. However, SMAP Remote Sensing Systems (RSS) 70 km generally outperformed its counterparts outside of areas with submesoscale SSS variation, whereas RSS 40 km performed better within freshening events such as a fresh tongue. HYCOM failed to detect the fresh tongue. These results will allow researchers to make informed decisions regarding the most ideal product and its drawbacks for their applications in this region and aid in the improvement of mesoscale and submesoscale SSS products, which can lead to the refinement of numerical weather prediction (NWP) and climate models.

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