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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Comparison of Satellite-Derived Sea Surface Temperature and Sea Surface Salinity Gradients Using the Saildrone California/Baja and North Atlantic Gulf Stream Deployments

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Author(s):
Vazquez-Cuervo, Jorge [1, 2] ; Gomez-Valdes, Jose [3] ; Bouali, Marouan [4]
Total Authors: 3
Affiliation:
[1] CALTECH, Jet Prop Lab, 4800 Oak Grove Dr, Pasadena, CA 91109 - USA
[2] 4800 Oak Grove Dr M-S 300-323, Pasadena, CA 91109 - USA
[3] Ctr Sci Res & Higher Educ Ensenada, Phys Oceanog Dept, Ensenada 22860, Baja California - Mexico
[4] Univ Sao Paulo, Inst Oceanog, BR-05508120 Sao Paulo - Brazil
Total Affiliations: 4
Document type: Journal article
Source: REMOTE SENSING; v. 12, n. 11 JUN 2020.
Web of Science Citations: 2
Abstract

Validation of satellite-based retrieval of ocean parameters like Sea Surface Temperature (SST) and Sea Surface Salinity (SSS) is commonly done via statistical comparison with in situ measurements. Because in situ observations derived from coastal/tropical moored buoys and Argo floats are only representatives of one specific geographical point, they cannot be used to measure spatial gradients of ocean parameters (i.e., two-dimensional vectors). In this study, we exploit the high temporal sampling of the unmanned surface vehicle (USV) Saildrone (i.e., one measurement per minute) and describe a methodology to compare the magnitude of SST and SSS gradients derived from satellite-based products with those captured by Saildrone. Using two Saildrone campaigns conducted in the California/Baja region in 2018 and in the North Atlantic Gulf Stream in 2019, we compare the magnitude of gradients derived from six different GHRSST Level 4 SST (MUR, OSTIA, CMC, K10, REMSS, and DMI) and two SSS (JPLSMAP, RSS40km) datasets. While results indicate strong consistency between Saildrone- and satellite-based observations of SST and SSS, this is not the case for derived gradients with correlations lower than 0.4 for SST and 0.1 for SSS products. (AU)

FAPESP's process: 17/04887-0 - Estimation of high resolution Sea Surface Temperature (SST) fields using multi-sensor satellite observations
Grantee:Marouan Bouali
Support Opportunities: Research Grants - Young Investigators Grants
FAPESP's process: 18/00528-9 - Estimation of high resolution sea surface temperature (SST) fields using multi-sensor satellite observations
Grantee:Marouan Bouali
Support Opportunities: Scholarships in Brazil - Young Researchers