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Estimation of high resolution Sea Surface Temperature (SST) fields using multi-sensor satellite observations


Accurate estimation of Sea Surface Temperature (SST) from satellite observations plays a pivotal role in a variety of applications. Ocean and atmospheric models as well as numerical weather prediction systematically use as input, gap free SST fields derived from SST analysis techniques. Most SST analysis currently run by oceanographic and meteorological operational agencies rely on the seminal Optimum Interpolation (OI) technique. Despite its robust statistical foundation, OI suffers from many limitations that lead to level 4 SST fields with significant amounts of blur. Consequently, SST analysis based on OI schemes are unable to capture ocean small scale structures that are typically seen in high resolution level 2 SST imagery derived from infrared satellite instruments. Given the growing importance of sub-mesoscale processes in the study of ocean dynamics and its interaction with the atmosphere, innovative research is needed to estimate high resolution gap free SST from multiple satellite missions, without any of the limitations of OI. In this project, we aim to develop a new SST analysis methodology able to produce SST fields that are both statistically accurate and geometrically consistent, i.e., able to preserve ocean small scale features. (AU)

Scientific publications
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
PEREIRA, F.; BOUALI, M.; POLITO, P. S.; DA SILVEIRA, I. C. A.; CANDELLA, R. N. Discrepancies between satellite-derived and in situ SST data in the Cape Frio Upwelling System, Southeastern Brazil (23 & x2da;S). REMOTE SENSING LETTERS, v. 11, n. 6, p. 555-562, JUN 2 2020. Web of Science Citations: 0.
VAZQUEZ-CUERVO, JORGE; GOMEZ-VALDES, JOSE; BOUALI, MAROUAN. Comparison of Satellite-Derived Sea Surface Temperature and Sea Surface Salinity Gradients Using the Saildrone California/Baja and North Atlantic Gulf Stream Deployments. REMOTE SENSING, v. 12, n. 11 JUN 2020. Web of Science Citations: 2.
BOUALI, M.; POLITO, P. S.; SATO, O. T.; VAZQUEZ-CUERVO, J. On the use of NLSST and MCSST for the study of spatio-temporal trends in SST gradients. REMOTE SENSING LETTERS, v. 10, n. 12, p. 1163-1171, DEC 2 2019. Web of Science Citations: 2.

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