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A New Global Sea Surface Salinity and Density Dataset From Multivariate Observations (1993–2016)

Authors :
Bruno Buongiorno Nardelli
Rosalia Santoleri
R. Droghei
Source :
Frontiers in Marine Science, Vol 5 (2018), Frontiers in Marine Science 5 (2018). doi:10.3389/fmars.2018.00084, info:cnr-pdr/source/autori:Droghei, Riccardo; Nardelli, Bruno Buongiorno; Santoleri, Rosalia/titolo:A New Global Sea Surface Salinity and Density Dataset From Multivariate Observations (1993-2016)/doi:10.3389%2Ffmars.2018.00084/rivista:Frontiers in Marine Science/anno:2018/pagina_da:/pagina_a:/intervallo_pagine:/volume:5
Publication Year :
2018
Publisher :
Frontiers Media S.A., 2018.

Abstract

Monitoring sea surface salinity (SSS) and density variations is crucial to investigate the global water cycle and the ocean dynamics, and to analyse how they are impacted by climate change. Historically, ocean salinity and density have suffered a poor observational coverage, which hindered an accurate assessment of their surface patterns, as well as of associated space and time variability and trends. Different approaches have thus been proposed to extend the information obtained from sparse in situ measurements and provide gap-free fields at regular spatial and temporal resolution, based on the combination of in situ and satellite data. In the framework of the Copernicus Marine Environment Monitoring Service, a daily (weekly sampled) global reprocessed dataset at 1/4 degrees x 1/4 degrees resolution has been produced by modifying a multivariate optimal interpolation (OI) technique originally developed within MyOcean project. The algorithm has been applied to in situ salinity/density measurements covering the period from 1993 to 2016, using satellite sea surface temperature differences to constrain the surface patterns. This improved algorithm and the new dataset are described and validated here with holdout approach and independent data.

Details

Language :
English
ISSN :
22967745
Volume :
5
Database :
OpenAIRE
Journal :
Frontiers in Marine Science
Accession number :
edsair.doi.dedup.....ff4432a83d7f01b8f8ddce841d499416
Full Text :
https://doi.org/10.3389/fmars.2018.00084/full