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A New Global Sea Surface Salinity and Density Dataset From Multivariate Observations (1993–2016)
- 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.
- Subjects :
- Multivariate statistics
in situ and satellite data
010504 meteorology & atmospheric sciences
lcsh:QH1-199.5
0211 other engineering and technologies
Climate change
Ocean Engineering
02 engineering and technology
Aquatic Science
multivariate optimal interpolation
lcsh:General. Including nature conservation, geographical distribution
Oceanography
01 natural sciences
global datasets
CMEMS
sea surface salinity
mesoscale resolving
lcsh:Science
021101 geological & geomatics engineering
0105 earth and related environmental sciences
Water Science and Technology
Global and Planetary Change
sea surface density
Salinity
Ocean dynamics
Sea surface temperature
Climatology
Temporal resolution
Environmental science
Satellite
lcsh:Q
Interpolation
Subjects
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