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Sea Surface Salinity Remote Sensing



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Autore: Yin Xiaobin Visualizza persona
Titolo: Sea Surface Salinity Remote Sensing Visualizza cluster
Pubblicazione: MDPI - Multidisciplinary Digital Publishing Institute, 2019
Descrizione fisica: 1 electronic resource (296 p.)
Soggetto non controllato: satellite salinity
one-dimensional (1D) aperture synthesis radiometer
smos
Gulf of Maine
retrieval errors
Aquarius
combined active/passive SSS retrieval algorithm
ocean surface roughness
upwelling
salt transport
quality assessment
sea ice
SMOS
microwave radiometry
Arctic Gateways
Aquarius satellite
validation
sea surface temperature
water transport
forward model
river discharge
sea surface salinity
remote sensing
retrieval algorithm
Water Cycle Observation Mission (WCOM)
SMAP
microwave remote sensing
alboran sea
surface velocity
Arctic Ocean
sea surface salinity (SSS)
coastal
brightness temperature (TB)
interferometric microwave imager (IMI)
Scotian Shelf
MICAP
different instrument configurations
bias characteristics
mediterranean sea
Gulf of Mexico
calibration
retroflections
Arctic ocean
salinity
Sea Surface Salinity
Arctic rivers
Argo
data processing
aquarius
ocean salinity
Aquarius Validation Data System (AVDS)
Persona (resp. second.): DinnatEmmanuel P
Sommario/riassunto: This Special Issue gathers papers reporting research on various aspects of remote sensing of Sea Surface Salinity (SSS) and the use of satellite SSS in oceanography. It includes contributions presenting improvements in empirical or theoretical radiative transfer models; mitigation techniques of external interference such as RFI and land contamination; comparisons and validation of remote sensing products with in situ observations; retrieval techniques for improved coastal SSS monitoring, high latitude SSS and the assessment of ocean interactions with the cryosphere; and data fusion techniques combining SSS with sea surface temperature (SST). New instrument technology for the future of SSS remote sensing is also presented.
Titolo autorizzato: Sea Surface Salinity Remote Sensing  Visualizza cluster
ISBN: 3-03921-077-7
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910367564803321
Lo trovi qui: Univ. Federico II
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