Assimilation of satellite salinity for modelling the Congo River plume
File(s)remotesensing-12-00011-v3.pdf (3.28 MB)
Published version
Author(s)
Phillipson, Luke
Toumi, Ralf
Type
Journal Article
Abstract
Abstract:Satellite salinity data from the Soil Moisture and Ocean Salinity (SMOS) mission was recently enhanced, increasing the spatial extent near the coast that eluded earlier versions. In a pilot attempt we assimilate this data into a coastal ocean model (ROMS) using variational assimilation and for the first time, investigate the impact on the simulation of a major river plume (the Congo River). Four experiments were undertaken consisting of a control (without data assimilation) and5the assimilation of either sea surface height, SMOS and the combination of both. Several metrics specific to the plume were utilised, including the area of the plume, distance to the centre of mass, orientation and average salinity. The assimilation of SMOS and SMOS-SSH consistently produced the best results in the plume analysis. Argo float salinity profiles provided independent verification of the forecast. The SMOS or SMOS-SSH forecast produced the closest agreement for Argo profiles over the whole domain (outside and inside the plume) for three of four months analysed, improving over the control and a persistence baseline. The number of samples of Argo floats determined to be inside the plume were limited. Nevertheless, for the limited plume-detected floats the largest improvements were found for the SMOS or SMOS-SSH forecast for two of the four months.
Date Issued
2019-12-18
Date Acceptance
2019-12-15
Citation
Remote Sensing, 2019, 12 (11), pp.1-20
ISSN
2072-4292
Publisher
MDPI AG
Start Page
1
End Page
20
Journal / Book Title
Remote Sensing
Volume
12
Issue
11
Copyright Statement
c 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access
article distributed under the terms and conditions of the Creative Commons Attribution
(CC BY) license (http://creativecommons.org/licenses/by/4.0/).
article distributed under the terms and conditions of the Creative Commons Attribution
(CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Identifier
https://www.mdpi.com/2072-4292/12/1/11
Subjects
Science & Technology
Technology
Remote Sensing
SMOS
data assimilation
4D-Var
Congo River plume
satellite salinity
Angola Basin
ROMS
SURFACE SALINITY
OCEAN
SYSTEMS
IMPACT
CIRCULATION
TEMPERATURE
PERFORMANCE
ESTUARY
GUINEA
0203 Classical Physics
0406 Physical Geography and Environmental Geoscience
0909 Geomatic Engineering
Publication Status
Published
Date Publish Online
2019-12-18