On the potential of data assimilation to generate SMOS-Level 4 maps of sea surface salinity

On the potential of data assimilation to generate SMOS-Level 4 maps of sea surface salinity

13 pages, 11 figures, 2 tables

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Main Authors: Hoareau, Nina, Umbert, Marta, Martínez, Justino, Turiel, Antonio, Ballabrera-Poy, Joaquim
Format: artículo biblioteca
Published: Elsevier 2014-04
Subjects:Data assimilation, Nudging, Eastern subtropical North-Atlantic Ocean, SMOS, Singularity analysis, Sea surface salinity, SSS,
Online Access:http://hdl.handle.net/10261/97546
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spelling dig-icm-es-10261-975462020-12-09T17:46:18Z On the potential of data assimilation to generate SMOS-Level 4 maps of sea surface salinity Hoareau, Nina Umbert, Marta Martínez, Justino Turiel, Antonio Ballabrera-Poy, Joaquim Data assimilation Nudging Eastern subtropical North-Atlantic Ocean SMOS Singularity analysis Sea surface salinity SSS 13 pages, 11 figures, 2 tables The Soil Moisture/Ocean Salinity (SMOS) satellite, launched in November 2009, measures visibilities at L-band, from which brightness temperatures are computed. This information is used to retrieve values of the sea surface salinity (SSS) and soil moisture; two variables whose observation is a key to better understand the oceanic component of the water cycle. A hierarchy of SSS products has been defined in the SMOS data processing chain. This work focuses on the so-called Level 3 (binned maps of SSS) and Level 4 (products combining SMOS data with any other source of information). The objective is to illustrate the feasibility of using data assimilation to produce Level 4 maps of sea surface salinity. The numerical model will increase the geophysical coherence of SMOS data as a dynamical interpolator. Here, the employment of data assimilation differs from its usual applications (improving model outputs for example). Indeed, the numerical model will interpolate the observations according to the general laws of fluid mechanics and, if possible, reduce the error contained in the original observations. The data assimilation method analyzed is a nudging algorithm. The domain of application for this feasibility study is the Northeast subtropical Atlantic gyre, a challenging region due to the presence of a large amount of noise that deteriorates the SMOS data. The main sources of errors are the vicinity of large landmasses that introduce a spurious bias, and the presence of a significant amount of artificial radio frequency interferences (RFI). While the Quality Controls already set up in the SMOS processing chain do filter the retrievals containing too large errors, wrong data are still present in Level 3 maps. Despite this difficulty, the results provide meaningful SMOS SSS Level 4 products in terms of their geophysical coherence (estimated using singularity analysis) and better agreement with in-situ data than Level 3 product. © 2013 Elsevier Inc. This study is supported by the Spanish Ministry of Economy and Competitiveness (MINECO) by means of the R&D projects MIDAS-6 (Ref. AYA2010-22062-C05) and MIDAS-7 (Ref. AYA2012-39356-C05- 03). M. Umbert recognizes support by the Spanish MEC through the FPI grant program Peer Reviewed 2014-06-02T10:45:56Z 2014-06-02T10:45:56Z 2014-04 2014-06-02T10:45:56Z artículo http://purl.org/coar/resource_type/c_6501 doi: 10.1016/j.rse.2013.10.005 issn: 0034-4257 e-issn: 1879-0704 Remote Sensing of Environment 146: 188-200 (2014) http://hdl.handle.net/10261/97546 10.1016/j.rse.2013.10.005 https://doi.org/10.1016/j.rse.2013.10.005 none Elsevier
institution ICM ES
collection DSpace
country España
countrycode ES
component Bibliográfico
access En linea
databasecode dig-icm-es
tag biblioteca
region Europa del Sur
libraryname Biblioteca del ICM España
topic Data assimilation
Nudging
Eastern subtropical North-Atlantic Ocean
SMOS
Singularity analysis
Sea surface salinity
SSS
Data assimilation
Nudging
Eastern subtropical North-Atlantic Ocean
SMOS
Singularity analysis
Sea surface salinity
SSS
spellingShingle Data assimilation
Nudging
Eastern subtropical North-Atlantic Ocean
SMOS
Singularity analysis
Sea surface salinity
SSS
Data assimilation
Nudging
Eastern subtropical North-Atlantic Ocean
SMOS
Singularity analysis
Sea surface salinity
SSS
Hoareau, Nina
Umbert, Marta
Martínez, Justino
Turiel, Antonio
Ballabrera-Poy, Joaquim
On the potential of data assimilation to generate SMOS-Level 4 maps of sea surface salinity
description 13 pages, 11 figures, 2 tables
format artículo
topic_facet Data assimilation
Nudging
Eastern subtropical North-Atlantic Ocean
SMOS
Singularity analysis
Sea surface salinity
SSS
author Hoareau, Nina
Umbert, Marta
Martínez, Justino
Turiel, Antonio
Ballabrera-Poy, Joaquim
author_facet Hoareau, Nina
Umbert, Marta
Martínez, Justino
Turiel, Antonio
Ballabrera-Poy, Joaquim
author_sort Hoareau, Nina
title On the potential of data assimilation to generate SMOS-Level 4 maps of sea surface salinity
title_short On the potential of data assimilation to generate SMOS-Level 4 maps of sea surface salinity
title_full On the potential of data assimilation to generate SMOS-Level 4 maps of sea surface salinity
title_fullStr On the potential of data assimilation to generate SMOS-Level 4 maps of sea surface salinity
title_full_unstemmed On the potential of data assimilation to generate SMOS-Level 4 maps of sea surface salinity
title_sort on the potential of data assimilation to generate smos-level 4 maps of sea surface salinity
publisher Elsevier
publishDate 2014-04
url http://hdl.handle.net/10261/97546
work_keys_str_mv AT hoareaunina onthepotentialofdataassimilationtogeneratesmoslevel4mapsofseasurfacesalinity
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AT martinezjustino onthepotentialofdataassimilationtogeneratesmoslevel4mapsofseasurfacesalinity
AT turielantonio onthepotentialofdataassimilationtogeneratesmoslevel4mapsofseasurfacesalinity
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