Centre de documentation
scientifique

On the assimilation of absolute geodetic dynamic topography in a global ocean model: impact on the deep ocean state / Alexey Androsov in Journal of geodesy, vol 93 n° 2 (February 2019)  

Public [article]  inJournal of geodesy > vol 93 n° 2 (February 2019) . - pp 141 - 157 Titre : On the assimilation of absolute geodetic dynamic topography in a global ocean model: impact on the deep ocean state Type de document : Article/Communication Auteurs : Alexey Androsov, Auteur ; Lars Nerger, Auteur ; Reiner Schnur, Auteur ; Alberta Albertella, Auteur ; Reiner Rummel, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 141 - 157 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale [Termes IGN] assimilation des données [Termes IGN] circulation océanique [Termes IGN] données altimétriques [Termes IGN] données CHAMP [Termes IGN] données GOCE [Termes IGN] données GRACE [Termes IGN] filtre de Kalman [Termes IGN] geoïde marin [Termes IGN] géoïde terrestre [Termes IGN] hauteurs de mer [Termes IGN] modèle de simulation [Termes IGN] modèle océanographique [Termes IGN] océanographie dynamique [Termes IGN] salinité [Termes IGN] température de surface de la mer Résumé : (auteur) General ocean circulation models are not perfect. Forced with observed atmospheric fluxes they gradually drift away from measured distributions of temperature and salinity. We suggest data assimilation of absolute dynamical ocean topography (DOT) observed from space geodetic missions as an option to reduce these differences. Sea surface information of DOT is transferred into the deep ocean by defining the analysed ocean state as a weighted average of an ensemble of fully consistent model solutions using an error-subspace ensemble Kalman filter technique. Success of the technique is demonstrated by assimilation into a global configuration of the ocean circulation model FESOM over 1 year. The dynamic ocean topography data are obtained from a combination of multi-satellite altimetry and geoid measurements. The assimilation result is assessed using independent temperature and salinity analysis derived from profiling buoys of the AGRO float data set. The largest impact of the assimilation occurs at the first few analysis steps where both the model ocean topography and the steric height (i.e. temperature and salinity) are improved. The continued data assimilation over 1 year further improves the model state gradually. Deep ocean fields quickly adjust in a sustained manner: A model forecast initialized from the model state estimated by the data assimilation after only 1 month shows that improvements induced by the data assimilation remain in the model state for a long time. Even after 11 months, the modelled ocean topography and temperature fields show smaller errors than the model forecast without any data assimilation. Numéro de notice : A2019-076 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-018-1151-1 Date de publication en ligne : 12/05/2018 En ligne : https://doi.org/10.1007/s00190-018-1151-1 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92190 [article]