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A large-scale view of oceanic variability from 2007 to 2015 in the global high resolution monitoring and forecasting system at Mercator Océan ArchiMer
Gasparin, Florent; Greiner, Eric; Lellouche, Jean-michel; Legalloudec, Olivier; Garric, Gilles; Drillet, Yann; Bourdalle-badie, Romain; Le Traon, Pierre-yves; Remy, Elisabeth; Drevillon, Marie.
The global high resolution monitoring and forecasting system PSY4 at Mercator Océan, initialized in October 2006, has achieved 11 years of global ocean state estimation. Based on the NEMO global 1/12° configuration, PSY4 includes data assimilation of satellite and multi-instrument in situ observations. In parallel to this monitoring system, a twin-free simulation (with no assimilation) has been performed for the period 2007-2015. In this study, monthly-averaged fields of both ocean state estimates are compared with observation products for the period 2007-2015, to examine the consistency of PSY4 fields with related observations for representing large-scale variability and to provide a baseline that is mainly focused on in situ comparisons for...
Tipo: Text Palavras-chave: Global ocean monitoring and forecasting system; Climate variability; System evaluation/qualification; Global ocean observing system.
Ano: 2018 URL: https://archimer.ifremer.fr/doc/00448/55956/57550.pdf
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Evaluation of real time and future global monitoring and forecasting systems at Mercator Ocean ArchiMer
Lellouche, Jean-michel; Le Gallouedec, O.; Drevillon, Marie; Regnier, C.; Greiner, Eric; Garric, Gilles; Ferry, N.; Desportes, C.; Testut, Charles-emmanuel; Bricaud, C.; Bourdalle-badie, R.; Tranchant, B.; Benkiran, Mounir; Drillet, Y.; Daudin, A.; De Nicola, C..
Since December 2010, the global analysis and forecast of the MyOcean system consists in the Mercator Océan NEMO global 1/4° configuration with a 1/12° "zoom" over the Atlantic and Mediterranean Sea. The zoom open boundaries come from the global 1/4° at 20° S and 80° N. The data assimilation uses a reduced order Kalman filter with a 3-D multivariate modal decomposition of the forecast error. It includes an adaptative error and a localization algorithm. A 3D-Var scheme corrects for the slowly evolving large-scale biases in temperature and salinity. Altimeter data, satellite temperature and in situ temperature and salinity vertical profiles are jointly assimilated to estimate the initial conditions for the numerical ocean forecasting. This paper gives a...
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Ano: 2012 URL: http://archimer.ifremer.fr/doc/00129/23983/21940.pdf
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Moose: An integrated multi-sites observatory system in the NW Mediterranean sea ArchiMer
Mantoura, F; Coppola, Laurent; Cousin, M.; Antoine, David; Beguery, Laurent; Blain, Stephane; Bouin, Marie-noelle; Cadiou, Jean-francois; Durrieu De Madron, Xavier; Forget, Philippe; Fraunie, Philippe; Gojak, Carl; Gorsky, Gaby; Goyet, Catherine; Lebaron, Philippe; Lellouche, Jean-michel; Ludwig, Hubert; Molcard, Anne; Mortier, Laurent; Petit De La Villeon, Loic; Petrenko, Anne; Piazzola, J.; Queguiner, B.; Raimbault, Patrick; Rigaud, Vincent; Sempere, Richard; Tamburini, Jean-simon; Testor, Pierre; Vuillemin, Renaud; Zakardjian, B..
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Ano: 2009 URL: http://archimer.ifremer.fr/doc/00122/23341/21166.pdf
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Recent updates to the Copernicus Marine Service global ocean monitoring and forecasting real-time 1∕12° high-resolution system ArchiMer
Lellouche, Jean-michel; Greiner, Eric; Le Galloudec, Olivier; Garric, Gilles; Regnier, Charly; Drevillon, Marie; Benkiran, Mounir; Testut, Charles-emmanuel; Bourdalle-badie, Romain; Gasparin, Florent; Hernandez, Olga; Levier, Bruno; Drilled, Yann; Remy, Elisabeth; Le Traon, Pierre-yves.
Since 19 October 2016, and in the framework of Copernicus Marine Environment Monitoring Service (CMEMS), Mercator Ocean has delivered real-time daily services (weekly analyses and daily 10-day forecasts) with a new global 1∕12° high-resolution (eddy-resolving) monitoring and forecasting system. The model component is the NEMO platform driven at the surface by the IFS ECMWF atmospheric analyses and forecasts. Observations are assimilated by means of a reduced-order Kalman filter with a three-dimensional multivariate modal decomposition of the background error. Along-track altimeter data, satellite sea surface temperature, sea ice concentration, and in situ temperature and salinity vertical profiles are jointly assimilated to estimate the initial conditions...
Tipo: Text
Ano: 2018 URL: https://archimer.ifremer.fr/doc/00458/56993/58884.pdf
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