{"refrec":{"BRefID":211119,"RR":"<b>Barth, A.; Alvera-Azcárate, A.; Beckers, J.-M.; Rixen, M.; Vandenbulcke, L.</b> (2007). Multigrid state vector for data assimilation in a two-way nested model of the Ligurian Sea. <i>J. Mar. Syst. 65(1-4)</i>: 41-59. <a href=\"https://dx.doi.org/10.1016/j.jmarsys.2005.07.006\" target=\"_blank\">https://dx.doi.org/10.1016/j.jmarsys.2005.07.006</a>","BEntID":203041,"PublicFlag":1,"CheckedFlag":1,"wosflag":1,"vabbflag":1,"RefStringPartII":". <i>J. Mar. Syst. 65(1-4)</i>: 41-59. <a href=\"https://dx.doi.org/10.1016/j.jmarsys.2005.07.006\" target=\"_blank\">https://dx.doi.org/10.1016/j.jmarsys.2005.07.006</a>","DocTypID":8,"DocType":"Journal article","MarineFlag":1,"FreshFlag":0,"BrackishFlag":0,"TerrestrialFlag":0,"Authorstring":"Barth, A.; Alvera-Azcárate, A.; Beckers, J.-M.; Rixen, M.; Vandenbulcke, L.","OrigTitleTranslFlag":0,"Authorstringtrunc":"Barth, A. <i>et al.</i>","Englishabstract":"A system of two nested models composed by a coarse resolution model of the Mediterranean Sea, an intermediate resolution model of the Provencal Basin and a high resolution model of the Ligurian Sea is coupled with a Kalman-filter based assimilation method. The state vector for the data assimilation is composed by the temperature, salinity and elevation of the three models. The forecast error is estimated by an ensemble run of 200 members by perturbing initial condition and atmospheric forcings. 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