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Assimilation of temperature into an isopycnal ocean general circulation model using a parallel ensemble Kalman filter Keppenne, C.L.; Rienecker, M.M. (2003). Assimilation of temperature into an isopycnal ocean general circulation model using a parallel ensemble Kalman filter. J. Mar. Syst. 40-41: 363-380. https://dx.doi.org/10.1016/S0924-7963(03)00025-3
In: Journal of Marine Systems. Elsevier: Tokyo; Oxford; New York; Amsterdam. ISSN 0924-7963; e-ISSN 1879-1573, meer
Ook verschenen in: Grégoire, M.; Brasseur, P.; Lermusiaux, P.F.J. (Ed.) (2003). The use of data assimilation in coupled hydrodynamic, ecological and bio-geo-chemical models of the ocean. Selected papers from the 33rd International Liege Colloquium on Ocean Dynamics, held in Liege, Belgium on May 7-11th, 2001. Journal of Marine Systems, 40-41. Elsevier: Amsterdam. 1-406 pp., meer
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Abstract |
Each time data are assimilated, multivariate background-error statistics estimated from the phase-space distribution of an ensemble of model states are used to calculate the Kalman gain matrix and the analysis increments. The resulting cross-field covariances are used to compute temperature, salinity and current increments. The layer thicknesses are left unchanged by the analysis. Instead, they are dynamically adjusted by the model between successive analyses. Independent acoustic Doppler current profiler data are used to assess the performance of the temperature data assimilation. The temperature analyses are also compared to analyses obtained with a univariate optimal interpolation (UOI) algorithm and to a control run without temperature assimilation. The results demonstrate that the multivariate EnKF is both practical and effective for assimilating in situ and remotely sensed observations into a high resolution ocean model in a quasi-operational framework. |
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