Assimilation of ocean colour data into a Biogeochemical Flux Model of the Eastern Mediterranean Sea

[摘要] An advanced multivariate sequential data assimilation system has beenimplemented within the framework of the European MFSTEP project to fita three-dimensional biogeochemical model of the Eastern Mediterraneanto satellite chlorophyll data from the Sea-viewing WideField-of-view Sensor (SeaWiFS). The physics are described by thePrinceton Ocean Model (POM) while the biochemistry of the ecosystem istackled with the Biogeochemical Flux Model (BFM). The assimilationscheme is based on the Singular Evolutive Extended Kalman (SEEK)filter, in which the error statistics were parameterized by means of asuitable set of Empirical Orthogonal Functions (EOFs).To avoidspurious long-range correlations associated with the limited number ofEOFs, the filter covariance matrix was given compact support througha radius of influence around every data point location. Hindcastexperiments were performed for one year over 1999 and forced withECMWF 6 h atmospheric fields. The solution of the assimilationsystem was evaluated against the assimilated data and the MedAtlasclimatology, and by assessing the impact of the assimilation onnon-observed biogeochemical processes. It is found that theassimilation of SeaWiFS data improves the overall behavior ofthe BFM modeland efficiently removes long term biases from themodel despite some difficulties during the spring bloomperiod. Results, however, suggest the need of subsurface data toenhance the estimation of the ecosystem variables in the deeplayers.

[学科分类] 海洋学与技术