Improving the multiannual, high-resolution modellingof biogeochemical cycles in the Baltic Sea by usingdata assimilation

摘要

The impact of assimilating temperature, salinity, oxygen, phosphate and nitrate observations on marineecosystem modelling is assessed. For this purpose, two 10-yr (19701979) reanalyses of the Baltic Sea are carriedout using the ensemble optimal interpolation (EnOI) method and a coupled physical-biogeochemical model ofthe Baltic Sea. To evaluate the reanalyses, climatological data and available biogeochemical and physical in situobservations at monitoring stations are compared with results from simulations with and without dataassimilation. In the first reanalysis, only observed temperature and salinity profiles are assimilated, whereasbiogeochemical observations are unused. Although simulated temperature and salinity improve considerablyas expected, the quality of simulated biogeochemical variables does not improve and deep water nitrate concentrationseven worsen. This unexpected behaviour is explained by a lowering of the halocline in the Balticproper due to the assimilation causing increased oxygen concentrations in the deep water and consequentlyaltered nutrient fluxes. In the second reanalysis, both physical and biogeochemical observations are assimilatedand good quality in all variables is found. Hence, we conclude that if a data assimilation method like the EnOIis applied, all available observations should be used to perform reanalyses of high quality for the Baltic Seabiogeochemical state estimates.