2014
DOI: 10.3402/tellusa.v66.24908
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Improving the multiannual, high-resolution modelling of biogeochemical cycles in the Baltic Sea by using data assimilation

Abstract: A B S T R A C TThe impact of assimilating temperature, salinity, oxygen, phosphate and nitrate observations on marine ecosystem modelling is assessed. For this purpose, two 10-yr (1970Á1979) reanalyses of the Baltic Sea are carried out using the ensemble optimal interpolation (EnOI) method and a coupled physical-biogeochemical model of the Baltic Sea. To evaluate the reanalyses, climatological data and available biogeochemical and physical in situ observations at monitoring stations are compared with results f… Show more

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Cited by 9 publications
(24 citation statements)
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“…Other "sophisticated" sample ensembles could be tested but this is beyond the scope of this study. An adaptive scaling factor was calculated to adapt to the instantaneous forecast error variance before each local analysis (Liu et al, 2013(Liu et al, , 2014. Further, localization is used to remove unrealistic long-range correlations with a quasi-Gaussian function and a uniform horizontal correlation scale of 70 km.…”
Section: Observationsmentioning
confidence: 99%
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“…Other "sophisticated" sample ensembles could be tested but this is beyond the scope of this study. An adaptive scaling factor was calculated to adapt to the instantaneous forecast error variance before each local analysis (Liu et al, 2013(Liu et al, , 2014. Further, localization is used to remove unrealistic long-range correlations with a quasi-Gaussian function and a uniform horizontal correlation scale of 70 km.…”
Section: Observationsmentioning
confidence: 99%
“…One experiment is a simulation without data assimilation (FREE). The other simulation is constrained by observations using the "weakly coupled" assimilation scheme based upon the EnOI method following Liu et al (2014) which was briefly described above (REANA). Both simulations, FREE and RE-ANA, are initialized for January 1970.…”
Section: Observationsmentioning
confidence: 99%
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