Abstract. Colored dissolved organic matter (CDOM) in marine environments impacts primary production due to its absorption effect on the photosynthetically active radiation. In coastal seas, CDOM originates from terrestrial sources predominantly and causes spatial and temporal changing patterns of light absorption which should be considered in marine biogeochemical models. We propose a model approach in which Earth Observation (EO) products are used to define boundary conditions of CDOM concentrations in an ecosystem model of the Baltic Sea. CDOM concentrations in riverine water derived from EO products serve as forcing for the ecosystem model. For this reason, we introduced an explicit CDOM state variable in the model. We show that the light absorption by CDOM in the model can be improved considerably in comparison to approaches where CDOM is estimated from salinity. The model performance increases especially with respect to spatial CDOM patterns due to the consideration of single river properties. A prerequisite is high-quality CDOM data with sufficiently high spatial resolution which can be provided by the new generation of ESA satellite sensor systems (Sentinel 2 MSI and Sentinel 3 OLCI). Such data are essential, especially when local differences in riverine CDOM concentrations exist.
We propose a new method for reconstruction of images in single photon emission computed tomography (SPECT), when the activity distribution of the object is time-varying. The activity evolution is modeled with the first-order Markov model, and linear observation model is used to characterize the measurement system. The statespace representation of the measurement sequence reduces to an illconditioned state estimation problem, which is solved recursively using the Kalman filter and smoother algorithms. Two special models, the compartmental model and the diffusion model, for the time variation are discussed. The method is evaluated using simulations. '
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