Stipa, T.

A fully prognostic 1-D thermodynamic model, functional for studies of sea-ice biogeochemistry is developed to better understand the physical processes and the interactions between the environment and the sea-ice ecosystem. The physical model is capable of simulating seasonal changes of snow and ice thickness. Particular attention is paid to reproduce the snow-ice and the superimposed ice formation which play important roles in the dynamics of sea ice algae. The assessment of the model capabilities is done in 1979--1993 at four different stations in the Baltic Sea. A sensitivity analysis stresses the importance of adequate surface forcing functions to properly simulate the onset of sea ice. Our results show that thickness of the ice layers and timing of the melting are in good agreement with the observed data and confirm that one of the key variables in modelling sea-ice thermodynamics is the snow layer and its metamorphism.

This work introduces a novel approach for the modelling and coupling of sea ice biology to sea ice physics. The central concept of the coupling is the definition of the Biologically Active Layer, which is the time-varying fraction of sea ice that is connected to the ocean via brine pockets and channels, and acts as a rich habitat for many microorganisms. A simple but comprehensive physical model of the sea ice thermohalodynamics is coupled to a novel sea ice microalgal model of growth in the framework of the Biogeochemical Flux Model. The physical model provides the key physical properties of the Biologically Active Layer and the biological model simulates the physiological and ecological response of the algal community to the physical environment. Numerical simulations of chl-a were compared with observations at two different ice stations, in the Baltic and off the coast of Greenland, showing that this new coupling structure is sufficiently generic to represent well the temporal and spatial distribution of sea ice algae during the whole ice season at both sites. This model implementation and coupling structure is viable as a new component of General Circulation Models, allowing for estimates of the role and importance of sea ice biology in the local and global carbon cycle.