Sea ice is a crucial component for short-, medium- and long term numerical weather predictions. Most importantly changes of sea ice coverage and areas covered by thin sea ice have a large impact on heat fluxes between the ocean and the atmosphere. L-Band brightness temperatures from ESA's first Earth Explorer SMOS (Soil Moisture and Ocean Salinity) have been proven to be a valuable tool to estimate mean thin sea ice thicknesses. Potentially, these measurements can be assimilated in forecasting systems to constrain the ice analysis leading to more accurate initial conditions and subsequently more accurate forecasts. As a first step, we use two different radiative transfer models as forward operators to generate top of atmosphere brightness temperatures based on ORAP5 model output for the 2012/2013 winter season. The simulations are then compared against actual SMOS measurements. The results indicate that both models are able to capture the general variability of measured brightness temperatures over sea ice. We identify one model to be favorable for brightness temperature assimilation purposes in the ORAP5 setup. The simulated brightness temperatures are dominated by sea ice coverage and thickness changes most pronounced in the marginal ice zone where new sea ice is formed. There we observe largest differences of more than 20 Kelvin over sea ice between simulated and observed brightness temperatures. We conclude that the assimilation of SMOS brightness temperatures yield high potential for forecasting models to correct for uncertainties in sea ice thicknesses of less than 0.5 meter and caution that uncertainties in sea ice fractional coverage may induce large errors.