In spite of its comparatively small volume sea ice plays a major part in the Arctic climate system, because the interactions with the ocean and the atmosphere lead to many feedbacks in the coupled system. Unfortunately, these interesting properties are also one reason why modeling sea ice is still not mature. Many physical processes, most prominently maybe the formation and evolution of leads, are still only poorly represented in numerical models. The cause of those misrepresentations is often very hard to pinpoint because many factors play a role. One possibility to address this problem is an adjoint model. Such a numerical tool takes one objective function out of the huge output of a climate model and calculates the gradients and thereby the sensitivities to all variables that are modeled. In a first step one property of the sea ice model such as the ice transport through a strait in a certain time span or the minimal summer sea ice extent is defined. The result of the adjoint model then gives directly the influence of all modeled variables of the ocean, sea ice and the atmospheric forcing on this property, resolved in space and time. This level of detail is in no way feasible to arrive at via traditional sensitivity analysis by parameter perturbation. With this information we want to investigate the role of different components of current sea-ice-ocean-models in the simulation results. For this we will focus for one part on the sensitivities of modeled sea ice distribution to the boundary, initial and forcing conditions prescribed to the model. The results can be used to inform future choices for additional measurements to improve model output. The other focus will be on the modeling framework itself, and the influence the rheology and the different physical parameterisations used in the sea ice models have on those calculated sensitivities.