Snow covered sea ice plays a crucial role in the earth's climate. This includes polar biology, local, regional and world weather and ocean circulations as well as indigenous people's way of life. Recent research has indicated significant climate change in the polar regions, especially the Canadian arctic. Polar climate processes are also among the most poorly misrepresented within global circulation models (GCMs). The goal of this thesis is to improve our understanding and capability to simulate arctic climate processes in a predictive sense. An electro-thermophysical relationship exists between the thermophysical characteristics (climate variables and processes) and electrical properties (dielectrics) that control microwave remote sensing of snow-covered first-year sea ice (FYI). This work explicitly links microwave dielectrics and a thermodynamic model of snow and sea ice by addressing four key issues. These includes: (1) ensure the existing one-dimensional sea ice models treat the surface energy balance (SEB) and snow/ice thermodynamics in the appropriate time scales we see occurring in field experiments, (2) ensure the snow/ice thermodynamics are not compromised by differences in environmental and spatial representation within components of the SEB, (3) ensure the snow layer is properly handled in the modeling env ronment, and (4) how we can make use of satellite microwave remote sensing data within the model environment. Results suggest that diurnal processes are critical and need to be accounted for in modeling snow-covered FYI, similar to time scales acting in microwave remote sensing signatures. Output from the coupled snow sea-ice model provides the required input to microwave dielectric models of snow and sea ice to predict microwave penetration depths within the snow and sea ice (an Electro-Thermophysical model of the Snow Sea Ice System (ETSSIS)). Results suggest ETSSIS can accurately simulate microwave penetration depths in the cold dry snow season and wet snow season (funicular snow regime). Simulated penetration depths become too large in the pendular snow regime since liquid water is not generated soon enough within the snow pack in the spring season. The inclusion of salinity in the mass balance of ETSSIS will improve the simulation of penetration depths in the pendular snow regime in future implementations of the model. (Abstract shortened by UMI.)