Abstract. The Laurentian Great Lakes significantly influence the climate of the Midwest and Northeast United States, due to their vast thermal inertia, moisture source potential, and unique heat and moisture flux dynamics. This study presents a newly developed coupled lake-ice-atmosphere (CLIAv1) modeling system for the Great Lakes by coupling the National Aeronautics and Space Administration (NASA)-Unified Weather Research and Forecasting (NU-WRF) regional climate model (RCM) with the three-dimensional (3D) Finite Volume Community Ocean Model (FVCOM) and investigates the impact of coupled dynamics on simulating the Great Lakes' winter climate. By integrating 3D lake hydrodynamics, CLIAv1 addresses the limitations of traditional one-dimensional (1D) lake and demonstrates superior performance in reproducing observed LSTs, ice cover distribution, and the vertical thermal structure of the Great Lakes compared to the NU-WRF model coupled with the default 1D Lake Ice Snow and Sediment Simulator (LISSS). CLIAv1 also enhances simulation of over-lake atmospheric conditions, including air temperature, wind speed, and sensible and latent heat fluxes, underscoring the importance of resolving complex lake dynamics for reliable climate projections. More importantly, this study addresses the crucial question about what are the key processes influencing lake thermal structure and ice cover that are missed by 1D lake models but effectively captured by 3D lake models. Through process-oriented numerical experiments, we identify key 3D hydrodynamic processes – ice transport, heat advection, and shear production in turbulence – that explain the superiority of 3D lake models over 1D lake models, particularly in cold season performance and lake-atmosphere interactions. Properly resolving these processes using 3D hydrodynamic model is crucial for successfully simulating the lake-ice-atmosphere coupled Great Lakes winter system. This research underscores the necessity of incorporating 3D hydrodynamic models in RCMs to improve our predictive understanding of the Great Lakes' response to climate change. The findings advocate for a shift towards high-resolution, physics-based modeling approaches to ensure accurate future climate and limnological projections for large freshwater systems.