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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 complex 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 simulations of the Great Lakes' winter climate. By integrating 3D lake hydrodynamics, CLIAv1 demonstrates superior performance in reproducing observed lake surface temperatures (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 the 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 regional Earth system projections. More importantly, the key contribution of this study is the identification of critical physical processes that influence lake thermal structure and ice cover – processes that are missed by 1D lake models but effectively resolved 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 to 1D lake models, particularly in cold season performance and lake–atmosphere interactions. Critically, all three of these processes are dynamically linked to water currents – spatially and temporally evolving flow fields that are structurally absent in 1D models. This study aims to advance our understanding of the physical mechanisms that underlie the fundamental differences between 3D and 1D lake models in simulating key hydrodynamic processes during the winter season, and it offers generalized insights that are not constrained by specific model configurations. 

Abstract Lake heatwaves (extreme hot water events) can substantially disrupt aquatic ecosystems. Although surface heatwaves are well studied, their vertical structures within lakes remain largely unexplored. Here we analyse the characteristics of subsurface lake heatwaves (extreme hot events occurring below the surface) using a spatiotemporal modelling framework. Our findings reveal that subsurface heatwaves are frequent, often longer lasting but less intense than surface events. Deep-water heatwaves (bottom heatwaves) have increased in frequency (7.2 days decade⁻¹), duration (2.1 days decade⁻¹) and intensity (0.2 °C days decade⁻¹) over the past 40 years. Moreover, vertically compounding heatwaves, where extreme heat occurs simultaneously at the surface and bottom, have risen by 3.3 days decade⁻¹. By the end of the century, changes in heatwave patterns, particularly under high emissions, are projected to intensify. These findings highlight the need for subsurface monitoring to fully understand and predict the ecological impacts of lake heatwaves.