Improving the Simulation of Large Lakes in Regional Climate Modeling: Two-Way Lake–Atmosphere Coupling with a 3D Hydrodynamic Model of the Great Lakes

Abstract

Accurate representations of lake–ice–atmosphere interactions in regional climate modeling remain one of the most critical and unresolved issues for understanding large-lake ecosystems and their watersheds. To date, the representation of the Great Lakes two-way interactions in regional climate models is achieved with one-dimensional (1D) lake models applied at the atmospheric model lake grid points distributed spatially across a 2D domain. While some progress has been made in refining 1D lake model processes, such models are fundamentally incapable of realistically resolving a number of physical processes in the Great Lakes. In this study, a two-way coupled 3D lake-ice–climate modeling system [Great Lakes–Atmosphere Regional Model (GLARM)] is developed to improve the simulation of large lakes in regional climate models and accurately resolve the hydroclimatic interactions. Model results are compared to a wide variety of observational data and demonstrate the unique skill of the coupled 3D modeling system in reproducing trends and variability in the Great Lakes regional climate, as well as in capturing the physical characteristics of the Great Lakes by fully resolving the lake hydrodynamics. Simulations of the climatology and spatiotemporal variability of lake thermal structure and ice are significantly improved over previous coupled, 1D simulations. At seasonal and annual time scales, differences in model results are primarily observed for variables that are directly affected by lake surface temperature (e.g., evaporation, precipitation, sensible heat flux) while no significant differences are found in other atmospheric variables (e.g., solar radiation, cloud cover). Underlying physical mechanisms for the simulation improvements using GLARM are also discussed.

The role of wave‐current interaction in Lake Erie's seasonal and episodic dynamics

“…In addition, it increased wind stress and wind stress curl, leading to accelerated longshore currents and enhanced gyre circulations, respectively. It is noteworthy that the lake, especially the wide Central Bain, showed spatial variations in its sensitivities to the wave‐induced heat flux owing to the three‐dimensional circulation structures in the basin. This supported the necessity of applying three‐dimensional hydrodynamic models in the air‐lake coupling system as recently suggested by Xue et al []. In addition, this study indicated the potential significance of the surface gravity waves in the air‐lake momentum and heat transfers, and Shimura et al .…”

Impact of Water Mixing and Ice Formation on the Warming of Lake Superior: A Model‐guided Mechanism Study

“…Finite Volume Community Ocean Model (FVCOM) (Chen et al ) is used in this study, which is an unstructured‐grid, finite‐volume, three‐dimensional (3D), primitive equation ocean model. FVCOM's unstructured‐grid feature allows for flexible geometrical fitting and local topography refinement, which has proven successful for research and applications to estuaries, coastal oceans, and Lakes (Xue et al , , ; Anderson and Schwab ; Beardsley et al ; Fujisaki‐Manome et al ; Safaie et al ). The horizontal resolution of the model grids varies from ∼ 1 km near the coast to 5 km in the offshore regions of the lake (Fig.…”

Evaluating and improving modeled turbulent heat fluxes across the North American Great Lakes

“…The datasets available for validation of ocean dynamical models include, for example, satellite-based surface water temperatures (Reynolds et al, 2007), sea surface height (Lambin et al, 2010), and when available, in situ measurements of sensible and latent heat fluxes (Edson et al, 1998). Dynamical and thermodynamic models for large lakes are often verified using similar measurements (Chu et al, 2011;Croley, 1989a, b;Moukomla and Blanken, 2017;Xiao et al, 2016;Xue et al, 2017). However, the spatiotemporal resolution of in situ measurements for these variables in lakes is comparatively sparse Published by Copernicus Publications on behalf of the European Geosciences Union.…”

“…The Finite Volume Community Ocean Model (FVCOM), for example, is a widely used hydrodynamic ocean model that has been found to provide accurate real-time nowcasts and forecasts of hydrodynamic conditions across the Great Lakes, including currents, water temperature, and water level fluctuations with relatively fine spatiotemporal scales (Anderson et al, 2015;Anderson and Schwab, 2013;Bai et al, 2013;Xue et al, 2017). FVCOM is currently being developed, tested, and deployed across all of the Great Lakes as part of an ongoing update to the National Oceanic and Atmospheric Administration's (NOAA's) Great Lakes Operational Forecasting System (GLOFS).…”