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.
High‐turbidity events (HTEs) are common phenomena in shallow‐water environments that can alter ecological interactions. The relative contributions of river input (external loading) vs. resuspension (internal loading) to the occurrence, duration, and influenced areas of HTEs are not fully understood in most systems, owing to the lack of long‐term, source‐specified sediment maps. Using a Finite Volume Community Ocean Model‐based wave‐current forced sediment model, we investigated sediment dynamics in the shallow, river‐dominated Western Lake Erie during ice‐free cycles (April–November) of 2002–2012. Results indicated that wind waves predominated sediment dynamics in the offshore areas, with river discharges causing substantial inshore to offshore gradients. Owing to varying wind waves and river discharges, both the mean and extreme sediment dynamics had distinctive seasonal variations. The basin was turbid during spring and fall, with frequent (> 15%), broad (O [102–103 km2]), and more persistent (means of 3.2/4.4 d during spring/fall) HTEs caused mainly by resuspension events. During summer, the basin was clearer with occasional (< 1%), small (O [1–102 km2]), and short (mean of 1.5 d) HTEs near the mouths generated by pulsing river loadings. Although river loading rarely induced basin‐wide HTEs, they were important during floods, enlarging the high‐turbidity areas by 11.3%. Overall, by delineating the drivers of HTEs in Western Lake Erie, this study furthered the understanding of sediment dynamics in shallow ecosystems and provides a basis for investigating the ecological impact of sediments from different sources in river‐ and wave‐energetic systems.
Ice Cover in the Great Lakes has significant impacts on regional weather, economy, lake ecology, and human safety. However, forecast guidance for the lakes is largely focused on the ice-free season and associated state variables (currents, water temperatures, etc.) A coupled lake-ice model is proposed with potential to provide valuable information to stakeholders and society at large about the current and near-future state of Great Lakes Ice. The model is run for three of the five Great Lakes for prior years and the modeled ice cover is compared to observations via several skill metrics. Model hindcasts of ice conditions reveal reasonable simulation of year-to-year variability of ice extent, ice season duration, and spatial distribution, though some years appear to be prone to higher error. This modeling framework will serve as the basis for NOAA’s next-generation Great Lakes Operational Forecast System (GLOFS); a set of 3-D lake circulation forecast modeling systems which provides forecast guidance out to 120 h.
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