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Abstract The physical processes of heat exchange between lakes and the surrounding atmosphere are important in simulating and predicting terrestrial surface energy balance. Latent and sensible heat fluxes are the dominant physical process controlling ice growth and decay on the lake surface, as well as having influence on regional climate. While one-dimensional lake models have been used in simulating environmental changes in ice dynamics and water temperature, understanding the seasonal to daily cycles of lake surface energy balance and its relationship to lake thermal properties, atmospheric conditions, and how those are represented in models is still an open area of research. We evaluated a pair of one-dimensional lake models, Freshwater Lake (FLake) and the General Lake Model (GLM), to compare modeled latent and sensible heat fluxes against observed data collected by an eddy covariance tower during a 1-yr period in 2017, using Lake Mendota in Madison, Wisconsin, as our study site. We hypothesized transitional periods of ice cover as a leading source of model uncertainty, and we instead found that the models failed to simulate accurate values for large positive heat fluxes that occurred from late August into late December. Our results ultimately showed that one-dimensional models are effective in simulating sensible heat fluxes but are considerably less sensitive to latent heat fluxes than the observed relationships of latent heat flux to environmental drivers. These results can be used to focus future improvement of these lake models especially if they are to be used for surface boundary conditions in regional numerical weather models. Significance Statement While lakes consist of a small amount of Earth’s surface, they have a large impact on local climate and weather. A large amount of energy is stored in lakes during the spring and summer, and then removed from lakes before winter. The effect is particularly noticeable in high latitudes, when the seasonal temperature difference is larger. Modeling this lake energy exchange is important for weather models and measuring this energy exchange is challenging. Here we compare modeled and observed energy exchange, and we show there are large amounts of energy exchange happening in the fall, which models struggle to capture well. During periods of partial ice coverage in early winter, lake behavior can change rapidly.
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This content will become publicly available on July 14, 2026
Enhancing winter climate simulations of the Great Lakes: insights from a new coupled lake–ice–atmosphere (CLIAv1) system on the importance of integrating 3D hydrodynamics with a regional climate model
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.
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- Award ID(s):
- 2438826
- PAR ID:
- 10659519
- Publisher / Repository:
- EGU
- Date Published:
- Journal Name:
- Geoscientific Model Development
- Volume:
- 18
- Issue:
- 13
- ISSN:
- 1991-9603
- Page Range / eLocation ID:
- 4293 to 4316
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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