Validating modeled turbulent heat fluxes across large freshwater surfaces

Turbulent fluxes of latent and sensible heat are important physical processes that influence the energy and water budgets of the Great Lakes. Validation and improvement of bulk flux algorithms to simulate these turbulent heat fluxes are critical for accurate prediction of hydrodynamics, water levels, weather, and climate over the region. Here we consider five heat flux algorithms from several model systems; the Finite-Volume Community Ocean Model, the Weather Research and Forecasting model, and the Large Lake Thermodynamics Model, which are used in research and operational environments and concentrate on different aspects of the Great Lakes' physical system, but interface at the lake surface. The heat flux algorithms were isolated from each model and driven by meteorological data from over-lake stations in the Great Lakes Evaporation Network. The simulation results were compared with eddy covariance flux measurements at the same stations. All models show the capacity to the seasonal cycle of the turbulent heat fluxes. Overall, the Coupled Ocean Atmosphere Response Experiment algorithm in FVCOM has the best agreement with eddy covariance measurements. Simulations with the other four algorithms are overall improved by updating the parameterization of roughness length scales of temperature and humidity. Agreement between modelled and observed fluxes notably varied with geographical locations of the stations. For example, at the Long Point station in Lake Erie, observed fluxes are likely influenced by the upwind land surface while the simulations do not take account of the land surface influence, and therefore the agreement is worse in general.