Turbulent Heat Fluxes during an Extreme Lake-Effect Snow Event

Abstract

Proper modeling of the turbulent heat fluxes over lakes is critical for accurate predictions of lake-effect snowfall (LES). However, model evaluation of such a process has not been possible because of the lack of direct flux measurements over lakes. The authors conducted the first-ever comparison of the turbulent latent and sensible heat fluxes between state-of-the-art numerical models and direct flux measurements over Lake Erie, focusing on a record LES event in southwest New York in November 2014. The model suite consisted of numerical models that were operationally and experimentally used to provide nowcasts and forecasts of weather and lake conditions. The models captured the rise of the observed turbulent heat fluxes, while the peak values varied significantly. This variation resulted in an increased spread of simulated lake temperature and cumulative evaporation as the representation of the model uncertainty. The water budget analysis of the atmospheric model results showed that the majority of the moisture during this event came from lake evaporation rather than a larger synoptic system. The unstructured-grid Finite-Volume Community Ocean Model (FVCOM) simulations, especially those using the Coupled Ocean–Atmosphere Response Experiment (COARE)-Met Flux algorithm, presented better agreement with the observed fluxes likely due to the model’s capability in representing the detailed spatial patterns of the turbulent heat fluxes and the COARE algorithm’s more realistic treatment of the surface boundary layer than those in the other models.

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 Operational Hydrodynamic Models for Real‐time Simulation of Evaporation From Large Lakes

“…To date, this step has been achieved; a small network of in situ eddy-covariance stations was deployed across the Great Lakes through an initiative launched by the International Joint Commission Spence et al, 2011) in the mid-to late-2000s, and the measurements have been used to validate the algorithms encoded in the operational models (Charusombat et al, 2018;Deacu et al, 2012;Fujisaki-Manome et al, 2017). First, in situ eddy-covariance stations needed to be deployed across the Great Lakes to (among other objectives) assess and refine the intrinsic flux algorithms in the models.…”

“…First, in situ eddy-covariance stations needed to be deployed across the Great Lakes to (among other objectives) assess and refine the intrinsic flux algorithms in the models. To date, this step has been achieved; a small network of in situ eddy-covariance stations was deployed across the Great Lakes through an initiative launched by the International Joint Commission Spence et al, 2011) in the mid-to late-2000s, and the measurements have been used to validate the algorithms encoded in the operational models (Charusombat et al, 2018;Deacu et al, 2012;Fujisaki-Manome et al, 2017).…”

“…Verifying modeled evaporation is a challenge for any freshwater body, and it is particularly challenging for the Great Lakes given their vast surface areas, the intrinsic spatiotemporal variability of fluxes across those surfaces (Blanken et al, 2000), and the spatial coverage of the valuable (but relatively sparse) in situ flux monitoring network Spence et al, 2011Spence et al, , 2013. While the recent model evaluation studies utilizing this monitoring network (Charusombat et al, 2018;Fujisaki-Manome et al, 2017) indicate that the flux algorithms in FVCOM-COARE and FVCOM-SOLAR provide reasonable simulations of sensible and latent heat fluxes at discrete monitoring points, we know of no previous study that has explicitly verified lakewide simulations of evaporation for any configuration of FVCOM.…”

The Need for an Integrated Land‐Lake‐Atmosphere Modeling System, Exemplified by North America's Great Lakes Region

“…Recent lake studies have found that declining duration of ice cover over the lakes and increasing lake surface water temperatures (Mason et al, ) have caused major summer convective storm water impacts in Midwestern cities (Kessler, ). Other meteorological impacts include wintertime lake‐effect snow in coastal communities, induced by rapid heat and moisture exchange over the Great Lakes (Fujisaki‐Manome et al, ). For example, in November 2014, an extreme lake‐effect storm in Buffalo, New York, delivered more than seven feet of snow due to sustained lake‐effect conditions.…”