Modeling summer circulation and thermal structure of Lake Erie

Beletsky, Dmitry; Hawley, Nathan; Rao, Yerubandi R.

doi:10.1002/2013jc008854

Cited by 83 publications

(104 citation statements)

References 54 publications

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“…We also note that (2) is consistent with the findings of Beletsky et al . [] for Lake Erie. A following question to ask is what are the primary mechanisms responsible for these observed model behaviors?…”

Section: Results: Observed and Simulatedmentioning

confidence: 99%

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An investigation of the thermal response to meteorological forcing in a hydrodynamic model of Lake Superior

Xue

Schwab

2015

J. Geophys. Res. Oceans

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Lake Superior, the largest lake in the world by surface area and third largest by volume, features strong spatiotemporal thermal variability due to its immense size and complex bathymetry. The objectives of this study are to document our recent modeling experiences on the simulation of the lake thermal structure and to explore underlying dynamic explanations of the observed modeling success. In this study, we use a three‐dimensional hydrodynamic model (FVCOM—Finite Volume Community Ocean Model) and an assimilative weather forecasting model (WRF—Weather Research and Forecasting Model) to study the annual heating and cooling cycle of Lake Superior. Model experiments are carried out with meteorological forcing based on interpolation of surface weather observations, on WRF and on Climate Forecast System Reanalysis (CFSR) reanalysis data, respectively. Model performance is assessed through comparison with satellite products and in situ measurements. Accurate simulations of the lake thermal structure are achieved through (1) adapting the COARE algorithm in the hydrodynamic model to derive instantaneous estimates of latent/sensible heat fluxes and upward longwave radiation based on prognostic surface water temperature simulated within the model as opposed to precomputing them with an assumed surface water temperature; (2) estimating incoming solar radiation and downward longwave radiation based on meteorological measurements as opposed to meteorological model‐based estimates; (3) using the weather forecasting model to provide high‐resolution dynamically constrained wind fields as opposed to wind fields interpolated from station observations. Analysis reveals that the key to the modeling success is to resolve the lake‐atmosphere interactions and apply appropriate representations of different meteorological forcing fields, based on the nature of their spatiotemporal variability. The close agreement between model simulation and observations also suggests that the 3‐D hydrodynamic model can provide reliable spatiotemporal estimates of heat budgets over Lake Superior and similar systems. Although there have been previous studies which analyzed the impact of the spatiotemporal variability of overwater wind fields on lake circulation, we believe this is the first detailed analysis of the importance of spatiotemporal variability of heat flux components on hydrodynamic simulation of 3‐D thermal structure in a lake.

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Section: Results: Observed and Simulatedmentioning

confidence: 99%

“…Recent work by Beletsky et al . [] demonstrated the potential shortcomings of interpolated wind conditions over Lake Erie in accurately representing circulation and thermal structure. Huang et al .…”

Section: Introductionmentioning

confidence: 99%

An investigation of the thermal response to meteorological forcing in a hydrodynamic model of Lake Superior

Xue

Schwab

2015

J. Geophys. Res. Oceans

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“…The FVCOM was widely used to study the hydrodynamic and transport process in aquatic areas such as lakes, estuaries and oceans [11][12][13][14] . It was applied in shallow waters, like Lake Taihu in China to study the surface mixed layer depth [15] , and also Lake El-Manzala in Egypt for salinity distribution and water management [16] . Recently, it was also used to investigate the seasonal circulation and thermal structure in Great Lakes [17] .…”

Section: Methodsmentioning

confidence: 99%

Numerical study of hydrodynamic process in Chaohu Lake

Chen

Liu

2015

J Hydrodyn

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Abstract:In this paper, the hydrodynamic characteristics of water flow in Chaohu Lake are studied by using the finite volume coastal ocean model (FVCOM), which is verified by the observed data. The typical flow field and the 3-D flow structure are obtained for the lake. The flow fields under extreme conditions are analyzed to provide a prospective knowledge of the water exchange and the transport process.The influence of the wind on the flow is determined by the cross spectrum method. The results show that the wind-driven flow dominates most area of the lake. Under prevailing winds in summer and winter, the water flows towards the downwind side at the upper layer while towards the upwind side at the lower layer in most area except that around the Chaohu Sluice. The extreme wind speed is not favorable for the water exchange while the sluice's releasing water accelerates the process. The water velocity in the lake is closely related with the wind speed.

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“…Aside from the specific application of CHAB forecasting, the observations and simulations shown here provide interesting insights on the physical processes that influence phytoplankton ecology in a polymictic lake. Previous studies of Lake Erie circulation and thermal structure considered the western basin to be largely unstratified [e.g., Beletsky et al ., ], but our study highlighted the importance of fine‐scale thermal structure in the western basin in a biological context. Surface mixed layer depth varies hour by hour due to subtle features in the temperature profile caused by the diel cycle of surface heating and cooling, further modified by varying wind stress.…”

Section: Resultsmentioning

confidence: 99%

Vertical distribution of buoyant Microcystis blooms in a Lagrangian particle tracking model for short‐term forecasts in Lake Erie

et al. 2016

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Cyanobacterial harmful algal blooms (CHABs) are a problem in western Lake Erie, and in eutrophic fresh waters worldwide. Western Lake Erie is a large (3000 km2), shallow (8 m mean depth), freshwater system. CHABs occur from July to October, when stratification is intermittent in response to wind and surface heating or cooling (polymictic). Existing forecast models give the present location and extent of CHABs from satellite imagery, then predict two‐dimensional (surface) CHAB movement in response to meteorology. In this study, we simulated vertical distribution of buoyant Microcystis colonies, and 3‐D advection, using a Lagrangian particle model forced by currents and turbulent diffusivity from the Finite Volume Community Ocean Model (FVCOM). We estimated the frequency distribution of Microcystis colony buoyant velocity from measured size distributions and buoyant velocities. We evaluated several random‐walk numerical schemes to efficiently minimize particle accumulation artifacts. We selected the Milstein scheme, with linear interpolation of the diffusivity profile in place of cubic splines, and varied the time step at each particle and step based on the curvature of the local diffusivity profile to ensure that the Visser time step criterion was satisfied. Inclusion of vertical mixing with buoyancy significantly improved model skill statistics compared to an advection‐only model, and showed greater skill than a persistence forecast through simulation day 6, in a series of 26 hindcast simulations from 2011. The simulations and in situ observations show the importance of subtle thermal structure, typical of a polymictic lake, along with buoyancy in determining vertical and horizontal distribution of Microcystis.

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Modeling summer circulation and thermal structure of Lake Erie

Cited by 83 publications

References 54 publications

An investigation of the thermal response to meteorological forcing in a hydrodynamic model of Lake Superior

An investigation of the thermal response to meteorological forcing in a hydrodynamic model of Lake Superior

Numerical study of hydrodynamic process in Chaohu Lake

Vertical distribution of buoyant Microcystis blooms in a Lagrangian particle tracking model for short‐term forecasts in Lake Erie

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