Figure - available from: Journal of Geophysical Research: Oceans
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Map of southern New England showing the LIS‐FVCOM model grid (colored region). Model bathymetry is shown by the color scale and the locations of freshwater sources are shown by light blue dots (from left to right: Hudson River, New York City wastewater treatment plants, Housatonic River, Quinnipiac River, Connecticut River, Niantic River, and Thames River). The location of the western Long Island Sound buoy is shown in magenta.
Source publication
Estimating surface heat fluxes via direct covariance measurements or bulk formulae is observation‐intensive and costly. We present a methodology whereby we estimate net surface heat fluxes as the difference between the depth‐integrated heat tendencies and the depth‐integrated horizontal heat exchanges in a hydrodynamic model. We calibrate the model...
Citations
... The hydrodynamic module in this work builds on that developed by McCardell et al. [23]. By incorporating both hydrodynamic and wave processes in a coupled model, it becomes possible to capture the complex feedback mechanisms and interactions between waves, currents, and water levels. ...
... The hydrodynamic model is forced at the open boundary with tidal components for the region, which were further refined based on tide gauge observations inside the estuary [23]. The riverine discharge was included using United States Geological Survey data. ...
The geometry of the Long Island Sound (LIS) renders the wave field fetch-limited and leads to marked differences between western and eastern areas. The mechanisms that contribute to the formation and dissipation of waves in the LIS are not well understood. We evaluated the ability of the wave module of a wave-coupled hydrodynamic model to simulate different wind–wave scenarios. We were unable to capture wave statistics correctly using existing meteorological model results for wind forcing due to the low resolution of the models and their inability to resolve the LIS coastline sufficiently. To solve this problem, we modified the wind fields using in situ wind observations from buoys. We optimized both the Komen and Jansen parameterizations for the LIS to better present the peak winds during storms. Waves in the LIS develop more quickly than simple theory predicts due to quadruplet nonlinear wave–wave interaction effects. Removing quadruplet nonlinear wave–wave interaction increases the time to full saturation by 50%. The spatial distribution of wave energy density input reveals the complex interaction between wind and waves in the LIS, with the area of greatest exposure receiving higher wave energy density. The interaction of nonlinear wave–wave interaction and whitecapping dissipation defines the shape of the directional spectrum along the LIS. Dissipation due to whitecapping and shoaling are the main parameters modulating a fully developed wave field.
... These comparisons suggest that simulation of the temperature field in LIS should be based on highly resolved wind fields since even small, but persistent biases in the surface fluxes can lead to errors in seasonal temperature cycles. McCardell et al. (2023) studied the monthly and seasonal temperature evolution in LIS using a numerical model. Figure 6 shows a comparison of the 24-hr averaged net surface heat flux estimated using wind data from WLIS (green), CLIS (blue), and WRF (red) to the 24-hr averaged heat tendency from the glider (black). ...
Seasonal variations in solar insolation and wind create an annual water temperature cycle that impacts circulation and biological processes. The waters of Long Island Sound (LIS) warm from March‐February until August‐October and then begin to cool. Ship surveys show that the vertical temperature structure becomes almost uniform during this season when the area experiences low air temperatures and high winds. However, no observations have resolved the temporal evolution of the vertical structure of temperature during these cooling periods because conditions inhibit ship operations. We report glider measurements of the vertical structure of water temperatures and salinities from 22 October to 4 November 2014, in eastern LIS. We find that 20 m of water can cool at approximately 0.5oC/day ${0.5}^{\mathrm{o}}\,\mathrm{C}/\mathrm{d}\mathrm{a}\mathrm{y}$ during intervals of cold air and strong winds. We use the data to estimate heat content tendencies and infer surface fluxes. We also estimate the surface heat fluxes using buoy‐mounted instruments and show they are consistent. The net heat flux to the atmosphere exceeds 600 W/m² during the gilder deployment and approximately 66% of this is due to latent heat transfer. Using the buoy fluxes and products of an operation regional model, we show that the agreement with the fluxes derived from heat budget is improved by using local wind observations. In addition to confirming the extremely large cooling rates, our results demonstrate that gliders can be used in a complex region with strong tidal currents to resolve the temperature structure and heat budget during the severe weather of the cooling season.
Long Island Sound (LIS) is a semi-enclosed urban estuary on the northeast US coast with a long east-west fetch and short north-south fetch. The geometry of the estuary renders the wavefield fetch-limited. The complex coastal geomorphology increases the sensitivity of wave simulation on forcing and resolution. In this dissertation, buoy observations were used to evaluate the accuracy of model simulations of waves in New Haven Harbor, an embayment partially isolated from LIS by three detached breakwaters. Two spectral wave models were assessed. Both models were largely consistent with observations during storms. Also, the sensitivity analysis indicates that wind forcing and the breakwaters significantly impact the results. A coupled wave-circulation model was implemented to study the mechanisms that contribute to the formation and dissipation of waves in LIS. Wind velocity predictions of existing meteorological models resulted in under-prediction of wave heights in western LIS. Empirical corrections were developed using in-situ wind observations. Comparison of buoy measurements and model predictions showed that optimal parameter choices were very different from values used for unlimited or large fetch limited basins. The model is particularly sensitive to the parameters that determined wave dissipation. The geometry of LIS and the direction of the wind control the shape of the directional wave spectrum and waves develop quickly due to nonlinear wave-wave interaction effects. Simple empirical wave models based on fetch and duration are, therefore, of limited value.
