Preprints
https://doi.org/10.5194/gmd-2023-151
https://doi.org/10.5194/gmd-2023-151
Submitted as: model experiment description paper
 | 
25 Oct 2023
Submitted as: model experiment description paper |  | 25 Oct 2023
Status: this preprint is currently under review for the journal GMD.

Development and performance of a high-resolution surface wave and storm surge forecast model (COASTLINES-LO): Application to a large lake

Laura L. Swatridge, Ryan P. Mulligan, Leon Boegman, and Shiliang Shan

Abstract. An automated real-time forecast model of surface hydrodynamics in Lake Ontario (Coastlines-LO) was developed to predict storm surge and surface waves. The system uses a dynamically coupled Delft3D – SWAN model with a structured grid to generate 48 h predictions for the lake that are updated every 6 h. The lake surface is forced with meteorological data from the High Resolution Deterministic Prediction System (HRDPS). The forecast model has been running since May 2021, capturing a wide variety of storm conditions. Good agreement between observations and modelled results is achieved, with root mean squared errors (RMSE) for water levels and waves under 0.02 m and 0.26 m, respectively. During storm events, the magnitude and timing of storm surges are accurately predicted at 9 monitoring stations (RMSE < 0.05 m), with model accuracy either improving or remaining consistent with decreasing forecast length. Forecast significant wave heights agree with observed data (1–12 % relative error for peak wave heights) at 4 wave buoys in the lake. Coastlines-LO forecasts for storm surge prediction for two consecutive storm events were compared to those from the Great Lakes Coastal Forecasting System (GLCFS) to further evaluate model performance. Both systems achieved comparable results with average RMSEs of 0.02 m. Coastlines-LO is an open-source wrapper code driven by open-data and has a relatively low computational demand, compared to GLCFS, making this approach suitable for forecasting marine conditions in other coastal regions.

Laura L. Swatridge et al.

Status: open (until 07 Jan 2024)

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Laura L. Swatridge et al.

Laura L. Swatridge et al.

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Short summary
We develop an operational forecast system, COATLINES-LO, that can simulate water levels and surface waves in Lake Ontario driven by forecasts of wind speeds and pressure fields from an atmospheric model. The model requires a relatively small computational demand and results compare well with near real-time observations, as well as with results from other existing forecast systems. Results show that with shorter forecast lengths, storm surge and waves predictions can improve in accuracy.