Preprints
https://doi.org/10.5194/gmd-2021-34
https://doi.org/10.5194/gmd-2021-34

Submitted as: model description paper 29 Mar 2021

Submitted as: model description paper | 29 Mar 2021

Review status: a revised version of this preprint is currently under review for the journal GMD.

An automatic lake-model application using near real-time data forcing: Development of an operational forecast model for Lake Erie

Shuqi Lin1, Leon Boegman1, Shiliang Shan2, and Ryan Mulligan1 Shuqi Lin et al.
  • 1Department of Civil Engineering, Queen’s University, Kingston ON Canada K7L 3N6
  • 2Department of Physics and Space Science, Royal Military College of Canada, Kingston ON Canada K7K 7B4

Abstract. For enhanced public safety and water resource management, a three-dimensional operational lake hydrodynamic forecast system called COASTLINES (Canadian cOASTal and Lake forecastINg modEl System) was developed. The modelling system is built upon the Aquatic Ecosystem Model (AEM3D) model, with predictive simulation capabilities developed and tested for a large lake (i.e., Lake Erie). The open-access web-based platform derives model forcing, code execution, post-processing and visualization of the model outputs, including water level elevations and temperature, is in near real-time. COASTLINES currently generates 240-h predictions using atmospheric forcing from 15 km and 25 km horizontal-resolution operational meteorological products from the Environment Canada Global Deterministic Forecast System (GDPS). Simulated water levels were validated against observations from 6 gauge stations, with model error increasing for longer forecast times. Satellite images and lake buoys were applied to validate forecast lake surface temperature (LST) and the water column thermal stratification. The forecast LST is as accurate as hindcasts, with a root-mean-square-deviation < 2 ℃. COASTLINES predicts storm-surge events and up-/down-welling events that are important for flood water and drinking water/fishery management, respectively. Model forecasts are available in real-time at https://coastlines.engineering.queensu.ca/. This study provides an example of the successful development of an operational forecasting system, entirely driven by open-access data, that may be easily adapted to simulate aquatic systems or to drive other computational models, as required for management and public safety.

Shuqi Lin et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • CEC1: 'Comment on gmd-2021-34', Astrid Kerkweg, 10 May 2021
    • AC1: 'Reply on CEC1', Shuqi Lin, 14 Jul 2021
  • RC1: 'Comment on gmd-2021-34', Anonymous Referee #1, 12 May 2021
    • AC3: 'Reply on RC1', Shuqi Lin, 15 Jul 2021
  • RC2: 'Comment on gmd-2021-34', Daisuke Tokuda, 16 May 2021
    • AC2: 'Reply on RC2', Shuqi Lin, 15 Jul 2021

Shuqi Lin et al.

Shuqi Lin et al.

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Short summary
An operational lake forecast system was developed and tested for a large lake. The system predicted storm-surge and up-/down-welling events that are important for flood water and drinking water/fishery management. This study provides an example of the successful development of an operational forecast system, driven by open-access meteorological forecast, validated by online real-time observations, that can be adapted to simulate aquatic systems as required for management and public safety.