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Development, implementation, and skill assessment of the NOAA/NOS Great Lakes Operational Forecast System

机译：NOAA / NOS大湖区业务预报系统的开发，实施和技能评估

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The NOAA Great Lakes Operational Forecast System (GLOFS) uses near-real-time atmospheric observations and numerical weather prediction forecast guidance to produce three-dimensional forecasts of water temperature and currents, and two-dimensional forecasts of water levels of the Great Lakes. This system, originally called the Great Lakes forecasting system (GLFS), was developed at The Ohio State University and NOAA's Great Lakes Environmental Research Laboratory (GLERL) in 1989. In 1996, a workstation version of the GLFS was ported to GLERL to generate semi-operational nowcasts and forecasts daily. In 2004, GLFS went through rigorous skill assessment and was transitioned to the National Ocean Service (NOS) Center for Operational Oceanographic Products and Services (CO-OPS) in Silver Spring, MD. GLOFS has been making operational nowcasts and forecasts at CO-OPS since September 30,2005. Hindcast, nowcast, and forecast evaluations using the NOSdeveloped skill assessment software tool indicated both surface water levels and temperature predictions passed the NOS specified criteria at a majority of the validation locations with relatively low root mean square error (4-8 cm for water levels and 0.5 to 1°C for surface water temperatures). The difficulty of accurately simulating seiches generated by storms (in particular in shallow lakes like Lake Erie) remains a major source of error in water level prediction and should be addressed in future improvements of the forecast system.
机译：美国国家海洋和大气管理局大湖区运行预报系统（GLOFS）使用近实时的大气观测和数值天气预报预报指南来生成水温和水流的三维预报，以及大湖水位的二维预报。该系统最初称为大湖预测系统（GLFS），于1989年由俄亥俄州立大学和NOAA的大湖环境研究实验室（GLERL）开发。1996年，GLFS的工作站版本移植到GLERL以生成半-每日进行业务预报和预报。 2004年，GLFS进行了严格的技能评估，并移交给位于马里兰州银泉的国家海洋局（NOS）业务海洋产品和服务中心（CO-OPS）。自2005年9月30日以来，GLOFS一直在CO-OPS上进行可操作的临近预报和预报。使用NOS开发的技能评估软件工具进行的后播，临近预报和预报评估表明，大多数验证位置的地表水位和温度预测均通过了NOS指定的标准，均方根误差相对较低（水位为4-8 cm， 0.5至1°C（地表水温度）。准确模拟暴风雨所产生的地形的困难（尤其是在伊利湖等浅湖中）仍然是水位预测误差的主要来源，应在未来的预报系统改进中加以解决。

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