Great Lakes Observing & Forecasting Systems

Overview and Objectives

This project evaluates the new National Centers for Environmental Prediction (NCEP) High-Resolution Rapid Refresh (HRRR) model output for the Great Lakes. The HRRR model is a rapid update weather model that uses radar and other observations to improve forecasted weather conditions. Currently, the operational forecasting systems (OFS) including the Great Lakes Operational Forecast System (GLOFS) and the Great Lakes Coastal Forecasting System (GLCFS) do not use radar data as part of the surface marine observations that drive the hydrodynamic simulations. In addition, the existing OFS use hourly, interpolated meteorological observations to determine over-lake conditions and as a result are unable to resolve fine-scale convective processes and some coarse-scale over-water wind conditions. Currently, the next generation of the GLCFS is under development using the Finite Volume Coastal Ocean Model (FVCOM); the first model, Lake Erie Operational Forecasting System (LEOFS), became operational in May 2016. The HRRR model has been identified as a candidate for meteorological forcing conditions needed by the FVCOM Lake Erie model (LEOFS); however, no study of hydrodynamic response on any body of water has been carried out. Although the potential for HRRR to improve meteorological outlooks is known, we do not know how well the HRRR resolves over-water conditions for the Great Lakes (at 3km scale) or how hydrodynamic models will respond to the implementation of rapid-update weather forcing. The objective of this project is to answer key questions pertaining to the suitability of HRRR for hydrodynamic OFS implementation and improvement to model skill.