Coordinating Improvements to Short-Term Forecasts of Ice, Water Temperature, Turbulent Heat Fluxes, and Lake-Effect Precipitation Forecasts with the Next-Generation NOAA Great Lakes Operational Forecast System (GLOFS)

Improvements to short-term forecasts can be achieved through several approaches such as refinement of model physics, model coupling, and improved data quality or assimilation. The time between upgrades of forecast modeling systems can be significant and coordination of upgrades among linked or coupled systems developed and maintained by different agencies can be difficult, thus hindering or impeding development of next-generation forecast systems. For some types of forecasts, such as lake-effect snow, these hindrances can be particularly impactful because improvements are required across several operational systems, including hydrodynamic, ice, and weather forecast models. In the next-generation NOAA Great Lakes Operational Forecast System (GLOFS), we aim to make coordinated improvements, between NOS, NWS, and OAR, to hydrodynamic processes and short-term forecasts of water temperature and heat flux, add a coupled ice model using the Los Alamos Sea Ice Model (CICE), and provide one-way linkage/coupling of lake surface conditions to weather forecast models, such as the NOAA High-Resolution Rapid Refresh (HRRR). Currently, there is no short-term ice forecast for the Great Lakes, as the existing GLOFS does not contain an ice model, and thus forecast guidance of winter marine conditions are limited. This gap in short-term ice forecasting has a significant impact on stakeholder needs such as commercial shipping and navigation, as well as on US Coast Guard operations like spill response and search and rescue. In addition, existing short-term weather forecast models do not use surface conditions from operational lake forecast models, but instead rely on satellite-based remote-sensing of lake surface temperatures (LST) from the NOAA/NWS/NCEP Real-Time Global (RTG) daily surface water temperature analysis. Due to cloud cover and dynamic lake-surface conditions, this can lead to inaccurately prescribed or out-of-date surface conditions and have consequential impacts to the accuracy of extreme weather events such as lake-effect snow. In this work, we detail the transition from research to operations of the next-generation GLOFS, a cross-NOAA and -academic collaboration, in which the Finite Volume Community Ocean Model (FVCOM) is coupled with CICE and implemented as a new version of GLOFS. Early results show the next-generation GLOFS provides improved water surface temperatures, accurate ice prediction, reasonable estimates of turbulent surface heat fluxes as compared to the Great Lakes Evaporation Network (GLEN), and improved surface conditions for HRRR lake-effect forecast guidance.