Ensemble Ice Forecasting for the Laurentian Great Lakes Region

Seasonal ice formation on the Laurentian Great Lakes has significant economic, commercial, and recreational impacts to the more than 35 million people that call the region home. The ice formation on the lakes can disrupt regional shipping, impact recreational activity, and is crucial to the migration and habitat of indigenous fauna., Annual and intra-seasonal variability of ice formation, in terms of both scale and timing, has proven difficult to forecast with significant lead-time, necessitating adaptation strategies and infrastructure investments to mitigate its impacts. Research at NOAA’s Great Lakes Environmental Research Laboratory (GLERL) aims to develop forecast capabilities that enable decision makers with probabilistic and actionable ice information within the Laurentian Great Lakes, over the one to two week forecast horizon.

GLERL's Great Lakes Coastal Forecasting System (GLCFS) is an experimental implementation of the Finite-Volume, primitive equation Community Ocean Model coupled to CICE (FVCOM-CICE), that produces a deterministic forecast of lake circulation and other physical processes, including ice dynamics, out to a maximum forecast horizon of five days. By leveraging the GLCFS framework, and utilizing the 31 members of the Global Ensemble Forecast System (GEFS) as individual atmospheric inputs to FVCOM, an ensemble set of ice forecasts may be assembled out to a forecast horizon of 10 or more days. This 31-member ice forecast dataset may then be utilized to produce a series of probabilistic forecast products, including gridded mean and ensemble spread information, and point-based plume forecasts for individual high priority and high impact ice locations. Case studies from periods of ice onset and expansion will be presented to show the additional insight that can be derived from the ensemble approach. An additional simulation will be presented using the ensemble mean of the GEFS atmospheric variables as forcing for a deterministic FVCOM-CICE forecast. This approach might be able to leverage information gained from the atmospheric ensemble for less computational costs than running FVCOM-CICE for an entire ensemble at the expense of losing probabilistic information.

The intended outcome of this forecast methodology is to assist regional forecasters and other Great Lakes decision makers with the tools for longer-term planning and mitigation strategies, than have previously been possible, with regards to ice formation, decay, and evolution.