Improving Great Lakes Regional Operational Water Budget and Water Level Forecasting

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Monday, 5 January 2015
Rebecca Bolinger, UCAR, Ann Arbor, MI; and K. Kompoltowicz, T. Hunter, and A. Gronewold

Accurately forecasting water levels of the North American Great Lakes is an important priority for regional research-oriented and operational institutions. Extreme persistent low water levels on the Great Lakes over the past 15 years, coupled with unprecedented seasonal water level increases, underscores the challenges associated with addressing this priority. NOAA, through its Great Lakes Environmental Research Laboratory (GLERL), and the Detroit District of the U.S. Army Corps of Engineers (USACE) routinely collaborate through formal research-to-operations projects focused on improving operational projections of the Great Lakes water budget and water levels. More specifically, the USACE (in partnership with colleagues from Environment Canada) is responsible for developing and distributing official operational forecasts of six-month water supply forecasts for each lake every month, while NOAA-GLERL (in partnership with other NOAA line offices and research laboratories) focuses on implementing recommended improvements to models, monitoring infrastructure, and forecasting protocol.

Here, we describe the latest evolution in the NOAA-USACE regional research-to-operations partnership that focuses on improving both historical estimates, as well as projections, of temperature (T) and precipitation (P) for the Great Lakes basin (as well as for the sub-basins of each individual lake). More specifically, we explore the extent to which model projections might be improved through alternative estimates of T and P, and alternative protocols for propagating those estimates into water budget and water level forecasts. We find that minor improvements in the current decision-making hierarchy within USACE, particularly those focused on explicitly quantifying relationships between regional and continental scale climate patterns, have the potential to significantly improve water budget and water level forecasting skill.