Advancing understanding of interannual variability and extreme events in the thermal structure of large lakes under historical and future climate scenarios

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The overarching goal is to advance understanding of the North American Great Lakes thermal variability and occurrence of extreme events in both the historical period and under future climate scenarios. The project will fill critical knowledge gaps in how Great Lakes thermal structure responds to climate change by examining changes in lake surface temperatures and ice cover as well as how temporal variabilities have changed in the past and how they will continue to change under future climate scenarios. Advanced understanding of the role of teleconnection patterns in driving Great Lakes climate variability will help distinguish between changes related to anthropogenic global warming and those related to natural climate variability, an important distinction in the discussion of climate change mitigation. Hydrodynamic-ice simulation results will be generated for the historical period and under future climate scenarios for the Great Lakes. Improved understanding of historical and future occurrence of extreme conditions in Great Lakes’ thermal conditions will benefit decision making in shipping, fishing, recreational use of the lakes, as well as coastal management and climate adaptation efforts.The project will investigate interannual variabilities of ice coverage, lake heat content, stratification strength and duration, as well as timing and trends of lake surface temperatures, occurrence of extreme conditions, and how these variabilities are related to the large-scale atmospheric circulations. Numerical experiments with a three-dimensional hydrodynamic-ice model will be conducted with atmospheric reanalysis and the projected future surface meteorology out to the end-century from select climate model outputs. The historical simulations will be verified by comparing with the publicly available observational datasets. Changes in thermal conditions and their variabilities under historical and projected climate conditions will be evaluated using timeseries analysis, changes in probability density functions and the Schmidt stability index, and extreme value analysis. The research will address how extreme events and climate variability in the Great Lakes change over time and the role of teleconnection patterns and low-frequency oscillations.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.