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

总体目标是增进对北美五大湖的热力变化以及在历史时期和未来气候情景下极端事件发生的了解。该项目将通过研究湖泊表面温度和冰盖的变化，以及过去的时间变化如何变化，以及它们在未来气候情景下将如何继续变化，来填补五大湖热结构如何应对气候变化的关键知识空白。深入了解遥相关模式在驱动五大湖气候变异性方面的作用，将有助于区分与人为全球变暖有关的变化和与自然气候变异性有关的变化，这是气候变化缓解讨论中的一个重要区别。将为五大湖的历史时期和未来气候情景生成水动力-冰模拟结果。加强对五大湖热状况历史和未来极端情况发生的了解，将有助于航运、渔业、湖泊娱乐利用以及海岸管理和气候适应工作的决策。该项目将调查冰盖、湖泊热含量、层化强度和持续时间的年际变化，以及湖面温度的时间和趋势、极端情况的发生，以及这些变化与大尺度大气环流的关系。将对一个三维流体动力--冰模式进行数值试验，对大气进行再分析，并从选定的气候模式输出中预测到本世纪末的未来地表气象。历史模拟将通过与公开可用的观测数据集进行比较来验证。热条件的变化及其在历史和预测气候条件下的变化将使用时间序列分析、概率密度函数和施密特稳定指数的变化以及极值分析来评估。这项研究将研究五大湖的极端事件和气候变化如何随时间变化，以及遥相关模式和低频振荡的作用。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

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.