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

总体目标是促进对北美五大湖在历史时期和未来气候情景下的热变率和极端事件发生的理解。该项目将填补五大湖热结构如何响应气候变化的关键知识空白，通过检查湖泊表面温度和冰盖的变化，以及过去的时间变率如何变化，以及它们将如何在未来的气候情景下继续变化。深入了解遥相关模式在推动五大湖气候变率方面的作用，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率有关的变化，这是讨论减缓气候变化时的一个重要区别。将生成五大湖历史时期和未来气候情景下的水动力-冰模拟结果。更好地了解五大湖热条件中极端条件的历史和未来发生情况，将有利于航运、渔业、湖泊的娱乐利用以及沿海管理和气候适应工作的决策。该项目将调查冰覆盖、湖泊热含量、分层强度和持续时间的年际变化，以及湖泊表面温度的时间和趋势、极端条件的发生，以及这些变化与大尺度大气环流的关系。将利用一个三维水动力-冰模式进行数值实验，同时进行大气再分析，并根据选定的气候模式输出预估到本世纪末的未来地表气象。历史模拟将通过与公开的观测数据集进行比较来验证。将利用时间序列分析、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历史和预估气候条件下热条件的变化及其变率。该研究将探讨五大湖的极端事件和气候变化是如何随时间变化的，以及遥相关模式和低频振荡的作用。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值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.