Modeling the Impact of Water Mixing and Ice on Deep, Inland Lake Warming

Session: 36. - Improving Model Predictions through Coupled System and Data Assimilation

Xinyu Ye, Michigan Tech University, [email protected]
Eric Anderson, NOAA, Great Lakes Environmental Research Laboratory (GLERL), [email protected]
Philip Chu, NOAA/GLERL, [email protected]
Chenfu Huang, Michigan Technological University, [email protected]
Pengfei Xue, Michigan Tech, [email protected]

Abstract

The Laurentian Great Lakes are one of the most prominent hotspots for the study of climate change induced lake warming. Warming trends in large, deep lakes, which are often inferred by the observations of lake surface temperature (LST) in most studies, are strongly linked to the total lake heat content through the winter to the following summer. In this study, we use a 3-D hydrodynamic model to examine the nonlinear processes of water mixing and ice formation that cause changes in lake heat content and further variation of LST in the following year. With a focus on mechanism study, a series of process-oriented experiments is carried out to understand the interactions among these processes and their relative importance to the lake heat budget. Using a numerical model, we estimate the lake heat content by integrating over the entire three-dimensional volume. Our analysis reveals that 1) Heat content trends do not necessarily follow (can even be opposed to) trends in LST; 2) Water mixing may play a more important role in regulating lake warming; 3) Ice albedo feedback, even in cold winters, has little impact on lake thermal structure, and its influence on lake warming may have been overestimated.  

4. Additional Keyword
Water mixing

5. Additional Keyword
Ice formation

6. Additional Keyword
Lake Superior warming