Assessing change in the overturning behavior of the Laurentian Great Lakes using remotely sensed lake surface water temperatures

Cédric G. Fichot, Katsumi Matsumoto, Benjamin Holt, Michelle M. Gierach, Kathy S. Tokos

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Most large temperate lakes experience overturning every spring and fall as surface water moves past 4 °C, the temperature of maximum density for freshwater. These semiannual, lake-wide overturning events play an important role regulating the thermal structure, deep-water ventilation, nutrient supply, water circulation, and nearshore water quality of the lakes. The general pattern of overturning has long been known from field observations and models, but its timing, duration, detailed spatio-temporal progression and seasonal and interannual variability remain largely undocumented, particularly in the context of recent climate-driven changes in lake thermal dynamics. Here, we used a reconstructed record of daily and spatially-explicit lake surface water temperatures (LSWT) to analyze the migration of the 4 °C thermal front as it progressed from the shorelines to the deep parts of the Laurentian Great Lakes during every overturning event between June 1995 to April 2012. The analysis revealed a strong asymmetry in the timing and duration of overturning between spring and fall, and no relationship with the lake-averaged LSWT or its rate of change. Key differences in the average spatio-temporal progression of overturning were also observed between spring and fall, with the spring progression being largely driven by latitude and water depth and the fall progression being less predictable and influenced by other factors such as wind. Narrow regions of very slow overturning progression were also identified, revealing areas of the lakes where persistent 4 °C thermal bars are likely to re-occur every year. The timing and duration of these seasonal overturning events varied between years by as much as one and two months, respectively, with a direct impact on the duration of lake-wide stratification. In 2012, Lakes Michigan and Ontario experienced an incomplete fall overturning, leading only to a partial winter stratification. Lakes Michigan and Ontario were more susceptible to experience an incomplete overturning than the other Laurentian Great Lakes, seemingly due to a combination of comparatively milder winter air temperatures and lower lake dynamic ratio (steepness of bottom slope). Overall, the duration of lake-wide winter stratification was found to be strongly correlated with mean winter air temperatures, and a simple trend analysis suggested that rising temperatures could lead to more frequent incomplete fall overturnings and partial winter stratifications in Lakes Michigan and Ontario over the next few decades. This study demonstrated that remote sensing provides an unparalleled tool for assessing the long-term variability in the overturning behavior of large lakes in the context of climate change.

Original languageEnglish (US)
Article number111427
JournalRemote Sensing of Environment
Volume235
DOIs
StatePublished - Dec 15 2019

Bibliographical note

Funding Information:
This work was directly supported by National Aeronautics and Space Administration (NASA) Physical Oceanography grant NNX13AM85G to K.M., B.H, and M.G. This research was carried out in part at the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration. We thank the European Space Agency (ESA) and ARC-Lake for free access to the reconstructed remotely sensed LSWT used in this study. We also thank the National Oceanic and Atmospheric Administration (NOAA) Great Lakes Environmental Research Laboratory for free access to the air temperature, ice cover, and wind speed data used in this study, and the NOAA National Data Buoy Center for access to the in-situ water temperature data. Finally, we thank Paul McKinney for discussion during the early stages of this study. The MathWorks Matlab® software was used for all computations done in this work. Simple and multiple linear regressions, error analyses, and all plots presented in this work were made using the R language and environment for statistical computing and graphics available from the Comprehensive R Archive Network ( https://cran.r-project.org ). The Generic Mapping Tools ( http://gmt.soest.hawaii.edu ) were used to generate all the maps presented in this work.

Funding Information:
This work was directly supported by National Aeronautics and Space Administration (NASA) Physical Oceanography grant NNX13AM85G to K.M. B.H, and M.G. This research was carried out in part at the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration. We thank the European Space Agency (ESA) and ARC-Lake for free access to the reconstructed remotely sensed LSWT used in this study. We also thank the National Oceanic and Atmospheric Administration (NOAA) Great Lakes Environmental Research Laboratory for free access to the air temperature, ice cover, and wind speed data used in this study, and the NOAA National Data Buoy Center for access to the in-situ water temperature data. Finally, we thank Paul McKinney for discussion during the early stages of this study. The MathWorks Matlab? software was used for all computations done in this work. Simple and multiple linear regressions, error analyses, and all plots presented in this work were made using the R language and environment for statistical computing and graphics available from the Comprehensive R Archive Network (https://cran.r-project.org). The Generic Mapping Tools (http://gmt.soest.hawaii.edu) were used to generate all the maps presented in this work.

Keywords

  • Dimictic lake
  • Lake stratification
  • Lake surface water temperature
  • Laurentian Great Lakes
  • Overturning
  • Thermal bar
  • Thermal front

Fingerprint Dive into the research topics of 'Assessing change in the overturning behavior of the Laurentian Great Lakes using remotely sensed lake surface water temperatures'. Together they form a unique fingerprint.

Cite this