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

Remote Sensing of Environment 235 (2019) 111427

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

T

Cédric G. Fichota,∗, Katsumi Matsumotob,∗∗, Benjamin Holtc, Michelle M. Gierachc, Kathy S. Tokosb a

Department of Earth and Environment, Boston University, Boston, MA, USA Department of Earth and Environmental Sciences, University of Minnesota, Minneapolis, MN, USA c Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA b

A R T I C LE I N FO

A B S T R A C T

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

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.

1. Introduction The Laurentian Great Lakes (Lake Superior, Huron, Michigan, Ontario, and Erie) are dimictic, meaning they mix from top to bottom (overturn) twice in a year (Fig. 1). Located in a temperate region, these large lakes experience overturning in the spring and again in the fall as

surface water temperature moves past ∼4 °C (3.94 °C), the temperature of maximum density for freshwater (Boyce et al., 1989). These semiannual mixing events typically affect the entire lake and are separated by periods of lake-wide stratification (Beletsky and Schwab, 2001; Boehrer and Schultze, 2008; Rao, 2012). Summer stratification is established after spring overturning when warm (» 4 °C) and buoyant

∗

Corresponding author. Corresponding author. E-mail addresses: cgfi[email protected] (C.G. Fichot), [email protected] (K. Matsumoto), [email protected] (B. Holt), [email protected] (M.M. Gierach), [email protected] (K.S. Tokos). ∗∗

https://doi.org/10.1016/j.rse.2019.111427 Received 21 March 2019; Received in revised form 9 September 2019; Accepted 16 September 2019 0034-4257/ © 2019 Elsevier Inc. All rights reserved.

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Fig. 1. Dimictic behavior of the Laurentian Great Lakes. (A) Map of the Laurentian Great Lakes region showcasing lake bathymetry and the location of the NOAA National Data Buoy Center (NDBC) buoys used in the validation of the remotely sensed lake surface water temperatures. NDBC buoy numbers are 45001 (Superior), 45003 (Huron), 45002 (Michigan), and 45012 (Ontario), 45005 (Erie). (B) Schematic representation of the seasonal overturning and stratification typical of large dimictic lakes such as the Laurentian Great Lakes.

1996; Matsumoto et al., 2015; Scavia and Fahnenstiel, 1987). It can also affect coastal water circulation and water quality (Holland and Kay, 2003b). Persistent 4 °C thermal fronts can hinder horizontal mixing by generating geostrophic currents flowing parallel to the shores (Bennett, 1971; Rao and Schwab, 2007). These “thermal bars” affect the degree to which nearshore and often more turbid or polluted waters mix with offshore waters, thereby influencing coastal water quality, especially during the spring overturning period which often coincides with a peak in river discharge (Auer and Gatzke, 2004; Moll et al., 1993). Thermal bars are also sometimes associated with eddies, which can affect crossshelf exchange (McKinney et al., 2018, 2012; Ralph, 2002). A detailed characterization of the overturning behavior of the Laurentian Great Lakes and of its variability is key to our understanding of how these large lacustrine ecosystems function and respond to environmental change. Assessing change in the overturning behavior of the Laurentian Great Lakes is all the more important because these large lakes are identified as hotspots of warming lakes worldwide (O'Reilly et al., 2015) and are known to be undergoing an important transformation. Annual air temperatures over the Laurentian Great Lakes region have increased by 1.1 °C over the past 50 years, and hydrology, lake ice cover, and lake water temperatures have responded to this regional change in climate (Austin and Colman, 2008; Bartolai et al., 2015; Croley II, 1994; Magnuson et al., 2000). In Lake Superior, observations (Austin and Colman, 2007) and models (White et al., 2012) showed that rising summer air temperatures have been accompanied by an even faster increase in surface water temperatures, an amplification that seems diagnostic of deep, cold lakes (Woolway and Merchant, 2017). The resulting decrease in summer lake-atmosphere temperature gradient has also destabilized the surface boundary layer and increased wind speeds over the lake (Desai et al., 2009). An earlier onset of summer stratification of two weeks was also predicted and reported (Austin and Colman, 2007; Trumpickas et al., 2009). Finally, models suggest that rising temperatures could alter the thermal structure and mixing dynamics of these lakes (Austin and Allen, 2011; Matsumoto et al., 2015; Piccolroaz et al., 2015; Titze and Austin, 2014), including less frequent seasonal overturning (McCormick, 1990; Mortsch and Quinn, 1996). A 3D model-based future projection of Lake Superior indicates that wintertime stratification might become dramatically weaker by the middle of the 21st century under global warming (Matsumoto et al., 2019). Despite these studies, it remains unclear if the

surface waters are isolated by a thermocline from colder, denser underlying waters; winter stratification is established after fall overturning when cold surface waters (0 < temperature < 4 °C) are isolated from slightly warmer water (∼4 °C) below by a weak thermocline and at times from the atmosphere above by ice cover. This dimictic behavior plays an important role regulating these lacustrine ecosystems by periodically altering the thermal structure of the water column, enhancing deep-water ventilation and nutrient supply to surface waters, and by affecting water circulation and nearshore water quality (Holland and Kay, 2003a; Rao and Schwab, 2007). Seasonal overturning typically affects the entire lake, but it does not occur everywhere on the lake at the same time and it generally progresses following a characteristic pattern in large lakes (Fig. 1B). Vertical mixing is induced by water-column instability when surface water reaches 4 °C, and locally the sinking of dense 4 °C surface water can effectively mix the entire water column. First, a narrow band of downwelling 4 °C surface water forms nearshore as a surface manifestation of this water-sinking phenomenon and constitutes a 4 °C thermal front (Holland and Kay, 2003a; Rodgers, 1965). This thermal front then migrates offshore from the shallow margins of the lake and until the entire lake is overturned (Elliott, 1971; Zilitinkevich et al., 1992). This general progression is expected during the warming phase in the spring and during the cooling phase in the fall (Beletsky and Schwab, 2001), and it has been repeatedly observed locally in the Laurentian Great Lakes (Consi et al., 2008; Csanady, 1974; Hubbard and Spain, 1976; Moll et al., 1993; Rao et al., 2004; Rodgers, 1965). Ullman et al. (1998) investigated the seasonal evolution of thermal fronts in the Laurentian Great Lakes using remotely sensed data collected during 1985–1995 and observed this nearshore-to-offshore progression of the 4 °C thermal front on a lake-wide scale. Although these studies all confirmed that this conceptual pattern of overturning applies to the Laurentian Great Lakes, the actual timing, duration, and detailed spatio-temporal progression of the spring and fall overturning in these five contrasted lakes still remain poorly documented, and their interannual variabilities are largely unexplored. Variability in the seasonal overturning can influence the properties and functioning of these lacustrine environments. It can directly influence the timing and duration of lake-wide stratification, with consequences for heat and gas exchange with the atmosphere, light distribution in the water column, primary production and pelagic communities (Boyce et al., 1989; Frenette et al., 1994; Goldman et al., 2

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ALIDxxxx_PLREC3N for AATSR, where PL corresponds to “per-lake”, REC corresponds to “reconstructed”, numbers 2 and 3 corresponds to the ATSR-2 and AATSR, respectively, and xxxx correspond to the lake ID (0002 for Lake Superior; 0005 for Lake Huron; 0006 for Lake Michigan; 0012 for Lake Erie; 0015 for Lake Ontario).

overturning behavior of the Laurentian Great Lakes has been undergoing change in response to recent climate-driven changes. The remote sensing of lake water surface temperatures (LSWT) can provide the spatio-temporal coverage needed to characterize the overturning behavior of these large lakes and assess its multi-year variability. Several studies have already demonstrated the value of remotely sensed surface temperature for assessing change in the thermal regimes of lakes on regional and global scales (O'Reilly et al., 2015; Schneider et al., 2009; Woolway et al., 2017) and for the large-scale detection and study of thermal fronts (Malm and Jönsson, 1993; Mortimer, 1988; Schott, 1986; Ullman et al., 1998). Here, we used a reconstructed record of daily and spatially-explicit remotely sensed lake water surface temperatures (LSWT) (MacCallum and Merchant, 2012) in order to track 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 events between June 1995 to April 2012. We specifically analyze the LSWT data to provide a detailed and comparative characterization of the spring and fall overturning patterns in these five contrasted lakes. Most importantly, the data are analyzed to determine the inter-annual variability in these lakes' overturning behavior, and assess if there were any potential change over the past two decades. These observations and results are also interpreted in light of regional climate indicators (Hunter et al., 2015) in an effort to identify the main factors influencing the overturning behavior of these large lakes.

2.2. In situ lake surface water temperature Hourly in situ measurements of surface-water temperatures made at fixed buoys in each of the five Laurentian Great Lakes were used to ground-truth the remotely sensed LSWT. The nighttime measurements only (average from local 12 a.m.–3 a.m.) were averaged and used as daily in situ surface water data to be compared to the remotely sensed LWST. The in situ measurements were made continuously at a reported depth of 0.6 m (Lakes Superior, Michigan, Ontario) or 1 m (Lakes Huron, Erie) by temperature probes mounted on tethered buoys located more or less in the middle of each lake (Fig. 1a). The data are available from the National Oceanographic and Atmospheric Administration (NOAA) National Data Buoy Center (NDBC) website (http://www.ndbc. noaa.gov). 2.3. Bathymetry

A flowchart illustrating how the data are used and analyzed to characterize the overturning behavior of the Laurentian Great Lakes and to assess change in their overturning behaviors is presented in the Supplementary Information (Supplementary Fig. 1).

A 3 arc-second bathymetry gridded data (∼90 m cell size) of each great lake was obtained from the National Oceanographic and Atmospheric Administration (NOAA) National Centers for Environmental Information (NCEI) website (https://www.ngdc.noaa. gov/mgg/greatlakes/), formerly the National Geophysical Data Center (NGDC). In order to facilitate analysis, the bathymetry data were interpolated to match the spatial resolution and grid of the ARC-Lake data.

2.1. Reconstructed remotely sensed lake surface water temperatures

2.4. Air temperatures and wind speed

Spatially-resolved (0.05°), daily lake surface water temperatures (LSWT) were obtained for the five Laurentian Great Lakes from the ATSR Reprocessing for Climate: Lake Surface Water Temperature & Ice Cover (ARC-Lake) website (http://www.laketemp.net/home/dataF/). ARC-Lake was a project funded by the European Space Agency that aimed to produce high-quality lake surface water temperature estimates from the series of along-track scanning radiometers (ATSRs). The data used in this study were derived from the ATSR-2 sensor (launched onboard the ERS-2 spacecraft in April 1995) and the Advanced ATSR (AATSR) sensor (launched onboard the ENVISAT spacecraft in March 2002). Both sensors included three thermal infrared bands at 3.7 μm, 11 μm and 12 μm, and produced infrared images at a spatial resolution of 1-km at nadir. The remotely sensed emitted thermal infrared radiation from the ATSRs have traditionally been used for retrieving sea surface temperatures (SST) and land surface temperatures (LST). The objective of the ARC-Lake project was to expand these measurements to also include lakes by improving cloud screening and addressing specific challenges of retrieving LSWT related to variations in atmospheric conditions, lake elevation and salinity, and lake-boundary effects through optimal estimation (MacCallum and Merchant, 2012). The ARC-Lake v3.0 reconstructed LSWT products were used in this study. These data products were derived from spatially and temporally complete reconstructions of the observed ARC-Lake LSWT products. Spatially complete reconstructions were derived from the observed LSWT using Empirical Orthogonal Functions (EOF)-based techniques, using the Data INterpolating Empirical Orthogonal Functions (DINEOF) software (Alvera-Azcárate et al., 2005). Details of the methodology used to derive these reconstructions are available in MacCallum and Merchant (2012). Specifically, the daily, spatially-resolved, per-lake (PL), reconstructed (REC), night-time (N), time-series data were used in this study. The data used in the study carried the following ARC-Lake ID (ALID) nomenclature: ALIDxxxx_PLREC2N for ATSR-2 and

Monthly wind speeds and average air temperatures over each lake basin for the 1948–2014 period were obtained from the National Oceanographic and Atmospheric Administration (NOAA) Great Lakes Environmental Research Laboratory (GLERL) Great Lakes Monthly Hydrologic Data (https://www.glerl.noaa.gov/ahps/mnth-hydro.html). A detailed description of the methods and data is published elsewhere (Hunter et al., 2015).

2. Data and methods

2.5. Ice cover Gridded, daily ice cover data were obtained for the five Laurentian Great Lakes from the NOAA GLERL Electronic Atlas of Great Lakes Ice Cover Winters for the 1995–2002 time period (2.5 × 2.5 km spatial resolution), and from the NOAA GLERL Great Lakes Ice Cover Data for the 2003-2012-time period (1.275 × 1.275 km spatial resolution). These data can be found on the NOAA GLERL website (https://www. glerl.noaa.gov/data). The gridded data were then compiled into daily % ice-cover (% of lake surface area covered by ice) and averaged to derive mean January/February/March/April (JFMA) % ice-cover values. In order to facilitate analysis, the ice-cover data were interpolated to match the spatial resolution and grid of the ARC-Lake data. 2.6. Estimation of uncertainties in remotely sensed LSWT A direct comparison with in situ measurements made from temperature probes mounted on tethered NOAA NDBC buoys was used to evaluate the average uncertainty associated with the reconstructed remotely sensed LSWT, using the in situ measurements as a reference (Fig. 2 and Supplementary Fig. 2). The remotely sensed LSWT was compared to coincident and co-located in situ measurements in each of the five Great Lakes and for most of the ice-free periods of all 16 complete years of the remote-sensing record (1996–2011). The 3

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Fig. 2. Validation of the reconstructed remotely sensed lake surface water temperatures (LSWT). Comparisons are between reconstructed night-time, remotely sensed LSWT and night-time, in situ surface temperatures measured by sensors mounted on NOAA NDBC buoys (depth of measurement = 0.6 or 1 m) for each day between 1996 and 2011 (between 2002 and 2011 for Lake Ontario). Only the data when both measurements were available are shown here. The locations of the NOAA NDBC buoys are shown in Fig. 1. Additional comparisons with other NDBC buoys, and histograms of the difference between in situ and remotely sensed temperatures are presented in the Supplementary Information (Supplementary Figs. 2 and 3, and Supplementary Tables 1 and 2). On average, the analysis revealed that remotely sensed LSWT were within ± 0.80 °C of the in situ surface temperatures and normally distributed around an error of 0.

temperature measurement, whereas the in situ measurements were made at a depth of approximately 0.6 m or 1 m (Donlon et al., 2002).

comparisons, which included linear regressions of the remotely sensed LWST on the in situ water temperatures (Supplementary Table 1), revealed that the reconstructed remotely sensed LSWT matched the in situ measurements remarkably well in all lakes and over the full range of temperature and with no major bias (Fig. 2). For each lake, the distribution of the difference between remotely sensed LSWT and in situ water temperatures was also examined and appeared normally distributed around a median and a mean of about 0, and with minimal skewness (Supplementary Fig. 3 and Supplementary Table 2). On average, the remotely sensed LSWT were within ± 0.8 °C (from ± 0.70 to ± 0.92 °C, depending on the lake) of the surface water temperatures measured in situ by the NOAA NDBC buoy, as indicated by the mean of the absolute values of the temperature difference (Supplementary Table 2). These uncertainties are in line with what has already been reported for these data sets (MacCallum and Merchant, 2012). Note that part of the difference between in situ and remotely sensed LSWT can come from the fact that the remotely sensed LSWT is essentially a “skin”

2.7. Calculation of durations of overturning and lake-wide stratification The evolution of spring and fall overturning in each lake was determined by monitoring the migration of the 4 °C surface isotherm (4 °C thermal front) on the daily maps of LSWT generated from the ARC-Lake reconstructed data. For every day between June 1995 and May 2012, a color map of LSWT with a 4°C contour was generated for the five Laurentian Great Lakes. The time series of maps allowed the direct determination of the onset (appearance of 4 °C surface water anywhere in the lake) and end (disappearance of any 4 °C surface water) of spring and fall overturning in any given year. Note that the evolution of the fall thermal bar typically started in the late fall and extended to the early months of the following year. The duration of winter stratification was calculated as the number of days between the last day of the fall 4

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a grid of the day of year when the 4 °C LSWT was present (day of occurrence) for each lake and each year, for both the spring and fall. A mapped climatology of the day of occurrence was then calculated as the average of the 17 grids (1 grid for each year of the record), corresponding here to a mapped representation of the average day of year when local overturning typically occurred (over the period corresponding to the observation record). This climatology was then used to calculate the longitudinal and latitudinal gradients in day of year between all elements of the grids. These gradients were then divided by the corresponding distance between grid elements in order to derive longitudinal and latitudinal migration rates of the 4 °C thermal front. The non-directional migration rate at each grid element was then calculated as the square root of the sum of squared longitudinal and latitudinal migration rates, resulting in a mapped climatology of the migration rates of the 4 °C thermal front.

turnover and the day marking the onset of the spring overturn. 2.8. Sensitivity of duration of stratification and overturning to uncertainties in LSWT A sensitivity analysis was performed in order to estimate the uncertainty in the calculated durations of stratification and overturning that originated from uncertainties in the remotely sensed LSWT. Briefly, noise was added to the original remotely sensed LSWT and the effect on the day of year when the 4 °C LSWT was reached was assessed for every location on the lake. Noise was added to the original LSWT as in Eq. (1) ˆ : to generate altered LSWT values denoted here as LWST

ˆ LWST = LWST + 0.8 ∗ ε

(1)

where 0.8 corresponds to the mean of the absolute values of the temperature difference between remotely-sensed LSWT and the corresponding NOAA NDBC-buoy surface water temperature, estimated from the comparative analysis with in situ measurements (see section 2.6), and ε is a random number generated from a normal distribution of mean 0 and standard deviation σ = 1/ 2/ π . Noise was added to every LSWT value in the gridded observation record. This approach allowed to randomly add additional noise in the remotely sensed LSWT drawn from a similar distribution as that observed in the comparative analysis with in situ measurements (Supplementary Fig. 3 and Supplementary Table 2). In order to keep the noise patterns realistic, some spatial and temporal correlation in the noise was included by randomly generating noise values over a spatial grid of 0.2° x 0.2° and for every 4 days in the record before interpolation to match the spatial and temporal resolution of the original LSWT observations (0.05° x 0. 05°, daily). The day of year when the 4 °C LSWT was reached at every location on the lake (day of year of 4oC-LSWT occurrence) was then estimated for every spring ˆ observation record. These vaand fall season using the altered LWST lues were then compared to the corresponding “reference” values generated using the original LSWT. This process was repeated a large number of times (> 100) for every lake and every year of the observation record. The average error in the estimated day of year was then calculated for each lake and for both overturning events (spring and fall) of every year of the record. On average, the estimated uncertainty in the remotely sensed LSWT led to uncertainties in the estimated day of year ranging from ± 2.0 days to ± 5.5 days depending on the lake and season considered. Uncertainties in the durations of overturning and stratification compounded errors from both overturning events (spring and fall). As result, the uncertainty in the duration of winter stratification ranged from ± 4.4 days in Lake Erie to ± 9.2 days in Lake Superior.

2.11. Calculation of probability of mean JFMA air temperature > 2.5 °C For each lake, the mean JFMA (January/February/March/April) air temperature was calculated for every year between 1948 and 2014. In all lakes, a histogram showed that the mean JFMA air temperatures followed approximately a normal distribution, which was confirmed by Shapiro-Wilk normality tests (p-values > 0.8). Assuming normality, it was therefore reasonable to use the mean and standard deviation to estimate the probability that a JFMA air temperature falls above or below a given threshold (here 2.5 °C). A running mean and running standard deviation with a decadal window for averaging was then used to derive the trend in JFMA air temperature over the basins of Lakes Michigan and Ontario between 1948 and 2014. The trends in mean and standard deviation were then used to calculate the trend in the probability that the JFMA air temperature is > 2.5 °C until 2014. The trends in the mean and standard deviation were then prolonged beyond 2014 (linearly extrapolated) and were used to calculate the corresponding probability of a mean JFMA air temperature > 2.5 °C until 2050. 3. Results and discussion 3.1. Timing and duration of overturning in the Laurentian Great Lakes Weekly climatologies calculated from the ARC-Lake remote-sensing record revealed the average seasonal variations in LSWT in the five Laurentian Great Lakes during the 1995–2012 period (Fig. 3). As Ullman et al. (1998) observed previously for the 1985–1995 period, the lake-averaged LSWT typically peaks around mid-August in all lakes and reach minimal temperature around mid-March (Fig. 3A). An exception was the shallow Lake Erie, where the minimum is reached two weeks prior. The warmest lake-averaged LSWT in August ranges between the lowest temperature of ∼15 °C in Lake Superior to the highest of ∼24 °C in Lake Erie, following the trend expected from the lakes’ latitudes (Superior < Huron < Michigan < Ontario < Erie). The lowest lakeaveraged LSWT in March was just above 0 °C in Lakes Superior, Erie, and Huron but remained at 1 and 2 °C in Lakes Michigan and Ontario, respectively. The rates of warming and cooling were remarkably similar in Lakes Huron, Michigan and Ontario throughout the year (Fig. 3B). Overall, the seasonal variations in lake-averaged LSWT were very similar in these three lakes, with the main difference being a near-constant offset of about +1 °C in Lake Michigan and an offset of +2 °C in Lake Ontario compared to Lake Huron. In the northernmost Lake Superior, warming was slow and delayed relative to the other lakes and cooling was also more slow. The slow thermal response is likely related to the large thermal inertia of this relatively deep lake. The reverse was observed in Lake Erie, the southernmost and shallowest lake with the smallest thermal inertia. A disconnect between lake-averaged LSWT and timing and duration of overturning in the five lakes was evident from this climatological

2.9. Calculation of lake susceptibility and dynamic ratio A unitless measure of lake susceptibility to experience an incomplete turnover was derived for each lake from the distributions of winter-stratification durations calculated for every year between June 1995 and May 2012. More specifically, lake susceptibility was calculated as the ratio of the standard deviation of winter stratification duration over the corresponding mean. As an index of lake morphometry, the lake dynamic ratio (Håkanson, 1982) is a measure of how deep the lake is relative to its surface area. It was calculated for each lake as the ratio of the square root of the lake surface area over the lake's average depth. 2.10. Calculation of climatologies of 4 °C thermal front occurrence (day of occurrence) and migration rates of 4 °C thermal front The daily grids of LSWT were used to estimate the closest day of year when the 4 °C LSWT was reached at any particular location on the lakes. This analysis was done for all 17 complete spring and fall overturning events during the 1995–2012 observation record, and produced 5

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Fig. 3. Seasonal variations in lake-averaged LSWT and average timing and duration of overturning for the spring and fall. (A) Weekly climatologies of lakeaveraged LSWT for the five Great Lakes, and (B) corresponding rates of change in lake-averaged LSWT (change of LSWT per week). Positive values indicate seasonal warming whereas negative values indicate seasonal cooling after peak summer LWST. The average timing of the spring and fall overturnings are superimposed as shaded areas and separate periods of lake-wide stratification.

duration of 2 months. The fall overturning usually started in most lakes in late November/early December, with the notable exception of Lake Ontario where overturning starts weeks later (mid-to-late December). Overall, the timing and duration of overturning showed little predictability based solely on the lake-averaged LSWT, its rate of change, or latitude, and exhibited a strong “asymmetry” between spring and fall, thereby suggesting there is considerable variability in the spatio-temporal progression of overturning among seasons and lakes.

analysis (Fig. 3). Daily climatological LSWT maps facilitated tracking of the 4 °C thermal front over time. Here, the beginning of overturning was defined as the first day a LSWT of 4 °C was observed anywhere on the lake, and the end of overturning as the last day. Using this approach showed that the average duration and timing of overturning varied substantially among the five lakes (Fig. 3). The spring overturning generally started in early to mid-April, except in Lake Superior where it started in mid-May. The average duration of the spring overturning varied from a little over 3 weeks in Lake Ontario to almost 2 months in Lake Superior. The fall overturning usually lasted only a month in Lakes Superior and Erie, whereas Lake Michigan had the longest overturning 6

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Fig. 4. Weekly climatology (1995–2012) of lake surface water temperature (LSWT) and 4oC isotherm in the Laurentian Great Lakes during the spring overturning period. The black contour line on each map represents the 4 °C isotherm. Spring overturning of the Laurentian Great Lakes typical starts in the shallow, eastern part of Lake Erie in early to mid-April, and terminates in early to mid-July in the deep parts of central Lake Superior.

3.2. Spatio-temporal progression of overturning in the Laurentian Great Lakes

(Fig. 4 and Fig. 5). These sequential maps showed that the spring overturning typically started first in Lake Erie in early April, progressing northeastwardly from shallow to deeper waters until it completed around mid-May. In late April/early May, overturning started in the shallow waters and bays of southern Lakes Michigan, Huron and Ontario, before progressing offshore. The overturning in these three lakes

Weekly climatological maps of LSWT showcasing the 4 °C surface isotherm provided a spatially explicit view of the average progression of overturning during spring and fall and of the seasonal “asymmetry” 7

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Fig. 5. Weekly climatology (1995–2012) of lake surface water temperature (LSWT) and 4oC isotherm in the Laurentian Great Lakes during the fall overturning period. The black contour line on each map represents the 4 °C isotherm. The fall overturning typical starts in the eastern and shallower regions of lakes Erie, Michigan, Superior, and Huron in late November – early December, and terminates in mid to late January in the deep parts of central lakes Michigan and Ontario.

progressing very rapidly from west to east. The observed spring overturning pattern conformed to the conceptual pattern of overturning typically expected in large lakes (Fig. 6). A compact view of the average overturning behavior of the lakes can be presented as maps of the “day of occurrence” of the 4 °C thermal front at any particular location on the lakes (Fig. 6A). These climatological maps of day of occurrence showed that the average spring overturning pattern was consistent with what can be expected from the latitude, depth and size of the lakes: 1) the spring overturning occurs later in the year at higher latitudes, and 2) the overturning progresses more slowly in large lakes and/or in relatively deep lakes with high thermal inertia. Latitude and bottom depth were both significantly correlated with the day of occurrence (r = 0.53–0.87), thereby confirming this observation (see Supplementary Fig. 4). A multiple linear regression further showed

generally ended by late May-early June, when at last overturning started in southern Lake Superior and progressed northwardly until mid-July. This general progression of the spring overturning was consistent with observations from the previous decade (e.g., 1985–1995) (Ullman et al., 1998). Although the fall overturning pattern bore similarities with the spring pattern, it also exhibited some important differences. The fall overturning also started in the shallow southwestern parts of the lakes, in late November/early December for most lakes and in mid-to-late December in Lake Ontario. Like in the spring, the progression of the 4 °C thermal front was northeastward, toward deeper water in Lake Erie, and towards the deep basins in Lakes Huron, Michigan, and Ontario. However, the fall overturning followed a much more pronounced eastward progression in these three lakes than in the spring. The overturning in Lake Superior was also particularly unique, 8

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Fig. 6. Patterns of the spring and fall overturning in the Laurentian Great Lakes. (A,B) Climatology (1995–2012) of the day of year when the 4oC thermal front was observed at any particular location in the Great Lakes (day of occurrence) during the spring and fall overturnings. Climatological wind vectors are overlaid as purple vector fields and highlight the influence of strong westerly winds on the progression of the 4 °C thermal front during the fall. (C,D) Estimated versus measured (= remotely sensed) day of occurrence at all locations on the Great Lakes. The estimated day of occurrence was derived using a multiple linear regression of day of occurrence on latitude and bottom depth. The 1-to-1 line is shown in gray and the adjusted R2 of the multiple linear regression is displayed on the plots. (E,F) Standard deviation associated with the climatological day of occurrence indicating the year-to-year variability in the occurrence of the thermal front at any location on the Great Lakes. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

In contrast, the average fall overturning pattern was not as predictable and indicated the influence of other factors than latitude and depth (Fig. 6). Latitude and depth could only predict 42% of the variability in the day of occurrence during the fall (Fig. 6D and Supplementary Fig. 4). The occurrence of strong westerly winds (Fig. 6B) is likely to be an important factor contributing to the more pronounced eastward progression of overturning during the fall. In the case of Lake Superior, a weak summer stratification, strong westerly winds, and steep bathymetry near the northern shore, likely combine to produce the very pronounced west-to-east progression observed in the

that latitude and depth together were able to predict almost 90% of the observed variability in the day of occurrence during the spring (Fig. 6C). Finally, an analysis of the standard deviation of the day of occurrence (among the different years) indicate the inter-annual variability in day of occurrence is greatest within the deeper regions of the lakes (Fig. 6E) and is strongly dependent on bottom depth (Supplementary Fig. 5). These findings are consistent with recent observations that the deep areas of these larges lakes experience a later onset of thermal stratification and are characterized by a shorter stratified warming season (Woolway and Merchant, 2018). 9

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Fig. 7. Climatology (1995–2012) of migration rates of the 4oC thermal front highlighting narrow regions of persistent slow-moving thermal fronts. (A,B) The inverse of migration rates is shown here in day km−1 (number of days needed to migrate 1 km). Warm colors highlight areas where the thermal front usually progresses slowly, usually in areas where bathymetry changes rapidly (steep bottom slope). (C,D) Coefficient of variation in % associated showing the average interannual variability in the front migration rates. The purple/blue colors show areas where the front migration rate varies little from year to year (< 50%). (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

regions of persistent thermal-bar formation, which can affect nearshoreoffshore exchange (Rao and Schwab, 2007) and are sometimes associated with eddies (McKinney et al., 2012). The spatial distribution of persistent slow-moving 4 °C thermal fronts (thermal bars) during the fall was substantially different than during the spring (Fig. 7). In general, these narrow zones form parallel to the coastline during the early stages of overturning, usually about 5–15 km away from the shore in areas where bathymetry changes rapidly (i.e., steep bottom slope). During the spring, these slow-moving fronts formed predominantly in the southern shores of Lake Superior and Ontario and along the eastern and western shores of Lakes Michigan and Huron (Fig. 7A,C). These correspond to areas where thermal bars have previously been reported during the spring in the Laurentian Great Lakes (Arifin et al., 2016; Auer and Gatzke, 2004; Consi et al., 2008; Csanady, 1974; McKinney et al., 2018; Yurista et al., 2016). In the fall, slow-moving fronts seemed to only form consistently in Lakes Michigan and Ontario (Fig. 7B,D), highlighting again the distinct overturning behavior of these two lakes. In sharp contrast with the spring, the unexpectedly fast west-to-east progression of fall overturning in Lake Superior does not allow slow-moving thermal fronts to

fall. Unlike during the spring, the inter-annual variability of the day of occurrence was not strongly dependent on bottom depth (Fig. 6F and Supplementary Fig. 5). Instead, the standard deviation of the day of occurrence showed remarkable homogeneity within any given lake, but was much greater in Lakes Michigan and Ontario than in the other lakes (Fig. 6F). The progression of the fall overturning is evidently more complex than in the spring, and does not conform as much to the conceptual overturning pattern. Our analysis also revealed that the progression of overturning was not uniform within each lake, and identified narrow regions of recurrent, slow-moving 4 °C thermal fronts (Fig. 7). Maps of day of occurrence facilitated the calculation of maps of average migration rates of the 4 °C thermal front in each lake (Fig. 7A–B, showing inverse of migration rates). These revealed the existence of 10-km-wide alongshore regions where the 4 °C thermal front progresses very slowly, typically requiring more than a day to progress 1 km toward the center of the lake. These regions were also associated with relatively low coefficients of variation (< 50%) indicating the slow-moving fronts tend to form consistently at the same location every year (Fig. 7C–D). These areas of slow migration are important because they likely represent 10

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Fig. 8. Variability of the duration of spring and fall overturning, showcasing the incomplete fall overturning of Lakes Michigan and Ontario in 2011–2012. (A) Inter-annual variability (1995–2012) in the duration of fall and spring overturning periods, and of the lake-wide winter-stratification period. The duration of winter stratification was null in Lakes Michigan and Ontario during the winter of 2011–2012. A sensitivity analysis (see methods) indicated the uncertainty in the durations of overturning and lake-wide winter stratification resulting from errors in remotely-sensed LSWT ( ± 0.80 °C relative to in situ measurements) ranged from ± 4.4 days up to ± 9.2 days depending on the lake. (B) Incomplete overturning of Lakes Michigan and Ontario during the winter of 2011–2012, highlighting how LSWT failed to reach the 4 °C threshold over deep regions of these two lakes during the winter of 2011–2012. White areas represent regions of the lakes covered with ice.

thereby providing a detailed description of every overturning event between June 1995 and April 2012 in all five lakes. In addition to confirming that major differences exist among the lakes and between spring and fall, the analysis revealed there is substantial variability in the timing and duration among years. For a given lake and season (e.g., spring of fall), timing could vary by as much as a month and duration by as much as two months. No significant linear trend in the timing and duration could be detected in any of the lakes during this relatively

manifest. 3.3. Inter-annual variability in overturning and contributing factors A more detailed analysis of the daily evolution of the 4 °C thermal front revealed there is substantial variability in the timing and duration of overturning from year to year (Fig. 8A). The daily evolution of the 4 °C thermal front was tracked over the entire period of observation, 11

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March/April) explained two thirds of the 1995–2012 inter-annual variability in the duration observed across four Great Lakes (Superior, Huron, Michigan, and Ontario) (Fig. 10A). The winter-stratification duration in Lake Erie was not influenced by mean winter air temperatures and departed from this main relationship, likely because the relatively shallow Lake Erie has a low thermal inertia and its LSWT can respond rapidly to shorter or less cold events that do not necessarily drive the average winter air temperature. The duration decreased faster with increasing air temperatures above -1 °C, possibly due to a positive feedback from the loss in ice cover at these temperatures (Fig. 10B). The general relationship between mean winter air temperature and winterstratification duration observed here points to a threshold of 2.5 °C above which Lakes Michigan and Ontario may experience an incomplete fall overturning. Significant scatter in the relationship with mean winter air temperature suggests the duration of winter stratification is also influenced by other factors (Fig. 10). Wind speed was not found to influence the winter-stratification duration. The percent ice cover could affect the duration by regulating heat exchange and solar heating (Austin and Colman, 2007), but it only accounted for an additional 5% of the variability in the duration. This moderate effect is most likely due to the strong linear relationship between winter air temperature and percent ice cover (Fig. 10B). The timing of the ice cover likely plays a more important role. For instance, significant ice cover early in the winter season can reduce extensive heat loss during the coldest months, ultimately leading to an early onset of spring overturning and a shorter winter-stratification period (Titze, 2016). In contrast, significant ice cover late in the winter season could have the opposite effect by limiting solar heating during a period of rapidly increasing solar irradiance (Titze, 2016). The timing of ice cover could therefore have contributed to the unusual observation made during the cold winter of 1996–1997 (Fig. 10A). Winter stratification was relatively short for the extremely low mean winter air temperature observed that year, causing 1996–1997 to deviate from the general relationship linking winter air temperature and duration of winter stratification (Fig. 10A). Significant ice cover was observed early during the winter season of 1996–1997 (Fig. 10B), which likely prevented extensive heat loss during the coldest months and balanced the effects of the extremely low temperatures.

short time-series, primarily because major changes often occurred between consecutive years. This variability in the timing and duration of both the spring and fall overturning implies that the timing and duration of lake-wide stratification (summer and winter) also varied substantially from year to year. This variability was particularly evident in Lakes Michigan and Ontario. The warm winter of 2011–2012 was marked by an incomplete fall overturning in Lakes Michigan and Ontario (Fig. 8A and B). Winter air temperatures over these two lake basins averaged 2 °C in 2011–2012, the warmest observed during 1995–2012. Usually, fall overturning in Lakes Michigan and Ontario is completed by early March (Fig. 8A). However, the warm winter of 2011–2012 was characterized by a late winter cooling and an early spring warming. By early March 2012, LSWT over deep offshore regions of the lakes remained at ∼ 5 °C (Fig. 8B). These residual warm pools from the previous summer never cooled to the 4 °C threshold. These two lakes thus appear to have experienced an incomplete fall overturning that year. The observational record, which lasted until April 8, 2012 (date of loss of ground contact with the Envisat mission), fully spanned the winter season and clearly showed the warm pools began to expand under spring warming. Importantly, the continued presence of the 4 °C front associated with the residual warm pools meant that a persistent thermal front did not form nearshore in the spring, as was typically observed during other years. Statistically, Lakes Michigan and Ontario were more susceptible to experience incomplete fall overturning than the other great lakes (Fig. 9). During the 17 years of observations, the duration of lake-wide winter stratification was shorter (60–70 days) and twice as variable ( ± 25–30 days) in Lakes Michigan and Ontario than in the other Great Lakes (Fig. 9A and B). Duration ranged by as much as 0–110 days in Lake Michigan and 0–130 days in Lake Ontario. Shorter and more variable durations suggest that Lakes Michigan and Ontario had less stable winter stratifications and were more likely to experience incomplete overturning. The ratio of standard deviation over mean of duration provides a simple, unitless measure of a lake susceptibility to experience an incomplete overturning (Fig. 9C). This susceptibility ranged four-fold among the five lakes, with Lake Superior being least susceptible and Lakes Michigan and Ontario being most susceptible. Lake susceptibility to incomplete fall overturning can be explained by the combined influence of air temperature and lake dynamic ratio (Fig. 9C,D,E). Unsurprisingly, higher air temperatures can contribute to shorter winter-stratification periods and therefore increase susceptibility. However, as suggested by our regression analysis, the lake dynamic ratio also helps explain the susceptibility differences. The dynamic ratio (Håkanson, 1982), calculated here as mean surface horizontal length divided by depth, is essentially a measure of lake's bottom slope. By themselves, the lake volume or lake depth could not help explain the differences in lake susceptibility among the lakes when used as a second predictor in addition to air temperature. The hypothesis presented here is that the bottom slope affects the lake's ability to respond rapidly to changes in air temperature. Specifically, relatively deep and steep-bottom lakes, like Lakes Ontario and Michigan, have a greater lateral change in thermal inertia than shallower lakes like Lake Erie. Neglecting dynamics, the migration rate of the thermal bar would be slower in the former. Lakes with low dynamic ratios require prolonged periods of cold air temperatures for the thermal bar to complete its nearshore-to-offshore migration, thereby making them more susceptible to incomplete overturning during mild winters. The high susceptibility of Lakes Michigan and Ontario therefore seems to result from a combination of relatively warm winter air temperatures and low dynamic ratio. Even though the dynamic ratio of Lake Superior is as low as those of Lakes Michigan and Ontario, Lake Superior was not subject to mild winter and may therefore not be as susceptible as the other two lakes. The mean winter air temperature influenced the duration of lakewide winter stratification in any given year. Lake-basin air temperatures averaged over the winter months (JFMA: January/February/

3.4. Toward a disruption of the fall overturning in Lake Michigan and Lake Ontario? Recent trends in winter air temperatures suggest the incomplete overturning of Lakes Michigan and Ontario might be occurring more frequently in the near future (Fig. 11). Winter air temperatures have risen at an average rate of 0.16 °C and 0.12 °C per decade (1948–2014) over Lakes Michigan and Ontario, consistent with trends observed for summer temperatures (Austin and Colman, 2007) and representing intermediary values among the rates observed for the five Great Lakes (Supplementary Fig. 6). Inter-annual variance has also increased steadily since the 1960s with extreme mean winter air temperatures, hot and cold, becoming increasingly frequent (Supplementary Fig. 6 and Supplementary Fig. 7). These trends show that mean winter air temperatures above the 2.5 °C threshold were extremely unlikely in the 1980s but can now occur occasionally (∼5% chance), as witnessed in 2011–2012. Assuming these observed trends in winter air temperature persist in the near-future, the likelihood would reach 15–20% by 2050. Although a more thorough model-based study would be needed to adequately assess the effects of warming on overturning, the simple analysis presented here suggest that rising air temperatures could lead to a recurrent disruption of the fall overturning in Lakes Michigan and Ontario in the next decades. A steady decrease in winter wind speed has also been observed over these two lakes since 1948 (Supplementary Fig. 6), and could also contribute to this trend by decreasing wind-induced surface mixing during winter. Our analysis also showed that the other three Laurentian Great Lakes are less likely to experience such 12

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Fig. 9. Duration of winter stratification and lake susceptibilities to experience an incomplete overturning in the fall. (A) Distribution of duration of lakewide winter stratification for the five Laurentian Great Lakes. (B) Mean duration of lake-wide winter stratification period versus corresponding standard deviation for each lake, highlighting the lake-wide winter stratification period is considerably shorter and more variable in lakes Michigan and Ontario. (C) Lake susceptibility, defined here as the ratio of the standard deviation over mean of duration, versus mean lake-basin JFMA air temperature. (D) Lake susceptibility versus lake dynamic ratio, calculated here as the square root of the lake surface area over the lake's average depth (how relatively shallow a lake is). (E) Measured lake susceptibility versus lake susceptibility estimated from lake dynamic ratio and mean JFMA air temperature using a multiple linear regression (adjusted R2 = 0.90).

thermal gradients promote alongshore currents and inhibit cross-shelf exchange. The physical barrier usually forms during a time of intense runoff, and leads to the accumulation of land-derived suspended particles, organic matter, contaminants and nutrients in nearshore waters where it impacts water quality (Auer and Gatzke, 2004; Holland and Kay, 2003a). As seen with the unusual onset of the 2012 spring overturning, an incomplete fall overturning tends to preclude the formation of a strong spring thermal bar. This would likely facilitate cross-shelf circulation and accelerate the transport of river-borne material to offshore waters, potentially alleviating water quality issues in nearshore waters.

disruption in the near future mainly because of their low susceptibility to experience an incomplete fall overturning. However, a 3D model of Lake Superior forced by future climate conditions projected for an intermediate IPCC warming scenario also predicts that even Lake Superior may experience a disruption in dimictic behavior by 2060 (Matsumoto et al., 2019). Recurring incomplete fall overturning could impact water circulation, cross-shelf exchange, and water quality in these large lakes. Surface circulation in the Great Lakes is wind-driven but is strongly influenced by thermal stratification and the seasonal presence of thermal fronts and associated eddies (Bennington et al., 2010; Boyce et al., 1989; McKinney et al., 2018, 2012; Ullman et al., 1998). During spring overturning, thermal bars associated with steep nearshore 13

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Fig. 10. Dependence of the duration of lake-wide winter stratification and ice cover on the mean winter (JFMA) air temperatures measured over the lake basin for the five Laurentian Great Lakes. (A) Duration of lake-wide winter stratification plotted against the JFMA air temperature for every year between June 1995 and May 2012 and for each lake. The uncertainty in the duration of lake-wide winter stratification was estimated by sensitivity analysis to range from ± 4.4 days in Lake Erie to ± 9.2 days in Lake Superior (see methods). The 3rd-degree polynomial regression was derived using all data except for those from Lake Erie, which departed from the main relationship (shown as faded red color). A JFMA air temperature of 2.5 °C over the lake basin represents a threshold beyond which an incomplete overturning of Lakes Michigan and Ontario is expected. The dashed-line circles show the data for the cold winter of 1996–1997 when percent ice cover was high early in the winter season. (B) Percent ice cover plotted against JFMA air temperature for every year between June 1995 and May 2012 and for each lake, showing linear regressions and corresponding coefficients of determination for each lake. Dashed-line circles show the data for the cold winter of 1996–1997. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

4. Conclusion

in the overturning behavior of large lakes, which can have important consequences for the functioning and role of these ecosystems. For instance, reduced vertical mixing associated with more frequent incomplete overturning could alter the lakes' biological productivity and biogeochemistry. Lakes are active sites of organic matter production,

Using the Laurentian Great Lakes as an example, this study demonstrated that tracking the daily evolution of the remotely sensed 4 °C surface isotherm provides a means to help identify potential disruptions

Fig. 11. Past and potential future trends in JFMA air temperatures over the basins of Lakes Michigan and Ontario. (A) Decadal trends in the mean JFMA air temperatures for Lakes Michigan and Ontario between 1948 and 2014, highlighting a positive trend in temperature and a steady increase in the temperature variance since the 1960s. (B) Corresponding decadal trends in the probability that the JFMA air temperature is > 2.5 °C (threshold for incomplete overturning in Lakes Michigan and Ontario) and predictions of this probability until 2050. Predictions are based on the trends in temperature and temperature variance observed over the past 50 years, showing that JFMA air temperatures over the 2.5 °C threshold can be expected over the basins of Lakes Michigan and Ontario once every 5–6 years by 2050 (15–20% chance in any given year). Predictions for Lakes Superior, Huron, and Erie are not shown because these lakes have very low susceptibilities to experience an incomplete overturning. 14

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doi.org/10.1016/j.rse.2019.111427.

processing, and accumulation (Tranvik et al., 2009), on which fall overturning has an important regulatory role (Encinas Fernández et al., 2014). Overturning exchanges and mixes oxygenated surface waters with deep waters richer in nutrients and carbon. Although deep waters do not always get fully ventilated by seasonal overturning (Matsumoto et al., 2015), an incomplete overturning could further delay and reduce deep-water ventilation and influence the timing of greenhouse gas exchange with the atmosphere. Reduced vertical mixing would also limit the supply of nutrients to the sunlit surface layers, thereby altering the location and timing of phytoplankton production and the overall biological productivity of lakes (Vincent, 2009). More significantly, the absence of vertical mixing over deep regions of the lakes could promote the development of hypoxic conditions and anaerobic processes during longer summer stratification periods, especially in warmer and more eutrophic lakes, directly impacting the biota (Stefan et al., 1996). Finally, a shift in overturning behavior could alter the role of temperate lakes as greenhouse gas emitters. Lakes worldwide are warming, albeit at very different rates (O'Reilly et al., 2015; Schneider and Hook, 2010). Our findings, although limited to the Laurentian Great Lakes, hint that temperate lakes with morphometry similar to Lakes Ontario and Michigan could also experience a shift in overturning behavior. Lakes can emit significant amounts of greenhouse gases such as methane and nitrous oxide (Bastviken et al., 2004; Tranvik et al., 2009; Williamson et al., 2009). Incomplete overturning can lead to poorer oxygenation and the development of hypoxic zones, which could enhance the production of such gases (Encinas Fernández et al., 2014; Knowles et al., 1981). For lakes which are deemed susceptible to incomplete overturning, mechanistic studies that link overturning dynamics and biogeochemical processes may provide important insights about the longterm impact of a change in overturning behavior.

References Alvera-Azcárate, A., Barth, A., Rixen, M., Beckers, J.M., 2005. Reconstruction of incomplete oceanographic data sets using empirical orthogonal functions: application to the Adriatic Sea surface temperature. Ocean Model. 9, 325–346. https://doi.org/ 10.1016/j.ocemod.2004.08.001. Arifin, R.R., James, S.C., de Alwis Pitts, D.A., Hamlet, A.F., Sharma, A., Fernando, H.J.S., 2016. Simulating the thermal behavior in Lake Ontario using EFDC. J. Great Lakes Res. 42, 511–523. https://doi.org/10.1016/j.jglr.2016.03.011. Auer, M.T., Gatzke, T.L., 2004. The spring runoff event, thermal bar formation, and cross margin transport in lake superior. J. Great Lakes Res. 30, 64–81. https://doi.org/10. 1016/S0380-1330(04)70378-0. Austin, J., Allen, J., 2011. Sensitivity of summer Lake Superior thermal structure to meteorological forcing. Limnol. Oceanogr. 56, 1141–1154. https://doi.org/10.4319/ lo.2011.56.3.1141. Austin, J., Colman, S., 2008. A century of temperature variability in Lake Superior. Limnol. Oceanogr. 53, 2724–2730. https://doi.org/10.4319/lo.2008.53.6.2724. Austin, J.A., Colman, S.M., 2007. Lake Superior summer water temperatures are increasing more rapidly than regional temperatures: a positive ice-albedo feedback. Geophys. Res. Lett. 34, 1–5. https://doi.org/10.1029/2006GL029021. Bartolai, A.M., He, L., Hurst, A.E., Mortsch, L., Paehlke, R., Scavia, D., 2015. Climate change as a driver of change in the great lakes st. Lawrence river basin. J. Great Lakes Res. 41, 45–58. https://doi.org/10.1016/j.jglr.2014.11.012. Bastviken, D., Cole, J., Pace, M., Tranvik, L., 2004. Methane emissions from lakes: Dependence of lake characteristics, two regional assessments, and a global estimate. Glob. Biogeochem. Cycles 18, 1–12. https://doi.org/10.1029/2004GB002238. Beletsky, D., Schwab, D.J., 2001. Modeling circulation and thermal structure in Lake Michigan: annual cycle and interannual variability. J. Geophys. Res. Ocean. 106, 19745–19771. https://doi.org/10.1029/2000JC000691. Bennett, J.R., 1971. Thermally driven lake currents during the spring and fall transition periods. In: Proc. 14th Conf. Great Lakes Res. Int. Assoc. Great Lakes Res. pp. 535–544. Bennington, V., McKinley, G.A., Kimura, N., Wu, C.H., 2010. General circulation of lake superior: mean, variability, and trends from 1979 to 2006. J. Geophys. Res. Ocean. 115, 1–14. https://doi.org/10.1029/2010JC006261. Boehrer, B., Schultze, M., 2008. Stratification of lakes. Rev. Geophys. 46. https://doi.org/ 10.1029/2006RG000210. Boyce, F.M., Donelan, M.a., Hamblin, P.F., Murthy, C.R., Simons, T.J., 1989. Thermal structure and circulation in the great lakes. Atmos.-Ocean 27, 607–642. https://doi. org/10.1080/07055900.1989.9649358. Consi, T.R., Anderson, G., Barske, G., Bootsma, H., Hansen, T., Janssen, J., Klump, V., Paddock, R., Szmania, D., Verhein, K., Waples, J.T., 2008. Real time observation of the thermal bar and spring stratification of Lake Michigan with the GLUCOS coastal observatory. Ocean. 2008. https://doi.org/10.1109/OCEANS.2008.5152000. Croley II, T.E., 1994. Hydrological impacts of climate change on the laurentian great lakes. Trends Hydrol 1. Csanady, G.T., 1974. Spring thermocline behavior in lake Ontario during IFYGL. J. Phys. Oceanogr. 4, 425–445. https://doi.org/10.1175/1520-0485(1974) 004<0425:STBILO>2.0.CO;2. Desai, A.R., Austin, J.a., Bennington, V., McKinley, G.a., 2009. Stronger winds over a large lake in response to weakening air-to-lake temperature gradient. Nat. Geosci. 2, 855–858. https://doi.org/10.1038/ngeo693. Donlon, C.J., Minnett, P.J., Gentemann, C., Nightingale, T.J., Barton, I.J., Ward, B., Murray, M.J., 2002. Toward improved validation of satellite sea surface skin temperature measurements for climate research. J. Clim. 15, 353–369. https://doi.org/ 10.1175/1520-0442(2002)015<0353:TIVOSS>2.0.CO;2. Elliott, G.H., 1971. A mathematical study of the thermal bar. In: Proc. 14th Conf. Great Lakes Res. Int. Assoc. Great Lakes Res., Toronto, pp. 545–554. Encinas Fernández, J., Peeters, F., Hofmann, H., 2014. Importance of the autumn overturn and anoxic conditions in the hypolimnion for the annual methane emissions from a temperate lake. Environ. Sci. Technol. 48, 7297–7304. https://doi.org/10. 1021/es4056164. Frenette, J.J., Demers, S., Legendre, L., Boulé, M., Dodson, J., 1994. Mixing, stratification and the fate of primary production in an oligotrophic multibasin lake system (Québec, Canada). J. Plankton Res. 16, 1095–1115. https://doi.org/10.1093/plankt/ 16.9.1095. Goldman, C.R., Elser, J.J., Richards, R.C., Reuters, J.E., Priscu, J.C., Levin, A.L., 1996. Thermal stratification, nutrient dynamics, and phytoplankton productivity during the onset of spring phytoplankton growth in Lake Baikal, Russia. Hydrobiologia 331, 9–24. https://doi.org/10.1007/BF00025403. Håkanson, L., 1982. Lake bottom dynamics and morphometry: the dynamic ratio. Water Resour. Res. 18, 1444–1450. https://doi.org/10.1029/WR018i005p01444. Holland, P.R., Kay, A., 2003a. A review of the physics and ecological implications of the thermal bar circulation. Limnol. - Ecol. Manag. Inl. Waters 33, 153–162. https://doi. org/10.1016/S0075-9511(03)80011-7. Holland, P.R., Kay, A., 2003b. A review of the physics and ecological implications of the thermal bar circulation. Limnologica 33, 153–162. https://doi.org/10.1016/S00759511(03)80011-7. Hubbard, D.W., Spain, J.D., 1976. The structure of the early spring thermal bar in Lake Superior. In: Proc. 16th Conf. Great Lakes Res, pp. 296–306. Hunter, T.S., Clites, A.H., Campbell, K.B., Gronewold, A.D., 2015. Development and application of a monthly hydrometeorological database for the North American Great Lakes - Part I: precipitation, evaporation, runoff, and air temperature. J.

Author contributions The main concept and story line were developed by C.F. and K.M. Design of the figures, and writing of the text were done by C.F, and results and data were discussed by C.F, K.M., B.H, and K.T. Monthly average ice cover data were compiled by B.H. and C.F. In situ lake water surface temperatures were compiled and made available by K. T. All authors commented on the manuscript. Acknowledgements 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 ARCLake 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. Appendix A. Supplementary data Supplementary data to this article can be found online at https:// 15

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characteristics during the thermal bar in Lake Ontario. Limnol. Oceanogr. 49, 2190–2200. https://doi.org/10.4319/lo.2004.49.6.2190. Rodgers, G.K., 1965. The thermal bar in the laurentian great lakes. In: Internat. Assoc. Great Lakes Res. Proc. 8th Conf. Great Lakes Respp. 358–363. Scavia, D., Fahnenstiel, G.L., 1987. Dynamics of lake Michigan phytoplankton: mechanisms controlling epilimnetic communities. J. Great Lakes Res. 13, 103–120. https:// doi.org/10.1016/S0380-1330(87)71635-9. Schneider, P., Hook, S.J., 2010. Space observations of inland water bodies show rapid surface warming since 1985. Geophys. Res. Lett. 37, 1–5. https://doi.org/10.1029/ 2010GL045059. Schneider, P., Hook, S.J., Radocinski, R.G., Corlett, G.K., Hulley, G.C., Schladow, S.G., Steissberg, T.E., 2009. Satellite observations indicate rapid warming trend for lakes in California and Nevada. Geophys. Res. Lett. 36, 1–6. https://doi.org/10.1029/ 2009GL040846. Schott, J.R., 1986. The role of remotely sensed data in studies of the thermal bar. Remote Sens. Rev. 1, 341–358. https://doi.org/10.1080/02757258609532073. Stefan, H.G., Hondzo, M., Fang, X., Eaton, J.G., Mccormick, J.H., 1996. Simulated long term temperature and dissolved oxygen characteristics of lakes in the north-central United States and associated fish habitat limits. Limnol. Oceanogr. 41, 1124–1135. https://doi.org/10.4319/lo.1996.41.5.1124. Titze, D.J., 2016. Characteristics, Influence, and Sensitivity of Ice Cover on the Great Lakes. University of Minnesota. Titze, D.J., Austin, J.A., 2014. Winter thermal structure of lake superior. Limnol. Oceanogr. 59, 1336–1348. https://doi.org/10.4319/lo.2014.59.4.1336. Tranvik, L.J., Downing, J.A., Cotner, J.B., Loiselle, S.A., Striegl, R.G., Ballatore, T.J., Dillon, P., Finlay, K., Fortino, K., Knoll, L.B., Kortelainen, P.L., Kutser, T., Larsen, S., Laurion, I., Leech, D.M., McCallister, S.L., McKnight, D.M., Melack, J.M., Overholt, E., Porter, J.A., Prairie, Y., Renwick, W.H., Roland, F., Sherman, B.S., Schindler, D.W., Sobek, S., Tremblay, A., Vanni, M.J., Verschoor, A.M., von Wachenfeldt, E., Weyhenmeyer, G.A., 2009. Lakes and reservoirs as regulators of carbon cycling and climate. Limnol. Oceanogr. 54, 2298–2314. https://doi.org/10.4319/lo.2009.54.6_ part_2.2298. Trumpickas, J., Shuter, B.J., Minns, C.K., 2009. Forecasting impacts of climate change on Great Lakes surface water temperatures. J. Great Lakes Res. 35, 454–463. https://doi. org/10.1016/j.jglr.2009.04.005. Ullman, D., Brown, J., Comillon, P., Mavor, T., 1998. Surface Temperature Fronts in the Great Lakes, vol. 24. pp. 753–775. Vincent, W.F., 2009. Effects of climate change on lakes. In: Pollution and Remediation. Elsevier Inc., pp. 55–60. White, B., Austin, J., Matsumoto, K., 2012. A three-dimensional model of Lake Superior with ice and biogeochemistry. J. Great Lakes Res. 38, 61–71. https://doi.org/10. 1016/j.jglr.2011.12.006. Williamson, C.E., Saros, J.E., Vincent, W.F., Smol, J.P., 2009. Lakes and reservoirs as sentinels, integrators, and regulators of climate change. Limnol. Oceanogr. 54, 2273–2282. https://doi.org/10.4319/lo.2009.54.6_part_2.2273. Woolway, R.I., Dokulil, M.T., Marszelewski, W., Schmid, M., Bouffard, D., Merchant, C.J., 2017. Warming of Central European lakes and their response to the 1980s climate regime shift. Clim. Change 1–16. https://doi.org/10.1007/s10584-017-1966-4. Woolway, R.I., Merchant, C.J., 2018. Intralake heterogeneity of thermal responses to climate change: a study of large northern hemisphere lakes. J. Geophys. Res. Atmos. 123, 3087–3098. https://doi.org/10.1002/2017JD027661. Woolway, R.I., Merchant, C.J., 2017. Amplified surface temperature response of cold, deep lakes to inter-annual air temperature variability. Sci. Rep. 7, 4130. https://doi. org/10.1038/s41598-017-04058-0. Yurista, P.M., Kelly, J.R., Scharold, J.V., 2016. Great Lakes nearshore–offshore: distinct water quality regions. J. Great Lakes Res. 42, 375–385. https://doi.org/10.1016/j. jglr.2015.12.002. Zilitinkevich, S.S., Kreiman, K.D., Terzhevik, A.Y., 1992. The thermal bar. J. Fluid Mech. 236, 27–42. https://doi.org/10.1017/s0022112092001320.

Hydrometeorol. 41, 65–77. https://doi.org/10.1016/j.jglr.2014.12.006. Knowles, R., Lean, D., Chan, Y., 1981. Nitrous oxide concentrations in lakes: variations with depth and time. Limnol. Oceanogr. 26, 855–866. https://doi.org/10.4319/lo. 1981.26.5.0855. MacCallum, S.N., Merchant, C.J., 2012. Surface water temperature observations of large lakes by optimal estimation. Can. J. Remote Sens. 38, 25–45. https://doi.org/10. 5589/m12-010. Magnuson, J.J., Robertson, D.M., Benson, B.J., Wynne, R.H., Livingstone, D.M., Arai, T., Assel, R.A., Barry, R.G., Card, V., Kuusisto, E., Granin, N.G., Prowse, T.D., 2000. Historical trends in lake and river ice cover in the northern hemisphere. Science 80 289, 1743–1747. Malm, J., Jönsson, L., 1993. A study of the thermal bar in lake ladoga using water surface temperature data from satellite images. Remote Sens. Environ. 44, 35–46. Matsumoto, K., Tokos, K.S., Gregory, C., 2015. Ventilation and dissolved oxygen cycle in Lake Superior: insights from a numerical model. Geochem. Geophys. Geosyst. 16, 3097–3110. https://doi.org/10.1002/2015GC005916. Matsumoto, K., Tokos, K.S., Rippke, J., 2019. Climate projection of Lake Superior under a future warming scenario. J. Limnol. https://doi.org/10.4081/jlimnol.2019.1902. McCormick, M.J., 1990. Potential changes in thermal structure and cycle of lake Michigan due to global warming. Trans. Am. Fish. Soc. 119, 183–194. https://doi.org/10. 1577/1548-8659(1990)119<0183:PCITSA>2.3.CO;2. McKinney, P., Holt, B., Matsumoto, K., 2012. Small eddies observed in Lake Superior using SAR and sea surface temperature imagery. J. Great Lakes Res. 38, 786–797. https://doi.org/10.1016/j.jglr.2012.09.023. McKinney, P., Tokos, K.S., Matsumoto, K., 2018. Modeling nearshore-offshore exchange in lake superior. PLoS One 13, 1–17. https://doi.org/10.1371/journal.pone.0193183. Moll, R.A., Bratkovich, A., Chang, W.Y.B., Pu, P., 1993. Physical, chemical, and biological conditions associated with the early stages of the Lake Michigan vernal thermal front. Estuaries 16, 92–103. https://doi.org/10.2307/1352767. Mortimer, C.H., 1988. Discoveries and testable hypotheses arising from coastal zone color scanner imagery of southern Lake-Michigan. Limnol. Oceanogr. 33, 203–226. https://doi.org/10.4319/lo.1988.33.2.0203. Mortsch, L.D., Quinn, F.H., 1996. Climate change scenarios for Great Lakes Basin ecosystem studies. Limnol. Oceanogr. 41, 903–911. https://doi.org/10.4319/lo.1996. 41.5.0903. O'Reilly, C.M., Sharma, S., Gray, D.K., Hampton, S.E., Read, J.S., Rowley, R.J., Schneider, P., Lenters, J.D., McIntyre, P.B., Kraemer, B.M., Weyhenmeyer, G.A., Straile, D., Dong, B., Adrian, R., Allan, M.G., Anneville, O., Arvola, L., Austin, J., Bailey, J.L., Baron, J.S., Brookes, J.D., de Eyto, E., Dokulil, M.T., Hamilton, D.P., Havens, K., Hetherington, A.L., Higgins, S.N., Hook, S., Izmest’eva, L.R., Joehnk, K.D., Kangur, K., Kasprzak, P., Kumagai, M., Kuusisto, E., Leshkevich, G., Livingstone, D.M., MacIntyre, S., May, L., Melack, J.M., Mueller-Navarra, D.C., Naumenko, M., Noges, P., Noges, T., North, R.P., Plisnier, P.-D., Rigosi, A., Rimmer, A., Rogora, M., Rudstam, L.G., Rusak, J.A., Salmaso, N., Samal, N.R., Schindler, D.E., Schladow, S.G., Schmid, M., Schmidt, S.R., Silow, E., Soylu, M.E., Teubner, K., Verburg, P., Voutilainen, A., Watkinson, A., Williamson, C.E., Zhang, G., 2015. Rapid and highly variable warming of lake surface waters around the globe. Geophys. Res. Lett. 42, 10773–10781. https://doi.org/10.1002/2015GL066235. Piccolroaz, S., Toffolon, M., Majone, B., 2015. The role of stratification on lakes' thermal response: the case of Lake Superior. Water Resour. Res. 51, 7878–7894. https://doi. org/10.1002/2014WR016259. Ralph, E., 2002. Scales and structures of large lake eddies. Geophys. Res. Lett. 29, 2–5. https://doi.org/10.1029/2001GL014654. Rao, Y.R., 2012. In: Bengtsson, L., Herschy, R.W., Fairbridge, R.W. (Eds.), Great Lake Processes: Thermal Structure, Circulation and Turbulent Diffusion Processes BT Encyclopedia of Lakes and Reservoirs. Springer Netherlands, Dordrecht, pp. 298–303. Rao, Y.R., Schwab, D.J., 2007. Transport and mixing between the coastal and offshore waters in the great lakes: a review. J. Great Lakes Res. 33, 202–218. https://doi.org/ 10.3394/0380-1330(2007)33. [202:TAMBTC]2.0.CO;2. Rao, Y.R., Skafel, M.G., Charlton, M.N., 2004. Circulation and turbulent exchange

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