NOAA Great Lakes Environmental Research Laboratory

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Q&A with NOAA scientists: Causes and impacts of 2024’s historically low Great Lakes ice cover

Many people have questions about the historically low Great Lakes ice cover this winter, and we’ve got answers! NOAA GLERL’s Bryan Mroczka (Physical Scientist) and Andrea Vander Woude (Integrated Physical and Ecological Modeling and Forecasting Branch Chief) answer the following frequently asked questions regarding the causes and impacts of this year’s low ice cover.

What’s driving the lack of ice? Is El Niño involved somehow?

The long-term trend shows a decline in ice cover in the Great Lakes region over the past several decades. Ice cover has been decreasing by approximately 5 percent per decade, for a 25 percent total decrease between 1973 and 2023. In addition, the length of the Great Lakes ice season has decreased by approximately 27 days on average over the same period.

Annual maximum ice cover on the Great Lakes, 1973-2023.

Factors that drive the lack of ice are climatic variables such as the El Niño-Southern Oscillation (ENSO) along the Equatorial Pacific in addition to other global oceanic oscillations. These atmospheric patterns in the ocean influence weather patterns in the Great Lakes, driving the climatic response of the lakes. Increases in air temperatures are responsible for the lack of ice in addition to the “heat memory” of the lakes as they retain heat from the summer season temperatures. 

While El Niño may have exacerbated the extreme low ice seen this year, the increased frequency of low ice years across the lakes is tied to generally warmer winter conditions, defined by fewer and generally shorter intrusion of arctic air into the region. While much of the Continental U.S. has seen a warming trend during the winter months, the upper Midwest/Great Lakes have seen some of the most dramatic warming.

Color-coded chart showing maximum annual ice cover percentage on the Great Lakes from 1973-2024. Bar colors indicate El Niño strength for each year, ranging from "very strong El Niño" to "El Niño not present"
This graph shows maximum ice concentration every year from 1973-2024, with color-coding to show El Niño strength each year. Note that 2024’s maximum ice cover of 16% is as of mid-February, and is subject to change if ice cover increases later in the season.

An important factor in a season’s ice potential across the Great Lakes is the weather patterns influencing the region during December. December is what we would consider a “priming” month, in which the first arctic air masses cool the lakes and begin the ice generation process within enclosed bays and along the shoreline. Recently, we have seen a multitude of Decembers exhibit above-average temperatures, including significantly above-average temperatures this winter in particular. The lack of early season cold air, and resulting late start to the ice generation season makes later significant gains in ice concentration harder to achieve.

How does the lack of ice impact the Great Lakes ecosystem, as well as towns and cities on the lakes? 

Ice is an important element for the ecosystems, economy, and coastal resilience across the Great Lakes. Ice is a natural part of the Great Lakes yearly cycle and many animal species, from microbial to larger fauna, rely on the ice for protecting young and harboring eggs. The Great Lakes also see most of their significant storms and large wave events during the colder months of late fall through winter. The shorebound ice sheets act as an important buffer against these waves, protecting the coast from erosion and damage to shoreline infrastructure. In years with very low ice, such as this one, the coast becomes more susceptible to the full onslaught of wave energy.

An ice shelf and pieces of floating ice line a residential seawall on Lake Huron on a sunny day.
Ice on the Lake Huron shoreline near Oscoda, MI on January 27, 2024. Credit: Clarice Farina

The economy of the Great Lakes can see negative and positive outcomes from a very low ice year. Two of the more important wintertime recreational sports in the Great Lakes include ice-fishing and snowmobiling. When the ice is scarce and thin, the ability to partake in ice-fishing is significantly reduced both spatially and temporally. When it comes to snowmobiling, warmer winters will generally result in more rain events compared to normal, as well as reduced snow cover and lower quality snow. 

One “silver lining” for the Great Lakes economy that may result from a low ice year, is a boost to the shipping industry. Low ice years are likely to extend the shipping season across the lakes, and may extend the season significantly if the locks are not hampered by significant ice. 

Is there still time for the ice to return before spring?

The ice season in the Great Lakes typically extends until the end of March, and the maximum ice cover for the year comes near the end of February to early March. The clear trend is one of decreasing ice, but it is still too early to determine how this year will ultimately compare to past years and the long term average. 

Winter is not close to being over, and periods of new ice generation are almost certain as we head through the next month. The longer term pattern into early March does suggest that a few bouts of arctic air will reach the Great Lakes, but similar to earlier portions of this winter, there does not appear to be a signal for any long term below average temperature events. The colder air events ahead are more likely to be short-lived (several days), and not long enough for significant gains in ice concentration. It is certainly possible that we’ll see the ice concentrations climb out of the current historic lows before the end of the month, but a major pattern shift (currently not in the forecast) would be required to drive ice concentrations out of below-normal realms for any of the lakes before the spring. 

How do low ice levels impact evaporation, water levels, and lake effect snow?

While Great Lakes water levels are generally lowest in the winter, most of the evaporation from the lakes actually happens in the fall. This is because evaporation is driven by a large difference between the air temperature and the water temperature, which happens in the fall when the air cools down but the water is still holding onto its summer heat. The graphic below illustrates the seasonal cycles that Great Lakes water levels undergo every year.

Graphic showing land in the background and water in the foreground, divided into four panels corresponding with the seasons. Text describes the water level changes throughout the year: Winter low, spring rise, summer peak, and fall decline.

As of right now, we are not seeing any significant impacts to water levels due to the lower ice. Water levels are essentially the same (within one inch) as the values we were seeing at this time last year, and running just a touch above the long term average. The U.S. Army Corps of Engineers is forecasting very little change in water levels for the next 6 months. The lakes are almost ice-free, but we are also not seeing any significant degree or duration of arctic air. Despite the lack of ice, the water temperatures are still cold – just a few degrees above freezing – so the generally small difference in water temperature and air temperature means that evaporation levels are kept in check.

One might assume that the lakes remaining ice-free might increase the amounts of lake effect snow, and this is possible given there is still a steady supply of colder air supportive of driving the lake effect. However, this winter, the lack of cold air arriving over the region has reduced the lake effect snow events, and promoted significant melting between events.

Why do NOAA GLERL’s ice records only go back to 1973?

The early 1970s is when we first had reliable satellite data with which to construct more accurate and complete datasets. Before the satellite era, information during the winter about ice concentration away from the shoreline was very limited. This is why we only use the 51-year dataset for our calculations, as this represents the highest quality data.

Learn more about this year’s low Great Lakes ice

Current and historical ice cover data from NOAA GLERL

NOAA Research: Great Lakes ice cover reaches historic low

Climate.gov: Ice coverage nearly nonexistent across the Great Lakes, as the historical peak approaches

Download images and graphics from this article on our 2024 ice Flickr album


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New under-ice observing capabilities could lead to new discoveries in the Great Lakes

***UPDATED DECEMBER 2022***

During the dog days of summer here in the Great Lakes, scientists at NOAA’s Great Lakes Environmental Research Laboratory (GLERL) are already thinking about the ice that will form on the lakes this winter.

This year, NOAA GLERL and a team of federal, university, and industry partners are conducting test deployments of an autonomous underwater vehicle (AUV) in Lake Michigan, with the ultimate goal of using it under lake ice during winter to collect ecological and water quality data. Observations of winter ecology are difficult to obtain compared to observations in the ice-free season, when most fieldwork takes place – which makes this hunt for winter data especially important. 

In the world of Great Lakes research, the start of winter traditionally signals the end of fieldwork for the year. Buoys come out of the water, and research vessels – which aren’t designed for use in ice-covered waters – are docked for the season. Scientists get to work analyzing new data from the previous field season and tuning up field equipment for a fresh start in the spring. This break leads to a several-month gap in most of GLERL’s field data, but this project aims to fill that gap using the high-tech SAAB Sabertooth AUV. 

Video by Great Lakes Outreach Media.

One underwater robot, many important jobs

One of the AUV’s main tasks will be to collect water quality data, benthic (lake bottom) data, and fish and zooplankton observations. These observations will be collected using an acoustic imaging system, and will contribute to our understanding of important wintertime ecological processes in the Great Lakes. While summer is widely considered to be the peak time of year for biological productivity, biological processes still occur during the winter and are understudied in the Great Lakes. NOAA GLERL’s winter observations may even lead to unexpected discoveries, as new GLERL data suggest that some Great Lakes biological processes may actually accelerate during the winter months. Ice cover is seen as a key variable in the regulation of biological processes in the lakes during winter. Enhancing our understanding of these processes is particularly important as climate change may have implications for the extent, thickness, and duration of seasonal ice cover. 

The Saab Sabertooth is an autonomous underwater vehicle (AUV) that NOAA GLERL will operate under ice during winter in the Great Lakes.

The AUV also will characterize winter distributions of prey fish using a multi-frequency echosounder. Spawning in prey fish species like bloater also take place during winter, in turn affecting predator stocks (like lake trout) that help underpin a 7 billion-dollar annual Great Lakes fishery. Additionally, the AUV will contribute valuable data on the distribution of invasive mussels to NOAA GLERL’s 25-year ecological monitoring program. The AUV will map the locations of invasive mussel reefs on the lake floor using sonar technology and high-resolution imagery.

World-class technology in the Great Lakes

The SAAB Sabertooth AUV is no average piece of fieldwork equipment; it’s among the most advanced and complex underwater vehicles in the world. Navigation is one of the biggest challenges AUVs face, since GPS signals are unavailable underwater. This AUV contains an Inertial Navigation System, which keeps track of the vehicle’s movements with extreme precision. Based on its known deployment location, the vehicle uses this navigation system to calculate its exact location throughout its mission with minimal error. When within range, acoustic beacons anchored nearby in the lake are also used to confirm the AUV’s location.

Acoustic beacon is deployed in Lake Michigan for AUV navigation system updates. Brad Hibbard dials in a highly accurate beacon location.  

In addition to the AUV itself, this effort also includes the development of a fully integrated docking station that allows the vehicle to recharge its battery and transfer the data it’s collected during its winter excursion. The vehicle’s ability to safely dock, charge its battery, and transmit data to scientists is a critical component in its ability to function under ice without human help.

AUV docking station built by Hibbard Inshore. The dock allows vehicle recharging and data transfer through a Sonardyne BlueComm optical communications system. Hibbard and Saab used Sonardyne acoustic beacons to enable autonomous docking.

***

DECEMBER 2022 UPDATE

The most recent phase of this project, conducted in December 2022 at the beginning of meteorological winter, tested the AUV’s docking station and charging capabilities for the first time. The highly successful field trials achieved several goals:

  • The AUV autonomously navigated through the Muskegon Channel and out into Lake Michigan, where it successfully collected ecological data and mapped the lake floor.
  • Back in the channel, the AUV autonomously docked itself, using Sonardyne acoustic beacons to confirm its location.
  • Once docked, the AUV transferred the data it had collected and successfully recharged its battery from a Teledyne Energy Systems Subsea Supercharger® hydrogen fuel cell. As a truly groundbreaking outing, this field trial was the first time the Saab AUV has ever been charged underwater using a fuel cell power source.

So, where will all this new data go? The AUV’s data will ultimately be added to GLERL’s Realtime Coastal Observation Network (ReCON).

Lowering the Teledyne Energy System’s Subsea Supercharger® hydrogen fuel cell into the water. The fuel cell was used to recharge Hibbard Inshore’s Saab AUV internal batteries.
After several days of testing the docking and
navigation capabilities, the AUV headed out into
Lake Michigan for a trial to collect ecosystem data.

***

Smooth sailing beneath the surface

The large size of the AUV provides ample space, flotation, and electrical resources for simultaneously carrying a large suite of sensors that make multitasking a breeze for this high-tech vehicle. The various sensors work together to ensure the vehicle stays upright, avoids collisions with boats, and doesn’t accidentally hit the bottom of the lake. Plus, robust propellers allow the AUV to make precise turns and hover at a fixed depth, making it much easier to maneuver than its torpedo-shaped cousins.

Preparing this AUV for deployment is no small task. Vehicle setup was completed by the Hibbard Inshore and Saab team over several days.

When it’s not in the Great Lakes helping NOAA with environmental research, this vehicle can usually be found performing tunnel inspections at hydroelectric power facilities around the world – including locations like California, South Korea, and Turkey. The AUV’s ability to navigate through these tunnels allows them to be inspected without being drained, saving considerable time and money. Just as it navigates through these enclosed tunnels, this impressive underwater robot could soon be navigating its way under Great Lakes ice cover.

NOAA GLERL’s partners on this project include Hibbard Inshore, Saab Dynamics AB, Teledyne Energy Systems, the Cooperative Institute for Great Lakes Research (CIGLR), and the United States Geological Survey (USGS).

NOAA Disclaimer: This publication does not constitute an endorsement of any commercial product or intend to be an opinion beyond scientific or other results obtained by NOAA.


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Looking back: The ups and downs of Great Lakes ice cover in 2021

Ice formations cover a pier on the Lake Michigan shoreline in Holland, MI. February 27, 2021. Credit: Clarice Farina.

It’s no secret that the Great Lakes had a wild ride in terms of ice cover this past winter. From a slow start that led to near-record low ice cover in January, to the sudden widespread freeze just a few weeks later, here’s a look back at how ice cover on the lakes has fluctuated during the 2020-2021 ice season.

As we highlighted in our last blog post on historic ice data, January 2021 had the second-lowest overall Great Lakes ice cover on record since 1973 (with the very lowest being January 2002). For all five individual lakes, January 2021 was in the top five lowest ice-cover Januarys since 1973.

This graph shows average Great Lakes ice cover for the month of January every year from 1973 to 2021, organized by lowest ice cover (far left) to highest ice cover (far right). Credit: NOAA GLERL.

Starting out at 10.65% on February 1st, ice cover rose dramatically over the next three weeks with the region’s extreme cold weather. Growing quickly and steadily, total Great Lakes ice cover finally topped out at 45.84% on February 19th. But with air temperatures warming back up shortly afterwards, this spike was short-lived. Within a week it was back down to around 20% and continued to taper off, falling below 1% on April 3rd and reaching 0.1% on April 20.

This graph shows Great Lakes ice cover in 2021 (black line) compared to the historical average ice cover from 1973-2020 (red line). Credit: NOAA GLERL.

This Winter vs. The Long-Term Average

While all five lakes were far below their January average, each one did something a little different during February, when compared to its 1973-2020 average. The following graphs show this winter’s ice cover (black line) vs. the 1973-2020 average (red line) for each lake.⁣

Lake Erie ice cover jumped dramatically up to 81% in the second week of February, well above its average seasonal peak of around 65%. It stayed above 75% for about two weeks until falling back down below its average at the beginning of March.


Lake Michigan ice cover increased steadily throughout February, with its highest percentage being 33% on February 18th — only briefly staying above its average for that time period. It dropped off quickly the following week, then decreased gradually throughout March.

Lake Superior spent about a week in mid-February above its average ice cover for those days, peaking at about 51% on February 19th. Similar to Lake Michigan, it only stayed above its average for a short interval before rapidly falling back down under 20%.

Lake Ontario ice cover took a while to ramp up, staying below 10% until mid-February. It reached maximum ice cover on February 18th, topping out at about 21% – slightly higher than its average for that day.


Lake Huron was the only lake that did not reach above-average ice cover for the entire winter. Its peak ice cover was 48% on February 20th, which was about the same as its average for that time of year.

Melting into Spring

Throughout March, ice cover on all five lakes continued to decrease steadily, with the exception of a spike in ice cover around the second week of the month likely due to fluctuations in air temperature. For Lakes Erie and Ontario, this short-lived jump was enough to get them back up near their average early March ice cover for a few days. 

As for the timing of each lake’s peak 2021 ice cover compared with the average, Lakes Erie, Michigan, Huron, and Ontario all peaked later than their average, while Lake Superior is the only one that peaked earlier than its average.

Ice covers the Lake Huron shoreline in Oscoda, MI on February 15, 2021. Credit: G. Farina, NOAA GLERL.

This winter’s maximum seasonal ice cover of 45.8% is just 7.5% less than the long-term average of 53.3%. While it’s below the average, it’s still more than double the 2020 seasonal maximum of 19.5% ice cover, but is just over half the 2019 seasonal maximum of 80.9%. With so much year-to-year variability, forecasting ice cover each year can be incredibly difficult. NOAA GLERL’s experimental ice forecast, updated in mid-February, predicted Great Lakes ice cover in 2021 to peak at 38% – not too far off from what it really was. NOAA GLERL continues to analyze both current and historical data to refine the ice forecast model, working to actively improve our experimental Great Lakes ice forecast each year.

This graph shows annual maximum ice cover on the Great Lakes each year from 1973 to 2021. Credit: NOAA GLERL.

For more on NOAA GLERL’s Great Lakes ice cover research and forecasting, visit our ice homepage here: https://go.usa.gov/xsRnM⁣

⁣Plus, access these graphs plus more Great Lakes CoastWatch graphs & data here: https://go.usa.gov/xsRnt⁣

Flat, jagged pieces of ice float in Lake Huron near Oscoda, MI on February 15, 2021. Credit: G. Farina, NOAA GLERL.
map of great lakes showing colors of model output


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Improving lake effect snow forecasts by making models talk to each other

If you live in the Great Lakes basin and have been on or even near a road recently, you might be feeling unreasonably ragey at the mere mention of lake effect snow. We get it. But bear with us, because we’re doing some cool science we’d like to tell you about. It may even make your commute easier someday, or at least more predictable.

GLERL scientists are working with researchers at the University of Michigan’s Cooperative Institute for Great Lakes Research (CIGLR), the National Weather Service, and NOAA’s Earth Systems Research Laboratory (ESRL) to make lake effect snow forecasts in the Great Lakes better.

NOAA’s high resolution rapid refresh (HRRR) model is the most commonly used weather model for predicting lake effect snow. An experimental version runs on a beastly high-performance computer at ESRL in Colorado, and predicts a whole list of atmospheric variables (including snowfall) every 15 minutes. The model relies on water surface temperature data, collected via satellite, to make its predictions. It’s important to give the model accurate water surface temperatures to estimate evaporation across the Great Lakes, since it is the main driver of lake effect snow.

Unfortunately, satellite temperature data has limitations. If clouds keep satellites from measuring the temperature at a specific location, the weather model will just use the most recent measurement it has. Since it’s especially cloudy in the Great Lakes during the lake effect snow season (late fall and early winter), that data could be days old. Because lake temperatures are changing quite rapidly this time of year, days-old data just doesn’t cut it.

As it turns out, GLERL already has a model that predicts Great Lakes surface temperature pretty well. The Great Lakes Operational Forecast System (GLOFS) spits out lake surface temperatures every hour. If we tell the weather model to use GLOFS output instead of satellite data, it has the potential to do a far better job of forecasting lake effect snow.

Linking two models like this is called “coupling”. GLOFS actually already uses input from HRRR—wind, air temperature, pressure, clouds and humidity data all inform GLOFS’ predictions. We’re just coupling the models in both directions. HRRR will send its output to GLOFS, GLOFS will “talk back” with its own predictions of water surface temperature (and ice cover), and HRRR will produce a (hopefully) more informed prediction of lake effect snow.

Initial results are promising. We used the coupled models to do a ‘hindcast’ (a forecast for the past) to predict lake effect snow for a major event over Lake Erie in November of 2014. They did a significantly better job than without coupling. The figure below shows the difference.

The coupled models improved cumulative snow water equivalent forecasts. Red shows where the model increased snowfall.

You’ll notice a band of blue on the southeastern edge of Lake Erie, indicating that the coupled models predicted less lake effect snow in that area. There’s a band of orange directly to the north of it, where the coupled models predicted more lake effect snow. What you’re seeing is the coupled model predicting the same band of snow, but further north, closer to where it actually fell.

That storm slammed the city of Buffalo, New York, killing 13 people. Better lake effect snow predictions have the potential to save lives.

GLERL and partners will be doing further testing this winter, and if it works out, the model coupling will be carried over in research-to-operations transitions.


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Scientists Work Around the Clock During Seasonal Lake Michigan Cruise

Last month, scientists from GLERL, the Cooperative Institute for Limnology and Ecosystems Research (CILER), and other university partners took the research vessel Laurentian for a multi-day cruise on Lake Michigan as part of seasonal sampling to assess the spatial organization of the lower food web—spatial organization simply means the vertical and horizontal location where organisms hang out at different times of day, and the lower food web refers to small organisms at the bottom of the food chain.

The research goes on around the clock. Scientists work in shifts, taking turns sleeping and sampling. The Laurentian spends a full 24 hours at each monitoring station, sampling vertical slices of the water column. Sampling at these same stations has been going on since 2010, providing a long-term dataset that is essential for studying the impact of things like climate change and the establishment of invasive species.

Sampling focuses on planktonic (floating) organisms such as bacteria, phytoplankton (tiny plants), zooplankton (tiny animals), and larval fishes which feed on zooplankton. Many of the zooplankton migrate down into deep, dark, cold layers of the water column during the day to escape predators such as fish and other zooplankton. They return unseen to warm surface waters at night to feed on abundant phytoplankton. Knowing where everything is and who eats whom is important for understanding the system.

Our researchers use different sampling tools to study life at different scales. For example, our MOCNESS (Multiple Opening Closing Net Environmental Sampling System) is pretty good at catching larger organisms like larval fish, Mysis (opossum shrimp), and the like. The MOCNESS has a strobe flash system that stuns the organisms, making it easier to bring them into its multiple nets.

The PSS (Plankton Survey System) is a submersible V-Fin (vehicle for instrumentation) that is dragged behind the boat and measures zooplankton, chlorophyll (a measure of phytoplankton), dissolved oxygen, temperature, and light levels. Measurements are made at a very high spatial resolution from the top to the bottom of the water. At the same time fishery acoustics show where the fish are. Together, these two techniques allow us to see where much of the food web is located.

Water samples are taken at various depths and analyzed right on the boat. This is a good way to study microbes such as bacteria and very small phytoplankton. The lower food web has been pretty heavily altered by the grazing of quagga and zebra mussels. Specifically, the microbial food web (consisting of microbes such as bacteria and very small phytoplankton) makes up a larger component of the food web than before mussel invasion, and scientists are working to find out exactly how this has happened.

Check out the photos below for a glimpse of life in the field!

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Central Michigan University students Anthony and Allie are all smiles as they prepare to head out!

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Getting the MOCNESS ready.

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Chief scientist Hank Vanderploeg looks at some data.

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Filtering a water sample—filtering out the big stuff makes it easier to see microbes.

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Paul prepares the fluoroprobe.

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Taking a water sample in the presence of a beautiful sunset!