NOAA Great Lakes Environmental Research Laboratory

The latest news and information about NOAA research in and around the Great Lakes

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New wave buoy will provide data to support wave and flood forecasting on Lake Champlain

The NOAA Great Lakes Environmental Research Laboratory (GLERL) and partners recently deployed a buoy in Lake Champlain that will measure the lake’s wave heights to assess the accuracy of a new experimental model for the lake. This is part of a five-year NOAA GLERL project that will improve public safety on Lake Champlain by contributing to flood preparedness and response around the shores of the lake. Wave conditions are critical to public safety both for recreational and commercial activities on the lake – such as for boats, harbors, and beaches – but also for predicting coastal flood impacts at the shoreline where waves can run up and significantly impact infrastructure.

Left: Newly deployed NOAA buoy in Lake Champlain. Credit: University of Vermont FEMC staff. Top right: NOAA GLERL partners at the University of Vermont’s Forest Ecosystem Monitoring Cooperative (FEMC) deployed the buoy on Lake Champlain in May 2021. Credit: University of Vermont FEMC staff. Bottom right: Sunset on Lake Champlain. Credit: Dan Titze, CIGLR.

The project is a major collaborative effort by bi-national, federal, and university partners of NOAA GLERL. Partners at the University of Vermont’s Forest Ecosystem Monitoring Cooperative (FEMC) deployed the seasonal buoy in May, and the Coastal Data Information Program (CDIP) at the University of San Diego Scripps Institute of Oceanography receives the data, manages its quality control, and posts it to NOAA’s National Data Buoy Center (NDBC) website. Researchers at the Cooperative Institute for Great Lakes Research (CIGLR) are currently leading the development of a wave model for Lake Champlain, which is providing experimental forecasts on the GLERL website.

The buoy is located in the middle of the lake near Schuyler Reef, where it will remain until late fall, and is collecting wave height observations that will be used to validate NOAA’s WAVEWATCH III model for Lake Champlain. The experimental model’s output data will be compared to the buoy’s observed data, which will help scientists assess how well the model performs.

Location of the new NOAA Lake Champlain wave buoy, depicted by a yellow diamond. Map credit: NOAA National Data Buoy Center.

The buoy’s environmental data can be found on the CDIP website, and on the buoy’s page on the NOAA NDBC website. The buoy and the experimental wave model will be a helpful new tool for the region’s National Weather Service Weather Forecast Office in Burlington, Vermont, which provides lake forecasts including wave data to mariners in the region.

In addition to regional weather forecasters and local mariners, this buoy’s data will also be useful to emergency managers in the counties and cities around Lake Champlain and the Richelieu River, as well as the NOAA National Centers for Environmental Prediction which will transition the WAVEWATCH III model to operations.

This project is funded by the International Joint Commission’s Lake Champlain-Richelieu River (LCRR) Study Board. The International Joint Commission (IJC) is a bi-national organization established by the governments of the United States and Canada under the Boundary Waters Treaty of 1909. It oversees activities affecting the extensive waters and waterways along the Canada–United States border. The IJC’s LCRR Study Board was created in 2016 to undertake a study of the causes, impacts, risks, and potential solutions to flooding in the LCRR basin.


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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.


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Five decades of Great Lakes ice cover data – and where to find it

Understanding the major effects of ice on the Great Lakes is crucial. Ice cover impacts a range of societal benefits provided by the lakes, from hydropower generation to commercial shipping to the fishing industry. The amount of ice cover varies from year to year, as well as how long it remains on the lakes. With almost five full decades of ice data to look at, GLERL scientists are observing long-term changes in ice cover as a result of climate change. Studying, monitoring, and predicting ice coverage on the Great Lakes plays an important role in determining climate patterns, lake water levels, water movement patterns, water temperature structure, and spring plankton blooms.

Maximum ice cover on the Great Lakes every year from 1973 to 2018. Credit: NOAA GLERL.

NOAA GLERL has been exploring the relationships between ice cover, lake thermal structure, and regional climate for over 30 years through the use of historical model simulations and observations of ice cover, surface water temperature, and other variables. Weekly ice cover imaging products produced by the Canadian Ice Service (CIS) started in 1973. Beginning in 1989, the U.S. National Ice Center (NIC) produced Great Lakes ice cover charts that combined both Canadian and U.S. satellite imagery. Today, these products are downloaded and processed at GLERL by our CoastWatch program, a nationwide NOAA program within which GLERL functions as the Great Lakes regional node. In this capacity, GLERL uses near real-time satellite data to produce and deliver products that support environmental decision-making and ongoing research. While the Great Lakes CoastWatch Program is a great resource for near real-time ice cover data, historical data is just as important – and that’s where GLERL’s Great Lakes Ice Cover Database comes in. Originally archived by GLERL through the National Snow & Ice Data Center, the Great Lakes Ice Cover Database houses data that dates back to 1973 and continues to be updated daily during the ice season every year.

Ice caves on Lake Michigan’s Glen Haven beach in 2005. Credit: National Parks Service.

Even though the CIS and NIC are the ones who actually collect Great Lakes ice cover data, GLERL plays the important role of re-processing this ice data into more accessible file formats, making it readily usable to anyone who needs it. Agencies and organizations that have used ice cover data from GLERL in the past include the NASA Earth Observatory, U.S. Army Corps of Engineers, U.S. Coast Guard, and National Geographic. Types of data requested might include historic minimum and maximum ice coverage for certain regions or lakes, or dates of the first and last ice cover in a region from year to year. This information can be helpful for managers in industries like energy production and commercial shipping.

This graph shows annual maximum ice coverage on the Great Lakes every year from 1973 to 2020. The red dashed line marks the long-term average maximum ice cover of 53.3%. Credit: NOAA GLERL.

GLERL scientists can also use this historic ice cover data to analyze how current ice cover conditions compare with previous years. For example, here’s how the ice cover during January 2021 stacks up against data for past Januarys:

  • Lake Michigan and the five-lake average had their second lowest January ice cover (with January 2002 being the first lowest).
  • The other lakes are all in the top five lowest ice cover for the month of January.
  • Six out of ten of the Januarys with the lowest ice cover have occurred during the last decade for the five-lake average (though 2014 was fourth highest January ice cover).
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.

GLERL is also working to make this data more user-friendly for anyone looking to utilize it. This recent paper from GLERL and the Cooperative Institute for Great Lakes Research (CIGLR) describes the scientists’ efforts to standardize two existing formats of historic ice cover data. The authors explain that “technology has improved and the needs of users have evolved, so Great Lakes ice cover datasets have been upgraded several times in both spatial and temporal resolutions.” The paper documents the steps the authors took to reprocess the data in order to make it more consistent and accessible, which ultimately makes it easier for users to study long-term trends.

Timeline of ice chart evolution and frequency, from the research paper described above (Yang et al 2020). Credit: Ting-Yi Yang, Cooperative Institute for Great Lakes Research.

Whether you’re looking for decades of Great Lakes ice data or just a few days, GLERL’s got you covered! Looking for more Great Lakes ice cover information? Visit our ice cover homepage here.

MODIS satellite image of ice cover on the Great Lakes, March 16, 2014. Credit: NOAA Great Lakes CoastWatch.


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Eight years of Great Lakes underwater glider data now available to the public

CIGLR’s Russ Miller deploying glider in Lake Huron, June 2017

NOAA Great Lakes Environmental Research Laboratory (GLERL) and the Cooperative Institute for Great Lakes Research (CIGLR) recently posted eight years’ worth of Great Lakes autonomous underwater vehicle (AUV), or “glider data ”  on NOAA’s Integrated Ocean Observing System (IOOS) Underwater Glider Data Assembly Center (DAC) map. The map is a collaborative effort and includes current and historical glider missions dating back to 2005 from around the planet. This data is useful to government agencies, researchers, environmental managers, and citizens who use Great Lakes data for better understanding the characteristics of Great Lakes water.

CIGLR glider just before a deployment in Lake Michigan at the NOAA GLERL Lake Michigan Field Station in Muskegon, MI.

The collection and analysis of this data is a close collaboration between NOAA GLERL, CIGLR and partner institutions. CIGLR owns and operates the glider, and it is deployed using NOAA GLERL vessels. Data managers and researchers from both organizations are working together to make this data as useful and accessible as possible. This cooperative project, which has been funded by the Great Lakes Observing System (GLOS; a part of the IOOS program), aims to support science, public safety, and security through the use of unmanned systems (UxS).

Glider Tech Specs

This glider is buoyancy-driven, meaning it controls its depth in the water by inflating and deflating a “bladder” that in turn makes it sink or float. It typically operates at around 30 meters (100 feet) below the lake surface, but can go as deep as 200 meters (650 feet) when needed. While the glider is able to work on it’s own, scientists wirelessly communicate with it regularly throughout its journey when it’s at the surface. It’s programmed to resurface regularly for check-ins, so we always know right where it is and we can even instruct it to change its mission path if necessary. It may only travel an average of 1 kilometer (0.6 miles) per hour, but its missions can last up to 60 days and provide us with amazing data sets to help answer questions about the Great Lakes ecosystem. Check out the video below from NOAA’s Ocean Service and visit this fact page for more on how the glider works.

The importance of data collection

With every deployment, the glider measures the water’s physical properties such as temperature, mineral content, pressure, and salinity. (Yes, even the Great Lakes have a tiny bit of salinity!) It also measures biological properties such as chlorophyll fluorescence and concentrations of dissolved organic matter, which indicate the region’s level of primary biological productivity (the amount of organic matter produced by phytoplankton in the water). Phytoplankton might be tiny, but their productivity is extremely important to the lakes’ ecosystems because it provides nutrients to the rest of the food web.

CIGLR glider floating just below the surface of the water.

When you piece together all these day-to-day measurements, you can use them to study seasonal changes such as movement of the thermocline – or steep temperature gradient in the lake – which can impact the rate of biological activity in the spring and summer. The size and intensity of spring algal blooms and occasional “whiting events” (accumulations of calcium carbonate particles in the water due to increased biological productivity) are other examples of seasonal biological phenomena the glider can observe. The glider collects high-quality data efficiently and cost-effectively, day and night in all weather conditions, ultimately allowing us to collect more data in a shorter amount of time than is possible with traditional ship-based methods. The robust datasets it gives us advance our understanding of Great Lakes processes on short-term, seasonal, and annual timescales — and lay a foundation for observing changes in the lakes over several decades.

This map shows NOAA GLERL/CIGLR underwater glider pathways in southern Lake Michigan, available on NOAA’s Integrated Ocean Observing System (IOOS) Underwater Glider Data Assembly Center map.  A long-term series of Lake Michigan observations in the southern basin of Lake Michigan began in 2012, criss-crossing between Muskegon, Milwaukee. This complements data collected by the NOAA National Data Center Station 45007, as well as temperature string in the southern basin of the lake,  connecting the observations of NOAA GLERL and University of Wisconsin-Madison. 

Glider paths shown on the maps include all deployment from 2012-2019. These paths expand observations collected by Federal and University research vessels in the same regions of the Great Lakes, through the use of other tools, such as NOAA GLERL’s Plankton Survey System (PSS) and Multiple Opening and Closing Net and Environmental Sampling System (MOCNESS). It is important to have a long period of observations from many types of collection across the lakes to better understand how things like water temperature at different depths, inputs from rivers, and seasonal changes to other characteristics of the water affect the ecosystem.This information is useful in understanding the impacts of invasive species, harmful algal blooms, and our changing climate.

This map shows NOAA GLERL/CIGLR underwater glider pathways in the Great Lakes, available on NOAA’s Integrated Ocean Observing System (IOOS) Underwater Glider Data Assembly Center map. In 2013, 2015, 2017, and 2018, glider deployments were chosen to complement ship- and glider-based observations of the Environmental Protection Agency (EPA), NOAA, United States Geological Survey (USGS), and Coordinated Science and Monitoring Initiative (CSMI) in Lakes Michigan, Ontario and Huron.  Lake Erie is too shallow for effective use of this glider, and Lake Superior has been monitored by EPA and University of Minnesota Large Lakes Observatory gliders.

Future deployments and collaboration

Planning is currently underway for future missions in the Great Lakes and potential applications for the glider’s wide variety of data. The glider will also be used this year on Lake Michigan for research and observations during the 2020 Cooperative Science and Monitoring Initiative (CSMI), a binational effort to coordinate science and monitoring activities in one of the five Great Lakes each year. This year’s CSMI research will likely use the glider to gain a better understanding of water quality in the lake’s nearshore regions – the area in the water from where waves begin to break, up to the lowest water point on the beach. With great partners like CIGLR and GLOS, the future is bright for NOAA’s underwater glider explorations.