NOAA Great Lakes Environmental Research Laboratory

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NOAA GLERL Physical Scientist receives NOAA National Ocean Service Peer Recognition Award

NOAA GLERL Physical Scientist James Kessler recently received a NOAA National Ocean Service (NOS) Peer Recognition Award for outstanding day-to-day collaborative efforts involving crosscutting programmatic tasks that contributed to the accomplishments of the NOS mission. 

Peer Recognition “Rafting” Awards recognize coordination among NOS offices and provide NOS employees the opportunity to express their appreciation to another NOAA federal colleague that has helped them in some unique way. Congratulations, James, from all of us at NOAA GLERL!

The award nomination below describes James’ invaluable contributions to interagency collaborations between NOAA NOS, NOAA’s Office of Oceanic and Atmospheric Research (OAR), and the U.S. Coast Guard:

The Great Lakes contain 20 percent of the world’s surface freshwater supply and provide drinking water to over 40 million people. When a pollution event or natural disaster occurs, NOAA’s National Ocean Service Office of Response and Restoration (NOS/OR&R) is responsible for providing scientific analysis that supports decision makers recommendations of protecting life, property, and the environment. To accomplish this, OR&R often draws upon subject matter expertise from other parts of NOAA. This award is to recognize the outstanding professional performance of James Kessler (OAR/GLERL) when selected to participate and support two different OR&R events.

The first was an invitation for Mr. Kessler to participate in the U.S. Coast Guard (USCG) led oil spill exercise held in Roger’s City, MI on July 19, 2022. Showcasing NOAA’s role and ability to provide unified scientific support to the USCG during a spill emergency is imperative. The success of this public event with an audience of federal, state, and local emergency responders was a testament to the positive collaboration between NOS/OR&R and OAR. This particular exercise was significant as the USCG obtained approval to use a highly visible green dye in the water to mimic spilled oil in order to highlight environmental transport in the exercise area. Without previous emergency response experience, James Kessler provided detailed information on the hydrodynamic properties of Lake Huron with uncommon zeal and vitality. He developed an oil dispersion animation for the exercise scenario using the Great Lakes Operational Forecast System (GLOFS), ran the model during the event, and presented to over 100 attendees the GLOFS, High-Resolution Rapid Refresh (HRRR), and Global Forecast System (GFS) systems. Mr. Kessler displayed expert knowledge of NOAA Great Lakes capabilities including the Great Lakes Observing System (GLOS) and often brought in a representative to discuss observation systems and gaps in coverage with interested stakeholders.

The collaboration between OR&R and GLERL directly reflected NOS priorities of preparedness and risk reduction; as well as NOAA’s strategic priorities of communicating NOAA’s comprehensive observing systems and partnerships in the Great Lakes that improve data delivery and services to government and state agencies, as well as private industry stakeholders. In another example representing Mr. Kessler’s support, the newly established USCG Center of Expertise (COE) in partnership with the OR&R, funded a research project to test uncrewed aircraft systems’ (UAS) ability to collect and share data from a USCG vessel in an ice environment. James Kessler joined the project planning team in January and delivered time critical analysis of current and historical ice data for the Great Lakes.

Mr. Kessler’s astute analysis of ice data archives between 1973-present and initiative to generate time series plots provided concrete information for project managers to shift the dates and location of the project to ensure proper ice conditions. As a result, the field deployment component of the project was moved from January 22 in Port Huron, to March 6 in Duluth, MN and directly led to the successful capture of a USCG vessel breaking fresh ice and completion of the first field experiment funded by the COE. The successful outcome of this project also led to defining protocols for data sharing between USCG and NOAA that will vastly improve product support for pollution spills and disaster responses nationwide. While in the field, Mr. Kessler’s charisma was noted on a daily basis by USCG SES and earned him a deep sense of respect by all within the project team. His exceptional professional knowledge, enthusiasm, and dedication to mission contributed significantly and was the motivating force to keep collaborative efforts between NOS/OR&R, GLERL, and USCG moving forward.


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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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NOAA GLERL Deputy Director Jesse Feyen receives AMS STAC 2023 Coastal Environment Committee Outstanding Service Award

Congratulations to NOAA Great Lakes Environmental Research Laboratory Deputy Director Jesse Feyen on receiving an American Meteorological Society (AMS) award this week! Dr. Feyen was awarded the Scientific and Technological Activities Commission (STAC) 2023 Committee on Coastal Environment Outstanding Service Award.

NOAA GLERL Deputy Director Jesse Feyen (center) accepts his award with Yun Qian (Pacific Northwest National Laboratory, left) and Greg Dusek (NOAA National Ocean Service, right).

Remarks from the AMS awards ceremony:

Dr. Feyen is receiving this award for serving the AMS Committee on the Coastal Environment with exceptional distinction for 6 years. Dr. Feyen served as the committee chair from 2020 – 2023, a period which was obviously characterized by COVID and the challenges that COVID and virtual world posed to our ability to plan and host our symposium at the AMS Annual Meeting.

Under Jesse’s leadership the committee successfully adapted to the first ever fully virtual Annual Meeting, and the first ever Hybrid Annual Meeting. Through these challenges we saw a growth in the coastal symposium, both in the number and diversity of attendees, up to this year, where we had the greatest number of presentations and posters we have ever had at our symposium.

His leadership also resulted in a larger and more diverse committee – in career stage, background, race and gender – resulting in the outstanding committee which put together the symposium you are at today.

On top of all that, even after his tenure, Jesse has continued to serve and support the committee and been an invaluable resource to Yun and I as we stepped into the chair and vice-chair roles.

Congratulations, Deputy Director Feyen, from all of us at NOAA!


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Low ice on the Great Lakes this winter

Ice coverage has reached a record low in the Great Lakes for this time of year. As of February 13, 2023, only 7 percent of these five freshwater lakes was covered in ice. Read the full story on NOAA Research.

This MODIS satellite image from February 12th, 2023 shows below-average ice cover for this time of year on the Great Lakes. Credit: NOAA GLERL / NOAA Great Lakes CoastWatch Node.


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Underwater robots significantly advance our ability to study Lake Erie’s harmful algal blooms

Newly published research from the NOAA Great Lakes Environmental Research Laboratory (GLERL), the Cooperative Institute for Great Lakes Research (CIGLR), and partners reveals that using underwater robots could significantly advance scientists’ ability to study the harmful algal blooms (HABs) that appear in the Great Lakes and oceans every summer. You may remember reading about NOAA’s collaborative fieldwork in 2019 that used these robots to detect toxins in Lake Erie’s harmful algal bloom. Three years later, the findings from this pioneering research come bearing good news!

This autonomous underwater vehicle (AUV), known as “Makai,” visited the Great Lakes from the Monterey Bay Aquarium Research Institute (MBARI) to help scientists study Lake Erie’s harmful algal bloom. Credit: Steve Ruberg, NOAA GLERL

What are HABs, and how do we study them?

HABs occur when colonies of algae grow out of control and produce toxic or harmful effects on people, fish, shellfish, marine mammals and birds. Western Lake Erie in particular has been plagued by intensified HABs over the past decade. These blooms consist of cyanobacteria, or blue-green algae, which are capable of producing toxins that endanger human and animal health, compromise drinking water supplies, foul coastlines, and impact communities and businesses that depend on the lake. 

Harmful algal bloom in western Lake Erie in October, 2011. Credit: NOAA Great Lakes CoastWatch

The underwater robot used in this research project is known as a long-range autonomous underwater vehicle, or LRAUV. As the name suggests, the LRAUV is built to travel long distances beneath the water’s surface, collecting data for an extended period of time. LRAUVs are useful research tools, as they can collect high-quality data more efficiently and cost-effectively than scientists taking samples from a ship or along the shore. They can be deployed day and night in all weather conditions, and can provide more detailed information to researchers and drinking water managers than other monitoring methods.

For this project, NOAA and CIGLR teamed up with the Monterey Bay Aquarium Research Institute and university partners to equip an LRAUV with a 3rd Generation (3G) Environmental Sample Processor (ESP) — a mobile version of what has previously been known as NOAA’s “lab in a can.” The 3G ESP’s job is to measure microcystin, a potent liver toxin produced by the cyanobacteria that cause harmful algal blooms in the Great Lakes. In just a few hours, the 3G ESP can collect and analyze water samples from the bloom with the same methods that scientists use to analyze samples back at the lab. It does this with the use of ‘omics, a collective suite of technologies used to analyze biological molecules such as DNA, RNA, proteins, or metabolites. These technologies can be used to identify the algal species that produce HABs, understand their behavior, and predict shifts in their population structure.

NOAA and partners deployed the LRAUV-3G ESP in Lake Erie to autonomously measure microcystin, a potent liver toxin produced by the cyanobacteria that cause harmful algal blooms in the Great Lakes. Photo credit: NOAA

Did this robot step up to the challenge?

Before widely adopting the use of the LRAUV-3G ESP to study Lake Erie HABs, scientists had to ensure that the data these instruments collect is accurate and reliable. A main goal of the new publication was to assess how dependable the LRAUV-3G ESP’s data is compared to data that was collected and analyzed by humans.

The authors used a variety of parameters to assess the vehicle’s performance of ‘omics tests on samples it collected from the HAB. They ultimately found that the LRAUV-3G ESP successfully performed flexible, autonomous sampling across a wide range of HAB conditions, and the results indicated equivalency between autonomous and manual methods. In fact, no significant differences were found between LRAUV-3G ESP and manual sample collection and handling methods in the 12 parameters tested. In other words, this robot passed the test!

Left: Scientists retrieve the LRAUV-3G ESP from its mission to measure algal toxins in Lake Erie. Photo credit: NOAA AOML. Right: First author Paul Den Uyl (CIGLR) CIGLR retrieves 3G ESP filters for analysis of Lake Erie microbial community DNA. Photo Credit: Kelly Godwin.

One of the most exciting aspects of this research is that it shows that scientists can use an autonomous sampling platform to replicate traditional ship-based sampling, and they can do so in a particularly challenging environment (Lake Erie’s shallow western basin) where HABs are a serious health concern. Using this instrument in Lake Erie’s shallow waters presented another challenge for the scientists involved. In response to the lake’s challenges, researchers worked on the LRAUV’s buoyancy to ensure that the instrument didn’t drag across the ground. With this technology – sampling DNA and measuring toxins on an autonomous platform – NOAA and partners may be able to provide an early warning system for HABs in the future.

The 3rd Generation Environmental Sample Processor demonstrates engineering advancements from the first and second generation ESPs. Photo credit: NOAA GLERL.

Partners on this research came from far and wide to conduct this important research:

  • National Oceanic and Atmospheric Administration (NOAA)
    • NOAA Atlantic Oceanographic and Meteorological Laboratory (AOML), Ocean Chemistry and Ecosystems Division
    • NOAA Great Lakes Environmental Research Laboratory
    • NOAA National Centers for Coastal Ocean Science (NCCOS)
    • NOAA Southwest Fisheries Science Center
  • Cooperative Institute for Great Lakes Research (CIGLR), University of Michigan
  • Northern Gulf Institute, Mississippi State University
  • Monterey Bay Aquarium Research Institute (MBARI)
  • Department of Earth and Environmental Sciences, University of Michigan

Explore more photos of this research on NOAA GLERL’s Flickr page.


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Decades in the making, NOAA’s newest Lake Superior and Lake Ontario forecast systems become fully operational

Did you know that NOAA operates a forecasting system that predicts water conditions on the Great Lakes? Whether you’re wondering about a lake’s temperature, currents, or water level changes, NOAA’s got you covered! This fall, NOAA implemented newly updated versions of the Lake Superior and Lake Ontario portions of this system, and added ice forecasts to all five lakes.

Lake Michigan waves at the St. Joseph North Pier Lighthouses following superstorm Sandy. October 29, 2012. Credit: S. Lashley, NOAA NWS.

GLOFS forecasts Great Lakes conditions

The publicly available Great Lakes Operational Forecast System (GLOFS) is a NOAA automated, model-based prediction system aimed at providing improved predictions of these conditions in the five Great Lakes (Erie, Michigan, Superior, Huron and Ontario) for the commercial, recreation, and emergency response communities. GLOFS models use current lake conditions and predicted weather patterns to forecast the lake conditions for up to five days (120 hours) in the future. GLOFS predictions enable users to increase the margin of safety and maximize the efficiency of commerce throughout the Great Lakes.

NOAA’s National Weather Service (NWS) and National Ocean Service (NOS) work together to run GLOFS operationally on NOAA’s High Performance Computing System. By running on NOAA’s High Performance Computing System, GLOFS has direct access to National Weather Service operational meteorological products that are required for reliable and timely operations.

A major update for Lakes Ontario and Superior

A key goal of NOAA’s Research branch is to continually make forecasts better, and GLERL scientists play a major role in improving the models that constitute GLOFS. Like the rest of GLOFS, the Lake Ontario and Lake Superior portions – Lake Ontario Operational Forecast System (LOOFS) and Lake Superior Operational Forecast System (LSOFS) – were originally based on the Princeton Ocean Model. As of October 2022, they’ve now been upgraded with higher-resolution versions that are based on a newer computer model.

MODIS satellite images of Lakes Superior (left) and Ontario (right) in March 2021.

The new LOOFS and LSOFS use the Finite Volume Community Ocean Model (FVCOM), coupled with an unstructured grid version of the Los Alamos Sea Ice model (CICE). The new model provides users with higher resolution of nowcast (near-present conditions) and forecast guidance of water levels, currents, water temperature, ice concentration, ice thickness and ice velocity out to 120 hours in the future, and it updates four times per day. By invoking advanced model schemes and algorithms, LOOFS and LSOFS are expected to generate a more accurate model output than their former versions. 

Before they were ready to become operational, the new versions of LOOFS and LSOFS were run experimentally at GLERL for several years, where they underwent extensive testing and evaluation. GLERL played a key role in developing these models and ran them as part of the Great Lakes Coastal Forecasting System (GLCFS) – an experimental version of GLOFS that GLERL uses to prepare new models to become operational.

With this transition, the GLOFS models for all five Great Lakes have now been upgraded to FVCOM versions, as the Lake Erie model was upgraded in 2016, and the Lake Michigan-Huron model was upgraded in 2019. A new FVCOM-based model for the Huron-Erie Corridor, which includes Lake St. Clair and both the St. Clair and Detroit Rivers, is scheduled to be added to GLOFS in 2023. Read more about the LOOFS and LSOFS transition here.

These output maps from the current 3rd generation GLOFS show Lake Superior wind speed
and direction (top) and Lake Ontario water temperatures (bottom).

GLERL has been improving GLOFS for over 30 years

GLOFS is based on the Great Lakes Forecasting System, originally developed by The Ohio State University (OSU) and GLERL in the late 1980s and 1990s under the direction of Dr. Keith Bedford (OSU) and Dr. David Schwab (NOAA GLERL). The original forecasting systems utilized the Princeton Ocean Model (POM) and used a set of uniformly structured bathymetric grids. The first routine nowcast, using a low-resolution grid for Lake Erie, began at OSU in 1992.

Starting in 2002, GLERL’s semi-operational GLCFS was expanded to five lakes using medium-resolution grids (5 – 10 km) and 48-hr forecasts were added. This version was successfully transferred from research to operations at NOAA NOS in 2010. The transition to operations at NOAA NOS was a joint effort between NOAA GLERL, NOS Center for Operational Oceanographic Products and Services (CO-OPS) and NOS Office of Coast Survey (OSC) Coast Survey Development Laboratory (CSDL), private industry, and academia (OSU).

NOAA GLERL has continued to make improvements to the experimental GLCFS; these include increasing the grid resolution (2 – 10 km), adding ice dampening and an ice model, and extending the forecasts to 120 hours during the period of 2006-2014 (generation 2). The current 3rd generation of the GLOFS is what you see run by NOS today, with a resolution of 200m to 2.5km and producing 120-hour forecasts.

The development and implementation of LSOFS and LOOFS is a joint project across several NOAA offices and external partners. 

  • NOAA National Ocean Service Center for Operational Oceanographic Products and Services
  • NOAA NOS Office of Coast Survey
  • NOAA Office of Oceanic and Atmospheric Research Great Lakes Environmental Research Laboratory
  • Finite Volume Community Ocean Model development group at the University of Massachusetts Dartmouth
  • NOAA National Weather Service National Centers for Environmental Prediction Central Operations


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Lessons from Lake Huron: A look back at NOAA GLERL’s 2022 fieldwork for the Cooperative Science and Monitoring Initiative

Every summer, NOAA GLERL scientists travel far and wide across the Great Lakes region to study the biological, chemical, and physical properties of these amazing lakes. A portion of this fieldwork contributes to a larger project called the Cooperative Science and Monitoring Initiative – or CSMI – which helps us take a deeper dive into studying a different Great Lake each year. Instituted under the 2012 Great Lakes Water Quality Agreement, CSMI is a multi-agency, international effort to coordinate science and monitoring activities in one of the five Great Lakes each year to generate data and information for environmental management agencies.

MODIS satellite image of Lake Huron on May 18, 2021. Credit: NOAA Great Lakes CoastWatch Node.

Each Great Lake gets a “CSMI year” once every five years, and 2022 was Lake Huron’s turn to shine. Sitting right at the center of the Great Lakes region, Lake Huron is shared by the state of Michigan and the Canadian province of Ontario. It’s the second largest of the Great Lakes and ranks as the fourth largest lake in the world by surface area. Lake Huron provides economically and culturally important services, including a productive fishery, a source of clean drinking water, and natural beauty that supports a significant tourism industry. It’s also home to Thunder Bay National Marine Sanctuary, the first ever NOAA National Marine Sanctuary to be established in the Great Lakes.

GLERL’s fieldwork for this year’s Lake Huron CSMI efforts focused on benthic and spatial surveys in Thunder Bay and Saginaw Bay. Here’s a look back at some of the highlights!

GLERL scientists Ashley Elgin and Rachel Orzechowski rinse down sediments collected by a Ponar grab.

NOAA GLERL has been conducting benthic (lake bottom) research in the Great Lakes since 1980, during which time we have built an unparalleled record of the arrival and expansion of invasive zebra and quagga mussels. CSMI provides the perfect opportunity to expand on this knowledge. Surveying the lake bottom allows us to track the population dynamics of these mussels, follow their impacts on native species, and also monitor for any new invasive benthic species. 
GLERL scientist Paul Glyshaw collects Ponar samples onboard the Fisheries and Oceans Canada/Canadian Coast Guard vessel Limnos for mussel length-weight analysis.

In June, July, and August of this year, GLERL conducted surveys that will allow us to update the status of invasive dreissenid mussels and other benthos of Lake Huron. As an exciting bonus, our benthic surveys in Saginaw Bay and Thunder Bay even received dive support from Thunder Bay NMS to supplement the samples collected with Ponar grabs.

Thunder Bay NMS divers Stephanie Gandulla and John Bright support GLERL’s benthic survey on board the R/V 5503.
The large metal claw used for a Ponar grab is no match for a mussel-covered rock like this, which is why we need NOAA’s Thunder Bay NMS Divers to support the benthic survey.

In the truly collaborative fashion that CSMI is known for, GLERL scientists maximized time on these cruises by collecting samples for several federal and university collaborators in addition to conducting our mussel survey.  For example, mussels and sediments went to the U.S. Geological Survey for mercury analysis, and researchers from the University of Michigan will be looking for mussel environmental DNA in water samples.

This sediment sample from Saginaw Bay has many benthic inverts present, including dreissenid mussels, chironomids, water mites, amphipods, and a snail. 
Paul Glyshaw collects and filters Lake Huron water onboard the Fisheries and Oceans Canada/Canadian Coast Guard vessel Limnos to measure carbon content. This helps us address potential impacts of climate change on the lake, including acidification, changes to production, and altered biogeochemical processes.

Plus, GLERL also teamed up with the U.S. Environmental Protection Agency, Fisheries and Oceans Canada (DFO), and the Canadian Coast Guard in a whole lake-benthic survey, during which GLERL assessed mussel body condition, mussel reproduction, inorganic carbon measures, and collected water for eDNA across the lake. In true CSMI spirit, DFO stepped up and supported the benthic survey when the EPA R/V Lake Guardian became unavailable. 

Fisheries and Oceans Canada/Canadian Coast Guard vessel Limnos pulls into Port Huron for the Lake Huron Benthic survey.

In addition to surveying what’s happening on the lake floor, GLERL also conducted an intensive spatial survey through CSMI to study Lake Huron’s food web in the area between Thunder Bay and Saginaw Bay. With a special focus on studying the interactions between larval fish and plankton, one of the key instruments used was GLERL’s Plankton Survey System (PSS). This high-tech piece of equipment is a towed multi-sensor platform capable of measuring turbidity, chlorophyll a, photosynthetically active radiation (PAR), conductivity, temperature, and zooplankton spatial distributions.

GLERL scientists use the PSS on Lake Michigan in the mid 2000s.

The plots below show a nearshore to offshore view of Lake Huron’s biological data measured by the PSS, like water temperature, dissolved oxygen, and chlorophyll, and plankton distribution. Check out more PSS plots from this spatial survey here.

While the PSS instrument was collecting data below the waves, lots of mayflies were catching a ride on this research cruise!

Now that the fieldwork is complete, the next step for GLERL’s CSMI work is to process our samples and analyze our data to continue building our knowledge of Lake Huron. Stay tuned in 2023, when CSMI heads east to study Lake Ontario!

For more CSMI information, data, and findings, visit greatlakescsmi.org. Plus, check out this related CSMI project in which GLERL and CIGLR developed an Experimental Biophysical Modeling Forecast System for Lakes Michigan and Huron.


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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.

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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.

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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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NOAA Wave Glider Camaro Gathers Key Data During 25-Day Cruise in Lake Superior

The NOAA Great Lakes Environmental Research Laboratory (GLERL) and Michigan Technological University (MTU) Great Lakes Research Center recently teamed up on the deployment of a wave glider in Lake Superior. The chemical and biological data collected will help researchers understand more about the Lake Superior foodweb and also be used to validate satellite information.

Autonomous wave glider that was recently deployed into Lake Superior by the MTU Great Lakes Research Center. Credit: Sarah Atkinson/Michigan Tech

Information gathered by autonomous vehicles, such as the wave glider, helps fine-tune satellite algorithms (instructions that tell a satellite how to interpret what it’s seeing). Satellites are a great tool for observing the lakes, as they provide a broader view than that from the ground. Researchers create Great Lakes-specific algorithms because those used in the ocean often do not work well in the lakes. The data collected by the wave glider will help validate the algorithms and allow researchers to understand more about the lakes, such as primary productivity (See MTU’s blog post for more.)

A team of researchers from MTU deployed the wave glider on August 30, 2021 and it spent 25 days surveying the lake and collecting data. The plan is to make the data public through the National Centers for Environmental Information (NCEI) so that information can be used in many ways including model development.

Path of the wave glider deployed on August 30th, 2021 and recovered on September 22, 2021 off the eastern coast of the Keweenaw Peninsula, near Bete Grise.

“It is a privilege for the Great Lakes Research Center to collaborate with NOAA GLERL on the wave glider experiment in Lake Superior, a first of its kind,” said Andrew Barnard, director of Michigan Tech’s Great Lakes Research Center. “This project continues to build a strong partnership between our organizations to push the boundaries of autonomy and sensing technologies. These new technologies in the Great Lakes support a better understanding of the physical processes in the lakes and will directly result in improved management insight for policy makers.”

Steve Ruberg of NOAA GLERL is thrilled with the MTU partnership as it expands our ability to collect data throughout the lakes. “Uncrewed vehicles give us the persistent large spatial observational capability to get in situ observations that will allow us to validate Great Lakes remote sensing.”

Left to right: Michigan Tech R/V Agassiz Jamey Anderson, assistant director of marine operations, Michigan Tech Great Lakes Research Center; Tim Havens, incoming director of the Great Lakes Research Center (January 2022) and John Lenters, associate research scientist at the Great Lakes Research Center ready the wave glider for deployment. Credit: Sarah Atkinson/Michigan Tech

This research project is a part of the Environmental Protection Agency’s Cooperative Science and Monitoring Initiative (CSMI). Federal and state agencies, tribal groups, non-governmental organizations and academic researchers from the United States and Canada team up yearly to assess conditions in one of the five Great Lakes. The survey focuses on a series of research areas that are tailored to the unique challenges and data needs associated with each lake.


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From safe drinking water to sustainable fisheries, NOAA GLERL’s Experimental Lake Erie Hypoxia Forecast is even more useful than anticipated

Four years ago, NOAA’s Great Lakes Environmental Research Laboratory (GLERL) and the Cooperative Institute for Great Lakes Research (CIGLR) began providing an Experimental Lake Erie Hypoxia Forecast Model to warn stakeholders of low-oxygen upwelling events that can cause water quality problems for over 2 million residents of northern Ohio. Now in its fifth year, this forecast model has turned out to serve additional purposes that NOAA’s scientists hadn’t even considered – including maintaining sustainable fisheries and solving a smelly mystery!

Water intake crib off the coast of Lake Erie in Cleveland, Ohio. By forecasting potential hypoxic upwelling events that could impact water quality, NOAA GLERL’s Experimental Hypoxia Forecast Model helps drinking water plant managers be prepared to adjust their treatment processes as needed.

Providing critical warnings to keep drinking water safe

Hypoxia – a state of low oxygen – occurs in the deep waters of Lake Erie’s central basin in July through September of most years. Low-oxygen water is an unfavorable habitat for fish, and may kill bottom-dwelling organisms that provide food for fish. While the hypoxic water generally stays near the lake floor, changes in wind and water currents can create upwelling events, in which this zone of low oxygen is brought to the surface along the coast.

Once it creeps into shallower parts of the lake, hypoxic water can upset drinking water treatment processes at water intakes along the shoreline. Hypoxic upwelling events cause rapid changes in water quality variables such as temperature, pH, dissolved organic matter, iron, and manganese. To maintain the quality of treated water, plant managers must adjust treatment in response to these changes. NOAA GLERL’s Experimental Hypoxia Forecast Model provides several days of advance notice that water quality is changing, so that drinking water plant managers can be prepared to adjust their treatment processes as needed.

This infographic from NOAA GLERL describes how hypoxia occurs in large bodies of water like the Great Lakes.

Plot twist: Benefiting more than just our water supply

NOAA GLERL’s Experimental Lake Erie Hypoxia Forecast has proven to be incredibly successful in its original goal – but our scientists were surprised to learn that its usefulness didn’t stop there. Recent stakeholder interviews conducted by CIGLR Stakeholder Engagement Specialist Devin Gill revealed that, in addition to helping manage the drinking water treatment process, the forecast has also become an unexpectedly vital tool for managing Lake Erie’s fisheries. 

One agency that makes use of the experimental hypoxia forecast is the Ohio Department of Natural Resources (DNR). The Ohio DNR is responsible for generating population estimates for Lake Erie’s yellow perch and walleye – estimates that ultimately help determine official catch limits to maintain the lake’s sustainable fisheries. 

“Large aggregations of fish may seek refuge at the edges of the hypoxic zone,” says Ann Marie Gorman, a fisheries biologist with the Ohio DNR’s Fairport Harbor Fisheries Research Station. “Our office tracks the location of the lake’s cold bottom water using the NOAA GLERL Hypoxia Forecast Model, and we may modify the timing of some of our surveys to minimize the potential impact of hypoxia on the results. Overall, the NOAA GLERL Hypoxia Forecast Model has become an integral tool for our survey planning.”

Understanding fish behaviors in response to hypoxia is important to conducting accurate population surveys of Lake Erie’s fish species. The ability of NOAA GLERL’s hypoxia forecast to warn fisheries managers of potential survey bias from these hypoxic events helps to save time, money, and energy that may have otherwise been used to conduct unsuccessful trawling surveys in hypoxic zones.

NOAA GLERL’s Experimental Hypoxia Forecast Model helps to guide the planning of trawling surveys like this one conducted by the Ohio Department of Natural Resources. Consulting the forecast helps the Ohio DNR to minimize the potential impact of hypoxia on survey results, which are used to set catch limits that keep Lake Erie’s fisheries sustainable. Photo credit: Ohio Department of Natural Resources.

Richard Kraus, a supervisory research fish biologist with the United States Geological Survey (USGS) Great Lakes Science Center Field Station in Ohio, also uses the experimental hypoxia forecast for his work with Lake Erie’s fisheries. Kraus explains that in Lake Erie, several cold-water fish species rely on finding refuge in colder, deeper waters of the lake – waters that are not impacted by warmer summer air temperatures. However, the presence of hypoxic zones in these deeper waters can impact how much refuge is available for these fish. As hypoxia reduces refuge habitats for cold-water species, chronic effects on growth and reproduction may develop, and in severe circumstances fish kills sometimes occur. The NOAA GLERL Hypoxia Forecast Model is instrumental in predicting where these potential ecosystem impacts could occur, in turn helping fisheries managers determine sustainable catch limits for each fish species in question.

The experimental forecast was also found to be useful to commercial and recreational fishers, who use the forecast to gauge the distribution of yellow perch in relation to hypoxic zones. Fishers can utilize the forecast on a daily basis to determine where to launch their boats, and where to search for aggregations of fish, depending on the hypoxia forecast for that day.

Plus, it’s not just routine fisheries management and recreation that the Experimental Hypoxia Forecast helps improve. In early September, it helped solve the mystery of a strange, foul smell coming from Lake Erie near Cleveland, Ohio, and fish kills associated with it. These phenomena resulted in many public inquiries regarding suspected gas leaks or pollutant spills. Thanks to the forecast, public officials knew that an upwelling of hypoxic water had recently occurred, likely carrying sulfur and nitrogen compounds that caused the stench, and were able to quickly eliminate other possible causes.

Half a decade in the making

Since it began in 2017, this NOAA project has grown into much more than just a computer model. The Experimental Lake Erie Hypoxia Forecast model was developed as a five-year project (2017-2021) with funding from NOAA’s Coastal Hypoxia Research Program, and is an extension of the Lake Erie Operational Forecasting System at NOAA’s Center for Operational Oceanographic Products and Services. Co-led by NOAA GLERL research scientists Drs. Mark Rowe and Craig Stow, and CIGLR’s Dr. Casey Godwin, project scientists provide an email update to public water systems, fisheries managers, and other stakeholders ahead of likely hypoxic events that contains links to the experimental forecast website and other useful NOAA webpages.

Map from the NOAA GLERL Experimental Lake Erie Hypoxia Forecast Model showing predicted change in Lake Erie temperature (top) and dissolved oxygen (bottom) during a three-day hypoxic upwelling event from August 31 to September 2, 2021.

Partners on this project include Ohio public water systems (including the cities of Cleveland and Avon Lake), NOAA’s National Ocean Service, and the Great Lakes Observing System. Special thanks to Devin Gill from the Cooperative Institute for Great Lakes Research for contributing stakeholder interview findings for this article.