NOAA Great Lakes Environmental Research Laboratory

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


Leave a comment

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.


Leave a comment

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

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.

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.

Preparing this AUV for deployment is no small task. Requiring multiple computers and a whole team of people, the initial calibration of the vehicle takes at least a full day.

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.

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 will soon be navigating its way under Great Lakes ice cover.

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


Leave a comment

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.


Leave a comment

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.


Leave a comment

Lake effect snow: What, why and how?

Winter is nearly here — and those who live and work in the Great Lakes region are already wondering what the winter of 2021 has in store. Early indications suggest a La Niña winter pattern, which shifts the odds towards cooler, wetter weather with more ice cover. 

More snow and ice can mean more fun, and can be great for winter sports like ice fishing, snowmobiling and skiing. Unfortunately, it can also mean severe weather events involving ice and snow. In the Great Lakes region, snow comes via the usual low pressure systems, but we also can get lake effect snow. 

Average location of the jet stream and typical temperature and precipitation impacts during La Niña winter over North America. Map by Fiona Martin for NOAA Climate.gov.

What is lake effect snow?

In the Great Lakes region, hazardous winter weather often happens when cold air descends from the Arctic region. Lake effect snow is different from a low pressure snow storm in that it is a much more localized and sometimes very rapid and intense snow event. As a cold, dry air mass moves over the unfrozen and relatively warm waters of the Great Lakes, warmth and moisture from the lakes are transferred into the atmosphere. This moisture then gets dumped downwind as snow.

Lake Effect Snow Can Be Dangerous

Lake effect snow storms can be very dangerous. For example, 13 people were killed by a storm that took place November 17-19, 2014 in Buffalo, New York. During the storm, more than five  feet of snow fell over areas just east of Buffalo, with mere inches falling just a few miles away to the north. Not only were lives lost, but the storm disrupted travel and transportation, downed trees and damaged roofs, and caused widespread power outages. Improving  lake effect snow forecasts is critical because of the many ways lake effect snow conditions affect commerce, recreation, and community safety.

Lake Effect Snow animation: Mid-December 2016 The lake effect snow EVENT resulted in extremely heavy snow across Michigan, Ohio, upstate New York as well as the province of Ontario east of Lake Superior and Huron.

Why is lake effect snow so hard to forecast?

There are a number of factors that make lake effect snow forecasting difficult. The widths of lake-effect snowfall bands are usually less than 3 miles — a very small width that makes them difficult to pinpoint in models. The types of field measurements scientists need to make forecasts better are also hard to come by, especially in the winter!  We would like to take frequent lake temperature and lake ice measurements but that is currently not possible to do during the winter, as conditions are too rough and dangerous for research vessels and buoys. Satellite measurements can also be hard to come by. The Great Lakes region is notoriously cloudy in the winter –  it’s not uncommon to go for over a week without usable imagery. 

MODIS satellite image of a lake effect snow event in the Great Lakes, caused by extensive evaporation as cold air moves over the relatively warm lakes. November 20, 2014. Credit: NOAA Great Lakes CoastWatch.

GLERL and CIGLR work to improve lake effect snow forecasting

Currently, NOAA Great Lakes operational models provide guidance for lake effect snow forecasts and scientists at NOAA GLERL and CIGLR are conducting studies to improve them. 

They use data from lake effect snow events in the past and compare how a new model performs relative to an existing model.  One way to improve forecast model predictions is through a model coupling approach, or linking two models so that they can communicate with each other. When they are linked, the models can share their outputs with each other and produce a better prediction in the end. 

Our lake effect snow research continues

Our lake effect modeling research is ongoing, and GLERL, CIGLR, NWS Detroit, the NOAA Global Systems Laboratory continue to address the complex challenges and and our studies build upon each other to improve modeling of lake-effect snow events. A new focus will be on running the models on a smaller grid scale and continuing to work to improve temperature estimates as both are key to forecasting accuracy.

A recent study, published by CIGLR and GLERL and other research partners, Improvements to lake-effect snow forecasts using a one-way air-lake model coupling approach,” is the latest in a recent series of studies* (see list below) that help to make lake effect snow forecasts better. This study takes a closer look at how rapid changes in Great Lakes temperatures and ice impact regional atmospheric conditions and lake-effect snow. Rapidly changing Great Lake surface conditions during lake effect snow events are not accounted for in existing operational weather forecast models. The scientists identified a new practical approach for how models communicate that does a better job of capturing rapidly cooling lake temperatures and ice formation. This research can result in improved forecasts of weather and lake conditions. The models connect and work together effectively and yet add very little computational cost. The advantage to this approach in an operational setting is that computational resources can be distributed across multiple systems.

Study model run: This panel of images shows model runs that looks at data from a lake effect snow event from January 2018 with and without the new type of model coupling. The image on the far right labeled Dynamic – Control Jan 06 shows the differences in air temperature (red = warmer, blue = colder) and wind (black arrows) when the models are coupled. The areas in color show how the new model coupling changed the model output considerably and improved the forecast.

Related news articles and blog posts:

From the CIGLR Winter 2020 eNewsletter – Improving Lake Effect Snow Forecasts

NOAA Research News, April 2019 NOAA research yields better lake-effect snow forecasts

NOAA GLERL Blog, 2018 – Improving lake effect snow forecasts by making models talk to each other

Related research papers: 

Fujisaki-Manome et al. (2020) Improvements to lake-effect snow forecasts using a one-way air-lake model coupling approach. 

Anderson et al. (2019) Ice Forecasting in the Next-Generation Great LakesOperational Forecast System (GLOFS) 

Fujisaki-Manome et al. (2017) Turbulent Heat Fluxes during an Extreme Lake-Effect Snow Event

Xue et al. (2016) Improving the Simulation of Large Lakes in Regional Climate Modeling: Two-Way Lake–Atmosphere Coupling with a 3D Hydrodynamic Model of the Great Lakes


Leave a comment

Special Two-Day Science Translation Session at IAGLR 2019

This June, fellow researchers from around the world will gather in Brockport, New York, on the shores of the Erie Canal for IAGLR’s 62nd annual Conference on Great Lakes ResearchHosted by The College at Brockport, State University of New York, the conference will feature four days of scientific sessions and speakers focusing on the theme Large Lakes Research: Connecting People and Ideas. Mark your calendars for June 10-14, 2019. You won’t want to miss it! 

During the conference there will be a special two-day session that highlights the importance of science translation.  The session, Beyond Peer Review: Why You Must Connect Your Science to Stakeholders (and how to do it), will consist of several components—17 formal presentations, a moderated panel discussion, a synthesis discussion with Q&A, as well as a Skills Café. Conference attendees are welcome to join us for any and all portions of this session. We hope to see you there!


Day 1 – Tuesday, June 11th

On Tuesday, the SciComm session will include 12 presentations and a panel moderated discussion with science communication thought leaders Peter Annin (Author), Andrea Densham (Shedd), Sandra Svoboda (DPTV) & TJ Pignataro (Buffalo News). The panelists will explore what they see happening now and what they think the future looks like for connecting people and ideas for large lakes research.

Tuesday Morning (Edwards Hall Room 103)

Tuesday Afternoon (Edwards Hall Room 103)

  • 1:40-3:20 pm – 5 presentations
  • 3:20-3:40 pm – Break
  • 3:40-5:20 pm – 4 presentations

Day 2 – Wednesday,  June 12th

On Wednesday, the SciComm session will continue with 5 formal presentations, and a synthesis discussion in the morning and a Skills Café in the afternoon.

Wednesday Morning (Edwards Hall Room 103)

  • 8:00-9:20 am – 3 presentations
  • 9:20-9:40 am – Break
  • 9:40-10:20 am – 2 presentations
  • 10:20-11:00 am – Interactive Synthesis Discussion and Question & Answer Session with Peter Annin (Author), Andrea Densham (Shedd), Sandra Svoboda (DPTV) & TJ Pignataro (Buffalo News)

Wednesday Afternoon (Edwards Hall Room 102)

  • 1:40 – 5:00 pm – Skills Café  –  This series of short interactive workshops will allow participants to practice a variety of skills that will make them more effective at communicating the “so what” of their research to lay – but key – audiences. 

The Panel: Hear the latest from science communication thought leaders!

Peter Annin, Author and Director of the Mary Griggs Burke Center for Freshwater Innovation

Peter Annin is the director of the Mary Griggs Burke Center for Freshwater Innovation and the author of The Great Lakes Water Wars, the definitive work on the Great Lakes water diversion controversy. Before coming to Northland College in 2015, Peter served as a reporter at Newsweek, the associate director of the Institute for Journalism and Natural Resources, and the managing director of the University of Notre Dame’s Environmental Change Initiative. He continues to report on the Great Lakes water diversion issue and has published a second edition of The Great Lakes Water Wars. 

Andrea Densham, Senior Director of Conservation and Advocacy at the Shedd Aquarium

Andrea Densham joined Shedd Aquarium in 2017 to lead the newly launched Conservation Policy and Advocacy team. Created to enhance Shedd’s position as a policy expert, Densham’s team develops and implements the institution’s policy goals. A government affairs thought leader and advisor, she brings more than 20 years of experience in not-for-profit management, strategic planning, research, and public policy and advocacy.

 

TJ Pignataro, Environmental Reporter for the Buffalo News

T.J. Pignataro has been a staff reporter for The Buffalo News for more than 20 years and the environment and weather reporter since 2013. He holds a juris doctor degree from SUNY Buffalo Law School and is completing his Certificate in Weather Forecasting this spring from the Pennsylvania State University’s Department of Meteorology and Atmospheric Science. TJ uses Twitter to convey Great Lakes environmental news, weather emergencies and Great Lakes science in plain language. 

Sandra Svoboda, Program Director, Great Lakes Now, Detroit Public Television

A nine-month stint with The Associated Press brought Sandra to Detroit … 29 years ago. She earned a bachelor’s in journalism from Indiana University and holds two master’s degrees from Wayne State, one in public administration and one in library and information science. The Special Libraries Association IT Division recognized her research with its 2018 Joe Ann Clifton Student Award for her paper on how Detroit voting dynamics can inform citizen engagement strategies. Sandra has worked for The (Toledo) Blade covering education/children’s issues, Detroit’s Metro Times and FEMA, where she deployed to Louisiana to help coordinate/communicate about community rebuilding/planning efforts for/after disasters. Sandra has won awards for broadcast, print, digital and community engagement work from the Michigan Associated Press, the Michigan Association of Broadcasters, Association of Alternative Newsweeklies, State Bar of Michigan, Michigan Press Association and Society of Professional Journalists-Detroit chapter, and Wayne State’s public administration program recognized her with the Distinguished Alumni Award in 2015 for her work covering Detroit’s bankruptcy. She has taught communications, writing, public policy, and political science at Wayne State University and the University of Michigan-Dearborn. As the Great Lakes region has always been her home Sandra has traveled between Minnesota and Tadoussac, Quebec, both on the water and on land. A competitive sailor, she races hundreds of miles each season on the Great Lakes, and once threw out a pitch at a Detroit Tigers game as recognition of her win with her team at the U.S. Women’s Match Racing Championship. She’s also eaten Asian carp as part of her coverage of invasive species.


The Skills Café: Get help communicating your research!

WHO: Do people’s eyes glaze over when you begin to talk about your research? Do you believe your research has the ability to make a difference, but you’re not sure how to get others excited about it too? Then this session is for you! For the researcher looking to improve their accessibility in attaining broader impacts; the early career professional seeking tips on how to set theirselves apart in a competitive market; the passionate scientist looking for ways to ensure their work makes an impact . . . the Skills Cafe is your opportunity to grow and try new things in a fun and supportive setting.

WHAT: This series of short interactive workshops will allow participants to practice a variety of skills that will make them more effective at communicating the “so what” of their research to lay—but key—audiences. Get tips on interacting with the media, hone your speaking skills, get feedback from a mock interview, and learn from the trials and tribulations of your peers!

WHEN: 1:40-5:00 pm on Wednesday, June 12.

WHERE: Edwards Hall, Room 102

For more information and a detailed schedule of activities stop by the NOAA exhibitor booth.


About IAGLR 2019: The 2019 International Association for Great Lakes Research Conference is hosted by The College at Brockport, State University of New York, June 10-14, 2019. The conference will feature four days of scientific sessions and speakers focusing on the theme “Large Lakes Research: Connecting People and Ideas.”

photo of building in water with skyline of city in backgroun


Leave a comment

NOAA and partners team up to prevent future Great Lakes drinking water crisis

A new video SMART BUOYS: Preventing a Great Lakes Drinking Water Crisis released by Ocean Conservancy describes how NOAA forecast models provide advance warnings to Lake Erie drinking water plant managers to avoid shutdowns due to poor water quality.

An inter-agency team of public and private sector partners, working with the Cleveland Water Department, are addressing drinking water safety for oxygen depleted waters (hypoxia). By leveraging NOAA’s operational National Weather Service and National Ocean Service forecast models and remote sensing for the Great Lakes, NOAA’s latest experimental forecast models developed by its Great Lakes Environmental Research Laboratory can predict when water affected by harmful algal blooms and hypoxia may be in the vicinity of drinking water intake pipes. Advance notice of these conditions allows water managers to change their treatment strategies to ensure the health and safety of drinking water.  

“Hypoxia occurs when a lot of organic material accumulates at the bottom of the lake and decomposes. As it decomposes, it sucks oxygen from the water, can discolor the water and allow for metals to concentrate,” explains Devin Gill, stakeholder engagement specialist for NOAA’s Cooperative Institute for Great Lakes Research, hosted at the University of Michigan.

Low dissolved oxygen on its own is not a problem for water treatment. However, low oxygen is often associated with a high level of manganese and iron in the bottom water that then leads to drinking water color, taste, and odor problems. In addition, the same processes that consume oxygen also lower pH and, if not corrected, could cause corrosion in the distribution system, potentially elevating lead and copper in treated water.

“Periodically, this water with depleted oxygen gets pushed up against the shoreline and the drinking water intakes pipes,” said Craig Stow, senior research scientist for NOAA’s Great Lakes Environmental Research Laboratory. “We have buoys stationed at various places and those guide our models to let us know when conditions are right for upwellings that would move this hypoxic water into the vicinity of the drinking water intakes.”

NOAA provides advanced warning of these events so that drinking water plant managers can effectively change their treatment strategies to address the water quality, which is a huge benefit in the water treatment industry.


For more information on NOAA GLERL’s harmful algal blooms and hypoxia research, visit www.glerl.noaa.gov/res/HABs_and_Hypoxia.

map of great lakes showing colors of model output


2 Comments

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.


Leave a comment

The HAB season is over, but the work goes on

It’s nearly winter here in the Great Lakes—our buoys are in the warehouse, our boats are making their way onto dry land, and folks in the lab are working hard to assess observed data, experiments, and other results from this field season.

habtracker2018

This is a retrospective animation showing the predicted surface chlorophyll concentrations estimated by the Experimental Lake Erie HAB Tracker model during the 2018 season. Surface chlorophyll concentrations are an indicator of the likely presence of HABs. For more information about how the HAB Tracker forecast model is produced and can be interpreted, visit our About the HAB Tracker webpage.

The harmful algal bloom (HAB) season is also long over in the region. The final Lake Erie HAB Bulletin was sent out on Oct. 11, as the Microcystis had declined in satellite imagery and toxins decreased to low detection limits in samples. In the seasonal assessment, sent out by NOAA’s Centers for Coastal Ocean Science on Oct. 26, it was determined that the season saw a relatively mild bloom—despite its early arrival in the lake—and the bloom’s severity was significantly less than that which was predicted earlier in the season. These bulletins and outlooks are compiled using several models. Over the winter, the teams working on the models take what they learn from the previous season, and update their models for future use.

Back in the lab, the HABs team—researchers from both GLERL and the Cooperative Institute for Great Lakes Research (CIGLR)—will spend the winter analyzing data they collected through a variety of observing systems. This summer was packed with the use of new observing technologies, like hyperspectral cameras and the Environmental Sample Processor (in case you missed it, check out this fun photo story of the experimental deployment of a 3rd generation ESP). In addition, GLERL and CIGLR staff maintained a weekly sampling program program, from which scientists are analyzing and archiving samples and conducting experiments.

43447135081_b893240224_o.jpg

Aerial photograph of the harmful algal bloom in Western Basin of Lake Erie on July 2, 2018, (Photo Credit: Aerial Associates Photography, Inc. by Zachary Haslick). Pilots from Aerodata have been flying over Lake Erie this summer to map out the general scope of the algal blooms. In addition to these amazing photos, during the flyovers, additional images are taken by a hyperspectral imager (mounted on the back of the aircraft) to improve our understanding of how to map and detect HABs. The lead researcher for this project is Dr. Andrea VanderWoude, a NOAA contractor and remote sensing specialist with Cherokee Nation Businesses. For more images, check out our album on Flickr.

This lab work is super important for understanding the drivers of toxic algae in the Great Lakes. For instance, in a new study released this month, researchers looking at samples from previous years found that “ . . . the initial buildup of blooms can happen at a much higher rate and over a larger spatial extent than would otherwise be possible, due to the broad presence of viable cells in sediments throughout the lake,” according to the lead author Christine Kitchens, a research technician at CIGLR, who works here in the GLERL lab. This type of new information can be incorporated into the models used to make the annual bloom forecasts.

As you can see, our work doesn’t end when the field season is over.  In spring 2019, when the boats and buoys are back in the water and samples are being drawn from the lakes, researchers will already have a jump on their work, having spent the winter months analyzing previous years, preparing, and applying what they’ve learned to the latest version of the Experimental HAB Tracker, advanced observing technologies, and cutting-edge research on harmful algal blooms in the Great Lakes.


1 Comment

Photo story: Using an AUV to track algae in Lake Erie

In late July and early September, during the peak of the 2018 harmful algal bloom in the Western Basin of Lake Erie, NOAA GLERL, NOAA National Centers for Coastal Ocean Science (NCCOS), NOAA Atlantic Oceanographic and Meteorological Laboratory (AOML) and CIGLR researchers teamed up with a group of scientists and engineers from the Monterey Bay Research Institute (MBARI). Their mission: to test how well a third-generation environmental sample processor (3GESP), mounted inside a long-range autonomous underwater vehicle (LRAUV), can track and analyze toxic algae in the Western Basin of Lake Erie. You can read more about the purpose of this project in this great news story by MBARI’s Kim Fulton-Bennett.

Below is a photo story showing all (well, much) of the hard work that went into this test deployment.

First, the new gear had to be shipped from California to the GLERL laboratory in Ann Arbor, Michigan.

 

ESP3-b (1)

Upon arrival, Jim Birch, Director of the MBARI SURF (Sensors Underwater Research of the Future) Center, & Bill Ussler, MBARI biogeochemist, got straight to work in GLERL’s Marine Instrumentation Lab.

Image from iOS (6)

The inside of the 3G ESP has a lot of moving parts. Since this is the first time the team is testing it in freshwater, before it can go out, everything needs to be fine-tuned to work in a variety of conditions in Lake Erie (more on that later.)

So. Many. Moving. Parts.

 

Image from iOS (7)

Once everything is in working order, the 3GESP gets inserted into an LRAUV or long-range autonomous underwater vehicle (the torpedo-looking thing). This gives the 3GESP the ability to move around in the water all by itself once researchers have set parameters for it. The team has named this particular vehicle, Makai, which is Hawaiian for “toward or by the sea.” Seems appropriate! That’s Brian Kieft, MBARI software engineer, on the right. He plays a crucial role in making sure Makai does her job.

IMG-1263

All hands on deck for a few more tweaks.

testing_b

Once everything is installed tightly, helium is added into the canister to check for leaks. CIGLR engineer, Russ Miller, is working with Jim to fill it up.

Now, the team is ready to head out to Lake Erie. Here’s where things start to get exciting!

 

20180822_134836.jpg

Before the team sets Makai free to track the algal bloom in the Western Basin of Lake Erie, they must first check her ballast and trim. This is especially important for such a shallow lake (relative to where the team has been testing this technology in the deep canyons of of Monterey Bay off the coast of California.)

20180822_133254

Brian has to do all of the hard work.

Image from iOS (8)

Because, science.

Image from iOS (11)

Time to load Makai onto the NOAA vessel, which is stationed in La Salle, Michigan. Captain Kent Baker, a contractor with NOAA, is in the background operating the crane. Kent takes NOAA and CIGLR researchers and technicians out to bi-weekly sampling stations, helps deploy buoys and other instrumentation, and is at the ready for pretty much anything that needs to happen in Lake Erie.

onboat

Once she’s all settled onto the boat, the team takes Makai to the first deployment location.

Screen Shot 2018-08-23 at 12.55.24 PM

The inaugural deployment was set to match up with the bi-weekly sampling stations.

inwater

Look closely and you’ll see Makai off on her way!

Makai and the team spent nearly two weeks tracking, sampling, adjusting, and learning about using this technology to track algal toxins in Lake Erie.

Image from iOS (1) copy

The team used the images from GLERL’s Experimental Lake Erie Harmful Algal Bloom (HAB) Tracker to determine where to send Makai.

Bloom Edge

Then, they would determine how many samples to take, and program her to go to specific waypoints.

Remember when we said this Lake Erie mission will be different than the ones the team has performed in Monterey Bay? Well, here’s one example of how.

20180826_132023

After a few hours of no communication, and a little hunting, this is how the team found Makai. Two problems here: One, with the propellor up and the nose down, Makai cannot transmit data, including her location, as the transmitter only works above water. And, two, well . . .

OLYMPUS DIGITAL CAMERA

The reason she was nose down in the first place is because Lake Erie is pretty shallow, and she’d taken on quite a bit of mud.

20180830_172121

Once she was all cleaned up, the team set Makai out again to complete the rest of her mission.

Once the deployment was over, the research didn’t stop there.

archive_full-liquid

Archive samples were taken so that folks back in the lab could further analyze them.

bps2

Here’s GLERL’s Observing Systems and Advanced Technology (OSAT) branch chief, Steve Ruberg (left), along with Paul Den Uyl, a researcher with CIGLR, helping Bill extract the sample filters from the cartridges.

Deunyl

The filters are being collected for analysis of DNA. The DNA will be extracted from each filter and analyzed. We’re looking at absolute quantity of known microcystin producing toxin genes in samples collected, information on bacterial community composition, and information on eukaryotic organism community composition. The samples will also analyzed through shotgun sequencing. This is where all of the genes in the sample are turned into human readable information and can be combined to make what can be thought of as an organism’s genetic instruction guide (what genes it has). This information will be very helpful in better understanding what causes the algae to be toxic (not all algae is toxic).