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.
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 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.
Understanding the major effects of ice on the Great Lakes is crucial. Ice cover impacts a range of societal benefits provided by the lakes, from hydropower generation to commercial shipping to the fishing industry. The amount of ice cover varies from year to year, as well as how long it remains on the lakes. With almost five full decades of ice data to look at, GLERL scientists are observing long-term changes in ice cover as a result of climate change. Studying, monitoring, and predicting ice coverage on the Great Lakes plays an important role in determining climate patterns, lake water levels, water movement patterns, water temperature structure, and spring plankton blooms.
Maximum ice cover on the Great Lakes every year from 1973 to 2018. Credit: NOAA GLERL.
NOAA GLERL has been exploring the relationships between ice cover, lake thermal structure, and regional climate for over 30 years through the use of historical model simulations and observations of ice cover, surface water temperature, and other variables. Weekly ice cover imaging products produced by the Canadian Ice Service (CIS) started in 1973. Beginning in 1989, the U.S. National Ice Center (NIC) produced Great Lakes ice cover charts that combined both Canadian and U.S. satellite imagery. Today, these products are downloaded and processed at GLERL by our CoastWatch program, a nationwide NOAA program within which GLERL functions as the Great Lakes regional node. In this capacity, GLERL uses near real-time satellite data to produce and deliver products that support environmental decision-making and ongoing research. While the Great Lakes CoastWatch Program is a great resource for near real-time ice cover data, historical data is just as important – and that’s where GLERL’s Great Lakes Ice Cover Database comes in. Originally archived by GLERL through the National Snow & Ice Data Center, the Great Lakes Ice Cover Database houses data that dates back to 1973 and continues to be updated daily during the ice season every year.
Ice caves on Lake Michigan’s Glen Haven beach in 2005. Credit: National Parks Service.
Even though the CIS and NIC are the ones who actually collect Great Lakes ice cover data, GLERL plays the important role of re-processing this ice data into more accessible file formats, making it readily usable to anyone who needs it. Agencies and organizations that have used ice cover data from GLERL in the past include the NASA Earth Observatory, U.S. Army Corps of Engineers, U.S. Coast Guard, and National Geographic. Types of data requested might include historic minimum and maximum ice coverage for certain regions or lakes, or dates of the first and last ice cover in a region from year to year. This information can be helpful for managers in industries like energy production and commercial shipping.
This graph shows annual maximum ice coverage on the Great Lakes every year from 1973 to 2020. The red dashed line marks the long-term average maximum ice cover of 53.3%.Credit: NOAA GLERL.
GLERL scientists can also use this historic ice cover data to analyze how current ice cover conditions compare with previous years. For example, here’s how the ice cover during January 2021 stacks up against data for past Januarys:
Lake Michigan and the five-lake average had their second lowest January ice cover (with January 2002 being the first lowest).
The other lakes are all in the top five lowest ice cover for the month of January.
Six out of ten of the Januarys with the lowest ice cover have occurred during the last decade for the five-lake average (though 2014 was fourth highest January ice cover).
This graph shows average Great Lakes ice cover for the month of January every year from 1973 to 2021, organized by lowest ice cover (far left) to highest ice cover (far right). Credit: NOAA GLERL.
GLERL is also working to make this data more user-friendly for anyone looking to utilize it. This recent paper from GLERL and the Cooperative Institute for Great Lakes Research (CIGLR) describes the scientists’ efforts to standardize two existing formats of historic ice cover data. The authors explain that “technology has improved and the needs of users have evolved, so Great Lakes ice cover datasets have been upgraded several times in both spatial and temporal resolutions.” The paper documents the steps the authors took to reprocess the data in order to make it more consistent and accessible, which ultimately makes it easier for users to study long-term trends.
Timeline of ice chart evolution and frequency, from the research paper described above (Yang et al 2020). Credit: Ting-Yi Yang, Cooperative Institute for Great Lakes Research.
Whether you’re looking for decades of Great Lakes ice data or just a few days, GLERL’s got you covered! Looking for more Great Lakes ice cover information? Visit our ice cover homepage here.
MODIS satellite image of ice cover on the Great Lakes, March 16, 2014. Credit: NOAA Great Lakes CoastWatch.
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.
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 theCooperative 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.
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.
Andrea VanderWoude on a flight over Grand Traverse Bay.
Andrea VanderWoude is a remote sensing specialist — that means she’s looking at things from far away. Whether she’s studying harmful algal blooms or rip currents, her job is to pull information out of pictures taken from airplanes or satellites. What makes her extra good at it? She’s got an artistic streak! Read on to learn more.
How would you describe your job?
As a remote sensor, I use satellites and airborne cameras to monitor the Great Lakes – specifically harmful algal blooms, rip currents and submerged aquatic vegetation. I am an oceanographer working on the Great Lakes and most people wonder how that is possible. The lakes are so large they behave similarly to the ocean. I coordinate flights out of the Ann Arbor, Michigan airport with a contracted pilot that we work with and we put a small hyperspectral camera in the back of the airplane to take photos of the lakes.
Hyperspectral means that there are many discrete [color] bands or channels that are used (these colors are more detailed than the human eye can see). These channels can be used to map harmful algal blooms, which absorb, scatter and reflect light in a specific way. The hyperspectral camera is also able to fly underneath the clouds where passive sensors on satellites are unable to see. My day is spent programming, writing algorithms to process the images and looking at beautiful imagery. It is a wonderful blend of science and art!
What is the most interesting thing you’ve accomplished in your job?
Every year we fly over the Sleeping Bear Dunes National Lakeshore to monitor submerged aquatic vegetation and specifically for cladophora. As a northern Michigander growing up in that area, it is always amazing to see that area from the sky and to dream about hiking the Manitou Islands again. I also enjoy contributing to aiding the mapping of submerged aquatic vegetation in an area that is personally important to me.
What do you feel is the most significant challenge in your field today?
The most significant challenge I think is keeping up with the changing technology at the speed it is developing at this time. We are working on getting our new hyperspectral camera on an unmanned aerial system (UAS) for rapid response and I am really interested in using UAS’s for frequent monitoring of rip current troughs in the Great Lakes.
Where do you find inspiration? Where do your ideas come from in your research or other endeavors in your job?
I found my inspiration from growing up on the lakes and my parents always made a point of being on the water during all times of the year, either on Lake Michigan or Lake Superior. I have always felt connected to the water and jump in the lake during every month of the year, as a surfer on the Great Lakes. My ideas come from the public and what public needs could be supported. While living on the west side of Michigan, I have really seen the effect of rip currents and was recently stuck in one myself. It was a scary event and even furthered my desire to help warning and detection of rip currents.
How would you advise young women interested in science as a career path, or someone interested in your particular field?
I would advise women to get outside. When asked this question, people frequently turn towards an answer that involves STEM involvement but for me, and I think this also rings true for my Michigan Tech cohorts from undergrad, it was getting outside and learning about the natural world that sparked my interest in science. I was allowed to watch a limited amount of television as a kid and my mom would send me outside to play in the woods. I would spend my time creating forts around trees in the woods or we would go to the lake to swim for hours. This love of the outdoors continued through my undergraduate and graduate degrees with a curiosity to learn how the earth was formed, different rock types or how ocean dynamics and biology could be measured from space.
What do you like to do when you AREN’T sciencing?
I love to bake, learn about different plants, go rock hunting, trail running, rustic camping, stand up paddle boarding and I am newly returning to surfing but on the Great Lakes. I also spend an enormous amount of time with my boys on the beach, searching for cool rocks or treasures on the beach.
What do you wish people knew about scientists or research?
Many scientists also have an artistic outlet as well as their science life. It creates a life-balance. I personally find balance spending my free-time creating art from found objects on the beach, drawing, painting and baking unique pastries. Constantly a life in motion, as a pendulum between science and art.
Dr. Andrea VanderWoude is a contractor and remote sensing specialist with Cherokee Nation Businesses. She is currently working with researchers from NOAA GLERL and the Cooperative Institute for Great Lakes Research.
Researchers at GLERL are using a new tool, a MOCNESS, to study the Great Lakes.
In the Great Lakes, communities of plants and animals vary depending on where and when you look. They are dispersed up and down and all around in the water, making it tricky to collect them for research studies. To answer questions about these organisms and how they interact in the Great Lakes ecosystem, scientists from NOAA’s Great Lakes Environmental Research Laboratory (GLERL) and CIGLR (Cooperative Institute for Great Lakes Research) are using a new high tech sampling tool called a MOCNESS (Multiple Opening and Closing Net and Environmental Sensing System).
GLERL’s MOCNESS is the first of its kind to be used in a freshwater system. Scientists are hopeful that this technology will lead to new discoveries about the Great Lake ecosystem, such as where plankton (microscopic aquatic plants and animals) live and what causes their distributions to change over space and time. The MOCNESS will also help scientists learn more about predator-prey interactions that involve zooplankton (microscopic aquatic animals), phytoplankton (microscopic aquatic plants), and larval and juvenile fishes.
A closer look the MOCNESS (Multiple Opening and Closing Net and Environmental Sensing System)
Keeping track of changes in plant and animal communities in the Great Lakes over time is important, especially with changes in climate, the onslaught of invasive species, and land use practices causing increased nutrient runoff into the lakes.
The MOCNESS is a big improvement over the traditional single mesh sized sample collection nets. The sampling system provided by this new tool has a series of nets of different mesh sizes to collect different sized organisms (see a few examples in the gallery below). The operator can remotely open and close these nets, much like an accordion. At the heart of the system is a set of sensors that measure depth, temperature, oxygen, light levels, and the green pigment found in algae, Chlorophyll-a. Because this data can be viewed in real time on the vessel, the operator can better determine what is going on below the water surface and choose where and when to sample different sized organisms.
Here are some of the key questions that the scientists hope to answer using this advanced technology:
How do plankton and larval fish respond to environmental gradients (water temperature, dissolved oxygen, UV radiation) over the course of the day, season, and across years?
What are the major causes for changing distributions of the animals across space and over time (long-term, seasonal, 24-hour cycle)?
How do these changes in affect reproduction, survival, and growth of individuals and their communities?
The MOCNESS has been tested in the waters of lakes Michigan and Huron for the past three years. The team, led by Dr. Ed Rutherford, is supporting GLERL’s long term study of the Great Lakes food webs and fisheries. “The MOCNESS will enhance the ability of our scientists to more effectively observe the dynamics of Great Lakes ecosystem over space and time—a critical research investment that will pay off for years to come,” says Rutherford.
This year, the team is actively processing samples that were collected in the spring and will continue to collect more samples through the fall. The MOCNESS will support ongoing ecological research on the Great Lakes and the results will be shared with others around the region who are working to make decisions about how to manage Great Lakes fisheries and other water resources.
The Great Lakes, along with their connecting waterways and watersheds, make up the largest lake system on the planet—more than 20% of the world’s surface freshwater! Water levels on the lakes change in response to a number of factors, and these changes can happen quickly. Changing water levels can have both positive and negative impacts on shipping, fisheries, tourism, and coastal infrastructure like roads, piers, and wetlands.
Currently, water levels on all of the Great Lakes are above their monthly averages, and have been developing since the spring of 2013, when a record-setting two-year rise in water levelsbegan on the upper Great Lakes. Extreme conditions in spring of 2017 produced flooding and widespread damage at the downstream end of the basin—Lake Ontario and the St. Lawrence River. In case you missed it, check out our infographicon this flooding event.
So, what’s happening now that it’s winter?
As we entered the late fall-early winter of 2017-2018, a warm weather pattern had forecasters looking toward a fairly warm winter. However, in late December, the conditions changed and a much colder than normal weather pattern took many folks living in the Great Lakes by surprise. Much like how water levels can change quickly in the Great Lakes, so can ice cover. Due to frigid air temperatures, between December 20 and January 7, total ice cover on the lakes jumped 26.3%. Lake Erie alone jumped up to nearly 90%!
After January 7th, ice coverage dropped a bit as the air temperatures warmed, then rose again as temperatures went back down, showing again how vulnerable the lakes are to even the slightest changes. Compare where we are now to where we were 2 years ago at this time, and you’ll easily see how variable seasonal ice cover can be in the Great Lakes.
What’s the outlook for ice and water levels?
Below, you’ll find what GLERL researchers expect to see for ice cover this winter, as well as the U.S. Army Corps’ water levels forecast into Spring 2018. Be sure to read further to find out more about the science that goes into these predictions!
On 1/3/2018, NOAA’s Great Lakes Environmental Research Laboratory updated the maximum 2018 Great Lakes basinwide ice cover projection to 60%. The long-term average is 55%. The updated forecast reflects changes in teleconnection patterns (large air masses that determine our regional weather) since early December 2017—movement from a strong to a weak La Nina, a negative to a positive Pacific Decadal Oscillation, and a positive to a negative North Atlantic Oscillation. These patterns combine to create colder than average conditions for the Great Lakes.
—Water Levels forecast into spring 2018—
According to the most recent weekly water level update from the U.S. Army Corps, water levels for all of the Great Lakes continue to be above monthly average levels and above last year’s levels at this time. All of the lakes have declined in the last month. Note that ice developing in the channels and on the lake surface can cause large changes in daily levels during the winter, especially for Lake St. Clair. Over the next month, Lake Superior and Lake Michigan-Huron are expected to continue their seasonal decline. Lake St.Clair, Lake Erie, Lake Ontario are expected to begin their seasonal rise.
More information on water levels and ice cover forecasting
How are water levels predicted in the Great Lakes?
Forecasts of Great Lakes monthly-average water levels are based on computer models, including some from NOAA GLERL, along with more than 150 years of data from past weather and water level conditions. The official 6-month forecast is produced each month through a binational partnership between the U.S. Army Corps of Engineers and Environment and Climate Change Canada.
At GLERL, research on water levels in the Great Lakes analyzes all of the components of the Great Lakes water budget. The information we gather is used to improve forecast models. The infographic below goes into more detail about the Great Lakes water budget.
How does winter ice cover affect water levels?
As mentioned in the recently released Quarterly Climate Impacts and Outlook for the Great Lakes, water levels in the Great Lakes tend to decline in late fall and early winter, mainly due to reduced runoff and streamflow combined with higher over-lake evaporation caused by the temperature difference between air and water. Factors such as surface water temperatures, long stretches of cold or warm air temperatures, and winds all impact the amount of lake ice cover as well as extreme winter events, such as lake-effect snow—which we’ve already seen plenty of this winter—and vice versa. All of these factors influence winter water levels in the Great Lakes. The timing and magnitude of snow melt and spring runoff will be major players in the spring rise.
GLERL researcher, George Leshkevich, drilling through the ice in Green Bay, Lake Michigan.
NOAA’s Great Lakes Environmental Research Laboratory (GLERL) is on the cutting edge of using satellite remote sensing to monitor different types of ice as well as the ice cover extent. To make this possible, an algorithm—a mathematical calculation developed at GLERL to retrieve major Great Lakes ice types from satellite synthetic aperture radar (SAR) data—has been transferred to NOAA’s National Environmental Satellite, Data, and Information Service (NESDIS) for evaluation for operational implementation.
Once operational, the algorithm for Great Lakes ice cover mapping holds multiple applications that will advance marine resource management, lake fisheries and ecosystem studies, Great Lakes climatology, and ice cover information distribution (winter navigation). Anticipated users of the ice mapping results include the U.S. Coast Guard (USCG), U.S. National Ice Center (NIC), and the National Weather Service (NWS).
For satellite retrieval of key parameters (translation of satellite imagery into information on ice types and extent), it is necessary to develop algorithms specific to the Great Lakes owing to several factors:
Ocean algorithms often do not work well in time or space on the Great Lakes
Ocean algorithms often are not tuned to the parameters needed by Great Lakes stakeholders (e.g. ice types)
Vast difference exists in resolution and spatial coverage needs
Physical properties of freshwater differ from those of saltwater
The relatively high spatial and temporal resolution (level of detail) of SAR measurements, with its all-weather, day/night sensing capabilities, make it well-suited to map and monitor Great Lakes ice cover for operational activities. Using GLERL and Jet Propulsion Lab’s (JPL) measured library of calibrated polarimetric C-band SAR ice backscatter signatures, an algorithm was developed to classify and map major Great Lakes ice types using satellite C-band SAR data (see graphic below, Methodology for Great Lakes Ice Classification prototype).
ICECON (ice condition index) for the Great Lakes—a risk assessment tool recently developed for the Coast Guard—incorporates several physical factors including temperature, wind speed and direction, currents, ice type, ice thickness, and snow to determine 6 categories of ice severity for icebreaking operations and ship transit. To support the ICECON ice severity index, the SAR ice type classification algorithm was modified to output ice types or groups of ice types, such as brash ice and pancake ice to adhere to and visualize the U.S. Coast Guards 6 ICECON categories. Ranges of ice thickness were assigned to each ice type category based on published freshwater ice nomenclature and extensive field data collection. GLERL plans to perform a demonstration/evaluation of the ICECON tool for the Coast Guard this winter.
Mapping and monitoring Great Lakes ice cover advances NOAA’s goals for a Weather-Ready Nation and Resilient Coastal Communities and Economies, and Safe Navigation. Results from this project, conducted in collaboration with Son V. Nghiem (NASA/Jet Propulsion Laboratory), will be made available to the user community via the NOAA Great Lakes CoastWatch website (https://coastwatch.glerl.noaa.gov).
Measuring different ice types on Green Bay used to validate the ICECON (ice type classification) Scale in a RADARSAT-2 synthetic aperture radar (SAR) scene taken on February 26, 2017.
The NOAA Great Lakes Environmental Research Laboratory (GLERL) is participating in an international, multi-agency effort to study invasive species, water quality, fisheries, and climate change in Lake Huron this field season—pursuing key knowledge gaps in the ecosystem. The Coordinated Science and Monitoring Initiative (CSMI) coordinates across U.S. and Canadian agencies to conduct intensive sampling in one Great Lake per year, on a five-year cycle. TheGreat Lakes Restoration Initiative, which is administered by the U.S Environmental Protection Agency (EPA), is funding this research.
“While GLERL has had a long-term research program focused on Lake Michigan, we are using this initiative to advance long-term research on Lake Huron,” said GLERL Director Deborah Lee. “Invasive species, warming temperatures, and changes in nutrient loading are putting as much stress on Lake Huron as on Lake Michigan. We want to better understand the Lake Huron ecosystem and develop modeling tools to predict how the lake is changing.”
Henry Vanderploeg, Ph.D., chief of GLERL’s Ecosystem Dynamics research branch and lead researcher for GLERL’s efforts in the pelagic (open water) portion of the initiative comments, “GLERL plays a critical role in the CSMI, addressing key science questions. GLERL’s high frequency temporal and spatial sampling will help determine nutrient and energy flows from tributaries, nearshore to offshore. This type of data is critical to effectively manage Lake Huron for water quality and fish production.” Frequent spatial surveys are key to understanding food web connections throughout the seasons.
Researchers from GLERL will expand upon their recent work in Lake Michigan (CSMI 2015) and past work in Huron (2012) to determine fine-scale food-web structure and function from phytoplankton to fishes along a nutrient-rich transect (from inner Saginaw Bay out to the 65-m deep Bay City Basin) and along a nutrient-poor transect (from inner Thunder Bay out to the Thunder Bay basin) during May, July, and September. GLERL will collect additional samples of fish larvae and zooplankton along both transects in June to help estimate larvae growth, diet, density, and mortality and to identify fish recruitment bottlenecks.
“GLERL was instrumental in establishing the long-term monitoring efforts that provide the foundation for current CSMI food-web studies,” said Ashley Elgin, Ph.D., research ecologist in the Ecosystem Dynamics research branch. Elgin serves as the NOAA representative on the CSMI Task Team, part of the Great Lakes Water Quality Act Annex 10, alongside partners from the U.S. Geological Survey (USGS), EPA, the U.S. Fish & Wildlife Service, Environment and Climate Change Canada, and the Ontario Ministries of Natural Resources and the Environment and Climate Change. This year, Elgin is conducting critical mussel growth field experiments in Lake Huron, expanding upon work she developed in Lake Michigan. She will be addressing the following questions: (1) How does quagga mussel growth differ between regions with different nutrient inputs?; and (2) How do growth rates compare between Lakes Michigan and Huron? Elgin will also coordinate a whole-lake benthic survey, which will update the status of dreissenid mussels and other benthic-dwelling organisms in Lake Huron.
GLERL’s key research partner, the Cooperative Institute for Great Lakes Research (CIGLR), will deploy a Slocum glider for a total of sixteen weeks to collect autonomous measurements of temperature, chlorophyll, colored dissolved organic matter (CDOM), and photosynthetically active radiation (PAR) between outer Saginaw Bay and open waters of the main basin. Deployment times and coverage will be coordinated with other glider deployments by the EPA Office of Research and Development (ORD) and/or USGS Great Lakes Science Center, spatial research cruises, and periods of expected higher nutrient loads (i.e., following runoff events).
CSMI research cruises began in late April and will continue through September. Researchers are using an impressive fleet of research vessels, including EPA’s 180-foot R/V Lake Guardian, GLERL’s 80-foot R/V Laurentian and 50-foot R/V Storm, and two large USGS research vessels, the R/V Articus and R/V Sterling. Sampling missions will also be conducted aboard Environment Canada’s Limnos across Lake Huron. The Laurentian is fitted out with a variety of advanced sensors and sampling gear, making it especially suitable for examining fine-scale spatial structure.
Scientists from the USGS Great Lakes Science Center, the Michigan Department of Natural Resources, and the University of Michigan are also participating in the Lake Huron CSMI.
Understanding the duration, extent, and movement of Great Lakes ice is important for the Great Lakes maritime industry, public safety, and the recreational economy. Lake Erie is ice-prone, with maximum cover surpassing 80% many winters.
Multiple times a day throughout winter, GLERL’s 3D ice model predicts ice thickness and concentration on the surface of Lake Erie. The output is available to the public, but the model is under development, meaning that modelers still have research to do to get it to better reflect reality.
As our scientists make adjustments to the model, they need to compare its output with actual conditions so they know that it’s getting more accurate. So, on January 13th of this year, they sent a plane with a photographer to fly the edge of the lake and take photos of the ice.
The map below shows the ice model output for that day, along with the plane’s flight path and the location of the 172 aerial photos that were captured.
NOAA GLERL Lake Erie ice model output with all aerial photo survey locations — January 13, 2017. Map Credit NOAA GLERL/Kaye LaFond.
These photos provide a detailed look at the sometimes complex ice formations on the lake, and let our scientists know if there are places where the model is falling short.
Often, the model output can also be compared to images and surface temperature measurements taken from satellites. That information goes into the GLSEA product on our website (this is separate from the ice model). GLSEA is useful to check the ice model with. However, it’s important to get this extra information.
“These photographs not only enable us to visualize the ice field when satellite data is not available, but also allow us to recognize the spatial scale or limit below which the model has difficulty in simulating the ice structures.” says Eric Anderson, an oceanographer at GLERL and one of the modelers.
“This is particularly evident near the Canadian coastline just east of the Detroit River mouth, where shoreline ice and detached ice floes just beyond the shoreline are not captured by the model. These floes are not only often at a smaller spatial scale than the model grid, but also the fine scale mechanical processes that affect ice concentration and thickness in this region are not accurately represented by the model physics.”
Click through the images below to see how select photos compared to the model output. To see all 172 photos, check out our album on Flickr. The photos were taken by Zachary Haslick of Aerial Associates.
Ice tail on Pelee Island. Photo Credit Zachary Haslick/Aerial Associates, Inc.
Open water downstream of Pelee Island. Photo Credit Zachary Haslick/Aerial Associates, Inc.
Ice edge northeast of Put-in-Bay. Photo Credit Zachary Haslick/Aerial Associates, Inc.
Shoreline ice east of the Detroit River. Photo Credit Zachary Haslick/Aerial Associates, Inc.
Shoreline and ice gap on the north shore. Photo Credit Zachary Haslick/Aerial Associates, Inc.
Shoreline and ice gap on the north shore. Photo Credit Zachary Haslick/Aerial Associates, Inc.
Ice field west of Point Pelee. Photo Credit Zachary Haslick/Aerial Associates, Inc.
Ice field moving past Point Pelee. Photo Credit Zachary Haslick/Aerial Associates, Inc.
NOAA Great Lakes Environmental Research Laboratory 
