NOAA Great Lakes Environmental Research Laboratory

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


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New algorithm to map Great Lakes ice cover

Leshkvich sampling ice

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).

 

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ICECON Scale

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.

 


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NOAA GLERL collaborating with partners to monitor the Lake Huron ecosystem

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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. The Great 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.


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“Just Because the Blooms in Lake Erie Slow Down, Doesn’t Mean We Do”

NOAA GLERL harmful algal blooms research program featured on Detroit Public Television

As part of a series on The Blue Economy of the Great Lakes, NOAA’s Great Lakes Environmental Research Laboratory (GLERL) is featured in a short video, produced by Detroit Public Television (DPTV) and published on the DPTV website. The video, which features GLERL and its partners from the Cooperative Institute for Great Lakes Research (CIGLR, known formerly as CILER), describes the advanced technology GLERL uses to monitor, track, predict, and understand harmful algal blooms (HABs) in the Great Lakes. More specifically, the video focuses on efforts in Lake Erie, where over 400,000 people were affected by a 3-day shutdown of the Toledo drinking water treatment facility in 2014. Since then, GLERL and CIGLR have enhanced their HABs research program—much of which is made possible by funding from the Great Lakes Restoration Initiative, or GLRI—to include cutting-edge technologies such as the hyperspectral sensors and an Environmental Sample Processor (ESP), as well as experimental forecasting tools like the Lake Erie HAB Tracker.

In addition to online coverage, the video will be broadcast via DPTV at a future time, yet to be determined.

View the video above, or visit http://bit.ly/2pK2g0J.

Aerial photo survey improves NOAA GLERL’s Lake Erie ice model

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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. Credit NOAA GLERL/Kaye LaFond.

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.

 

This gallery contains 10 photos


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Arrival of wave GLIDER SV2 platforms to expand GLERL data collection capacity in the Great Lakes

Left and bottom right: OSAT staff learning the ropes on the Wave GLIDER SV2 during a three-day training in Kawaihae, Hawaii. Top right: CILER’s Russ Miller (left) and GLERL’s Kyle Beadle (right) work in GLERL’s laboratory to prepare the newly acquired Wave GLIDERS for deployment.

GLERL’s OSAT (Observing Systems and Advance Technology) team, in collaboration with the Michigan Technological University’s (MTU) Great Lakes Research Center, is preparing to deploy the Wave GLIDER SV2 to expand its monitoring capacity in the Great Lakes. The Wave GLIDER functions as an autonomous surface vehicle that uses wave energy propulsion and communicates via Iridium satellite, providing real-time data back to users. This wave powered vehicle can be fitted with numerous instruments to collect data on a variety of physical characteristics of the lakes, including: waves, CTD (conductivity, temperature, depth), and currents. These data can be used for remote sensing algorithm validation. With the instrumentation on board, the Wave GLIDER  can continuously run transects throughout much of the year in all Great Lakes weather conditions and can be piloted and monitored by researchers at GLERL.

The two Liquid Robotics-designed Wave Glider SV2 platforms, to be deployed in the upcoming field season ,were surplused to GLERL by NOAA’s National Data Buoy Center (NBDC) in FY 2016. To ensure safe and reliable operation of these persistent, autonomous data collection platforms, Steve Constant and Steve Ruberg participated in a three-day training in Kawaihae, Hawaii at the Liquid Robotics Training Center this past January. They were accompanied by colleagues Russ Miller (Cooperative Institute for Limnology and Ecosystems Research (CILER)), Jamey Anderson (MTU), and Chris Pinnow (MTU). The training focused on instrument assembly, care, programming, piloting, and deployment and retrieval of the newly acquired wave glider units.

The vehicles, as currently configured, will be used for real-time observations supporting commercial shipping and validation of operational forecasts and satellite remote sensing products. Future applications include mapping of hypoxic zones impacting drinking water and acoustic fisheries parameters in U.S. coastal and Great Lakes regions.